Antibodies and T-Cell Receptors,

ADVANCES IN PROTEIN CHEMISTRY Volume 49 Antigen Binding Molecules: Antibodies and T-cell Receptors

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ADVANCES IN PROTEIN CHEMISTRY EDITED BY FREDERIC M. RICHARDS

DAVID E. EISENBERG

Department of Molecular Biophysics and Biochemistry Yale University New Haven, Connecticut

Department of Chemistry and Biochemistry University of California, Los Angeles Los Angeles, California

PETER S. KIM Department of Biology Massachusetts Institute of Technology Whiteheadlnstitute for Biomedical Research Howard Hughes Medical lnstitute Research Laboratories Cambridge, Massachusetts

VOLUME 49

Antigen Binding Molecules: Antibodies and T-cell Receptors EDITED BY EDGARHABER Department of Biological Sciences Harvard School of Public Health Harvard Medical School Boston, Massachusetts

ACADEMIC PRESS San Diego London Boston New York Sydney Tokyo Toronto

This book is printed on acid-free paper.

@

Copyright 0 1996 by ACADEMIC PRESS All Rights Reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher.

Academic Press, Inc. 525 B Street, Suite 1900, San Diego, California 92101-4495, USA http:lfwww.apnet.com Academic Press Limited 24-28 Oval Road, London NWl 7DX, UK http://www.hbuk.co.uk/ap/ International Standard Serial Number: 0065-3233 International Standard Book Number: 0-12-034249-9 PRINTED IN THE UNITED STATES OF AMERICA 96 97 9 8 9 9 00 0 1 B C 9 8 7 6 5

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To the memory of Christian B. Anfinsen,

without whose insights into the structure of protein molecules much of what is written here could not have been accomplished.

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CONTENTS

PREFACE

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Antigen-Specific T-cell Receptors and Their Reactions with Natural Complexes Formed by Peptides with Major Histocompatibility Complex Proteins HERMAN N . EISEN, YURISYKULEV, AND THEODORE J. TSOMIDES Overview . . . . . . . . . . History and Background . . . . . . . T-cell Receptor Genes . . . . . . . T-cell Receptor Proteins . . . . . . . T-cell Receptor Ligands: Peptide-MHC Complexes T-cell Responses to PepMHC . . . . . T-cell Receptor Accessory Proteins . . . . Altered Peptide Ligands: Partial Agonists and Antagonists . . . . . . . . . . IX. MHC Restriction by Self and Nonself MHC: Paradox of Alloaggression . . . . . . . . . X. Concluding Remarks . . . . . . . References . . . . . . . . . .

I. 11. 111. IV. V. VI. VII. VIII.

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1 3 8 11 15 22 39

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57 68 74 79

X-Ray Crystallography of Antibodies EDUARDO A. PADUN

Introduction . . . . . . . . . X-Ray Crystallography of Whole Antibodies . . X-Ray Crystallography of Fc . . . . . . X-Ray Crystallography of Antigen Binding Fragments X-Ray Crystallography of Complexes of Antibodies with Specific Ligand . . . . . . . . . VI. Conclusions . . . . . . . . . . References . . . . . . . . . .

I. 11. 111. IV. V.

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87 125 128

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CONTENTS

Vlll

Insight into Antibody Combining Sites Using Nuclear Magnetic Resonance and Spin Label Haptens

HARDEN M. MCCONNELL AND MARIAMARTINEZ-YAMOUT I. Introduction . . . . . . . . 11. Antibodies ANOn . . . . . . . 111. Difference Spectra . . . . . . . IV. Selective Deuteration . . . . . . V. NMRSignalAssignments . . . . . VI. Diamagnetic Haptens . . . . . . VII. Distance Titrations . . . . . . . VIII. Combining Site Dynamics and Reaction Kinetics IX. Crystal Structure ofAN02 . . . . . X. Conformational Heterogeneity . . . . XI. Synopsis and Outlook . . . . . . . . . . . . . . References .

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135 136 138 138 139 141 143 143 144 145 147 148

Computational Biochemistry of Antibodies and T-cell Receptors JIRI

NOVOTNY AND JURCEN BAJORATH

I. Background . . . . . . . . . . 11. Tools of Computer Analysis . . . . . . 111. Structures, Sequences, and Superfamilies . . . IV. Molecular Anatomy of Antibody Binding Site . . V. In Search of Effector Sites . . . . . . VI. Protocols for Three-Dimensional Modeling of Binding Sites . . . . . . . . . . . VII. Binding Affinity and Specificity . . . . . VIII. Molecular Basis of Protein Antigenicity . . . IX. Antibody Engineering . . . . . . . X. T-cell Receptor Modeling and Engineering . . References . . . . . . . . . .

150 154 162 168 173 177 194 213 220 232 236

Catalytic Antibodies

EDWARD M. DRICCERS AND PETER G. SCHULTZ

. . . . . I. Introduction 11. Immunological Evolution of Catalysis 111. Structural Studies . . . .

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261 262 266

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CONTENTS

IV. V. VI. VII. VIII.

Evolving Functions Not Yet Found in Nature Unnatural Cofactors . . . . . . Difficult ChemicalTransformations . . Future Directions . . . . . . Conclusion . . . . . . . . References . . . . . . . .

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270 273 275 280 283 284

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289 290 298 300 303

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The Nature of the Antigen MICHAEL SELA AND ISRAEL PECHT

I. 11. 111. IV. V. VI. VII. VIII. IX. X. XI.

. . . . . . . Introduction Antigens, Antigenicity, Immunogenicity . Molecular Criteria forhtigenicity . . Role ofConformation inhtigenicity . . Antibody-Antigenic Epitope Interactions . Conformational Transitions Induced by Hapten Binding . . . . . . . . . T-Cell-Antigenic Epitope Interactions . . Thymus-Independent Antigens . . . Superantigens . . . . . . . Tumor Antigens . . . . . . . Concluding Remarks . . . . . References . . . . . . . .

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306 31 1 316 319 32 1 323 323

Antibody Binding Sites S. HUSTON, MICHAELN. MARGOLIES, AND EDGAR HABER I. Overview . . . . . . . . . . . 11. Protein Chemistry of Antibody Fragments and Antigen Binding Regions . . . . . . . . . . . . . . . 111. Engineered Antibody Binding Sites IV. Antibody Combining Site Structure: Antiarsonate and . . . . . . . . Antidigoxin Antibodies V. Enhancing Enzyme Selectivitywith Substrate-Selective Antibodies . . . . . . . . . . . References . . . . . . . . . . . JAMES

330 330 347 380

427 439

CONTENTS

X

Maturation of the Immune Response CESAR

MILSTEINAND MICHAEL S. NEUBERGER

. . . . . . . . . I. Introduction 11. Genetic and Structural Diversity of Primary Repertoire 111. Available Repertoire and Onset of Immune Response IV. Hypermutation . . . . . . . . . V. Antigenic Selection . . . . . . . . . . . VI. Structural and Evolutionary Implications References . . . . . . . . . . AUTHOR INDEX SUBJECT INDEX

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45 1 454 46 1 464 470 477 48 1 487

525

PREFACE

Immunology began at the end of the nineteenth century when Paul Ehrlich became fascinated by precipitation reactions in the serum of immunized animals. His work was followed by a systematic analysis by Karl Landsteiner of the exquisite specificity of what we now know to be the antigen-antibody interaction. Yet the precipitin reaction remained in the realm of phenomenology until the 1950s, during which Rodney Porter and Gerald Edelman defined the modular structure of the antibody molecule and demonstrated that antigen binding was the property of only one domain of this multifunctional molecule. Renaturation experiments from my laboratory and those of Michael Sela and Charles Tanford soon implied that there had to be a great many different antibody molecules to account for the wide range of antigen binding specificities, since the amino acid sequence of an antibody determined its specificity. After the earliest amino acid sequences of myeloma proteins (homogeneous surrogates for the very heterogeneous serum antibodies) became available in 1965 from Norbert Hilschmann and Lyman Craig, it was apparent that a hypervariable region accounted for the antigen binding domain. The ability to clone examples of real antibodies by the hybridoma method of George Kohler and Cksar Milstein then led to a surge of activity in the 1970s that defined many aspects of the structure and function of the antigen binding site. Soon it was clear that the same principles of binding applied not only to humoral antibodies but to T-cell receptors and many members of what we now call the immunoglobulin superfamily. Interest in antigen binding waned for a decade while the detailed mechanisms of the cellular immune response were explored and defined. Now in the 1990s we are witnessing a revival of interest in antigen bindings as its broad relevance to many immunologic processes has become apparent and a variety of new analytic tools have allowed for deeper insights into the nature of antigen binding. Advances in molecular engineering permit the recapitulation of clonal selection and affinity maturation of antibodies in vitro. It is possible to produce antibodies to selected antigens without the mediation of an animal host, and it is even possible to turn an antigen binding site into a highly selective enzyme. This volume brings the reader up to date on the covalent and threedimensional structures of the antibody molecule’s antigen binding domain and the synthesis and use of this domain as a separate small molecule. The reader will find a full account of antibody three-dimensional structure (as xi

xii

PREFACE

revealed by x-ray crystallography and computational biochemistry) as well as an analysis of how antigens bind. The nature and the structure of an antigen are defined, and the affinity maturation of antibodies is examined in relation to gene structure and diversification. The exciting field of catalytic antibodies has advanced to include a range of enzymatic functions not even contemplated when the first examples were described a few years ago. The T-cell receptor, which has some elements in common with the antibody molecule, is far more complex in its antigen recognition function. The T-cell receptor is analyzed here in the context of its binding to antigen and to the essential major histocompatibility complex. The role of the T-cell receptor’s accessory proteins in binding and activation is also defined. Not only immunologists but also biologists and chemists should profit from reading this volume: it reveals a mature yet evolving field of broad interest to other areas of science. EDGAR HABER

ANTIGEN-SPECIFIC T-CELL RECEPTORS AND THEIR REACTIONS WITH COMPLEXES FORMED BY PEPTIDES WITH MAJOR HISTOCOMPATIBILITYCOMPLEX PROTEINS By HERMAN N. EISEN, YURl SYKULEV, and THEODORE J. TSOMIDES Center for Cancer Research and Department of Biology Massachusetts Institute of Technology Cambridge, Massachusetts02139

I. 11. 111. IV. V. VI.

VII.

VIII. IX. X.

Overview ............................................... History a ound . . . . . . . . . . T-cell Receptor Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T-cell Receptor Proteins T-cell Receptor Ligands: Peptide-MHC Complexes. . . . . . . . . . . . . . . . . . . . T-cell Responses to PepMHC A. Affinity: Intrinsic Equilibri B. Kinetics . . . . . . . . . . . . . . . . . C. Time Required to Approach .......................... D. Epitope (PepMHC) Density E. TCR-PepMHC Engagement: .................... F. Specificity, Degenerac T-cell Receptor Accessory Proteins. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. C D 3 a n d c . . . . . . . . . . . B. C D 4 a n d C D 8 . . . . . . . . Altered Peptide Ligands: Partial Agonists and Antagonist MHC Restriction by Self and Nonself MHC: The Paradox Concluding Remarks. . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 3 8 11 15

22 23 26 29 30 32 35 39 39 40 41 43 47 48

I. OVERVIEW

The most distinctive feature of the vertebrate immune system is its ability to recognize an enormous number of organic molecules and molecular complexes, termed antigens, distinguishing broadly between those that are foreign to the responding animal (nonself) and those that are indigenous (self). This property is due to antigen-specific receptors on lymphocytes, small cells that comprise -5% of all cells in the body (estimated at 101'-lO1z out of about loL3 cells in an adult human). The receptors on the two major classes of lymphocytes, B and T cells, are similar structurally but profoundly different functionally. On B cells the receptors ADVANCES I N PROTEIN CHEMISTRY W1. 49

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Copyright 63 1996 by Academic Press, Inc. All rights of reproduction in any form reselved.

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HERMAN N . ElSEN ET AL.

are immunoglobulins (Ig) embedded in the cell surface as integral membrane proteins; in response to recognition of antigens, B cells produce large amounts of the receptors and secrete them as soluble antibody molecules. The antigen-specific receptors on T cells (T-cell receptors or TCR) are also Ig-like cell surface integral membrane proteins; their recognition of antigens triggers T cells to exercise a great variety of functions but not to secrete the receptors. Both Ig and TCR molecules are heterodimers, each subunit consisting of two or more domains, with each domain having a characteristic threedimensional shape called the Ig fold. The N-terminal domains (termed variable or V domains) differ in amino acid sequence from one lymphocyte clone to another. The variable domains of each heterodimer pair to form a single antigen binding site that determines the unique ability of each clone to recognize and respond to only very few of the millions of different antigens to which an individual animal can respond. The enormous diversity of B- and T-cell receptors arises from the many germline gene segments that encode them; as each lymphocyte matures, different combinations of these segments are joined (combinatorial diversity) and additional variations in sequence are introduced at the junctures (junctional diversity), leading to an immense number of variable domain sequences. Despite extensive similarities in amino acid sequence between Ig and TCR and in the organization and recombination of the gene segments that encode them, these receptors differ remarkably in the universe of antigens they recognize. The antigens recognized by antibodies (or their membranebound form on B cells) vary enormously: Physically they may be soluble, colloidal, particulate, or parts of virions or microbial or eukaryotic cells, and chemically they may be proteins, peptides, carbohydrates, lipids, nucleic acids, or any of a limitless number of diverse small organic molecules. In contrast, the TCR reviewed here normally recognize and respond only to complexes formed between small peptides and a specialized set of proteins encoded by the major histocompatibility complex (MHC). Because MHC molecules (sometimes called histocompatibilityantigens) are integral membrane proteins, these complexes (termed pepMHC) are confined to cell surfaces, and the TCR of a T cell is therefore normally able to recognize antigenic complexes only on the surfaces of other cells, called antigen presenting cells or target cells. Inasmuch as both TCR and their natural pepMHC ligands are embedded in cell surface membranes, analysis of their interaction at the molecular level poses a major challenge. Later in this review we focus on how this challenge is being met and emphasize recent results that illuminate the way in which TCR react with (or “recognize”) their natural pepMHC ligands, particularly the TCR on those T cells (called cytotoxic T lymphocytes or CTL) that destroy other cells (termed target cells).

ANTIGEN-SPECIFIC T-CELL RECEPTORS

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11. HISTORY AND BACKGROUND The immune system has been under study for about 100 years, but only in the past 30 years have T and B cells been distinguished and only in the past 12 years have TCR molecules and the genes encoding them been identified. Nevertheless, for decades before T cells and TCR emerged as recognized entities, their existence was foreshadowed by certain antigenspecific inflammatory responses produced by injecting antigens into the skin of individuals with previous exposure to such antigens, either through natural infection of deliberate inoculation (immunization). Around 1890, Robert Koch showed that the injection of tubercle bacilli (or a mixture of proteins called “tuberculin” from supernatants of tubercle bacilli cultures) elicited an intense inflammatory response in guinea pigs if they had been previously infected with these microorganisms. The responses appeared 1 2 4 8 hr following antigen injection, and similar delayed-type hypersensitivity (DTH) responses, always specific for the original inciting antigen, were subsequently demonstrated with crude protein mixtures from many other microbes (bacteria, fungi, and later, viruses). Responses sometimes occurred following deliberate immunization with purified proteins (e.g., ovalbumin) or even with small organic molecules applied to the skin, providing they reacted in situ to form covalent derivatives of skin proteins (as with 2,4-dinitrochlorobenzene,or a catechol in the case of poison ivy). In contrast to the late appearance of DTH responses, many other antigen-specificskin responses appear almost immediately, e.g., within 1 min or sometimes 2-3 hr. Because the transfer of serum antibodies from an immunized to a nonimmunized (naive) individual confers on the recipient the same prompt antigen-specific responses, it was clear that these rapid or immediate-type responses were mediated by antibodies. But serum failed to transfer the delayed-type responses (e.g., to tuberculin). Although efforts were made to reconcile these failures with a role for special antibodies, it came to be widely believed that antigen-specific cells rather than soluble antibody molecules were the direct mediators of DTH responses. This belief was supported by the finding that DTH responses could be transferred to naive recipients with inflammatory cells from immunized donors, although the transferred cells were complex mixtures of leukocytes that probably included some antibody-forming cells. The resolution of all doubt came after T cells were distinguished from B cells, largely through studies involving extirpation of the thymus from newborn mice. These studies led to the establishment of a clear dichotomy between those lymphocytes that develop from immature precursors in the thymus (T cells) and those that develop to maturity in the bone marrow (B cells). B cells were shown to be the source of Ig and antibodies, and T cells were

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HERMAN N . EISEN ET AL

shown to be required for the optimal production of antibodies. In addition, highly purified populations of T cells could transfer DTH responses, suggesting that T cells bear receptors that recognize antigens. Early studies on the nature of the antigen-recognizing receptors on T cells were marked by intense disagreements arising largely, it appears in retrospect, because the T-cell populations studied were often contaminated by small numbers of B cells and because reliance was placed almost exclusively on serological analyses using anti-Ig antisera. Antigen-specific molecules on T cells were variously suggested to be Ig molecules firmly attached to T cells, to be some other (non-Ig) type of cell-associated protein, or to be some other type of nonprotein informational macromolecule. The debate was resolved by the development of monoclonal antibody (MAb) technology and the ability to grow T-cell clones in culture. Using MAb raised against T-cell clones, one a malignant lymphoma and the others normal T cells, three independent studies succeeded in immunoprecipitating a T-cell surface protein that was unique to cells of the immunizing clone (Allison et al., 1982; Meuer et al., 1983; Haskins et al., 1983). The clonally specific (or clonotypic) protein was in each case a disulfidelinked heterodimer (-90 kDa) consisting of a relatively acidic membranebound a chain and a more basic membrane-bound p chain. The idea that these clone-specific heterodimers were antigen-specific receptors was strengthened by two findings. First, antibodies against them could block antigen-driven responses of the corresponding T-cell clones (Lancki et al., 1983). Second, amino acid sequences of proteolytic fragments from isolated a and p subunits suggested that, like Ig heavy and light chains, they had some regions where amino acid sequences varied from clone to clone and others where these sequences were invariant (Kappler et al., 1983; Meuer et al., 1984; McIntyre and Allison, 1983). The isolation and sequencing of cDNA clones for the b subunit (Yanagi et al., 1984; Hedrick et al., 1984; Saito et al., 1984a) and then for the a subunit (Saito et al., 1984b; Chien et al., 1984) finally demonstrated unambiguously that the clonally diverse heterodimers greatly resembled Ig and had all the characteristics expected of cell surface integral membrane proteins serving as antigen-specific receptors. Moreover, introduction of genes for both the a and /3 subunits into a T-cell clone having unrelated specificity transferred the antigen-specific responsiveness of the donor cell to the recipient cell (Dembic et al., 1986; Saito et al., 1987). In the course of searching a T-cell cDNA library for clones for the a and p subunits, cDNA for a third related subunit was found (Saito et al., 1984a). Termed y, the third gene turned out to encode an Ig-like chain that paired with the Ig-like product of a fourth gene, 6, to form a y6 heterodimer (Chien et al., 1984). Closely similar to the ab TCR, y6 heterodimers are

ANTIGEN-SPECIFIC T-CELL RECEPTORS

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another type of antigen-specific receptor found on a subset of T cells located primarily in epithelia. yd cells constitute about 1-5% of peripheral T cells in mice and humans; these TCR will not be considered further here, as their natural ligands are not as well-defined as those recognized by aB TCR and the hnction of yd T cells is still not clear. Ten years before the molecular identity of the ab TCR began to take shape, several observations pointed to the special character of its natural ligands. By transferring T cells to athymic (nude) mice, Kindred and Shreffler (1972) saw that these cells reacted only when the T cells and the recipients had the same MHC type. The ineffectiveness of MHC-dispartate T cells could not be attributed to their immune elimination in the recipient because athymic mice do not reject allografts (see Alloaggression, Section IX). It was therefore concluded that the MHC “must play an active role in ensuring cooperation between B and T cells.” Shortly thereafter, in vitro studies of T-cell enhancement of the production of antibodies by B cells (Katz et al., 1973) and of T-cell responses to antigens presented by macrophages (Rosenthal and Shevach, 1973) clearly indicated that successful T-cell responses required the responding T and B cells, or T cells and macrophages, to have the same MHC type. Then, in a seminal publication, Zinkernagel and Doherty (1974) reported that virusinfected target cells were lysed by T cells from a mouse infected by that virus only if the target cells expressed the same MHC products as the infected animal. Work with different antigens revealed similarly that antigenspecific lysis of antigen-bearing target cells by cytotoxic T cells depended on target cell expression of a proper MHC protein (Shearer, 1974; Bevan, 1975; Gordon et al., 1975).This dual requirement of antigen recognition, referred to as “MHC restriction” (Zinkernagel and Doherty, 1979), has since been found to be characteristic of all a/?TCR-mediated reactions. To explain MHC restriction, two models were proposed. In the tworeceptor model, T cells had one receptor for an MHC product and another for antigen, and both had to be occupied for a successful T-cell response (Cohn and Epstein, 1978). According to the alternative onereceptor model, each T cell had a single type of receptor that recognized an antigen-MHC complex. The one-receptor model was shown to be correct by various approaches. In one, a hybridoma resulting from the fusion of two cells recognizing antigen A and MHC X or antigen B and MHC Y responded specifically to cells expressing either A + X or B + Y but not to those expressing A + Y or B X, indicating that the T cell did not see the antigen and the MHC product separately (Kappler et al., 1981). The antigeneMHC complex was sometimes referred to as “altered self’ because in this context the restricting MHC is indigenous (self) with respect to the responding T cells and is therefore nonimmunogenic, while the

+

+

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HERMAN N. EISEN E T AL

antigen is foreign (nonself) and somehow alters the character of self MHC, imposing “foreignness” and ability to elicit a reaction. Mature T cells bearing ap TCR fall into two groups, each marked by one of two cell surface glycoproteins. Termed CD4 and CD8 (formerly called Lyt-1 and Lyt-2,3 in the mouse), both are present on,immature (double positive) T cells in the thymus, and one of them is lost by what appears to be a stochastic process (Corbella et al., 1994) to yield single positive (CD4+ or CD8+) mature T cells. Some mature CD4+ T cells, termed helper (Th2) cells, are required for optimal B-cell responses, while other helper cells (Thl) produce cytokines that cause inflammation, as in DTH responses. In contrast, CD8+T cells, which also produce some cytokines, behave primarily as CTL, lysing target cells that bear appropriate antigenic MHC complexes. The CD4/CD8 T-cell dichotomy also extends to the types of MHC protein that restrict antigen recognition. Class I MHC proteins (MHC-I) restrict antigen recognition by CD8+ T cells, and class I1 MHC proteins (MHC-11) restrict antigen recognition by CD4+ T cells (Table I). Virtually all cells express MHC-I and can present peptides to CD8+ cells, whereas only specialized cells (principally macrophages, dendritic cells, and B cells) express MHC-I1 for interactions with CD4+ cells. In common usage, cells that present pepMHC-I1 complexes to CD4+ cells are called antigen presenting cells (APC), whereas those that present pepMHC-I complexes to CD8+ CTL are termed target cells. Once it became established that a single heterodimeric receptor on T cells reacts with an antigen displayed on the surface of another cell and TABLE I

Peptide Binding to MHC-I and MHC-II Molecules Parameter Distribution Domain structure Accessory molecule Typical T-cell response Origin of most bound peptides Length of bound peptides Pockets in MHC groove Peptide N and C termini Many critical contacts Equilibrium constant, Ka

MHC-I

All nucleated cells az, a3

+ Pzm

CD8 Cytolytic activity Cytosolic (endogenous) Usually 8-9 residues Yes Buried in groove Peptide side chains -104-109 M-I measured

MHC-I1 Specialized APC al, a2 + P I ,PZ CD4 B-cell help, DTH Extracellular and membranous proteins Variable, 12-25 residues Yes May extend outside groove Peptide backbone 106-1 OH h.T’measured

-

-

ANTIGEN-SPECIFIC T-CELL RECEPTORS

7

that the antigen includes both a self (restricting) MHC protein and a bona fide foreign element (such as a virus-encoded protein), it was reasonable to assume that the MHC protein and the foreign protein combine to form an antigenic complex in the plasma membrane of the target cell (e.g., Cohen and Eisen, 1977). However, the subsequent finding that T cells responding to viral infections are paradoxically specific for intracellular proteins not found at the cell surface (e.g., influenza virus nucleoprotein) (Townsend and McMichael, 1985; Yewdell et al., 1985) led Townsend and colleagues to the discovery that short peptides (about 8-25 amino acids in length) derived from internal viral proteins can sensitize target cells bearing appropriate MHC molecules for lysis by CD8+ T cells (Townsend et al., 1986). It has since become clear that (1) the natural ligands for TCR are cell surface complexes each consisting of a short peptide and an MHC protein (a pepMHC complex); (2) under normal conditions the peptides are produced intracellularly by limited proteolysis of intracellular proteins (processing) and are then transported as pepMHC complexes to the cell surface (reviewed by Heemels and Ploegh, 1995); and (3) this physiological pathway can be circumvented by adding, to whole cells, synthetic peptides that bind directly to a subset of cell surface MHC molecules that are free of naturally processed peptides or bind them weakly and lose them readily by dissociation. The idea that fragmented protein antigens, i.e., peptides, can be recognized by T cells actually emerged from the earlier studies of Unanue and Allen (1987) on antigen presentation to CD4+ T cells by MHC-I1 on APC. Indeed the first unequivocal and quantitative demonstration of the binding of a defined peptide to an MHC molecule was obtained for MHC-I1 (Babbitt et al., 1985). In mice and humans, MHC-I proteins are encoded by genes at three linked loci (termed K, D, and L in mice, and A, B, and C in humans), and MHC-I1 proteins by several genes at two or three linked loci (termed IA and IE in mice, and DP, DQ, and DR in humans). Most of these genes are extremely polymorphic, some having as many as 50 (or more) allelic variants. Any particular individual inherits alleles for only a small number of MHC proteins, at most six MHC-I and six MHC-I1 in humans, because of heterozygosity at each gene locus. Some inbred mouse strains have only two MHC-I proteins and a single MHC-I1 protein. Remarkably, however, these few proteins can effectively present an enormous number of different peptides to a vast number of TCR, each MHC protein having the capacity to bind to thousands of different peptides with equimolar (1 :1) stoichiometry. Although some peptides can be bound by more than one MHC protein, each MHC protein binds to distinctly different sets of peptides. How each of these protein molecules is able to bind to so many different peptides, and yet retain a significant degree of selectivity, has

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HERMAN N. EISEN E T AL.

become clear as a result of striking advances over the last 5 years, particularly in the solution of several three-dimensional structures of crystallized pepMHC complexes (see Section V).

111. T-CELLRECEPTOR GENES

The genes that encode TCR a and chains are assembled in developing T cells in the thymus by the juxtaposition of variable (V), diversity (D), and joining (J) gene segments to form VJ or VDJ or VDDJ exons, separated by a short intron from an exon for the constant (C) domain. The great similarity in organization of TCR and Ig gene segments is striking (Davis, 1990) and includes the canonical heptamer and nonamer signal sequences adjacent to V, D, and J segments; these signal sequences are almost the same for TCR and Ig genes and indeed are interchangeable (Yancopoulos et al., 1986). TCRP gene segments are spaced over 700-900 kb of human (or mouse) DNA, with an array of multiple VP segments separated from two tandemly duplicated sequences each including one DP, six JP, and one CP segment. All these segments have the same transcriptional orientation except for one downstream VP segment (Fig. 1). TCR a gene segments are also distributed in a long, linear array, but these were found surprisingly to be interrupted by J and C sequences of the TCR 6 chain (Chien et al., 1984). The pairing of a 6 with a y chain forms the yd heterodimeric receptor on the small subset of T cells (yd+) referred to previously. Because a single locus contains gene segments for both a and y chains, the rearrangements and expression of a and y genes are regulated by an intricate process (Winoto and Baltimore, 1989; Diaz et al., 1994). Evidently, a V gene from the same upstream array in this locus can join either to Jd (or Dd and Jd

5 4

4 “VVY JyCyl

“y

Jut*

- - -

VY Cfl(‘r)

-C)-..e...++t...+...+...i)c - -

TcRy

FIG 1. Arrangements of V (variable), D (diversity), J (junction), and C (constant) TCR gene segments in three loci in the mouse genome. Transcriptional orientation is indicated by arrow. (From Davis, 1990.)

ANTIGEN-SPECIFIC T-CELL RECEPTORS

9

segments) to form a complete VJSCS (or VDSJSCS) sequence for a Q chain, or to one of many Ja segments to form a complete VJaCa sequence for an a chain. In T cells that express an a/3TCR, the joining of a V gene to a Ja eliminates 6 gene sequences and thus precludes expression of a 6 chain. In T cells that express yS receptors, the joining of a V segment to a DS and/or JS takes place first and evidently suppresses subsequent rearrangements involving a gene segments. Despite many similarities in the organization of Ig and TCR genes and their extensive amino acid sequence homology, they differ in the following important respects. 1. Localization of hyperuariable sequences in TCR V domains. In Ig there are three especially variable (hypervariable) regions in V domains of light and heavy chains, and X-ray crystallographic studies show that these form the boundaries of antigen binding sites of antibodies (Davies et al., 1990). Because they determine the complementary fit of antibody to antigen, they are referred to as complementarily determining regions or CDR (i.e., CDRl, CDR2, and CDR3). Comparisons of the amino acid sequences of a and /3 variable domains from many TCR have shown that, in contrast to those of Ig, the CDRl sequences of a/3 TCR vary very little and the CDR2 sequences vary only slightly more, but that the CDR3 sequences vary considerably in length and sequence. The great variation in CDR3 reflects the very large number of TCR J gene segments as compared with those for Ig genes (e.g., about 50 Ja and 12 J/3 segments in contrast to 4J H and 5 J K segments for murine Ig). As discussed later, the extensive variation in CDR3 and J sequences suggests that the most diverse element of the pepMHC ligand that binds to a T-cell receptor, the peptide moiety, might make contact primarily with the CDR3 region of the receptors, whereas the less variable flanking a-helical regions of the MHC protein might make contact primarily with CDRl and CDR2. 2. Alternative RNA splicing. Alternative splicing of RNA transcripts of Ig genes plays a critical role in modifying the 3' ends of mRNA in order to generate proteins that are secreted as antibodies or retained as cell surface antigen-specific B-cell receptors. In contrast, RNA splicing is not involved in the expression of TCR genes, and TCR molecules are not secreted; they invariably remain as integral membrane proteins on T-cell surfaces. 3. Isotype switching. Gene sequences for the V domains that determine the specificity of antibodies for antigens can be spliced to one of several different immunoglobulin C regions to yield various forms of heavy chains called isotypes. Different Ig isotypes have different functional roles: For example, certain isotypes bind to receptors on B cells and macrophages, certain others can be transported across the placenta, and still others bind

10

HERMAN N . EISEN ET AL

to receptors on mast cells to mediate anaphylactic reactions. During the course of normal B-cell differentiation, switching of isotypes can occur (with no change in antigen specificity). For TCR, there is no comparable switching because there are no forms homologous to Ig isotypes. 4. Somatic mutation. A distinctive feature of the antibodies produced in response to antigenic stimulation is the progressive increase over time in the intrinsic affinities of the antibodies made against an antigenic epitope. These changes are the result of extensive somatic mutation that takes place in the V, D, and J regions of rearranged Ig genes during prolonged or repeated antigenic stimulation, together with selection by the antigen of B cells producing high-affinity antibodies (for a recent minireview see Foote and Eisen, 1995). Comparisons among the sequences of several hundred V regions from TCR a and /? mRNA or cDNA failed to reveal systematic evidence for somatic mutation, as the sequences nearly always matched one or another of the germline sequences (Davis, 1990).The important implication is that progressive increases or maturation in the intrinsic affinities of TCR does not occur, and thus TCR affinities for their ligands generally reflect the distribution of affinities arising from germline sequences and variations introduced by joining V, D, and J gene segments. However, Zheng et al. (1994), in a careful analysis of lymphocytes in lymph mode germinal centers (where B cells undergo somatic mutation), found evidence for somatic mutation of TCR V regions. Whether antigen selection of the mutated T cells takes place, as it does for B cells, is not yet clear. 5. Allelic exclusion. In a newly developing, immature thymocyte, productive (in-frame) rearrangement of a V/? gene segment in one chromosome prevents rearrangement of additional V/? gene segments in the other chromosome (Van Meerwijk et al., 1991; Malissen et al., 1992). However, Va segments on both chromosomes rearrange at the same time and can continue to rearrange until a complete ap TCR is formed and the cell is stimulated (by positive selection in the thymus) to mature into a single positive T cell (CD4+ or CD8+). As a result, almost one-third of mature T cells in the periphery carry two productively rearranged a genes and have on their surface two TCR species, differing in the a chain but having the same/? chain (Padovan et al., 1993; Heath and Miller, 1993; Mason, 1994). Because antibodies can bind via their constant (Fc) region to certain receptors (called FcR) on target cells, some antibodies to a TCR can mimic the natural ligand of the TCR and trigger “redirected lysis” of an FcR+ target cell by CTL expressing that TCR (Kranz et al., 1984b), even though the target cell lacks a pepMHC complex that is recognized by the TCR. Thus, a target cell expressing FcR was shown to be lysed by a CTL having two TCR, call them alp1and a$,, in the presence of either antibody to al

ANTIGEN-SPECIFIC T-CELL RECEPTORS

11

or antibody to az,indicating that each TCR of such a two-receptor T cell can, when ligated via its Va domain, trigger T-cell activation (Padovan et al., 1993). This circumstance raises an interesting possibility, not yet critically tested, that a mature two-receptor T cell that is stimulated to proliferate via one TCR will result in an increased number of cells expressing both TCR molecules, perhaps increasing the possibility of reactions with different pepMHC. Because the two receptors on such a T cell would be expected to have different specificities, they might increase opportunities for reactions against autoantigens or MHC-disparate cells (see Section IX). Experiments with mice transgenic for a TCR p subunit suggest, however, that in antigenically stimulated T cells there may be unknown mechanisms that hinder expression of a nonutilized TCR (Hardardottir et al., 1995), as in the case of Ig receptors on B cells transfected with multiple K chain genes (Lozano et al., 1993).

IV. T-CELLRECEITOR PROTEINS Once the primary structures of several T-cell receptors became known through the sequences of their V, D, J, and C genes, it became possible to look for clues regarding their tertiary structures. It was obvious on the basis of sequence homologies that TCR belong to the so-called immunoglobulin superfamily. That is, the domains of a heterodimeric TCR WaVp and CaCP) were expected to have the same chain topology and secondary structure elements as the canonical Ig fold (reviewed elsewhere in this volume). However, this observation did not lead to an understanding of how TCR recognize an antigenic universe consisting of relatively few MHC proteins combined with a great many different peptides (thousands for each MHC protein). Further analyses of sequence homologies between Ig and TCR (roughly 25-30% identity between the two groups) led to more detailed structural predictions. Following the first complete cDNA sequence of the TCR, Novotny et al. (1986) aligned the sequences of TCR a, p, and y chains with those of Ig of known three-dimensional structure and concluded that a TCR molecule was likely to possess a single antigen binding site that is essentially no different from that of an Ig. Later, Chothia et al. (1988) identified 40 amino acid residues critical for the conserved structure of Ig variable domains, either because they serve as framework residues or because they are crucial for interdomain contacts (VL-V, or VH-CHl), and compared them with the corresponding residues in -200 TCR Va and Vp sequences. They found a high percentage of the same or very similar residues at these positions, often 90+% identity, and they also found im-

12

HERMAN N. EISEN E T AL.

portant similarities in the distribution of hypervariable regions between Ig (three such regions per VL or VH chain) and TCR (Va and Vp chains). As mentioned earlier, these noncontiguous hypervariable regions combine in the three-dimensional folded structure of an Ig to form the antigen binding site and are termed complementarity determining regions (CDR). Unlike Ig, however, the first and second predicted CDR of a TCR are much less variable than the third, called CDR3 (approximately residues 95-105 from the N terminus). Building on the discovery that peptides are an integral part of the antigenic structures recognized by T-cell receptors, Davis and Bjorkman (1988) proposed a model for T-cell recognition in which two CDR3 regions (from Va and Vp) interact primarily with peptide, while CDRl and CDR2 (each from both V a and Vp) interact with the two a helices flanking the peptide binding site (see Figs. 2 and 3). These authors also emphasized the greater diversity in TCR CDRS regions than in CDRl and CDR2; the latter are fully encoded by germline V genes, of which there are relatively few, whereas CDR3 is formed by the joining of V and J genes (in TCR a and y) or V, D, and J genes (in TCR /3 and 6 ) . Because of prevalent N-region additions at these junctions (due presumably to terminal deoxynucleotidyltransferase), as well as other mechanisms for diversification, TCR variability is highly concentrated in the CDRS region (Davis and Bjorkman, 1988). Because the MHC sites in contact with a TCR are generally less variable than the peptide residues recognized by a TCR, the preceding model provided a rationale for the greater sequence diversity of CDRS than of CDRl or CDR2; it also accommodated functional data from studies in which variations in only the CDR3 residues within a set of T-cell clones affected peptide recognition but not MHC specificity (Fink et al., 1986; Winoto et al., 1986). Furthermore, this model, independently suggested by Chothia et al. (1988) and by Claverie et al. (1989), was consistent with the dimensions observed in the first crystal structure of an MHC protein (Bjorkman et al., 1987a): The peptide binding groove is -10 A wide and 25 A long (Fig. 2), while the spacing between the predicted CDR3 segments in the TCR is 10-15 A. The two CDRS regions were projected

-

FIG.2. Ribbon diagram of MHC-I and MHC-I1 proteins. Shown for the MHC-I heterodimer are three domains of a or h e p y chain (the polymorphic a1 and a 2 domains, which together form the peptide binding groove, and the conserved a3 domain) and the 82microglobulin or light chain. Shown for the MHC-I1 heterodimer are the two domains for each subunit, i.e., the polymorphic a2 and82 domains. In this view the a helices flanking the peptide binding groove are clearly evident. Although there is virtually no sequence identity between MHC-I and MHC-I1 proteins, their three-dimensional structures are remarkably similar (Brown et al., 1988).(Courtesy of L. J . Stern and D. C. Wiley.)

Class I

Class II

14

HERMAN N. EISEN E T AL.

A

B

FIG. 3. Ribbon diagram of a top view of the peptide binding sites of (A) MHC-I and (B) MHC-I1 proteins (HLA-A2 and HLA-DR1, respectively). Note that the peptide adduct is longer (10-20 amino acids) in MHC-I1 than in MHC-I (8-10 amino acids) proteins. (Courtesy of L. J. Stern.)

ANTIGEN-SPECIFIC T-CELL RECEPTORS

15

to interact with about five residues of a bound peptide (Claverie et al., 1989; see also Section IX). In a revealing study, Jorgensen et al. (1992) immunized mice transgenic for either the a or the /? chain of a particular TCR with a series of variant peptides. Analysis of the T-cell responses in these mice indicated that some peptide variants elicited T cells having complementary charges in the CDR3 regions of their TCR; furthermore, the contact sites for two peptide side chains could be assigned to either the TCR V a or V/?chain. To date, no three-dimensional structure of a complete TCR molecule has been reported. Such a structure is eagerly awaited, not only to illuminate the structure of the TCR itself but hopehlly to explain in molecular terms how the TCR universe of antigens is limited to pepMHC complexes while that of antibodies is virtually limitless. The recently reported structure of a TCR /? chain revealed Ig-like domains and three CDR loops plus an additional hypervariable loop whose significance is not yet clear (Bentley et al., 1995). V . T-CELLRECEPTOR LIGANDS: PEPTIDE-MHC COMPLEXES

Beginning with Townsend and colleagues (Townsend and Bodmer, 1989), a common method for studying the ligands recognized by T cells on various target cells (e.g., virus-infected, tumor, or allogeneic cells) has been to add synthetic peptides to different target cells that express an appropriate MHC protein, forming pepMHC complexes that can elicit a measurable T-cell response. This approach has been successfd in part because the added synthetic peptide need not precisely match the natural ligand (e.g., a processed viral peptide); it can be substantially longer, for example, and then undergo limited trimming by proteases in the assay medium or on cell surfaces to reach the optimal length for binding to an MHC protein. However, in some instances, it is important to know the exact identity of a naturally processed peptide, in order, for instance, to determine the number or density of specific pepMHC complexes on the surfaces of target cells (reviewed in Tsomides and Eisen, 1993a). An understanding of the relationship between the synthetic peptides that can be used to elicit T-cell responses and the naturally processed peptides that are generated within cells has rested on two principal lines of investigation: ( 1) X-ray crystallographic determination of MHC structures; and (2) direct biochemical isolation and sequencing of endogenous peptides associated with MHC molecules. The nature of the MHC and its ligand was greatly illuminated when the first crystal structure of an MHC protein, the human MHC-I protein called HLA-AP, was determined by Bjorkman

16

HERMAN N . EISEN

Er

AL

et al. (1987a). The molecule consisted of four domains of -90 amino acids each, three derived from an a chain (a,,a2,and a3)and one comprising P2-rnicroglobulin V2m). While the membrane proximal a3 and P2m domains resembled Ig domains, a l and az paired to form a novel structure: an eight-stranded antiparallel fi sheet underlying two long a helices (Figs. 2 and 3). Between the two a helices was a continuous region of unassigned electron density later shown to represent a complex mixture of peptides that copurified with HLA-A2; since A2 purification takes several days at least, this observation proved to be the first clue that some naturally processed peptides can form extremely stable complexes with MHC-I proteins, often having dissociation half-lives in the tens of hours (Cerundolo et al., 1991; Tsomides et al., 1991; Olsen et al., 1994).The crystal structure of HLA-A2 furthermore suggested that the unknown peptides harbored between the two a helices might be 8-20 amino acids long, based on the approximate dimensions of the binding site (25 x 10 x 11 A) (Bjorkman et al., 1987b). More precise definition of some natural ligands was achieved through an acid elution technique used to separate peptides from MHC molecules (Buus et al., 1988; Rotzschke et al., 1990a), followed by characterization of the isolated peptides. The first naturally processed peptides to be identified were viral products obtained from infected cells (van Bleek and Nathenson, 1990; Rotzschke et al., 1990b) and were eight or nine residues long. Other MHC-I-associated peptides present at relatively high levels were resolved by high-performance liquid chromatography (HPLC) and sequenced by Edman degradation Uardetzky et al., 1991; Corr et al., 1992) or by the mass spectrometric approach pioneered by Hunt and colleagues (1992a); these peptides proved to arise from a variety of intracellular proteins and were often eight or nine residues in length, though sometimes longer (Henderson et al., 1992; Wei and Cresswell, 1992). Rammensee and colleagues then performed a critical experiment in which they subjected the total pool of peptides eluted from MHC-I molecules to sequencing by Edman degradation (Falk et al., 1991a).While they found each amino acid at virtually every cycle during the Edman procedure, they discovered several key facts about naturally processed peptides: (1) For a given MHC-I protein (such as HLA-A2), the eluted peptides contained a predominance of one or two amino acids at certain key “anchor” positions (e.g., leucine or methionine at position 2, and valine or leucine at position 9); (2) amino acid yields dropped precipitously after nine cycles, suggesting that most MHC-I bound peptides are nonamers (octamers for certain MHC-I molecules); and (3) the “motifs” characterizing peptide length and anchor positions were distinctive for each MHC-I protein. These motifs have been highly useful in the rapid identification of candidate peptides recognized by T cells when the parent protein sequence is

ANTIGEN-SPECIFIC T-CELL RECEPTORS

17

known (Rotzschke et al., 1991a; Pamer et al., 1991). However, this approach is not infallible for several reasons: (1) Some MHC-binding peptides do not conform to the expected motif and therefore will be missed (e.g., Udaka et al., 1992); (2) synthetic peptides found to be active need not always correspond to naturally processed peptides, even when optimized for activity, since heteroclitic reactions can occur for T-cell receptors (Bodmer et al., 1988) as well as for antibodies; and (3) nonphysiological crossreactions can be observed when target cells are sensitized with high doses of synthetic peptides because of the resulting artificially high pepMHC densities (Milligan et al., 1990; Schild et al., 1990; Dutz et al., 1994; Tsomides et al., 1994). Despite these caveats, several naturally processed peptides recognized by T cells have turned out to match precisely the peptides predicted from motifs (Rotzschke et al., 1990b, 1991a; van Bleek and Nathenson, 1990; Pamer et al., 1991; Tsomides et al., 1994) (Table 11), leading to the reasonable assumption that this is often the case. All the biochemical information about naturally processed peptides bound to MHC-I molecules fits neatly with the emerging crystallographic data. Monopeptidic pepMHC complexes were obtained and crystallized, revealing important structural similarities and differences among peptides binding to the same MHC-I molecule (Fremont et al., 1992; Zhang et al., 1992; Madden et al., 1993).Pockets within the MHC binding site were shown to accommodate peptide side chains at the positions described as anchors (Garrett et al., 1989; Matsumura et al., 1992a; Young et al., 1994). Peptides longer than nine residues could fit by bulging out in the middle, with both peptide termini substantially buried in the binding site (Guo et al., 1992). Within a short time, a coherent picture emerged of how a single MHC molecule can bind selectively to an enormously diverse variety of peptides. Comparable findings (peptide motifs, MHC pockets) were later made for MHC-I1 molecules, although in this case the situation proved more complex. Naturally processed peptides binding to MHC-I1 molecules turned out to include sets of nested peptides sharing a core sequence but having different N and C termini (Demotz et al., 1989; Nelson et al., 1992; Chicz et al., 1992). These peptides tended to be longer than those eluted from MHC-I proteins, ranging from about 12 to 25 residues (Rudensky et al., 1991; Hunt et al., 1992b). Again, this information correlated well with the results of crystallography. The structure of an MHC-I1 molecule complexed with endogenous peptides (Brown et al., 1993) or with a single viral peptide (Stern et al., 1994) revealed two major differences from MHC-I: (1) The MHC-I1 binding groove allows bound peptides to extend out at both ends rather than having their termini tucked into the binding site, thereby explaining the length heterogeneity among naturally occurring MHC-I1 associated peptides (see Fig. 3B); and (2) many of the peptide-

TABLE 11

Naturally Processed Peptides Associated with MHC Molecules" Class and MHC protein Class I H-2Kd H-2Db H-2Kh H-2Kb H-2Kd H-219 H-2Ld HLA-A2.1 HLA-A2.1 Class I1 IAb

IEb

IAk

HLA-DR1

Peptide origin Influenza NP 147-155 Influenza NP 366-374 Vesicular stromatitis virus NP52-59 Ovalbumin 257-264 Listeria monocytogenes listeriolysin 91-99 Mouse a-ketoglutarate dehydrogenase Mouse a-ketoglutarate dehydrogenase HIV-1 reverse transcriptase 476-484 HIV-I gag 77-85 Murine leukemia virus envelope 145-1 57 145-158 I-E a chain 56-73 Invariant 39-53 Murine leukemia virus envelope 454-467 454-468 454-469 Bovine serum albumin 141-154 Hen egg lysozyme 48-60 48-6 1 48-62 52-64 Invariant chain 105-118 105-1 19 96-1 18' 96-1 19' 96-120' 97-1 18' 97-1 19' 97-120' 98-1 18' 98-1 lgL 99-1 18'

Peptide sequence'

Refs.

SIINFEKL GYKDGNEYI

Rotzschke et al. (1990b) Rotzschke et al. (1990b) Van Bleek and Nathenson (1990) Rotzschke et al. (1991a) Pamer etal. (1991)

LSPFPFDL

Udaka et al. (1992)

VAITRIEQLSPFPFDL

Udaka et al. (1993)

ILKEPVHGV

Tsomides et al. (1 994)

SLYNTVATL

Tsomides et al. (1994)

HNEGFWCPGPHR HNEGFYVCPGPHRP ASFEAQGALANIAVDKA KPVSQMRMATPLLMR

Rudensky el al. (1991)

SPSYVYHQFERRAK SPSYVYHQFERRAKY SPSYVYHQFERKAKYK

Rudensky et al. (1991)

TYQRTRALV ASNENMETM RGYVYQGL

GKYLYEIARKHPYF DGSTDYGILQINS DGSTDYGILQINSR DGSTDYGILQINSRW DYGILQINSRWWC

Nelson et al. (1993)

KMRMATPLLMQALP KMRMATPLLMQALPM LPKPPKPVSK ...P LPKPPKPVSK...PM LPKPPKPVSK...PMG PKPPKPVSK...P PKPPKPVSK...PM PKPPKPVSK...PMG KPPKPVSK...P KPPKPVSK...PM PPKPVSK...P

Chicz el al. (1992)

' Adapted from Tsomides and Eisen (1993a).

'

Only MHC-I binding natural peptides that are recognized by established T-cell clones are shown; MHC-I binding sequences identified on the basis of their relatively high abundance are not included. ' For brevity, invariant chain residues 106-1 17 are represented by ellipses (...).

ANTIGEN-SPECIFIC T-CELL RECEPTORS

19

MHC-I1 contacts involve the peptide backbone rather than specific peptide side chains, implying different mechanisms for degenerate peptide binding by MHC-I and MHC-I1 proteins (Table I). Once it was appreciated that purified MHC-I molecules are normally occupied by stably bound endogenous peptides, the failure of early attempts to demonstrate significant peptide binding to purified MHC-I molecules (Chen and Parham, 1989; Tsomides and Eisen, 1990) became understandable. Soon techniques based on whole-cell binding assays (Christinck et al., 1991), MHC-I immunoprecipitation from cell lysates (Cerundolo et al., 1991), or in vitro binding to empty MHC-I molecules purified from transfected Drosophila cells (Matsumura et al., 199213; Saito et al., 1993) or other cells (Boyd et al., 1992; Ojcius et al., 1993; Fahnestock et al., 1994) allowed the measurement of equilibrium binding constants for a wide variety of peptide-MHC-I reactions. Parker et al. (1992, 1994) used ppm dissociation as a surrogate indicator for the stability of pepMHC-I complexes, and Olsen et al. (1994) found that peptides were able to bind well to purified MHC-I molecules at reduced temperatures. Each of these experimental systems suffers from certain limitations, a shared one being that the binding of synthetic peptides to fully formed MHC-I molecules may not accurately mirror events in the ER, where this reaction ordinarily takes place. Nevertheless, these equilibrium values seem to reflect the specificities otherwise observed for peptide-MHC-I reactions, and similar measurements have proved useful as indicators of potential peptide immunogenicity (Feltkamp et al., 1993; Celis et al., 1994; Sette et al., 1994). Given the ability to measure equilibrium constants for the peptideMHC reaction, the number of pepMHC complexes per target cell required to trigger the activity of a given T-cell clone can be estimated in assays where T-cell activity depends on the concentration of synthetic peptides (added to the extracellular medium). The estimates are based on the Karush (1970) form of the law of mass action (Day, 1990):

r = Kcnl(1 + Kc)

(1)

In Eq. ( l ) , r is the number of pepMHC complexes per target cell, K is the equilibrium association constant for a peptide-MHC reaction, c is the free concentration of peptide that sensitizes target cells for a particular level of lysis (e.g., half-maximal) by a given CTL, and n is the total number of MHC binding sites per target cell accessible to extracellular peptide. For several reasons, the calculated values of r should be regarded as only reasonable approximations, e.g., because the peptide may be subject to proteolytic degradation during the assays. More importantly, the number of accessible sites ( n )changes over time as newly synthesized MHC molecules migrate to the target cell surface and some (unknown) proportion have accessible peptide binding sites, either because they are empty or because

20

HERMAN N . EISEN E?’ AL.

they are occupied by rapidly dissociating natural peptides that exchange readily with peptides in the extracellular medium. Nevertheless, Eq. (1) yields reasonable approximations for those peptides whose reactions with MHC (on intact cells) reach a steady state within a short time (e.g., 2-3 hr). As discussed later, and in contrast to values of a few hundred reported in earlier studies (Harding and Unanue, 1990; Demotz et al., 1990; Vitiello et al., 1990; Christinck et al., 1991), the minimum number of activating complexes per target cell was found to vary over several orders of magnitude depending on the particular T cell, MHC-I molecule, and peptide, from several thousand per target cell to fewer than 10 in optimal combinations (Kageyama et al., 1995) (see Section V1,D). How do pepMHC complexes recognized by T cells arise? CD8+ T cells react with pepMHC-I complexes that form within the ER of a cell as newly synthesized MHC-I molecules assemble (reviewed by Monaco, 1992; Yewdell and Bennink, 1992; Germain and Margulies, 1993; Heemels and Ploegh, 1995). The peptides are generated by limited proteolysis in the cytosol and translocated into the ER by MHC-encoded peptide transporters (transporters associated with antigen processing, TAP) (Spies et al., 1991), or in some cases via TAP-independent pathways (Anderson et al., 1991; Henderson et al., 1992; Zweerinket al., 1993; Hammond et al., 1993; Zhou et al., 1993). Once inside the ER, peptides may or may not be subjected to further proteolysis (Falk et al., 1990; Yewdell et al., 1994) before binding to nascent MHC-I molecules, which are then exported to the cell surface as mature pepMHC complexes. Given several thousand intracellular proteins potentially available for degradation in any given nucleated cell, and manyfold higher numbers of peptides theoretically available for transport into the ER and for subsequent binding to MHC-I molecules, it is apparent that competition among peptides must be a significant feature of antigen presentation. It may be that only tightly binding peptides compete effectively for MHC-I binding sites, explaining the slow dissociation rates that have been measured. Certainly peptide selectivity exists at the levels of MHC binding (Falk et al., 1991a; Schumacher et al., 1991) and TAP-mediated peptide translocation into the ER (Shepherd et al., 1993; Neefjes et al., 1993; Schumacher et al., 1994), and perhaps also at the level of proteolysis (Goldberg and Rock, 1992), but much remains to be clarified about the generation of MHC-Ibinding peptides in vivo. It is clear that the pepMHC-I complexes ultimately arriving at the surface of a cell represent a sampling of the contents of that cell, with some peptides present in relatively high copy numbers, e.g., several hundred to perhaps several thousand identical pepMHC-I complexes per cell, and a greater number of peptides relatively scarce, e.g., between 1 and 100 com-

ANTIGEN-SPECIFIC T-CELL RECEPTORS

21

plexes per cell (van Bleek and Nathenson, 1990; Falk et al., 1991b; Hunt et al., 1992a; Udaka et al., 1992; Tsomides et al., 1994). Most natural MHCI-binding peptides arise from the normal self proteins of an individual and are not recognized efficiently by the mature T cells of that individual, which are purged of most self-reactive cells as they develop in the thymus (negative selection) or rendered unresponsive (anergic)in the periphery (Schwartz, 1989). However, peptides from a foreign protein, e.g., originating from a virus or other intracellular microbe (Townsend and Bodmer, 1989), or an anomalous self protein, such as the mutated protein of a tumor cell (Lurquin et al., 1989; Mandelboim et al., 1994), can (in association with a self MHC-I protein) elicit and react with CD8+ T cells. Peptides from certain normal (nonmutated) self proteins in some tumors can also be recognized, in association with MHC-I, by T cells that react against the tumor (Boon, 1994); for example, CD8+ T cells that can be isolated from excised human melanomas (Kawakami et al., 1994a,b; Coulie et al., 1994; Castelli et al., 1995; Bakker et al., 1994; Tsomides et al., 1996) or lymph nodes (Cox et al., 1994) have recently been shown to recognize peptides from nonmutated melanocyte-specific proteins in association with HLA-A2. The underlying requirement for all these responses to be productive is that the abundance of the naturally processed pepMHC complex be sufficient and the TCR affinity and kinetics be favorable (see Section VI). CD4-t T cells, in contrast to CD8+ cells, react with pepMHC-I1 complexes on specialized APC (e.g., macrophages, dendritic cells, B cells). Peptides that bind to MHC-I1 proteins generally arise from integral membrane proteins or from endocytosed proteins, either soluble or membraneassociated (Tables I and 11). These peptides are produced in special endosomal organelles by a set of cellular proteases that differ from those that generate MHC-I-binding peptides. Newly synthesized MHC-I1 molecules, complexed with a nonpolymorphic invariant chain, traffic into this endocytic pathway (Neefjes et al., 1990) and come into contact with the available peptides. There the invariant chain is partially degraded, allowing some of the peptides to bind to MHC-I1 molecules under the acidic conditions that prevail in these organelles (pH optimum -5.0) and leading to egress of pepMHC-I1 complexes to the cell surface. Studies aimed at quantitating the binding between synthetic peptides and MHC-I1 molecules succeeded before those involving peptide-MHC-I reactions (Babbitt et al., 1985; Buus et al., 1986; Jardetzky et al., 1990; Roche and Cresswell, 1990; Roof et al., 1990; Rothbard and Gefter, 1991). As in the case of MHC-I-binding peptides, immunodominance describes the phenomenon whereby only one or a few peptides from a given protein are bound ef€iciently by a given MHC-I1 molecule and presented to T cells, accounting for the bulk of a polyclonal T-cell response to that protein.

22

HERMAN N . EISEN El' AL.

Of considerable interest are the kinetics of the reactions between peptides and MHC proteins. The first kinetic data, obtained for MHC-11, indicated unusually slow on- and off-rates for the peptide-MHC reaction [e.g., tl,2(off) = 5-10 hr at 37"C, Buus et al., 19861. Sadegh-Nasseri and McConnell (1989) subsequently found evidence for rapid formation of a quickly dissociating complex that slowly converted to a stable form [tl,2(off) > 30 hr]; the long half-life for peptide dissociation was shown to limit the association rate for an added peptide (Tamp6 and McConnell, 1991). These kinetically distinguishable pepMHC-I1 complexes correlated with different behaviors in sodium dodecyl sulfate (SDS)-polyacrylamide gel electrophoresis: the short-lived complex dissociated into MHC-I1 a and p subunits, whereas the more stable complex migrated as an intact heterotrimer (a,p, peptide) (Sadegh-Nasseri and Germain, 1991, 1994; Stern and Wiley, 1992). Nelson et al. (1994) found that the dissociation half-times of pepMHC-I1 complexes vary widely, with selective persistence of the most stable complexes on APC helping to account for the striking immunodominance of certain peptides. Conversely, while a rapidly dissociating pepMHC-I1 complex is expected to be relatively ineffective at eliciting T-cell responses, it might also be ineffective at eliciting negative selection in the thymus and thus allow maturation of the corresponding autoreactive T cells. Thus, Fairchild et al. (1993) and Mason and McConnell (1994) suggested that, for this reason, a self peptide from myelin basic protein might fail to induce T-cell tolerance toward this peptide. The failure would leave potentially autoreactive T cells that could eventually cause autoimmune encephalomyelitis if activated by cross-reacting viral peptides (see Oldstone, 1987; Wucherpfennig and Strominger, 1995; Section V1,F). It remains to be seen whether such a mechanism also applies to peptides interacting with MHC-I proteins. A related possible mechanism for evading tolerance could be extrathymic posttranslational modification of a self peptide, leading to inadequate negative selection of T cells specific for the modified peptide (Wu et al., 1995). VI. T-CELL RESPONSES TO PEPMHC

The intensity of mature T-cell responses to pepMHC complexes on other cells is greatly affected by the cell surface abundance of these complexes and by small changes in peptide sequence, as illustrated in Fig. 4. When the same T cells and target cells (or APC) are used in the representative assays shown, synthetic peptides with closely related sequences can differ as much as several millionfold in the concentrations required for half-maximal intensity of the responses they elicit (SD5o values, Tsomides

23

AN'IIGEN-SPECIFIC T-CELL RECEPTORS

-+- LSPFPFM p X a

--+-- ANERADLIAYLKQATK

MCC ANERADLIAYLEOATK MCC(99E) --t ANERADLIAYLKQASK MCC(t02S) --&- ANERADLIAYLKQTAK PCC

-+- QLSPFPFDL

QL9 LSPFPFDLL LL9

U

1000

B

- 1 4 - 1 3 - 1 2 - 1 1 - 1 0 - 9 -8 -7 -6 -5

-9

-8

-7

-6

-5

-4

-3

Log peptide concentration, M FIG. 4. Responses of T cells to target cells sensitized with various concentrations of cognate peptides or their structural analogs. (A) Cytotoxic responses by a CD8+ CTL clone (2C) to a naturally occurring octapeptide p2Ca from a-ketogluterate dehydrogenase and three contiguous overlapping nonapeptides from this protein (QL9, SL9, and LL9) presented by the MHC-I protein Ld on I?-transfected target cells (T2-Ld) shown as percentspecific lysis of the target cells (Sykulev et al., 1994h). (B) IL-2 production by a CD4+ T-cell hyhridoma (2B4) in response to peptides from cytochrome c of mouse (MCC) or pigeon (PCC)presented by the MHC-I1 protein IEk on IEk-transfected CHO cells (Matsui et al., 1994).

et al., 1991). In attempts to account for these enormous differences, some T cell-target cell systems have been analyzed extensively in terms of (1) the affinity of T-cell TCR for particular pepMHC complexes; and (2) the abundance of these complexes on target cells (epitope density). As discussed in Section VI,C, TCR reactions with pepMHC complexes approach equilibrium rapidly, indicating that intrinsic equilibrium constants for these reactions (TCR affinities) may be relevant to understanding the responses illustrated in Fig. 4. A. Afinity: Intrinsic Equilibrium Constants of TCR-PePMHC Reactions

Several approaches have been used to determine the equilibrium binding constants of TCR-pepMHC reactions. They include (1) competition assays in which soluble pepMHC complexes compete with lZ5I-labeledantibodies (or Fab' fragments) for binding to TCR on intact T cells; (2)direct binding of soluble '*51-labeledpepMHC complexes to TCR on intact cells; or (3) binding of unlabeled soluble pepMHC complexes to TCR molecules produced in soluble form by genetic engineering, immobilized on a solid

24

HEKMAN N . EISEN

Er

AL.

support, and the reaction evaluated by surface plasmon resonance (SPR, below). All these approaches have been sufficiently consistent (Table 111) to suggest the fimctional equivalence of the genetically engineered soluble analogs of TCR and MHC proteins to their native membrane-associated forms. The first measurement of an intrinsic TCR-pepMHC equilibrium constant involved competition for the TCR on intact CD4+ T cells between a soluble pepMHC-I1 complex and 1z51-labeledFab fragments of an antibody to the TCR VP domain (Matsui et al., 1991). The free pepMHC concentration that inhibited binding of the lZ5I-labeledFab by 50% was 5 x 10-5M . This value (Kd) and the other equilibrium constants discussed here are all expressed in the following discussion as association constants (K, = 1/&) (Table 111).A slightly higher K , was found in another study that used another soluble TCR to inhibit the response of an intact CD4+ T cell (measured by T-cell cytokine production) to an intact APC. By comparing the inhibitory effect of the soluble TCR with the inhibitory effect of an anti-MHC Fab' fragment, it was estimated that the intrinsic affinity of the TCR for the pepMHC-I1 complex was lo3M-I (Weber et al., 1992). This result should be viewed with the understanding that it was indirect and based not on a measured physical interaction between TCR and its ligand but on the production of interleukin-2 (IL-2). The equilibrium constants determined by Matsui et al. (1991) and Weber et al. (1992) (2 x 104M-' and -lo5 M-I, respectively)were consistent with the often expressed expectation that TCR affinities would generally fall in the low range exhibited by antibodies having germline V domain (i.e., not somatically mutated) sequences (e.g., Eisen, 1986; Davis, 1990). However, TCR with substantially higher intrinsic affinities were subsequently found by Sykulev et al. (1994a): 1-2 x lo6 M-l in a binding assay involving the Iz5I-labeledFab' fragment of an anticlonotypic antibody to the TCR on a CD8+ T-cell clone (2C) in competition with a soluble pepMHC complex [formed by the MHC-I protein Ld and an octapeptide from a-ketoglutarate dehydrogenase, LSPFPFDL, termed p2Ca (Udaka et al., 1992, 1993)] (Table 111). Later, the same TCR was found to have a 10-fold higher affinity (1-2 x lo7M-') for a related pep.Ld complex in which the peptide differed from p2Ca only by an additional glutamine residue at the N terminus (QLSPFPFDL, QL9) (Sykulev et al., 199413). Given this high intrinsic affinity, it proved possible to measure the direct binding of QL9.Ld complexes (trace-labeled with Iz5I)to TCR on intact 2C cells, obviating the need for indirect measurement by competition with an antireceptor antibody. The values obtained by direct and indirect approaches were in close agreement, indicating the feasibility of measuring TCR affinities on diverse T-cell clones without requiring rare (e.g., clonotypic) anti-TCR antibodies.

-

TABLE I11

Equilibrium Association Constantsfor Binding of PeptUie-MHC Complexes to TCR T-cell clone (CD4 or CD8)

Peptidea Name

MHC

Sequence

Class

Allele

Equilibrium constant, P (M-I)

Method6

Refs.'

5C.C7 (CD4) 228.5 (CD4)

MCC MCC(99E)

ANERADLIAYLKQATK ANERADLIAYLEQATK

I1 I1

IEk I Ek

2.0 x 104 1.9 x 104

Competition Competition

(1) (11

14.3d (CD4)

m110-120

CFERFEIFPKE

I1

IEd

2.0 x 105

Competition

(2)

QL9 QL9 p2Ca SL9 p2Ca-A3 p2Ca-A5 p2Ca-A8 p2Ca pvsv pOV8 p2Ca p2Ca

QLSPFPFDL QLSPFPFDL LSPFPFDL SPFPFDLLL LSAFPFDL LSPFAFDL LSPFPFDA LSPFPFDL RGYVYQGL SIINFEKL LSPFPFDL LSPFPFDL

1

Ld Ld Ld Ld Ld Ld Ld

LO x 107 2.0 x 107 2.0 x 106 1.4 x 104 2.0 x 104 1.6 x 104 1.7 x lofi 3.0 x 103 <3.0 x 103 ~ 3 . xo 103 1.0 x 106 8.0 x lofi

Competition Direct Competition Competition Competition Competition Competition Competition Competition Competition s.p.r. s.p.r.

(3) (3) (4) (4) (4) (4) (4) (4) (4) (4) (5)d

4G3 (CD8)

pOV8

SIINFEKL

1

Kb

lo6

Direct

(3)

2B4 (CD4)

MCC MCC(102s) PCC

ANERADLIAYLKQATK ANERADLIAYLKQASK ANERADLIAYLKQTAK

I1 I1 I1

IEk IEk IEk

104 104 104

s.p.r. s.p.r. s.p.r.

(6) (6)

2C (CD8)

1 1

1

I 1

I I 1 1 1 I

K6 Kb

Kb Ld Ld

1.5 x 1.5 x 1.0 x 1.9 x

(51d (6)

a Peptide MCC is from mouse cytochrome c, PCC from pigeon cytochrome c, HA from influenza virus hemagglutinin, p2Ca and related peptides from mouse a-ketoglutarate dehydrogenase (Udaka et al., 1992, 1993),pVSV from vesicular stomatitis virus, and pOV8 from ovalbumin. Competition: Soluble pepMHC inhibits the binding of 1z51-labeledFab' fragment of an anti-TCR Ab to TCR on intact T cells, or binding of soluble TCR to pepMHC on intact AFT inhibits the response of CD4+ T cells to the APC. Direct: Binding of '251-labeled soluble pepMHC to TCR on intact T cells. s.p.r., surface plasmon resonance of soluble pep.MHC binding to immobilized soluble TCR. (I)Matsui etal. (1991); (2)Weberet al. (1992); (3) Sykulevet al. (1994b); (4) Sykulevetal. (1994a); (5) Correlal. (1994); (6) Matsui etal. (1994). K , values calculated from association and dissociation rate constants, using two different models (see Table IV).

'

26

HERMAN N . EISEN E T AL.

Thus, in a direct binding assay with an "'I-labeled soluble pepMHC complex formed by the MHC-I protein Kb and an octapeptide from ovalbumin (SIINFEKL, pOV8), the affinity of the TCR of an ovalbumin-specific CD8+ CTL clone (4G3) was found to be 1.5 x lo6 At', indicative of another high-affinity reaction (Table 111). Whether the low affinities of the reactions between TCR on CD4+ T cells and pepMHC-I1 complexes and the higher affinities of the reactions between TCR on CD8+ T cells and pepMHC-I complexes represent consistent differences between CD4+ and CD8+ clones is perhaps possible. More likely, the differences found so far reflect a wider range of intrinsic affinities for TCR-pepMHC reactions than had been expected. Among the relatively small number of intrinsic affinities determined for TCR reactions with pepMHC ligands, the highest values are similar to those often encountered for monoclonal antibodies against protein antigens (about lo7At'). However, in view of the absence of extensive somatic mutation in TCR genes, it is doubtful that TCR affinities will match the highest intrinsic affinity values found for antibody reactions with protein antigens, which are often in the range 10s-109 M-' and can be as high as 10'" M-' (see Foote and Eisen, 1995, and Section VI,E, 1).

B. Kinetics Given the structural similarities between TCR and Ig molecules, the question arises as to whether TCR reactions with their natural ligands are similar kinetically to those of antibodies with antigens. In studying TCR kinetics, the main approaches taken so far are much like those used to measure TCR affinities; e.g., they involve TCR molecules on intact T cells or genetically engineered TCR that are produced as soluble molecules and subsequently immobilized on a solid support for analysis by an optical method (surface plasmon resonance). Both approaches were used to study the reaction between the TCR of the CD8+ T-cell clone 2C (2C TCR) and the octapeptide p2Ca it recognizes in association with Ld. Based on competition between soluble p2Ca.Ld complexes and an "'I-labeled Fab' fragment of a clonotypic antibody for binding to the 2C TCR, the association and dissociation rate constants were found to be 1.1 x lo4 M-I sec-' and 5.5 x sec-I, respectively, at 25°C. For the higher affinity reaction of the same TCR with the closely related pepMHC complex QL9*Ld,the on-rate constant was slightly higher and the off-rate constant was considerably lower than for p2Ca.Ld (Sykulev et al., 1994a,b) (Table W ) . Using soluble p2Ca.Ld complexes and soluble 2C TCR (Slanetz and Bothwell, 1991), Corr et al. (1994) measured their interaction by surface plasmon resonance. In this procedure, pepMHC complexes flow over

27

ANTIGEN-SPECIFIC T-CELL RECEPTORS

TABLE IV

Kinetic Constantsfor Binding of PeptideeMHC Complexes to TCR Ligand (peptideoMHC)'

(M-' sec-')

tl/Z(off) (sec)

QL9*Ld QLS~L~ p 2 ~ a . ~ ~ p2Ca.Ld p 2 ~ a * ~ ~

5.3 x lo4 3 . 8 lo4 ~ 1.1 x lo4 2.1 x lo4 2.6 x lo5

4G3 (CD8)

pOV8*Kb

2B4 (CD4)

T-cell clone (CD4 or CD8) 2C (CD8)

k+i

r (sec)

Method'

Refs.c

222 275 126 27 35

234 396 182 3Sd

Direct Competition Competition s.p.r. s.p.r.

(1) (1) (2) (3)' (3)'

2.2 x lo4

30

48

Direct

( 1)

MCC.IEk 0.09 x 104 MCC(102S)*IEk 0.1-0.3 x lo4 PCC-IE~ 0.17 x lo4

12 2-5 8

18d 3-10d 1 ld

s.p.r. s.p.r. s.p.r.

(4) (4) (4)

50d

' Peptide sequences given in Table 111. Methods outlined in footnote to Table 111; s.p.r., surface plasmon resonance.

' ( I ) Sykulev et al. (1994b); ( 2 )Sykulev et al. (1994a); ( 3 )Corr et al. (1994); (4) Matsui et al. (1994). z values were not reported; they are calculated here using the relationship l/z = ( k + l L+k-l, where k + l and k-1 are on- and off-rate constants, respectively, for the TCR-pep.MHC reaction and L is unbound peptide concentration; under physiological conditions @ + I ) (L) << (k-1) and t is thus effectively determined by l/k-1. ' k + l and t 1 values ~ were derived from nonlinear least squares fit analysis of experimental data, with the TCR-pep.MHC reaction modeled as either a classic bimolecular reaction (upper line) or a two-step reaction (fast and slow, lower line); in the latter case only the fast component of k+ 1 and the slow component of ti12 are given.

TCR produced in soluble form and bound covalently to a dextran surface by carbodiimide chemistry. The binding of pepMHC complexes to TCR results in a local increase in refractive index which is measured by a shift in resonance angle. Experimental data were fit to a single exponential equation, as for a simple bimolecular reaction, as well as to a double exponential equation to improve the fit. Both analyses yielded essentially the same dissociation rate constant (2.0 - 2.6 x lo-* sec-I), which was four to five times faster than had been measured using the TCR on intact 2C cells. This disparity could be due to the TCR microenvironment on intact T cells or to the different pep*Ldcomplexes used in the two studies. The surface plasmon resonance study made use of a diverse population of Ld molecules that had been isolated from mammalian cells and probably contained a variety of endogenous peptides in addition to the cognate peptide p2Ca. Heterogeneity of TCR molecules randomly immobilized on the insoluble support may also have contributed to the disparity. Of the two association rate constants found by surface plasmon resonance (Corr et al., 1994), the

28

HERMAN N . EISEN E T AL.

lower value agreed with the on-rate constant measured with intact 2C cells (Sykulev et al., 1994a). The rate constants measured for the TCR of another high-affinity CD8+ CTL clone, 4G3, and its natural ligand, the ovalbumin peptide SIINFEKL plus Kb (pOV8.Kb),were determined by direct binding of pOV8*Kbto the TCR on intact 4G3 cells and were similar to those found for the 2C TCR reaction with one of its known natural ligands, p2Ca-Ld (Table IV). Matsui et al. (1994) also used surface plasmon resonance to analyze the reactions between soluble TCR from a CD4+ T-cell clone (2B4) and each of three closely related cytochrome c peptides complexes with IEk, an MHC-I1 protein. In keeping with the very low affinity of the TCR of this clone for these pepMHC complexes (Table 111),the on-rate constants were extremely low (0.9-1.7 x lo3 M-I sec-') and the dissociation rates were rapid (tllz (off) values of 2-12 sec, Table IV) (see also Section VI,E,2). 1. Temperature effects. All the kinetic measurements recorded in Table IV were made at 25°C. The few taken at both 25" and 37°C showed (1) a small increase in the association rate constant at the higher temperature (presumably due to higher diffusion coefficients at 37°C than at 25°C); and (2) an approximately fivefold increase in the dissociation rate constant. The equilibrium constant in this case was thus only slightly lower at 37°C than at 25°C (Table V). 2. Summary of on- and off-rates for T C R p e p M H C reactions. The kinetic measurements made to date indicate that the association rate constants for TCR-pepMHC reactions range from 1O3 to lo5M-I sec-'. In contrast, the intrinsic on-rate constants for antibody reactions with protein antigens are generally about 105-106M-I sec-' (Mason and Williams, 1980; Foote

-

-

TABLE V

Temperature Dependence of Equilibrium and Rate Constantsfor Reaction between 2C TCR and the QL9.Ld Complexa 2 c TCR Binding parameter

25"Cb 1.5 x lo7 5.3 x lo4 3.9 3.1 x 3.7

a

+ QLS.L~ 37°C 6.0 x lo6 9.0 x lo4 1.1 1.5 x lo-' 0.7

Data from Sykulev et al. (199413). QL9 sequence given in Table 111. Room temperature (22"-25"C).

ANTIGEN-SPECIFIC T-CELL RECEPTORS

29

and Milstein, 1991; Foote and Eisen, 1995), the higher value representing an upper limit that probably arises in part from diffusion rates of protein (Northrup and Erickson, 1992). TCR tend to dissociate faster from pepMHC complexes than antibodies from protein antigens, with TCR tl,2(off) values varying from a few seconds to 1-2 min and tl,n(off) values for antibody-protein antigen complexes generally ranging from a few minutes to an hour or more. These differences reflect the generally higher intrinsic affinities of antibodies than of TCR for their respective ligands, which is probably due to antigenic selection of B cells having somatically mutated Ig genes and the absence of a comparable process for T-cell selection in uiuo. High intrinsic affinities can greatly enhance the efficacy of antibody molecules in solution, but they are less likely to have a correspondingly large impact on cell surface TCR, which is enormously multivalent (about lo5TCR molecules per mature T cell). It has been suggested that, overall, an affinity ceiling for TCR (-10' M-') is about 1000-fold lower than the affinity ceiling for antibodies (- 10" M-I) (see Foote and Eisen, 1995, and Section VI,E,l). In general, the on- and off-rates of TCR reactions with pepMHC complexes are much faster than the rates involved in the reaction of peptides with MHC proteins. For some peptide-MHC reactions, association rate constants are slow (10"-104 M-' sec-', Corr et al., 1994), and several hours (at room temperature) are often required to approach equilibrium (Kageyama et al., 1995). These reactions also tend to have long dissociation half-times, ranging from -1 hr to 100 hr (Buus et al., 1986; Cerundolo et al., 1991; Tsomides et al., 1991; Olsen et al., 1994), although in some instances they may be as short as 20 min (Fairchild et al., 1993; Mason and McConnell, 1994) or even less (Vturina et al., in preparation). C. Time Required to Approach Equilibrium

T cells move continuously over other cells (Chang et al., 1979), but within 2-6 min of establishing contact with a suitable target cell, the response of a T cell to antigen can be detected by an increase in its intracellular Can+concentration (Poenie et al., 1987; Su et al., 1993). Can the reaction between TCR on the T cell and pepMHC on the target cell reach a steady state within this brief interval? Equilibrium for a simple bimolecular reaction is approached asymptotically at a rate that is generally defined by the time constant t, the time required to form 63% (i.e., 1 - l/e) of the equilibrium number of receptor. ligand complexes. By measuring the net rate of accumulation of specific TCRopepMHC complexes on intact CD8+ 2C cells, Sykulev et al. (1994a,b) found that z was -3 min for p2Ca-Ld at 25°C and -1 min for QL9*Ldat

30

HERMAN N . EISEN E T AL

37°C. The value of z varies with the pepMHC concentration, becoming longer as the ligand concentration decreases, but it cannot be longer than approximately the half-time for dissociation [the tl,z(off) value]. This limit follows because l/z = k+lL kl,where L is the free pepMHC concentration and k + l and k-, are on- and off-rate constants, respectively, for the TCRpepMHC reaction. Thus, for the most stable TCR-pepMHC binding reaction measured so far (2C TCR QL9-Ld),equilibrium is approached in less than a minute (tli2(off) was 0.7 min at 37"C, Table V). For reactions where t1/2(off)values are lower, equilibrium is approached even faster.

+

+

D. Epitope (PepMHC) Density Many observations imply that the intensity of a T-cell response depends on the number of pepMHC complexes (epitopes) the T cell recognizes on another cell. For example, in the assays shown in Fig. 4 the extent of the CTL cytotoxic response varies with peptide concentration, which affects the total number of the corresponding pepMHC complexes on target cells (epitope density). Similarly, the density of naturally processed peptides is critical. For example, human immunodeficiency virus (H1V)-infectedcells expressing low levels of processed viral peptides were lysed less effectively by HIV-specific CTL than infected target cells expressing higher levels of the same peptides (Tsomides et al., 1994). Other studies pointing to a critical role for epitope density involve the effects of peptide concentration on the fate of developing thymocytes (positive and negative selection, AshtonRickardt et al., 1994) and the demonstration of nonphysiological T-cell cross-reactions when high concentrations of synthetic peptides were added to target cells (Milligan et al., 1990; Schild et al., 1990; Dutz et al., 1994). The first attempts to measure epitope densities involved incubating target cells (or APC) with 1251-labeled peptides at minimally active concentrations. The restricting MHC protein, together with its associated peptides, was then immunoprecipitated and the number of 1z51-labeledpepMHC complexes per target cell determined. The results indicated that a minimum of about 100-400 complexes were required to elicit cytokine production by CD4+ T-cell hybridomas (Harding and Unanue, 1990; Demotz et al., 1990) or lysis of target cells by CD8+ T-cell lines (Christinck et al., 1991). Subsequent studies of antigen recognition by CD8+ CTL made use of mutant target cells (RMA-S, T2) with a defect in the transporter (TAP)that translocates peptides from the cytosol, where they are generated, into the ER (Townsend et al., 1989; Ljunggren et al., 1990; Schumacher et al., 1990; Cerundolo et al., 1990). In such cells, newly synthesized MHC-I proteins arrive at the cell surface membrane deficient in bound peptides (e.g., peptide-free or with weakly bound peptides derived perhaps from protein

ANTIGEN-SPECIFIC T-CELL RECEPTORS

31

signal sequences), and then they undergo rapid denaturation (at 37°C) unless stabilized by the binding of synthetic extracellular peptides. By raising the extracellular concentration of peptide, the cell surface epitope density is increased, resulting in greater target cell lysis by CTL. The free concentration of peptide required to sensitize target cells for half-maximal lysis (called the SD50 value, Tsomides et al., 1991) is a useful indicator (though not in itself a measure) of the density of pepMHC complexes needed to elicit CTL-mediated lysis. Similarly, for stimulated CD4+ T cells that respond by proliferating and producing cytokines, increasing the concentration of extracellular peptide increases the responses. Cytotoxicity assays are typically carried out for 4 hr (Fig 4), and for many peptides their reactions with MHC on the target cell reach equilibrium (steady state) during this time. For these peptides an approximate average epitope density (r) on target cells may be estimated from the free concentration of synthetic peptide (c) in the extracellular medium, the equilibrium association constant for the peptide-MHC reaction ( K ) , and the total number of pepMHC sites available for binding peptide (n),the later being determined with saturating concentrations of the peptide [see Eq. (l),r = Kcn/(l + Kc)].Using this approach, Kageyama et al. (1995) determined the approximate epitope densities required to effect halfmaximal lysis of target cells in a study involving 16 peptides and 3 MHC-I proteins on intact cells (Kb, Ld,and HLA-A2).With different combinations of peptides, MHC proteins, and T-cell clones, the epitope densities required for half-maximal lysis were found to vary from several thousand pepMHC complexes per target cell to fewer than 10.The significance of this wide range emerged from the subsequent development of a quantitative model for CTL-target cell interactions (see Fig. 5 below and the following discussion). To check the accuracy of epitope densities determined according to Eq. (l),the amount of an "51-labeled peptide (I1-QLSPYPFDL, termed II-QLS-YS) that binds to Ld (an MHC-I protein) on intact cells was measured directly, taking advantage of a method for preparing radioiodinated peptides with extremely high specific radioactivities [3.5 x lo1' cpm per mole of monoiodinated peptide, the same as the specific activity of carrier-free L251 (Tsomides and Eisen, 1993b)l. The epitope densities found by this direct approach and those calculated by Eq. (1)agreed to within a factor of 2 or 3 . When the same high specific activity peptide (1251~-QL9-Y5) was added to target cells at a concentration that resulted in half-maximal cytotoxicity (SD50-5 pM), an average of only three peptide molecules were bound to Ld per target cell. From the distribution of Ld on the target cells, it appeared that a single pepMHC per target cell may be able to trigger a cytolytic T-cell response (Sykulev et al., 1996).A single

32

HERMAN N. EISEN E T AL

complex can bind at any instant to only a single TCR molecule (i.e., engage in univalent binding). It seems therefore that univalent ligation of a TCR, without cross-linking several TCR molecules, can elicit a cytolytic T-cell response. Whether more complex responses, requiring the activation of previously silent genes (as in cytokine production), can also be triggered by univalent TCR ligation remains to be seen. It is notable, however, that Brower et al. (1994) deduced from their model system that 3-5 pepMHC complexes could stimulate T cells to produce y-interferon. Measuring epitope densities of naturally processed (endogenous) peptides on the cells that produce them requires a different approach. At low pH, peptides dissociate rapidly from pepMHC complexes (Buus et al., 1988; Rotzschke et al., 1990a). In one effective procedure cells are treated for about 30 sec with isotonic buffer at pH3, stripping peptides from cell surface MHC without lysing the cells (Storkus et al., 1993). The peptides can then be fractionated by HPLC, and particular peptides detected by bioassay with specific clones of CTL: Sensitivities of 110-'2M peptide have been obtained for several CTL-peptide-target cell systems (Bodmer et al., 1988; Reddehase et al., 1989; Tsomides et al., 1991; Rotzschke et al., 1990b, 1991a; Falk et al., 1991b), and a theoretical limit for peptide at 10-'3-10-14M has been postulated (Kageyama et al., 1995). In each case, the efficiency of peptide recovery must be quantitated for an accurate assessment of natural peptide abundance (reviewed in Tsomides and Eisen, 1993a; for examples see Table 11).While current efforts emphasize identification of the naturally processed peptides involved in T-cell responses to tumor cells, allografts, cells infected by viruses or other pathogens, target cells of autoimmune reactions, etc., a reasonable next step will be to measure the abundance of these peptides in order to find out whether epitope densities commonly limit T-cell responses (Tsomides, 1995).

E. TCR-PepMHC Engagement: An Afinity Model The intensity of the T-cell response has been widely assumed to be determined, in large measure, by TCR affinity for pepMHC complexes and the number of these complexes on target cells (epitope density). The preceding section dealt with epitope density; here we focus on TCR afinity. Since the TCR-pepMHC reaction approaches equilibrium rapidly (see Section VI,C), equilibrium constants for this reaction could govern the outcome of T cell-target cell encounters. However, TCR molecules and pepMHC complexes are confined to the surface membrane of T cells and target cells, respectively. Hence, the question arises as to whether their interaction can be described in terms of the law of mass action, which ordinarily deals with interactions that involve freely difhsable reactants.

ANTIGEN-SPECIFIC T-CELL RECEPTORS

33

Nevertheless, in developing a quantitative model for the antigen recognition step in the activation of T cells, Sykulev et al. (1995) assumed from the law of mass action that (TCR-pepMHC) = K (TCR) (pepMHC)

(2) where (TCRopepMHC) and (pepMHC) refer, respectively, to the number of pepMHC complexes per target cell that are or are not engaged by TCR molecules, and (TCR) is the concentration of unengaged TCR molecules (assumed to be the same as the total TCR concentration because only a very small proportion of TCR molecules of a mature T cell engage pepMHC complexes in any particular cell-cell interaction). K, the TCR affinity, is the equilibrium association constant for the TCR-pepMHC reaction. The total epitope density, designated (pepMHC)o, was assumed to equal the sum of TCR-bound and unbound pepMHC; hence by substituting (pepMHC)o(TCRepepMHC) for (pepMHC), it follows that

log(pepMHC)o = log(TCR*pepMHC)- log[K(TCR)/l + K(TCR)] (3) On the assumption that [TCR.pepMHC] is fixed for a given level of T-cell response (e.g., half-maximal cytolysis) and a particular T cell-target cell system, Eq. (2) describes the relationship between total epitope density and TCR affinity. A satisfactory fit was found between Eq. (3) and experimentally determined values for the total epitope densities required for half-maximal T-cell cytotoxic responses and the TCR affinities for several TCR-pepMHC reactions (Fig. 5). As shown in Fig. 5 and predicted by Eq. (3), over a wide range of affinity values ( Clo4 to about lo6 M-'), the log epitope density was a linear function of the log TCR affinity with a slope of -1. The fit suggests that in a T cell-target cell conjugate the extent of ligation of the T cell's TCR molecules by pepMHC complexes on the target cell can be described by a relationship in the form of the law of mass action (Fig. 5). The validity of this model should become evident when its predictive ability is put to the test: Since the product of epitope density and TCR affinity is constant (over the linear range shown in Fig. 5), with a peptide whose target cell epitope density at a half-maximal cytotoxic response is known, the model can predict the affinity of the TCR of the responding T cells. Whether the predicted affinity values will prove to be correct remains to be seen. 1. TCR Ajinity Ceiling

Equation (3) predicts that at TCR afinities above some upper level (affinity ceiling) the epitope density values plateau at a lower limit (Fig. 5), which corresponds for a specified level of response (half-maximal cytotoxicity) to the minimal number per target cell of ligated pepMHC com-

34

HERMAN N . EISEN E T AL.

x c .v)

C

a, U a,

Q

0 c .-

Q

a, -

-

([I

c

0

0,

0

-J

3

4

5

6

7

8

9

10

Log K FIG. 5 . Relationship between target cell epitope density required for a half-maximal T-cell response (target cell lysis) and the intrinsic affinity of TCR-pep.MHC reactions. The solid line corresponds to the best fit between Eq. (3) and experimentally determined values for epitope density and affinity ( K ) , using a TCR concentration of lo-' M . Curves that fit the experimental data about as well, but are based on limiting epitope densities of one or three pepMHC complexes per target cell, are shown by the broken lines. (From Sykulev et al., 1995.)

plexes. From the limited amount of data available, at high-affinity values the minimum epitope density value was seen to fall between 1 and 10 pepMHC complexes per target cell (for TCR affinities above approximately 5 x lo6M ' ) .The prediction from the model was supported by the subsequent finding (made with the high specific activity radiolabeled peptide) that an average of three pepMHC complexes per target cell were sufficient to elicit half-maximal target cell lysis by a CTL clone whose TCR affinity for these complexes was sufficiently high (above lo6M-'). Although the precise value of the TCR affinity ceiling is not well defined by the available experimental data (Fig. 5), in principle it equals the reciprocal of the effective TCR concentration and this concentration remains to be defined. From the best fit between experimental data and Eq. (3) plotted as the solid line in Fig. 5, the concentration may be about lo-' M , a value that can be justified by the number of TCR molecules per mature T cell (about lo5; see Matsui et al., 1991; Sykulev et al., 1994), and the fact that with extensive changes in T-cell shape and surface area, the cell surface TCR molecules might occupy over time a volume that approximates the volume of the T cell (about lO-',ul per cell).

ANTICEN-SPECIFIC T-CELL RECEPTORS

35

2. Kinetic Control of T-cell Responses Equations (2) and (3) and the results shown in Fig. 5 assume that in T cell-target cell encounters the TCR-pepMHC reaction essentially reaches a steady state and that TCR affinity is a critical determinant of the response. Under some conditions, however, it is possible that rates of dissociation of pepMHC from TCR, rather than equilibrium constants, might determine the response. In particular, if TCR-pepMHC bond lifetimes were close to the bond residence time required to activate a signal transduction pathway, dissociation rate differences could be decisive. This possibility is evident from a study by Matsui et al. (1994). Markedly different concentrations of three similar peptides were needed to elicit equivalent responses by a CD4+ T-cell hybridoma whose TCR had about the same low affinity (-lo4 M-’) for all three peptides in association with the MHCI1 protein IEk. Based on the belief that these peptides interacted equally well with IEk (and thus formed the same epitope densities at the same peptide concentrations), it was concluded that the different peptide concentrations required to elicit the T-cell response might relate to the differences found in tli2(of€)values of the TCR from the respective pepMHC complexes (2-1 2 sec). Thus, while the affinity model just described emphasizes the average number of TCR-pepMHC bonds present at any instant under steady-state conditions, an alternative view suggests that under some circumstances the TCR-pepMHC bond lifetime might play a decisive role. Just how short the lifetime would have to be to serve as an independent controlling factor in a T-cell response is not clear. In Section VI,D it was noted that a single pepMHC on a target cell can activate a T-cell cytotoxic response. At any instant a single complex can bind to only one TCR molecule, but over time it can bind to one or a few TCR molecules repetitively, or serially to many different TCR molecules, as proposed by Valitutti et al. (1995). Since it was suggested that many serial engagements enhance T-cell responses, Valitutti et al. (1995) predicted that high TCR-pepMHC dissociation rates, which are generally associated with low-affinity reactions, would promote T-cell responses. Other studies, however, show that high-affinity TCR-pepMHC reactions, which are generally associated with slow dissociation rates, enhance T-cell cytotoxic responses (Sykulev et al., 1994a,b). F. SpeciJicity,Degeneracy, and Molecular Mimicry

It seems to be widely believed that high levels of specificity in immune reactions are manifestations of high-affinity interactions. However, measurements of TCR affinities have shown that exquisite specificity can be manifested by very low-affinity reactions. The lowest TCR intrinsic affinity

36

HERMAN N . EISEN E T AL

measured so far, for the reaction of the 2C TCR with the naturally occurring peptide p2Ca (LSPFPFDL) in association with Kb, is 3 x lo3 M-’ (Table 111). Even with this low affinity, it was possible for 2C CTL to lyse target cells bearing p2Ca.K’ complexes (Sykulev et al., 1994a; Dutz et al., 1994) and, moreover, to exhibit a striking degree of specificity: As shown in Fig. 6, p2Ca and another naturally occurring octapeptide that differ only by a Phe+Tyr substitution (LSPYPFDL, called p2Ca-Y4), are clearly distinguished by 2C CTL in cytotoxicity assays with Kb’ target cells (T2-Kh) (Wu et al., 1995). Though both peptides bind equally well to Kb, T2-Kbcells sensitized with p2Ca were lysed, whereas those sensitized with p2Ca-Y4 were not. This pronounced difference could be explained if the 2C TCR affinity for the p2Ca.K’ complex (3 x lo3M-’) were just above the affinity threshold required for a cytotoxic response (we assume it to be 1 x 10’ M-l) and the 2C TCR affinity for the p2Ca-Y4.Kb complex were just below it. It is also possible that it is not the lower affinity per se but rather perhaps a faster off-rate that is responsible for failure of the ineffective complex to elicit a cytotoxic response. In distinguishing sharply between two pepMHC complexes that differ by a single oxygen atom, the TCR of CTL clone 2C matches the highest level of specificity exhibited by the most discriminating antibodies or enzymes. Comparable levels of discrimination are also suggested by the widely different concentrations of closely related synthetic peptides required to elicit responses by a given T-cell clone (e.g., Fig. 4). However, unless the cell surface pepMHC densities formed by the different peptides are known, large differences in T-cell responses could result from differences in the epitope densities of the corresponding complexes rather than from differences in TCR affinities for these complexes. Degeneracy. In contrast to the high level of specificity described previously (e.g., Fig. 6), a TCR can also react with a wide variety of different pepMHC complexes. Thus, a T cell arising in the course of viral infection characteristically reacts with a peptide of viral origin plus one of the infected individual’s own MHC proteins (a foreign-self complex). But such a T cell, like most others, can also react with a different MHC protein from another individual of the same species (allogeneic MHC or alloMHC) (Nahill and Welsh, 1993; see Section IX), and each of these alloreactions may involve a particular peptide in association with the alloMHC molecule (e.g., Udaka et al., 1992; see Section IX). Moreover, this T cell is expected to have been stimulated to mature in the thymus (positive selection) by reaction of its TCR with thymic peptides in association with an indigenous MHC protein (Schwartz, 1989; von Boehmer, 1994; Sha et al., 1988a,b; Ashton-Rickardt et al., 1994; Hogquist et al., 1994).

-

ANTIGEN-SPECIFIC T-CELL RECEPTORS

50

i

L

/

-8 -7 -6 -5 -4 -3 -2 - 1

0 + 1 +2

10080 60 40 -

20 -

-2

0 1 2 3 Log peptide concentration bglml) -1

FIG.6. High specificity of low affinity reactions: TCR on CD8+ CTL clone 2C distinguishes sharply between two naturally processed peptides, p2Ca and p2Ca-Y4, in association with the same syngeneic MHC-I protein, Kb. (Upper) Specific lysis of T2-Kb target cells by CTL 2C in the presence of various concentrations of p2Ca and p2Ca-Y4. (Lower) Binding of p2Ca (A)and p2Ca-Y4 (A) to Kb as shown by peptide-stabilized expression of Kb on Kb-transfected T2 cells, measured by fluorescent staining with a monoclonal anti-Kb antibody and flow cytometry (from Wu et al., 1995; see also Dutz et al., 1994). The 2C TCR affinity for the p2Ca.Kb complex (3 x lo3 M-I, Table 111) is the lowest measured so far for a TCR-pepMHC reaction (Sykulev et al., 1994a).

37

38

HERMAN N. EISEN ET AL.

The cross-reactions exhibited by T cells with sets of peptides having closely related or overlapping sequences, as in Fig. 4, are readily understandable. More interesting are the cross-reactions of viral or bacterial peptides with T cells that react with apparently unrelated self peptides, e.g., myelin basic protein found in the central nervous system (Wucherpfennig and Strominger, 1995; see also Selin et al., 1994). These crossreactions can involve peptides having no amino acids in common except the few that serve as anchors to bind to MHC protein. Ascribed to “molecular mimicry” (Oldstone, 1987), these reactions may play an important role in stimulating autoreactive T cells (those that react with a self peptide plus a self MHC protein), thereby triggering autoimmune disorders (Wucherpfennig and Strominger, 1995). Molecular mimicry implies topological similarity between ligands that are structurally very different. However, the crystal structures of the specific complexes formed by an antibody (anti-lysozyme) with two different ligands (lysozyme and an antibody to the binding site of the anti-lysozyme antibody) has shown that in this case the mimicry is more functional than topological (Field et al., 1995); Bhat et al., 1994). The same may well apply to many bizarre T-cell cross-reactions, e.g., a CTL clone (2C) that recognizes the naturally occurring peptide p2Ca (LSPFPFDL, see Table 11) in association with Ld also reacts with the NE-2,4-dinitropheny1atedform of an HIV peptide (ILKEPVHGV) in association with the same MHC protein (Ld)(Tsomides, unpublished data). Since Va and VP domains of TCR have so much amino acid sequence similarity to VL and V H domains of antibodies, why should the variety of pepMHC that can be recognized by any particular TCR seem far greater than the variety of antigens that react with an antibody? (For strange crossreactions of antibodies, see Michaelides and Eisen, 1974.) The difference seems especially pronounced if one considers that a T cell can be restricted in peptide recognition by more than one MHC (see Section IX). One possible explanation is that the Va-VP binding site is more flexible than the VL-VH binding site and can adapt its conformation to fit many different ligands. Flexibility could account for the difficulties currently being experienced in obtaining well-ordered TCR crystals for structure analysis. Another, perhaps more likely, explanation is that T-cell reactions with pepMHC can be detected with far greater sensitivity than antibody-antigen reactions: For example, peptides at M can elicit half-maximal responses (see Fig. 4),and TCR-pepMHC reactions having affinity values as low as 3 x M-’ can result in target cell lysis (Table 111, Fig. 6); an antibody-antigen reaction having such a low intrinsic affinity would ordinarily not be detectable. The great multivalency of T cells (about 10’ TCR molecules per mature T cell), the great abundance of pepMHC

ANTIGEN-SPECIFIC T-CELL RECEPTORS

39

ligands on many target cells, the ability of very few cognate pepMHC (< 10 per target cell) to elicit a T-cell response, and the amplifying effect of signal transduction in T cells must all contribute to the extraordinary sensitivity of T-cell reactions and to the wide range of their cross-reactions.

VII. T-CELLRECEPTOR ACCESSORY PROTEINS A . CD3andC

The antigen-specific heterodimeric (ap)TCR exists at the cell surface as part of a large multichain complex that includes the four invariant chains of CD3 (7, 6, and two E chains) plus the structurally distinct 5 molecule, which is found in most T cells as a disulfide-linked homodimer. On some T cells an alternatively spliced form of 5, termed q, is present as 57 heterodimers (reviewed by Ashwell and Klausner, 1990; see also Irving and Weiss, 1991). Immunoprecipitation (Blumberg et al., 1990) and quantitative immunofluorescence analysis (Punt et al., 1994) showed that there are two E chains per ap TCR molecule on intact T cells; the exact stoichiometry of the 5 chain homodimer or I;q heterodimer with other chains of the TCR complex is not clear. When cDNA for the a, p, and y TCR subunits were first isolated and sequenced (Hedrick et al., 1984; Saito et al., 1984a,b), the deduced amino acid sequences revealed, curiously, a positively charged residue in the otherwise hydrophobic transmembrane domain. The CD3 y, 6, and E subunits and 5 chain turned out to have in their hydrophobic transmembrane domains a negatively charged amino acid residue, suggesting that these charged sites are involved in assembling TCR heterodimers with the CD3 and 5 complex (see Davis, 1990). CD3 chains immunoprecipitate together with ap TCR molecules. Although 5 molecules do not coprecipitate with ap, their essential involvement in the TCR complex is indicated by the fact that their expression, like that of CD3 y, 6 , and E , is required for cell surface expression of the ap TCR. Minor truncations or alterations of 5 structure can abolish TCR function, as revealed by loss of responsiveness to antigens. The binding of antibodies to TCR or CD3 molecules on intact T cells activates two major signal transduction pathways, one resulting in hydrolysis of phosphatidylinositol 4,5-diphosphate and transient increases in intracellular Ca2+,and the other leading to tyrosine phosphorylation of cytoplasmic domains of CD3 subunits and the 5 dimer (reviewed by Weiss and Littman, 1994). None of these subunits exhibit intrinsic kinase activity; they appear to be substrates for Fyn, a member of the Src family of

40

HERMAN N. EISEN E T AL

tyrosine kinases that coprecipitates with CD3 (Samelson et al., 1990). Similarly, the Src family member Lck interacts with cytoplasmic domains of CD4 or CD8 (Rudd et al., 1988). A critical role for the cytoplasmic domains of CD3 and 5 chains in TCR-mediated signaling is suggested by experiments involving T-cell hybridomas transfected with genes for chimeric proteins consisting of various extracellular domains linked to cytoplasmic domains of CD3 or 5; antibodies to the extracellular domains of these chimeric proteins elicited T-cell responses (Wegener et al., 1992; Letourneur and Klausner, 1992). Mutational analyses of the cytoplasmic domains revealed an antigen recognition activation motif (ARAM) that includes tyrosine and leucine (i.e., D/E--Y--WI(-)S_XY-WI) (reviewed by Weiss, 1993). The ARAM may serve as a tyrosine phosphorylation site, allowing the recruitment of other intracellular molecules via SH2 domain-phosphotyrosine interactions. Thus, TCR ligation results in intracellular tyrosine phosphorylation of CD3 and 5 and recruitment of signaling proteins that bind specifically to phosphotyrosine via their SH2 domains. One of these signaling proteins, ZAP70, is associated with the phosphorylated form of 5 (Chan et al., 1992).There are three copies of ARAM per 5 chain but only one copy in each of the CD3 chains, structural features that may be related to different requirements for inducing diverse signaling pathways. For example, Sloan-Lancaster et al. (1994) found a different extent of 5 chain phosphorylation after challenging a clone of CD4+ T cells with different peptides of related sequence in association with an MHC-I1protein (see Antagonist peptides, Section VIII). B. C D 4 a n d C D 8

As noted in Section 11, the mutually exclusive expression of cell surface glycoproteins CD4 and CD8 on mature T cells distinguishes between the two major T-cell lineages. During development in the thymus, immature T cells express both markers (CD4+CD8+ or double positive cells); these cells make up the majority of thymocytes and appear to undergo commitment stochastically to either the CD4+ or CD8+ single positive phenotype as they mature (Davis et al., 1993; Chan et al., 1993). CD4 is a singlechain transmembrane glycoprotein, while CD8, which consists of two membrane-associated polypeptides, can be either an aa homodimer or an a/3 heterodimer; functional distinctions between them are not yet clear (see Weiss and Littman, 1994). In humans and mice, -60% of peripheral ap TCR+ cells are CD4+ cells and the rest are CD8+. The preponderance of CD4+ over CD8+ cells is not universal, however, and in the African green monkey -80% of peripheral T cells are CD8 and 10% are CD4+ (Ennen et al., 1994).

+

-

ANTIGEN-SPECIFIC T-CELL RECEPTORS

41

CD4 and CD8 are both members of the Ig superfamily, and each has a positively charged CDR-like loop that protrudes from the N-terminal domain (CD4 or CD8a) and is thought to make contact with an invariant region of MHC-I1 or MHC-I molecules, respectively (Wang et al., 1990; Ryu et al., 1990; Leahy et al., 1992). The binding of a soluble, genetically engineered MHC-I1 protein (HLA-DR4) to a soluble, immobilized preparation of CD4 was reported to have an equilibrium constant of 1 x lo5M-' (Cammarota et al., 1992). If a CD8 molecule on a T cell binds to precisely the same pepMHC-I complex on the target cell that is bound by the T-cell TCR, the CD8MHC-I interaction would be expected to enhance the overall stability of the TCR-pepMHC-I complex, and the same would be expected for CD4 and pepMHC-I1 complexes. However, no evidence for such stabilization was found when the binding of soluble pepMHC complexes (either class I1 or class I) to TCR on intact CD4+ or CD8+ T cells was measured (Matsui et al., 1991; Sykulev et al., 1994a).These negative results are in accord with the finding of the same equilibrium constant for the TCR-pepMHC-I1 reaction as measured with soluble pepMHC and either intact CD4+ T cells or genetically engineered, immobilized TCR (Matsui et al., 1994). Leuscher et al. (1995), however, have succeeded in showing with intact T cells and a photoaffinity-labeled soluble pepMHC-I complex that CD8 can modulate the TCR-pepMHC interaction. Different monoclonal antibodies to CD8a and CD8a chains appear to have different effects on the CD8-MHC-I interaction; while most antLCD8 antibodies are inhibitory, some enhanced CD8-MHC binding, suggesting that small conformational changes in the CD8 protein might influence its interaction with MHC. It is possible that the extent of interaction of CD4 and CD8 with MHC proteins may depend on the particular TCR and pepMHC complexes involved. Some observations also suggest the possibility that CD8 (and by implication CD4 as well) may also interact with the TCR itself (So0 and Kranz, 1993).

VIII. ALTERED PEPTIDE LIGANDS: PARTIAL AGONISTS AND ANTAGONISTS Until recently, the TCR was generally viewed as an on-off switch, with its binding site vacant or occupied by a ligand, with the liganded form, in sufficient amount and stability, causing the T cell to become activated. Surprisingly, however, it has turned out that small variations in the peptide component of pepMHC ligands can result in different manifestations of T-cell activation (Evavold and Allen, 1991; De Magistris et al., 1992; Alexander et al., 1993; Jameson et al., 1993; Racioppi et al., 1993; SloanLancaster et al., 1993; Vignali and Strominger, 1994). This phenomenon

42

HERMAN N . EISEN ET AL.

was clearly evident with a peptide derived from hemoglobin, HB64-76 (GKKVITAFVEGCK),in association with IEk (Sloan-Lancaster et d., 1993). Antigen presenting cells bearing this pepMHC complex stimulated a characteristic activation response by a CD4 T-cell clone: T-cell proliferation, cytokine secretion [IL-2, IL-3, y-interferon (y-IFN)], and hydrolysis of intracellular inositol phosphates. However, when the peptide was modified by a single Ala+Ser substitution at position 70 and presented with IEk, the T cells responded only partially; they failed to proliferate, produce cytokines, or hydrolyze inositol phosphates, but they were able to express high levels of IL-2 receptors and LFA-1 (an adhesion molecule), indicating that they could make a limited response to the altered peptide. Moreover, T cells exposed to the altered peptide were unable to proliferate for several days in response to the unmodified, optimally active (agonist) peptide Hb64-76. The persistent absence of proliferation in response to an immunogenic peptide appears to correspond to what was described earlier as T-cell anergy, a state resulting from the stimulation of CD4+ T cells via TCR ligation in the absence of a second costimulatory signal (see Mueller et al., 1989). Costimulation for most T cells is provided by engagement of the T-cell surface molecule CD28 by a protein ligand on AF'C, called B7, for which various subtypes have been described (reviewed by Linsley and Ledbetter, 1993; June et al., 1994; Jenkins, 1994). Anergy has been described for various CD4+ T cells ( T h o , T h l , and Th2) as well as for CD8+ T cells. Its hallmark is aberrant T-cell responsiveness to TCR engagement, notably failure of ligand binding to drive T-cell proliferation but preserved ability to trigger other manifestations of T-cell activation, such as production of cytokines or lysis of target cells. Some altered peptides (antagonists) even inhibit the cytolytic responses to an agonist peptide by T cells exposed to both peptides at around the same time (Jameson et al., 1993). The anergic state induced by an altered peptide ligand (a partial agonist or an antagonist peptide) has been found to be characterized by aberrant signal transduction (Sloan-Lancaster et al., 1994; Madrenas et al., 1995). Binding of agonist pepMHC complexes to a TCR results in a distinctive pattern of tyrosine phosphorylation of cytoplasmic domains of CD3 components and 5 chains. Since some altered peptides (partial agonists) induced a modified pattern of 5 chain phosphorylation, anergy is likely to result from activation of a distinct signal transduction pathway. The responses elicited by altered peptide ligands parallel to a large extent the activation of T cells by various monoclonal antibodies to the TCR or CD3. These antibodies can differ considerably from one another in the concentrations required to elicit a given T-cell response; the differences may be due to the different epitopes involved, as they seem not to correlate with variations in the affinities of antibodies for TCR (Rojo and

+

ANTIGEN-SPECIFIC T-CELL RECEPTORS

43

Janeway, 1988; Rojo et al., 1989; Yoon et al., 1994). However, the signal transduction events evoked by these surrogate ligands do not completely mimic those resulting from physiological ligands (pepMHC complexes). For example, both pepMHC complexes and antibodies to the E subunit of CD3 can trigger tyrosine kinase activity, but this response is inhibitable by CAMP only when the physiological stimulus is used (Klausner et al., 1987). Given the complexity of the multisubunit structure that includes the aB TCR, various CD3 subunits and chains, and probably CD8 or CD4 as well, it is likely that there are many different opportunities for various ligands that bind to the TCR complex to activate different signaling pathways. Whether the different responses elicited by agonist and partial agonist peptides (in pepMHC complexes) and by various anti-TCR antibodies result from differences in affinity or kinetics (e.g., bond lifetimes) or both is unclear. However, recent findings show that both equilibrium and rate constants are different for TCR reactions with agonist and antagonist pepMHC ligands (Alam et al., 1996; Lyons et al., 1996). Not surprisingly, an additional complexity is that the effects elicted by altered peptide ligands can vary with different T-cell clones raised against the same pepMHC. The biological significance of these complex effects is indicated by the finding that some naturally processed peptides of viral origin appear to act as antagonists (or partial agonists), even at extremely low concentrations, for some antiviral CTL (Klenerman et al., 1994; Bertoletti et al., 1994).

IX. MHC RESTRICTION BY SELF AND NONSELF MHC: THEPARADOX OF ALLOACCRESSION All the a/?TCR molecules on the mature T cells of an individual are imprinted, as it were, with the capacity to recognize that individual’s own MHC proteins (syngeneic MHC or “synMHC”) in the form of pepMHC complexes. The basis for this imprinting is emerging from studies on Tcell maturation in the thymus (e.g., reviewed by von Boehmer, 1994). Immature double positive (CD4+CD8+) thymocytes are stimulated to mature into single positive (CD4+ or CD8+) T cells through “weak” interactions of their TCR with pepMHC complexes on thymic epithelial cells (positive selection), whereas double positive cells that interact “strongly” with these complexes on thymic cells of hematopoietic origin undergo programmed cell death (negative selection). Although the peptides involved in these reactions have not been identified, and the kinetics, affinity, and specificity of the reactions in the thymus are all unknown, it is clear that the MHC proteins involved in both positive and negative

44

HERMAN N . EISEN E T AL.

selection are indigenous, i.e., synMHC. As long as they can associate with a synMHC, an enormous number of different foreign peptides can be recognized by one or another of the clonally diverse TCR on the mature T cells that migrate out of the thymus; in other words, antigen recognition is normally restricted by synMHC. Paradoxically, however, the same mature T cells can also react specifically with different MHC proteins from other individuals of the same species (“alloMHC”) (Bevan, 1975; Nahill and Welsh, 1993), and these reactions, like those restricted by synMHC, generally involve pepMHC complexes (Heath et al., 1989; Rotzschke et al., 1991b; Heath et al., 1991; Udaka et al., 1992, 1993). As described in Section 11, MHC genes are the most polymorphic known; for example, there are over 50 allelic variants of the murine gene Kb. The frequency of T cells in an individual that can react with any particular alloMHC is so high (e.g., -1:100, Fischer Lindahl and Wilson, 1977; Erard et al., 1985) that virtually every TCR must be able to recognize not only a peptide restricted by synMHC but also one or more alloMHC molecules, also associated with peptides. CTL clone 2C, referred to earlier (e.g., Tables 111-V), is an example of such an alloreactive clone. It was obtained from an H-2bmouse immunized with H-2d cells and responds specifically to Ld (one of the three MHC-I proteins on H-2d cells) in association with a peptide (termed p2Ca) that derives from the cellular protein a-ketoglutarate dehydrogenase (aKGDH) (Kranz et d., 1984a; Udaka et d., 1992, 1993). Genes for the a and /3 subunits of the TCR on 2C cells have been expressed as transgenes in mice with different MHC halotypes (Sha et al., 1988a,b). In mice with the H-2d haplotype, double positive thymocytes that express transgenes for the 2C TCR undergo programmed cell death and fail to develop into mature T cells (negative selection), probably because of strong interactions in the thymus between this receptor and Ld in association with thymic peptides (e.g., p2Ca or other longer peptides [p2Cb] from the same ubiquitious protein) (see Udaka et al., 1993). However, in mice that lack Ld and have the H-2b haplotype (the background haplotype in which the 2C cell arose), double positive thymocytes having the 2C TCR are positively selected by Kb (synMHC), presumably as a result of weak interactions with pep-Kb complexes (whose peptides are still unknown). Thus, most peripheral T cells in H-2b 2C TCR transgenic mice express the 2C TCR, and despite having been positively selected by Kb they are able to react strongly with Ld in association with p2Ca (and related peptides from a-KGDH). To compound this paradox the affinity of the 2C TCR for the pep.alloMHC ligand p2Ca-Ld is unusually high; indeed, it has been suggested that TCR affinity generally tends to be higher for pep.alloMHC than for pep. synMHC complexes (Sykulev et al., 1994b, and see Fig. 7).

45

ANTIGEN-SPECIFIC T-CELL RECEPTORS

4

B

\

\

\

\

\

\

I

\

\

\

\

3

4

5

6

7

8

9

3

4

5

6

7

\

8

9

Log K FIG. 7. Hypothetical distribution of intrinsic TCR affinities in populations of T cells recognizing syngeneic MHC (solid line) and allogeneic MHC (dashed line), pepMHC complexes, before (A) and after (B) thymic selection. The higher affinity (K in M-I units) for peptide-alloMHC than for peptide-syngeneic MHC complexes (B) is ascribed to differences in affinity for the MHC components of the respective complexes (see text).

Why should a TCR restricted by a syngeneic MHC also be restricted by an ostensibly unrelated allogeneic MHC, and why might TCR affinity for pep~alloMHCtend to be higher than for pep-synMHC? The answers to these questions probably stem from the fact that TCR genes and MHC genes segregate independently. In an outbred population the TCR genes inherited from each parent probably encode a TCR repertoire that is so highly diversified that it can recognize virtually any MHC protein of the species. This broad repertoire is then narrowed down in each individual by positive and negative selection in the thymus to become restricted for antigen recognition by MHC proteins produced in that individual (syngeneic MHC). Through negative selection, immature T cells whose TCR happen to have high affinity for a syngeneic MHC are actively eliminated; those that do not recognize syngeneic MHC die 0% and those that react weakly with them are stimulated to proliferate and become mature T cells, whether or not their TCR happen to have high affinity for an alloMHC. Hence a mature T cell, having survived negative selection and been positively selected, has an immeasurably low but significant affinity for a syngeneic MHC (i.e., the restricting MHC), but can still have high affinity for one (or more) allogeneic MHC proteins. The resulting hypothetical distribution of TCR affinities for synMHC and alloMHC before and after thymic selection is illustrated in Fig. 7.

46

HERMAN N . EISEN ET AL.

The difference between a mature T cell's affinity for a syngeneic and an allogeneic MHC protein might be estimated if the measured affinities for pepMHC complexes (pepmsynMHCand pep-alloMHC, respectively) could each be resolved into two affinity values, one for the peptide adduct and the other for its MHC partner. To this end it may be useful to consider the pronounced amino acid sequence similarities between TCR and antibodies (see Section IV) and the crystal structures of antigen-antibody complexes (Amit et al., 1986; Davies et al., 1990). In the complex formed by lysozyme and the Fab fragment of an antilysozyme antibody, approximately 17 amino acid side chains of the antigen, presenting a solvent-accessible area of 650 make contact with the antibody binding site. The intrinsic affinity for the interaction of lysozyme with this Fab fragment at 25°C is about 3 x 108M-l (Bhat et al., 1994; Foote and Winter, 1992), or 11,450 calories per mole of antigen bound. Hence the antigenic epitope contributes, per mole bound, -20 cal/Az of accessible ligand area, or close to the 25 cal/Az estimated for various proteinprotein interactions (Janin and Chothia, 1978). In applying this estimate to TCR-pepMHC reactions, it is notable that X-ray crystallographic analyses of several pepMHC complexes have shown that about 70-80% of the solvent-accessible area of the peptide moiety is buried in the MHC binding groove (Fremont et al., 1992; Madden et al., 1993; Zhang et al., 1992). For example, the exposed area of octamer or nonamer peptides bound to K" or D" and available to interact with a TCR was only about 175 despite marked differences in peptide sequence (Young et al., 1994), suggesting that perhaps peptides quite generally may be expected to contribute -3500 cal per mole bound, with the rest of the binding energy for the TCR-pepMHC reaction coming from the MHC component. Consider, for example, the reaction of the alloreactive CTL 2C with QL9-Ld, a pep-alloMHC complex (Table 111).With a 2C TCR affinity for this complex of 1.5 x lo7M-' (Sykulev et al., 1994b), AGO = 9700 cal per mole pepMHC bound (at 25°C) or, deducting 3500 cal for the peptide contribution, -6000 cal per mole alloMHC (Ld)bound, it follows that the hypothetical equilibrium constant for the reaction of the 2C TCR with the Ld part of the composite epitope is -3-4 x lo3 M-'. Since affinity values this low can support a cytotoxic response (Sykulev et al., 1994a), providing the epitope density is high enough (Dutz et al., 1994; see also Fig. 6), these estimates can explain why some alloreactive CTL appear to react with alloMHC regardless of associated peptide adducts (Rotzschke et al., 1991b; Elliott and Eisen, 1990; Zhou et al., in progress). Note added inproot Some dipeptides bind to Ld and confer on it the ability to elicit a cytolytic response by CTL clone (2C) (Vturina, Sykulev, and Eisen, in preparation). This clone can engage in vigorous alloreactions with Ld in association with various nanomers (e.g., Fig. 4) and longer peptides. The affinity of the 2C

Az,

Az,

ANTIGEN-SPECIFIC T-CELL RECEPTORS

47

TCR for these Ld-dipeptide complexes, estimated from the relationship shown in Fig. 5 , is about 1 x lo4M-'. Since the dipeptide adduct in these complexes probably made no direct contact with the 2C TCR, this affinity value is in reasonable agreement with the calculated value of around 4 x lo3M-' (above) for the 2C TCR affinity for Ld. To the extent that the 2C TCR reaction with Ld-peptide complexes is representative of many alloreactions, it would seem that the relatively high affinity of the TCR for the MHC component of pepaalloMHC complexes could account for several of the key differences between a T cell's reaction with syngeneic and allogeneic MHC proteins (as pepMHC complexes), i.e., less stringent requirements for particular peptide sequences and therefore a wider range of cross-reactive peptide adducts in the alloreactions. These differences could account for the exceptionally high frequency of alloreactive T cells.

X. CONCLUDING REMARKS

Since the TCR was first identified, the naturally processed peptides that serve in association with MHC-I or MHC-I1 proteins as the receptor's natural ligands have been extensively characterized. A start has been made toward establishing the abundance of these ligands on target cells and APC, determining the kinetics and affinities of their reactions with TCR, and correlating these values with the magnitude of TCR-mediated responses by intact T cells. More extensive analyses of this kind, as well as measurements of TCRepepMHC bond lifetimes, should provide a solid basis for understanding the great variations in magnitude of T-cell responses and help explain why different pepMHC having only slightly altered peptides can elicit very different responses. Much of the progress made to date has been facilitated by the use of a small number of stable T-cell clones or T-cell hybridomas. Are these cells authentic representatives of normal T cells? Most T cells undergo senescence or apoptosis in vivo in response to repeated ligand binding to their TCR, and only a rare T cell can be successfully established as a cultured clone by current techniques, e.g., only one or two clones from an optimally immunized mouse. Given the idiosyncratic nature of each clone, it would be useful to be able to generate and study large numbers of individual clones and even more useful to develop rigorous methods for analyzing polyclonal T-cell populations. Beyond these challenges is the far greater one of applying the accumulating information about the TCR and its reactions for manipulating T cells and their responses in vzvo, augmenting them against epitopes on pathological targets (e.g., cancer cells and HIVinfected cells), or suppressing them in autoimmune disorders.

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NOTE

We regret that many significant and relevant publications are not included in the reference list, which was assembled without an attempt to be comprehensive, but rather to reflect the review’s particular focus. The manuscript was completed in March 1995. Publications appearing since that date are cited only if they seemed especially relevant to issues being stressed.

ACKNOWLEDGMENT The preparation of this review was supported in part by research grants (CA60686 and AI34247), a training grant (R35-CA42504), and a Cancer Center Core grant (CA14051), all from the National Institutes of Health.

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X-RAY CRYSTALLOGRAPHY OF ANTIBODIES By EDUARDO A. PADLAN Laboratory of Molecular Biology National institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health Bethesda, Maryland 20892

I. Introduction. .................... . . . . . . . . . . . . . . A. Elements o B. Analysis and Presentation of Crystal Structures . . . . . . . . . . . . . . . . . . . . . . C. Definitions and Conventions. . . . . . . . . . . . . A. General Structure of Antibodies

..................... ..................

..................

A. General Structure

B. Rotational Symme C. F a b B e n d . . . . . . . . D. Hypervariable or Complementarity-Determining Regions . . . . . . . . . . . . .

..................................

57 58 66 67 67 68 70 70 72 74 75 78 79 79 81 81 85 86 87 87 94 120 125 128

I. INTRODUCTION

The detailed structure of antibodies and various fragments, including isolated domains, from different isotypes and from different species has become available from X-ray crystallography. Also, amino acid and nucleotide sequence data have been obtained for thousands of different chains (Kabat et al., 1991), so that a detailed correlation of primary and three-dimensional structures can be performed. With this wealth of information, we can now begin to understand the biological functions of antibodies in structural terms. ADVANCES IN PROTEIN CHEMISTRY, Vul. 49

57

58

EDUARDO A. PADLAN

The aim of this article is to review what is currently known about antibody structure from X-ray crystallography. A very detailed analysis of the structure of antibodies has been made by the author (Padlan, 1994a) and a separate tome devoted to antibody-antigen complexes has been written (Padlan, 1994b). This review extends those earlier analyses to include the more recently available data. We will start with a brief description of X-ray crystallography as applied to protein structure: what it can provide, and what its limitations are. We will then analyze the results of the crystallographic studies of antibodies, their fragments, and ligand complexes, and see how the results of these studies have led to comparisons and generalizations with regard to the structure and biological properties of these molecules. A list of antibody structures that have been elucidated using X-ray crystallography is presented in Table I. Other reviews to be consulted include Braden and Poljak (1995), Colman (1991), Davies and Chacko (1993), Sheriff (1993), and Wilson and Stanfield (1993). A. Elements of X-Ray Crystallography For a comprehensive discussion of the technique, see “Protein Crystallography” by Blundell and Johnson (1976), “X-ray Structure Determination’’ by Stout and Jensen (1989), “Principles of Protein Crystallography” by Drenth (1994), and the collection of papers in “Methods in Enzymology,” Volumes 114 and 115 (Wyckoff et al., 1985) and in ImmunoMethods Volume 3 (1993). X-rays, like other electromagnetic waves, are scattered (diffracted) by charged particles. The extent of scattering is directly proportional to the charge of the scatterer and inversely proportional to its mass. X-rays impinging on an object, therefore, are primarily scattered by the electrons, and the structure obtained from the analysis of the diffraction pattern represents mainly the distribution of electrons in the diffracting material. The distribution of electrons is unique to each diffractor, so that every molecular species has its characteristic diffraction pattern. Similar structures produce similar diffraction patterns. When X-rays pass through a sample containing a collection of molecules, the resulting diffraction pattern is the (vector) sum of the individual scattering patterns. When the molecules are in an ordered array, as in a crystal, the molecular diffraction pattern is amplified. Further, interference produces strong peaks where the individual patterns reinforce each other and blank regions where the patterns cancel each other, so that the resulting pattern is discrete; in solution, the molecules are in disarray and the diffraction pattern is continuous. The diffraction pattern of a crystal is

TABLE I Immunoglobulin Structures Determined by X-ray Cytallography

Antibody

lsotype

Fragment

Human Dob KO1

Whole Ig Whole Ig

Mcg

Whole Ig

New

Fab Fab Fab Fab Fab Fab Fv L-Dimer L-Dimer L-Dimer L-Dimer L-Dimer L-Dimer L-Dimer L-Dimer L-Dimer L-Dimer L-Dimer L-Dimer L-Dimer L-Dimer L-Dimer

Kol Hi1 3D6 TRl.9 Pot Mcg

PDB code

2IG2 1MCO 7FAB 2FB4 8FAB 1DFB

1IGM 2MCG 3MCG lMCB 1MCC 1MCD 1MCE 1MCF 1MCH 1MCI 1MCJ IMCK lMCL 1MCN 1MCQ lMCR

Resolytion (A)

4.0 3.0 3.2 2.0 3.5 1.9 1.8 2.7 1.97 2.3 2.0 2.0 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7 2.7

R value

Ligand

0.207 0.232 0.169 Vitamin KlOH

0.189 0.173 0.177 0.180 0.201 0.187 0.208 0.204 0.199 0.190 0.191 0.194 0.252 0.177 0.193 0.189 0.189 0.183 0.204 0.204

Refs.

Sarma and Laudin, 1982 Marquart et al., 1980 Guddat et al., 1993 Saul and Poljak, 1992 Amzel et al., 1974 Marquart et al., 1980 a

He et al., 1992 b

Acetyl-QFHP-OH Acety-QFHP-NH2 Acetyl-FAHP-NH2 Acetyl-QFHPA-OH Acety 1-QFHPAA-OH Acetyl-QFHPAA-OH AcetyI-FHP-OH Acetyl-FHP-NH2 Acetyl-EHP-NH2 Acetyl-HP-OH Acetyl-HP-NHs Acetyl-HP-NH2 Acetvl-HP-OH

Fan et al., 1992 Ely et al., 1989 Ely et al., 1989 Edmundson et al., Edmundson et al., Edmundson et al., Edmundson et al., Edmundson et al., Edmundson et al., Edmundson et al., Edmundson et al., Edmundson et al., Edmundson et al., Edmundson et al., Edmundson et al., Edmundson et al..

1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 (continued)

TABLE I (continwd)

Antibody

Isotype

Loc

1

Mcg-Weir Rei Au Rhe ROY Wat Pooled

1 K K

1 K

K

IgGl 161

0,

M06 1 IgGi “Humanized’ murine 4D5

H52 Murinehuman chimera B72.3 BR96 Murine MAb231 McPC603

1gG2,,~

IgA, K

Fragment

PDB code

L-Dimer L-Dimer L-Dimer VL-Dimer VL-Dimer VL-Dimer VL-Dimer VL-Dimer Fc Fc Fc

IBJL 2BJL 1MCW IRE1

Resolution

(4

R value

lwTz lFCl 1FC2 1FCC

3.0 2.8 3.5 2.0 2.5 1.6 3.0 1.9 2.9 2.8 3.5

0.194 0.216 0.170 0.24 0.31 0.149 0.33 0.157 0.22 0.24 0.289

Fv Fab Fab Fab Fv

IFVC lFVD IFVE 2FGW 1FGV

2.2 2.5 2.7 3.0 1.9

0.183 0.179 0.171 0.178 0.180

Fab Fab

IBBJ (1CLZ)k

3.1 2.5

0.176 0.238

1MCP 2MCP 21MM 21MN

3.5 2.7 3.1 2.00 1.97

0.188 0.225 0.196 0.149 0.149

Whole Ig Fab Fab VL

VL, CDR-1 replaced

2FUIE

Refs.

Ligand

-

~

Fragment B of protein A C2 fragment of protein G

Chang et al., 1985 Schiffer et al., 1989 Ely et al., 1985 Epp et al., 1975 Fehlhammer et al., 1975 Furey et al., 1983 Colman et al., 1977 Huang et al., 1994 Deisenhofer, 1981 Deisenhofer, 1981 Sauer-Encksson et al., 1995 Eigenbrot et al., Eigenbrot et al., Eigenbrot et al., Eigenbrot et al., Eigenbrot et al.,

Nonoate methyl ester Lewis Y

Phosphocholine

1993 1993 1993 1994 1994

Brady et al., 1992 Jeffrey et al., 1995b Harris et al., 1992 Satow et d.,1986 Padlan et al., 1985 Steipe et al., 1992 Steipe et al., 1992

HyHEL-5

Hed 10 CF4C4

NClO

IgG1, K

Fab Fab Fab Fv Fv Mutant Fv Fab Fab Fab Fab Fab Fab Fab Fab Fab Fab Fab Fab scFv’ Fab Fab Fab Fab Fab Fab Fab Fab Fab Fab Fab Fab Fab

2FBJ 1FDI lVFB lVFA 1NCA 1NCC lNCB INCD 2HFL 2IFF 1BQL

lJEL

3HFM 4FAB 2F19 1FA1 2IGF 1IGF

lCBV 1NBV 6FAB 1BAF

1.95 2.5 2.6 1.8 1.8 1.8 2.5 2.5 2.5 2.9 2.54 2.65 2.6 3.0 4.0 2.8 3.5 2.2 3.0 3.0 2.7 2.8 2.7 2.5 2.8 2.8 3.0 4.0 2.66 2.0 1.85 2.9

0.194 0.184 0.27 0.158 0.185 0.208 0.191 0.2 12 0.165 0.157 0.245 0.183 0.191 0.272 0.470 0.193 0.213 0.203 0.246 0.215 0.182 0.189 0.179 0.22 0.18 0.25 0.28 0.191 0.246 0.248 0.195

C

Lysozyme Lysozyme Lysozyme Influenza virus neuraminidase Neuraminidase I368R mutant Neuraminidase N329D mutant Influenza virus neuraminidase Lysozyme Lysozyme R68K mutant Lysozyme (bobwhite quail)

E. colz HPr Influenza virus neuraminidase Influenza virus neuraminidase Lysozyme Fluorescein

D1.3 Fab Myohemerythrin peptide Angiotensin I1

DNP-spin label hapten

Fischmann et al., 1991 Bentley et al., 1989 Bhat et al., 1994 Ysern et al., 1994 Tulip et al., 1992a Tulip et al., 1992b Tulip et al., 1992b Tulip el al., 1992a Sheriff et al., 1987 Chacko et al., 1995 d

Cygler et al., 1987 Vitali et al., 1987 Prasad et al.. 1993 Malby et al., 1994 Kortt et al., 1994 Padlan et al., 1989 Herron et al., 1989 Lascombe et al., 1992 Lascombe et al., 1992 Bentley et al., 1990 Stanfield et al., 1990 Stanfield et al., 1990 Garcia et al., 1992 Garcia el al., 1992 Herron et al., 1991 Herron et al., 1991 Strong et al., 1991 Bruenger et al., 1991 (continued)

TABLE I (continued)

Antibody NQ10/12.5 TE33 Se155-4

R45-45-11 MAb28

Isotype IgGI, K IgG, K IgGI,I

IgGI, K

PDB code

Resolution

(4

R value

2.8 3.0 2.3 2.0 2.1 2.1 2.1 1.7 2.7 2.5 2.5

0.182 0.19 0.148 0.185 0.163 0.160 0.183 0.166 0.177 0.176 0.2 1

]GIG 1DBA 1DBB 1DBJ 1DBK 2DBL

2.3 2.8 2.7 2.7 3.0 2.9

0.195 0.202 0.210 0.214 0.21 1 0.205

Fab Fab Fab

1DBM 1IKF

2.7 2.5 7

0.218 0.164

Fab Fab Fah Fah Fab

lMAM

2.45 2.8 2.8 3.1 2.9

0.215 0.152 0.174

Fragment Fab Fab Fab Fab Fab Fab Fab Fv Fab Fah Mutant Fah Fah Fab Fab Fah Fab Fab Fab

lTET 1MFE 1MFC lMFB lMFD 1MFA 1IGI 1IGJ

1HIN lHIM

0.22 0.20

Refs

Ligand 2-phenyloxazolone Cholera toxin peptide Dodecasaccharide Heptasaccharide Heptasaccharide Trisaccharide Trisaccharide Digoxin

Alzari et al., 1990 Alzari et al., 1990 Shoham, 1993 Cygler et al., 1991 e e

Bundle et al., 1994 Zdanov el ah, 1994 Jeffrey et al., 1993 Jeffrey et al., 1993 Bruenger, 1991 Wilson et al., 1991

f Progesterone Etiocholanolone 5B-Andostane-3,17-dione 5a-Pregnan-20-one, 3p-hemisuccinate Progesterone 1la-hemisuccinate Cyclosporin A HIV-1 reverse transcriptase and DNA

YsT9-1 Fab Hemagglutinin peptide Hernagglutinin peptide

Arevalo et al., Arevalo et al., Arevalo et al., Arevalo et al., Arevalo et al..

1993a 1993a 1993b 1993b 1993b

Arevalo et al., 1993h Vix et al., 1993 Arnold et al., 1992 Rose et al., 1993 Evans et al., 1994 Evans et al., 1994 Rini et al., 1992 Rini et al., 1992

2619 50.1

59.1 8F5 F9.13.7 CHA255 1F7 NC6.8

5 2 01

D11.15 17-IA 17E8 730.1.4 409.5.3 CNJ206 D44.1 Jell03

MOPC2 1 M29b .]el 72

Fab Fab Fah Fab Fab Fab Fah Fab Fab Fab Fab Fab Fab Fab Fab Fv Fab Fab Fab Fab Fab

lHIL lIFH 1FRG 1GGB 1GGC 1GGI lACY 1BBD

1IAI 1IAI 2GFB

2.0 2.8 2.8 2.8 2.8 2.8 3.0 2.8 2.5 3.0 2.2 2.8 3.0 2.6 2.2 2.4 2.75 2.5 2.9 2.9 3.0

0.19 0.170 0.190 0.20 0.19 0.188 0.21 0.190 0.179 0.190 0.188 0.176 0.220 0.2 18 0.214 0.214 0.174 0.186 0.2 1 0.2 1 0.2 1

Fab Fab Fab Fab Fab Fab

1MLB 1MLC 1MRC 1MRD 1MRE 1MRF

2.1 2.1 2.4 2.3 2.3 2.4

0.181 0.184 0.191 0.195 0.192 0.184

Fab VL Fah

1rcc 1IVL

2.6 2.17 2.7

0.168 0.175 0.188

lFBI lIND lINE 1FIG 1CGS 2CGR lJHL 1FOR

Hemagglutinin peptide Hemagglutinin peptide

HIV- 1 g~ 120 V3 loop HIV- 1 g~ 120 V3 loop Rhinovirus VP2 peptide Lysozyme (guinea fowl) Hydroxyethyl EDTA + indium Hydroxyethyl EDTA + iron Transition state analog NC174 sweetener Lysozyme (pheasant) Transition state analog Fab 409.5.3 Fab 730.1.4

Lysozyme Inosine 5‘-diphosphate Guanosine 5’-diphosphate Deoxyinosine 5’-monophosphate Protein G

Rini et al., 1992 Schulze-Gahmen et al., 1993 g h h

Rini et al., 1993 Ghiara et al., 1994 Tormo et al., 1992 Tormo et al., 1994 Lescar et al., 1993 Love et al., 1993 Love et al., 1993 Haynes et al., 1994 Guddat et al., 1994 Guddat et al., 1994 Chitarra et al., 1993 Liu et al., 1994 Zhou et al., 1994 Ban et al., 1994 Ban et al., 1994 Golinelli-Pimpaneau et al., 1994 Braden et al., 1994 Braden et al., 1994 Pokkuluri et al., 1994 Pokkuluri et al., 1994 Pokkuluri et al., 1994 Pokkuluri et al.. 1994 Derrick and Wigley, 1994 Essen and Skerra, 1994 Mol et al., 1994a

(continued)

TABLE I (continued)

Antibody Jel318 c3 R6.5 L5MK16 40-50 BR96 Rabbit Guinea pig Rat

Isotype

Fragment Fab Fab Fab diAb Fab Fab Fc pFc' Fc

PDB code 1FPT 1RMF lLMK 1IBG (1CYL) 1PFC 1FRT

Reso!ution (A) 2.8 3.0 2.8 2.6 2.7 2.78 2.7 3.125 4.5

R value

Ligand

0.207 0.23 0.188 0.20 0.209 0.197

Ouabain Nonoate methylester Lewis Y

0.303 0.423

Neonatal Fc receptor

Viral peptide

Refs. Mol et al., 1994b Wien et al., 1995 i

Perisic et al., 1994 Jeffrey et al., 1995 Jeffrey et al., 1995 Sutton and Phillips, 1983 Bryant et al., 1985 Burmeister et al., 1994

Saul, F., and Poljak, R. J. (to be published), cited in PDB entry 8FAB. Chacko, S., Padlan, E. A., Portolano, S., McLacblan, S. M., and Rapoport, B. (to be published). Bhat, T. N., Padlan, E. A., and Davies, D. R. (to be published), cited in PDB entry 2FBJ. Chacko, S., Silverton, E., Hibbits, K., Xavier, A., Willson, R., and Davies, D. (to be published), cited in PDB entry lBQL. Zdanov, A,, Li, Y., Bundle, D. R., and Cygler, M. (to be published), cited in PDB entry IMFB. Bizebard, T., Daniels, R., Kahn, R., Golinelli-Pimpaneau, B., Skehel, J. J., and Knossow, M. (to be published), cited in PDB entry 1GIC. Churcbill, M. E. A,, Stura, E., Pinilla, C., Appel, J. R., Dwight, R. A. H., Kono, H., Balderas, R. S., Fieser, G. G., Schulze-Gahmen, U., and Wilson, I. A. (to be published), cited in PDG entry 1FRG. Stanfield, R. L., Takimoto-Kamimura, M., Rini, J. M., Profy, A. T., and Wilson, I. A. (to be published), cited in PDB entry IGGB. Jedrzejas, M. J., Miglietta, J., Griffin,J. A,, and Luo, M. (to be published); cited in PDB entry 1RMF. scFV, single-chain Fv. PDB codes enclosed in parentheses signify that the atomic coordinates are on hold as of this writing. Only the most recent reference, or that for the highest-resolution study, is cited. a

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

65

more easily measured and is more amenable to interpretation in terms of molecules and atoms. The structure of a diffractor can be obtained by performing an inverse operation, i.e., by obtaining the (vector) sum of the scattered waves to produce an image; this is entirely equivalent to what an optical lens does with visible light. This summation requires both the amplitude and the phase of the individual waves. It is relatively easy to measure the amplitude of a diffracted X-ray wave, but the determination of its phase is not straightfonvard. The phases can be obtained by using heavy-atom derivatives, and the early work on antibodies employed this method. The structure can also be determined by molecular replacement, a search method that uses a known structure as a probe, and most of the more recently determined antibody structures have been obtained by this procedure. The use of heavy-atom derivatives requires no previous knowledge of the structure and is totally unbiased in that regard. Molecular replacement, on the other hand, assumes a similarity between the unknown structure and the probe; any difference that may exist has to be removed by painstaking rebuilding and exhaustive refinement (see later discussion). The structural detail that can be discerned from an electron density map, i.e., its resolution, depends on the wavelength of the X-rays used in the experiment and on the extent and accuracy of the diffraction data used in generating the map. At low resolution, about 5 A, only gross features of a protein molecule can be discerned (e.g., molecular boundaries, quaternary structure, and secondary structural features like helices and sheets), but the course of the polypeptide chain often cannot be traced. At intermediate resolution, about 2.5 A, the tertiary structure, structural details like disulfide bridges, and the ordered side chains can be discerned. At higher resolution, 2.0 A or better, most of the side chains can be clearly seen and individual atoms begin to be discernible; also, solvent molecules, if they are ordered, can often be located with confidence. The precision of a crystal structure analysis is usually assessed by computing the value of the crystallographic residual, the R value, an agreement factor that relates the observed intensities with those expected on the basis of the proposed structure. The R value is defined as the percentage difference between actual and computed wave amplitudes, averaged over all the data used in the analysis. In the structure analysis of large molecules, R values of 20% or lower usually signify good agreement between the computed and experimentally obtained diffraction data. A proposed crystal structure is refined, i.e., adjusted, until the R value is reduced to a minimum. During refinement, bond lengths, bond and dihedral angles, nonbonded contacts, and other measures of stereochemistry are monitored to ensure that they do not deviate too far from ideal values.

66

EDUARDO A. PADLAN

Structures determined to only low or intermediate resolution may have large uncertainties. Conservative estimates of the probable errors in atomic positions can be several tenths of a! A. For example, a crystal structure determined at a resolution of 2.5 A and refined to a crystallographic R value of 25% may have an uncertainty of 0.4 A, while one determined at a resolution of better than 2.0 A aad refined to an R value of less than 20% may have an uncertainty of 0.25 A or less. These estimates (Luzzatti, 1953) are for the most ordered, usually interior, parts of the molecule; the uncertainties in the more exposed parts, especially in the atoms of the side chains, can be expected to be higher. Sometimes certain regions of the molecule are not discernible, or are “invisible,” on the electron density map. This is probably because these regions are not ordered in the crystal; they assume several different orientations or positions in the lattice and are then averaged out. Conscientious crystallographers omit these regions when depositing the coordinates [in the Protein Data Bank (PDB) (Abola et al., 1985; Bernstein et al., 1977)], or label them appropriately.

B. Analysis and Presentation of Crystal Structures Protein structures are often presented as ball-and-stick models, and sometimes as stereo drawings to produce a three-dimensional effect. Rapidly becoming standard is the use of ribbon diagrams, pioneered by Richardson (198 1) as free-hand drawings and nowadays as computergenerated illustrations. Secondary structures, e.g., a-helices and @-sheets, are more easily recognizable and tertiary structure is more easily traced in ribbon diagrams. Where warranted, details are presented using ball-andstick illustrations superimposed on ribbon drawings. In many instances, the topography of the surface of a protein molecule is of interest. Van der Waals and solvent-accessible surfaces are often presented. Points on the molecular surface are usually computed using the algorithm of Lee and Richards (1971), often employing the program MS of Connolly (1983). Certain aspects of the molecular surface, e.g., its electrostatic properties (Sharp et al., 1991),are sometimes computed and displayed. Hopefully, the usual depiction of molecular structure and surface does not give the impression that protein structures are static. Proteins in solution are in fact dynamic (Karplus, 1977) and some parts may be more mobile and more deformable than others. Protein structures, especially those involving complexes, are often analyzed in terms of interatomic contacts, subunit interfaces, etc. In this regard, there is no consensus among researchers on what constitutes a contact, or what solvent radius to use in the calculation of molecular surfacgs. Some consider two atoms as being in contact if they are within, say, 4.0 A of each

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

67

other; others define contact in terms of the van der Waals radii of the atoms. Here, two atoms are designated as being in contact if they are within the sum of their van der Waals radii plus 0.5 A from each other [using van der Waals radii for extended atoms (Gelin and Karplus, 1979)l; the 0.5 A allowance assumes an average uncertainty in atomic positions of 0.35 A, which is roughly the average for the crystal structures obtained so far for antibodies and their fragments (Table I). Polar atoms are designated as being hydrogen-bonded if the distance between them is at most 2.90 A (taken to be the standard hydrogen bond length) plus 0.5 A; oppositely charged atoms are designated as forming an ion pair if the distance between them is at most 2.85 A (taken to be the standard ion pair distance) plus 0.5 A. A solvent radius of 1.7 8, is used in all calculations of molecular surface. C. Definitions and Conventions

The numbering convention of Kabat et al. (1991) will be used here unless otherwise noted. Their delineation of the complementaritydetermining regions (CDRs) and of the boundaries between the various domains will be followed also. No distinction is made here between Fab and Fab', and Fab will be used to represent the fragment that contains the VL, CL,VH,and CH1domains. 11. X-RAYCRYSTALLOGRAPHY OF WHOLE ANTIBODIES

Crystals of antibodies have been available since at least 1938 when spontaneous crystallization of myeloma proteins was reported by von Bonsdorff et al. (1938). More reports on crystalline macroglobulin from human sera followed (e.g., Kratochvil and Deutsch, 1956; Caputo and Appella, 1960). Crystals of intact rabbit anti-p-azobenzoate antibody were reported in 1967 (Nisonoff et al., 1967), but they gave a poor diffraction pattern (Rossi and Nisonoff, 1968).Shortly thereafter, more ordered crystals were obtained for a human immunoglobulin (Terry et al., 1968) and the three-dimensional structure of an intact antibody soon became available (Sarma et al., 1971). Crystal structures for four intact antibodies have now been reported in the literature. These structures are for the human myeloma proteins Dob, Mcg, and Kol, and for the murine monoclonal antibody MAb23 1, which is directed against canine lymphoma. The first structure obtained was for the human myeloma protein Dob, which was determined with heavy-atom derivatives at 6 A resolution (Sarma et al., 1971).A reasonable outline of the molecular boundary was traced on the electron density map, revealing a T-shaped molecule. However, no other details could be extracted from the map. After the structures of Fabs and of Fc became available, the electron density map was reinterpreted

68

EDUARDO A. PADLAN

and a structure for protein Dob was proposed, with the two Fabs in close association with the Fc (Silverton et al., 1977). Later, diffraction data to 4.2 A were collected, but no further details of the structure were revealed (Sarma and Laudin, 1982). A more detailed and accurate structure has been obtained for the human myeloma protein Kol. The crystal structure was determined using heavy-atom derivatives, first at 5 A resolution (Colman et al., 1976) and later at 3.0 A (Marquart et al., 1980). The electron density map allowed a detailed description of the Fabs and the upper part of the hinge, but the Fc was not at all visible. The Fc had ostensibly assumed several different locations and orientations in the crystal lattice. The crystal structure of the human myeloma protein Mcg was first determined at 6.5 A resolution using heavy-atom derivatives (Rajan et al., 1983). As in the case of Dob, the electron density map showed the two Fabs to be in close contact with the Fc. The structure analysis was subsequently extended to 3.2 A resolution, and an atomic model for protein Mcg has been built (Guddat et al., 1993). The crystal structure of the intact murine monoclonal antibody MAb231 has been determined at 3.5 A resolution by molecular replacement and refined to an R value of 18.8% (Harris et al., 1992). The analysis permitted the location of all parts of the antibody molecule including the hinge. The overall structure was found to be quite asymmetric, and the hinge appears to be in an extended configuration. The antibodies for which crystal structures are available are all of the IgG type, and so their Fc portions contain only the CH2and CH3domains. Yet to be studied crystallographically are antibodies with an additional domain in their Fcs. A . General Structure of Antibodies

Electron microscopic studies have shown that antibody molecules possess segmental flexibility (Valentine and Green, 1967) and this flexibility has proven to be the bane of X-ray crystallographers. Of the four intact antibodies for which crystal structures are available, two, Dob and Mcg, have deletions in the hinge region (Fett et al., 1973; Steiner and Lopes, 1979) that render these molecules more rigid and ostensibly more amenable to crystallization. Not unexpectedly, in these two antibodies, the Fabs are found to be in close association with the Fc. A schematic representation of the structure of protein Mcg is presented in Fig. 1. ~

FIG 1. Ribbon drawing of the human antibody Mcg (PDB entry 1MCO). The heavy chains are darker. The Fabs are on top and the Fc is at the bottom. The carbohydrates between the CH2 domains are portrayed in ball-and-stick format. (Courtesyof Chacko, NIH.)

70

EDUARDO A. PADLAN

A normal hinge is present in Kol, but segmental flexibility, which could cause crystalline disorder, has apparently prevented visualization of the Fc (Fig. 2). The occurrence of segmental flexibility has been proposed to explain the crystallographic results for the human myeloma protein Zie also. For this molecule, the diffraction patterns for crystals of the whole antibody and for the F(ab)n are indistinguishable (Ely et al., 1978).

B. Fragments

The two Fabs and the Fc are roughly the same size, each Fab being about 80 A long with an average cross section of about 45 A, while the Fc is slightly shorter at 70 A. In the murine antibody MAb231, the three fragments are seen as structurally independent units, with the Fabs tethered to the Fc by flexible hinge segments. In the human antibody Kol, only the two Fabs are visible, but they are more closely associated (Fig. 2). The structure of Fc and of the Fabs is presented in greater detail later. C. Domains

The basic unit in the construction of an antibody molecule is the domain. All antibody domains are found to have the same basic tertiary structure (Poljak et al., 1973; Schiffer et al., 1973), named the immunoglobulin fold by Poljak and co-workers (Poljak et al., 1973). Each domain consists of two P-pleated sheets, both formed by antiparallel strands of polypeptide chain and linked by a disulfide bond. The interior of an antibody domain is filled by hydrophobic residues, including several with

FIG.2. Ca trace of the human antibody Kol (PDB entry 2IG2). The lower hinge and the Fc were not visible in the crystal structure because of disorder.

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

71

aromatic side chains. The architecture of an antibody domain is strong, as evidenced by the fact that the loops connecting the P-strands could vary in length and amino acid sequence without disturbing the basic structure of the domain. A ribbon diagram depicting the immunoglobulin fold, drawn by Richardson (1981), is reproduced in Fig. 3 . The variable domains of both light and heavy chains have four strands in one sheet and five in the other; CL, CHI, and CH3have four strands in one and three in the other; CH2has four strands in both sheets. There is greater lateral interaction between the homologous domains, VL and VH, and CL and CH1 in the Fab, than between domains in the same chain. There are strong lateral interactions also between the two CH3 do-

FIG.3. The immunoglobulin fold. Ribbon drawing of a variable domain. [Reproduced with permission from Richardson (1981).]

72

EDUARDO A. PADLAN

mains in the Fc. In contrast, the two cH2 domains are far apart and interact, albeit only weakly, through their carbohydrate moieties.

D. Hinges The ability of an antibody to cross-link two antigens, or to bind to two epitopes on the same antigen, is critically dependent on segmental flexibility. The Fab can flex, as evidenced by the many different elbow bends observed (see later discussion);but the presence of two polypeptide chains in this fragment, the L chain and the Fd, restricts its ability to twist. The ability to rotate and reorient the combining site(s) resides primarily in the hinge. Following Burton (1985), the hinge region can be subdivided into three parts: (1) the upper hinge, which includes the region between the end of the Fab up to the first inter-heavy chain disulfide bridge; (2) the middle hinge, which contains the inter-heavy chain disulfides and included residues; and (3) the lower hinge, which extends from the inter-heavy chain disulfides to the beginning of the Fc. The hinge regions of the various human Ig classes are presented in Table 11. The end of the Fab is clearly delineated in human IgGl in which a disulfide bridge exists between the COOH terminus of the L chain and Cys-220 (Eu numbering) at the COOH-terminal segment of CHI. In isotypes where the LH disulfide is formed with a cysteine in the NH2-terminal segment of CH1,demarcation of the physical end of the Fab is not straightforward. Neither is the beginning of the Fc. In IgG, Fc, the first residue that was visible in the X-ray structure (see later discussion) is Pro-238 (Eu numbering) (Deisenhofer, 1981). The upper and middle hinges, the segment DKTHTCPPC (residues 234-242), have been visualized in the crystal structure of the human IgGl immunoglobulin Kol, but not the lower hinge (Marquart et al., 1980). The segment KTHT forms an a-helix, while the CPPC segments of the two heavy chains form a poly(L-proline) double helix cross-linked by the two pairs of cysteines (Fig. 4).The presence of these secondary structural elements and the known stabilizing effect of disulfide bridges strongly suggest that this region of the afitibody is rigid. Segmental flexibility is probably conferred by the octapeptide PAPELLGG, which represents the lower hinge and is not .visible in either the Kol structure or the human IgG, Fc structure (see later discussion). The compactness of the structure of the upper hinge in human IgGl suggests that at least a partial unraveling may be required to allow the Fabs to rotate in antibodies of this subclass. This may be the case also in human IgG3 in view of the high sequence similarity between IgGl and IgGs in this region (Table 11). Interestingly, the upper hinge appears to be missing in human IgG2 and IgG4.

TABLE I1 Hinge in Human Antibodies ~

~~

Heavy chain Yl

Upper DXTET

Middle

Lower

CPPC

PAPELLGG

CVECPPC

PAPP-VAG

Y2 Y3

LGDTTET

CPRCPEPKSCDTPPPCPRCPEPKSCDTPPPCPRCPEPKSCDTPPPCPRCPAPELLGG

Y4

PP

CPSC

a1 a2 6

PVPSTPPTPSPSTPPTPSPS

cc cc

PVPPPPP

M Q A S s V P T A Q P Q A s G S L ~ R ~ ~ ~ QC ~ ~ T ~ P E

PAPEPLGG H H PSETQP

E

[CEZ domain]

C

ADSNPRG

P

[Cp2 domain]

C

VPDQDTA

74

EDUARDO A. PADLAN

FIG.4. Stereo drawing of the CL:CHI modules and the upper and middle hinges of antibody Kol (PDB entry 2IG2).

The middle hinges of human IgGP, IgG3, and IgG4 probably assume a polyproline-like structure similar to that observed in IgG1, although their lengths are very different. The hinge of human IgG3 has been modeled and its length has been predicted to be as much as 140 A (Marquart et al., 1980). All four human IgG subclasses have similar lower hinges, so the flexibility observed in human IgGl probably exists also in the other human IgGs. The hinges in the other antibody classes are just as varied. The two human IgA subclasses appear to have very stiff hinges in view of the many prolines. Surprisingly, the IgAs appear not to have lower hinges. In contrast, human IgD probably has a very long, flexible upper hinge and a middle hinge that appears to consist of a single disulfide bond (Table 11). A lower hinge appears to be present in human IgD, as well as in IgE and IgM. In IgE and IgM, however, a whole immunoglobulin domain exists between the Fabs and the last two domains of the heavy chains (which are homologous to Cy2 and Cy3, the domains that form the Fc in IgGI). Although the lower hinge appears to be flexible in the crystal structure of human IgGI, this region may not be dynamically, i.e., continuously, deformable even in solution. Indeed, bent forms of IgG and of IgE, in which the Fabs are not coplanar with the Fc, have been observed (Zheng et al., 1991, 1992). 111. X-RAYCRYSTALLOGRAPHY OF Fc Crystals were obtained by Northrop in 1942 from trypsin-treated antidiphtheria antitoxin, but the exact nature of the fragment was not known. The first crystalline antibody fragment of known identity was the Fc of rabbit y-globulin (Porter, 1958). The first X-ray crystallographic study of an antibody also involved rabbit Fc and was performed by Poljak and Dintzis who in 1966 determined the space group, lattice constants, and

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

75

density of the crystals. Those preliminary studies were extended to include human Fc (Humphrey, 1967; Poljak et al., 1967) and established the crystallographic, i.e., exact, equivalence of the two chains in the fragment (Goldstein et al., 1968). The crystallographic study of human Fc was pursued by Deisenhofer and co-workers and a crystal structure was determined, first at 4 A (Deisenhofer et al., 1976b) and later at 3.5 A resolution (Deisenhofer et al., 1976a), using heavy-atom derivatives. The structure was then refined using 2.9 A data to an R-value of 22% (Deisenhofer, 1981). The structure of rabbit Fc has also been elucidated, first at 4.5 A resolution using heavy-atom derivatives and later partially refined using 2.7 A data (Sutton and Phillips, 1983). In addition, a refined structure for guinea pig IgGl pFc' at 3.1 A resolution has been reported (Bryant et al., 1985). The crystal structures of the intact antibodies also serve as a source of information on Fc. In the crystals of the human myeloma proteins Dob and Mcg, a crystallographic symmetry axis relates the two halves of the molecule, so the Fc has exact twofold symmetry. This is not the case in the crystal structure of the isolated human Fc or in the crystal structure of the intact murine monoclonal antibody MAb231. Other sources of information on the structure of Fc are the available crystal structures of complexes with ligand, namely, the 2.8 A structure of the complex of human IgG, Fc with fragment B of protein A from Staphylococcus aureus (Deisenhofer et al., 1978; Deisenhofer, 1981), the 3.5 A structure of the complex of human IgGl Fc with the C2 fragment of streptococcal protein G (Sauer-Eriksson et al., 1995), and the 4.5 A structure of the complex of rat IgG Fc with neonatal Fc receptor (Burmeisteret al., 1994). A . Overall Structure of Fc

The most accurate structure for Fc is that obtained for human IgGl Fc (Deisenhofer, 1981) (PDB entry lFCl), as shown in Fig. 5. In the crystal structure, the two chains in the Fc are related by a pseudo twofold axis of symmetry. Only residues 238443 [Eu numbering (Edelman et al., 1969)] were visible in this structure. The two cH3 domains are found to be related by a rotation of 179.3", which is essentially an exact dyad, whereas the two cH2 domains are related by a rotation of 174.3". Both domains of the Fc have the immunoglobulin fold and both resemble the CLand CHI domains of an Fab (as discussed later). The two cH3 domains are in close association, with more than 20 residues from each chain involved in the contact (Table 111); approximately 2000 A2 of surface area are buried in the cH3:cH3 interface. The cH2 domains, on the other hand, are far apart and interact only through the

76

EDUARDO A. PADLAN

FIG. 5 . Ca trace of human IgGl Fc (PDB entry lFC1). The thicker lines represent the strands that form the twoj3-sheets in each domain.

carbohydrate moieties attached to An-297 (Eu numbering) and only b the terminal sugar residues. The cH3 domains are approximately 20 (center-to-center distance) apart, while the cH2 domains are approximately 35 A from each other. The cH3 domains were found to be more ordered in the crystal than the cH2 domains, presumably because of the compactness of the c H 3 : c H 3 module. The CH3domains interact through their four-strand sheets; in the cH2 domains, the homologous sheet is covered by the carbohydrate. The longitudinal association of the C Hand ~ cH3 domains is substantial, with approximately 780 of surface area buried in the interface. The CH2:CH3 interaction involves loops connecting the strands in the /?-sheets; 17 amino acid residues, 8 from CH2and 9 from CH3, are involved in this contact (Table IV). In the crystal structure of human IgGl Fc (Deisenhofer, 1981) (PDB entry 1FC1), the pseudo dyad axis relating the two c H 2 domains and that relating the two cH3 domains are not collinear; i.e., the Fc is not straight. In fact, there is a slight “elbow bend” of 177.8’ between the cH2:cH2 and cH3:cH3 modules. In contrast, in the complex with fragment B of protein A of S. aurew (Deisenhofer, 1981) (PDB entry 1FC2), in the complex with

K

A2

TABLE I11

CHjr:cHJ Contacts between First and second Chaiw in H u m n lgG1 Fc: PDB Entq 1FCI Second chaina First chain Q347 Y349 L351 P352 S354 E356 E357 T366 L368 K370 N390 K392 T394 P395 V397 L398 D399 S400 F405 Y407 K409 K439 Totals Y349 L35 1 P352 s354 E356 E357 K360 s364 T366 L368 K370 N390 K392 T394 P395 v397 L398 D399 S400 F405 Y407

K409 K439 Totals a

1

2

1 4 10 1

2 1 3

1

5

12

1

5s 3s 1

1

9

1

2 2

2 2 1

4 5

3 1

3

1

5

1

10 9 2 4 3 8

1

1

1

3 5

3

1

1

5 7

2 1

1 0

L .

16

7

1

1

los

3

15

14

7

Presence of a salt bridge in the contact is indicated by 5.

2

2 4

1

18 4 1 4 9 13 3 2 10

13

11

2

4

4

3

1

3

16 6

9

31

2 7

14

9 31 12 11 5

169

78

EDUARDO A. PADJAN

TABLE Iv

CH2:cHjr Contacts in Human 1gGl Fc: PDB Entry I F C I , First Chain in the EntT

C H ~ Y373

E376 1

P247 K248 L25 1 M252 L314 K338 A339 K340

2 2

Totals

4

a

P374

I377

E380

M428

H429

3s

5 2 3

4

1 1

2

1

E430

H435

1

1

3

10

4

3

7

4 7s

1

14

8

Totals

2 8 16 3 5 8 3 2

47

Presence of a salt bridge in the contact is indicated by s.

the C2 fragment of streptococcal protein G (Sauer-Eriksson et al., 1995) (PDB entry lFCC), and in the complex with the rat neonatal Fc receptor (Burmeister et al., 1994) (PDB entry IFRT), the Fc is straight. B. Carbohydrate an Fc

The structural importance of the carbohydrate is not clear from the crystal structure of the Fc, but the presence and nature of carbohydrate apparently have very significant biological implications (Lund et al., 1995). In the crystal structure of rabbit Fc (Sutton and Phillips, 1983), the carbohydrate moieties were found to be more asymmetrically disposed and to interact more strongly than in human Fc. All the other heavy-chain types are probably glycosylated at the same (homologous) position, except in IgA. In IgM and in IgE, the Cp3 and Ce3 are the homologs of Cy2, and Cp4 and Ct4 correspond to Cy3. Thus the sites of glycosylation homologous to Asn-297 in IgGl are in Cp3 and Ce3. In IgA, the probable site of glycosylation is the asparagine at position 258 (Eu numbering); the residue at position 258 in IgGl is close to the end of the carbohydrate and makes many contacts with the last sugar residue. It has been suggested that carbohydrate emanating from residue 258 in IgA probably follows a course reversed in relation to that found in IgG,, but likewise covering the homologous face of Ca2 (Deisenhofer, 1981).

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

79

C. Complexes of Fc with Ligands

Crystal structures for three complexes of Fc with ligand are available. Interestingly, all three ligands bind to roughly the same site on Fc, i.e., the junction of the cH2 and cH3 domains. The three ligands are very different in structure: Fragment B of protein A of S . aureus is trihelical (Deisenhofer, 1981), the C2 fragment of streptococcal protein G has a four-stranded /3-pleated sheet structure with one helix (Sauer-Eriksson et al., 1995), and the rat neonatal Fc receptor has a structure very similar to that of class I MHC antigens (Burmeisteret al., 1994). The three complexes are shown in Fig. 6. Fragment B of protein A interacts with both CH2 and CH3 domains (Deisenhofer, 1981).Approximately 1200 Az of surface area are buried by the interaction. The contact is mainly hydrophobic, with a few hydrogen bonds contributing to the interaction. The C2 fragment of protein G also interacts with both cH2 and cH3 domains (Sauer-Eriksson et al., 1995). The contact involves the helix, one edge of the P-sheet, and some loop residues in the C2 fragment. Here, however, the interaction is predominantly polar, with very few hydrophobic residues involved in the contact. The neonatal Fc receptor likewise interacts with both domains of the Fc (Burmeister et al., 1994). Like class I MHC antigens, the receptor has a heavy chain which is associated with P2-microglobulin; the heavy chain forms a sheet of antiparallel t’3 strands, with two a helices lying across the sheet. The interaction with Fc involves mainly loop regions at one end of the sheet, with some contributions from the µglobulin. The involvement of the cH2:cH3 junction in all three Complexes is intriguing. Indeed, a loop in the corresponding region in IgE has been implicated in IgE binding to its high-affinity receptor, Fce (Helm et al., 1995). These observations strongly suggest that this part of the antibody molecule may play an important role in effector functions.

IY X-RAYCRYSTALLOGRAPHY OF ANTIGEN BINDING FRAGMENTS By far, the part of the antibody molecule that has attracted the most attention from crystallographers is the antigen binding region. Scores of different Fabs have been studied crystallographically, many with bound specific ligand. The ligands range in size from small haptens, e.g., phosphocholine, to large proteins, e.g., influenza virus neuraminidase. The crystal structures of several Fvs, light chain dimers, and isolated variable domains have also been determined (Table I). The first crystal structure of an Fab to be determined was that of the human myeloma protein New, obtained by Poljak and co-workers in 1972

80

EDUARDO A. PADLAN

FIG. 6. The complexes of Fc with fragment B of protein A from Staphylococcus aureus (top), the C2 fragment from streptococcal protein G (middle), and the rat neonatal Fc receptor (bottom).

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

81

at 6 %, resolution. These authors estimated the gross dimensions of the fragment and visualized the mode of association of the four domains of the Fab, but no further structural details could be obtained from the lowresolution structure. The analysis was extended to 2.8 %, resolution (Poljak et al., 1973) and later to a nominal resolution of 2 A (Poljak et al., 1974), revealing for the first time the tertiary structure of the Fab domains and their interactions. A . General Structure of Fab

In three dimensions, the Fab is modular. The VL and VH domains are closely associated and form a compact module, the Fv; the CL and CHI domains also form a compact module. The Fv and the CL:CHl modules are loosely connected and their relative disposition often varies from Fab to Fab, indicative of segmental flexibility. The flexibility of the Fab is due to the presence of the switch region, a short peptide between the variable and the constant domains in each chain. Three amino acid residues comprise the switch region in heavy chains and in lambda (A)light chains; there are only two residues in the kappa (IC)light chain switch. On average, about 1400 A2 is buried between VLand VH in the Fv; in the CI.:CH1 module, roughly 1700 A' are buried (Padlan, 1994a). There is variation in the VL:VH as well as in the CL:CH1 mode of association. The contact between the variable domains involves CDR residues, which presumably contributes to this variation. The involvement of the CDRs in the VL:VH contact ranges from about one-fifth to more than one-half of the total contact (Padlan, 1994a). The variation in the CI,:CH1 association, however, cannot be attributed to sequence differences because it is also seen in cases where there is sequence identity. This variation probably simply reflects the fact that the VL and VH, and the CL and CH 1, associate with binding constants of only 105-106 M-' (Schiffer et al., 1988) and can slide relative to each other. B. Rotational Symmetry between Homologous Domains in Fab

Pseudo symmetry relates the domains in the Fab. The two variable domains, VLand VH,are related by an approximate twofold axis, as are the two constant domains, CLand CHI. The parameters describing the relative disposition of the homologous domains of the Fab are presented in Table V. The pseudo dyad relating VL and VH ranges from 164.3", for New Fab, to 178.6" for NC6.8 Fab. These values apparently do not depend on the ligand state of the Fab. In liganded molecules, the variable domains are related by rotational angles varying from 166.0-178.1', while in unliganded molecules, the range is 164.3-178.6'.

82

EDUARDO A. PADLAN

TABLE V

heudo Symmetry in Antigen Binding Regions: Atomic Coordinates Available fiom Protein Data Bank

Antibody

Isotype

Murine McPC603

IgA, K

J539 D1.3

IgA, K IgGl, K

HyHEL-5

IgGI, K

HYHEL-10 IgGI, K D11.15 IgGI, K F9.13.7 IgGl, K

PDB code

lMCP 2MCP 2FBJ 1FDL lVFA 1VFB 2HFL 2IFF 1BQL 3HFM lJHL lFBI 1MLB 1MLC

lJEL lACY 21GF 1IGF

1F7 R45-45-11 MOPC21 NC41

IgGl, K IgG1, K IgGI, K IgGZa, K

lTET 6FAB 1BAF 1DBA lDBB 1DBJ 1DBK 1DBM 2DBL 1FIG lIKF 1IGC 1NCA lNCB lNCC 1 NCD 1FPT 1RMF 1FOR lBBD

VL:VHSymmetry

CL:CHISymmetry

Rotation Translation (deg)

Rotation Translation

Fab bend'

-

173.4 173.6 168.7 166.2 167.3 167.9 171.4 172.5 172.2 170.6 174.9 175.1 173.4 173.4 173.7 173.8 172.3 167.1 172.4 172.5 172.7 176.1 176.2 173.3 177.0 177.4 177.7 177.7 176.8 178.0 170.5 176.5 171.0 177.6 177.8 178.1 177.6 175.5 176.4 171.5 173.7

0.1 0.3 0.2 0.7 0.9 0.7 0.1 0.0 0.0 -0.3 0.5 0.1 0.2 0.1 0.3 -0.6 0.2 0.5 0.1 0.0 0.1 -0.2 -0.1 -0.5 -0.2 -0.1 -0.1 0.0 -0.2 0.0 -0.5 0.2 0.0 0.4 0.4 0.5 0.4 -0.4 -0.3 -0.5 -0.7

171.8 171.9 173.9 171.1 b

-2.8 -2.7 -2.0 -1.9

169.1 170.1 169.7 167.7

-2.0 -1.9 -2.1 -2.0

171.0 170.1 167.9 171.5 169.6 170.1 170.5 170.6 170.0 170.9 170.0 171.5 167.4 170.3 169.7 169.9 170.3 169.3 169.5 174.2 172.5 169.5 171.2 171.5 171.3 171.2 171.7 170.4 171.9 171.0

-2.1 1.8 -2.4 -1.9 2.2 2.1 -1.9 -2.0 -2.0 -2.0 2.2 -2.0 -2.2 -2.0 -1.9 -2.0 -2.0 -2.0 -1.9 2.1 -1.8 2.0 2.1 2.0 2.1 2.1 -1.7 -1.9 -1.7 -2.1

131.3 131.8* 143.8 173.0*

161.7* 161.8*

160.4* 145.6* 173.8* 175.2* 160.6 166.3* 163.6* 154.5* 135.5* 155.8* 153.0 155.4 142.2* 166.6 153.8* 177.3 177.3* 176.9* 177.2* 177.2* 177.2* 132.5* 143.4* 130.5 147.1* 146.6* 147.2* 146.6* 134.4* 176.5 153.6 127.2

83

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

TABLE V

Antibody

Isotype

PDB code

1719

50.1

IgGZa, K

2619 26- 10

IgGZ,, IgG2,,

4-4-20 CNJ206

1gC2,,~ IgGZ,,K

K K

YsT9-1 BV04-01

IgG2h, K IgGnb,K

Jell03

IgG2b, K

40-50 R19.9

IgGZb,K IgG2b,K

NC6.8

IgGzb, K

CHA255

IgGI,I

Se155-4

IgG1,I

HC19

IgGi,1

IHIN IIFH 1CXB 1GGC 1GGI lFRG IIGI 1IGJ 4FAB 2GFB

lMAM lCBV 1NBV 1MRC 1MRD 1MRE 1MRF lIBG 2F19 1FA1 lCGS 2CGR IIND IINE IMFB 1MFC IMFD 1MFE 1MFA IGIG

(continued)

-

VL:VHSymmetry Rotation Translation (deg) (-4 170.3 168.9 169.1 169.5 168.9 168.5 173.9 174.4 166.6 166.0 170.2 173.7 172.7 173.9 175.5 170.3 170.3 170.5 170.6 170.5 170.3 170.6 170.7 175.1 176.8 173.5 173.6 174.3 173.8 174.2 172.9 175.2 175.0 178.6 175.1 173.0 173.1 177.9 177.5 177.8 177.9 175.3 167.2

-0.1 0.2 0.2 -0.3 -0.3 -0.3 1.3 1.2 0.0 -0.3 0.3 0.3 0.4 -0.4 -0.3 2.2 2.2

2.2 2.2 2.2 2.2 2.2 2.2 -0.1 -0.1 0.3 0.3 0.3 0.1 0.2 -0.1 0.3 0.3 -0.4 -0.3 0.0 0.0 -0.1 -0.2 -0.1 -0.1 0.3 0.1

Rotation Translation

Fab bend‘”

-

171.8 171.7 171.3 171.2 172.3 172.1 170.2 172.1 171.5 171.9 171.8 171.4 171.5 171.3 174.3 172.2 172.1 172.1 172.0 172.1 172.0 171.9 171.9 172.4 170.6 172.3 169.7 169.5 169.7 170.1 172.3 166.8 167.8 170.7 170.6 169.2 169.5 168.7 168.9 168.9 168.9

-1.9 2.0 -1.7 1.9 1.6 -1.9 -1.6 -1.9 -2.0 -1.6 1.8 2.0 -1.8 1.6 -1.7 -1.8 -1.7 -1.7 -1.7 -1.8 -1.7 -1.8 -1.5 -1.8 1.a -1.9 -2.0 -1.8 -1.8 1.4 -2.0 -1.8 -2.0 -2.1 3.0 3.1 -2.9 -3.0 -3.0 -3.0

159.7 160.5 172.7* 171.6* 175.1* 174.0* 172.9 174.9 163.4* 175.4* 173.1* 172.7 175.4* 175.5* 174.9* 144.0 144.0 144.5 144.1 144.2 144.1 144.5 144.2 148.1 173.5* 172.5 141.9 140.7* 139.5* 140.4* 135.4* 176.2 176.1 -170.0 152.0* -166.5* -166.0* 175.2* 174.5* 175.2* 175.4*

169.7

-3.3

146.7

1 .a

(continued)

84

EDUARDO A. PADLAN

TABLE V (continued)

VL:VH Symmetry

Antibody

Isotype

L5MK16

Murine/human chimera B72.3 Humanized murine H52 4D5

PDB code

Rotation Trans$ion (A) (deg)

1LMK

176.1 177.8 176.5 177.3

-0.1 0.2 0.1 0.0

lBBJ

172.4

0.2

1FGV 2FGW lFVC

175.3 170.7 174.0 174.4 173.5 174.3 174.0 174.0 174.0

0.2 0.3 0.1 -0.1 -0.3 0.1 -0.1 -0.1 0.0

167.9 164.3 171.2 174.8 166.8 174.4

-0.1 -0.5 0.3 0.1 0.2 0.0

lFVD lFVE lFVE

2FB4 7FAB 8FAB 1DFB lIGM

CL:CH1 Symmetry

Rotation Translation (deg)

(4

Fab bend' (deg)

168.1

-2.2

138.3

168.5

2.2

135.0

167.8 168.9 168.5 168.5 169.2

2.1 -2.0 2.0 2.0 -2.1

155.7 153.7 155.6 155.6 153.9

170.4 170.4 174.6 168.8 169.5

3.4 -3.8 2.7 -3.3 -2.1

165.2 129.9 147.2 135.7 174.9

' Asterisk (*), liganded.

*

If no values are provided for C L : C Hsymmetry, ~ or for the Fab bend, the structure is that for an Fv. A negative value for the Fab bend signifies that the VL and CL are closer to each other than VH and CHI are; i.e., the light chain is more bent than the Fd. These quantities were computed on the basis of 72 core residues in the variable domains and 63 in the constant domains (Padlan, 1994a). If there is more than one Fab in the asymmetric unit of the crystal, e.g., in CNJ206 where there were eight, values are given for each.

The relative disposition of the CL and CHI also does not appear to depend on the ligand state of the Fab. In fact, molecules belonging to the same light and heavy chain isotypes, so that their CL and CHI domains have the same amino acid sequence, display large differences in their rotational parameters. The pseudo-symmetry values relating the CL,and CHI domains in the Fabs belonging to the IgGl K isotype range from 167.4 to 174.2", those belonging to the IgG2, K isotype have values ranging from 170.2 to 174.3", and those belonging to the IgGPb K isotype have values

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

85

ranging from 166.8 to 172.4'. These differences are not dependent on whether a disulfide bond bridges the light and the heavy chains of the Fab. The molecules belonging to the IgGeb K isotype on the list, for example, all have disulfide bonds between their light and heavy chain components.

C. Fab Bend The pseudo twofold axes relating the VLand VHand the CL and CH1 are not parallel. The angle between the two pseudo dyads, usually referred to as the elbow bend of the Fab, or simply the Fab bend, ranges from a tight 127.2' to an almost straight 177.3' (Table V). The Fab bend also does not appear to depend on the ligand state of the Fab. In some molecules the liganded form of the Fab is more bent, e.g., in NC6.8; in other molecules, it is the unliganded form that is more bent, e.g., 17/9. Usually, the heavy chain component of the Fab displays a tighter angle between its variable and constant domains. However, in two known cases, NC6.8 and CHA255, it is the light chain that has a sharper angle between its domains (Fig. 7). The variation in Fab bends is obviously simply a reflection of the flexibility of the fragment. A demonstration of the dynamic flexibility of an Fab was seen in the crystal structure of the NClO-neuraminidase complex (Malby et al., 1994) where the C&H1 module was invisible on the electron density map, implying disorder in the crystal.

FIG.7. Ca trace of representative Fabs displaying different elbow bends. From left to right: Fab of 8F5 (PDB entry IBBD) with an elbow angle of 127.2", NC41 (PDB entry INCA) with an elbow angle of 147. lo, 17/9 (PDB entry IHIN) with an elbow angle of 175.lo,and CHA255 (PDB entry IIND) with an elbow angle of-166.5". The heavy chain is drawn darker.

86

EDUAKDO A. PADLAN

D. Hypervariable or Complementarity-Determining Regions The relative disposition of the variable domains brings together the six CDRs at the NH2-terminal tip of the Fab (Fig. 8). The CDRs in each domain are mainly in the form of loops connecting the strands in the bilayer P-sheet structure. The framework or nonhypervariable regions are found to be highly conserved in three-dimensional structure. Superposition of structures reveals that the structural variation among the VL and V H domains occurs mostly in the CDRs (Padlan and Davies, 1975). A comparison of CDR structures has led to the proposal of canonical structures for these segments (Chothia and Lesk, 1987; Chothia et al., 1989). The canonical structures appear to be determined by the nature of certain framework residues that interact with the CDRs.

FIG.8. Stereo drawings of HyHEL-10 Fv (PDB entry SHFM). The CDR residues are represented by filled circles. The VL is on the left and the VH, drawn darker, is on the right. The beginning and end of each CDR is labeled, as are the NH2 and COOH termini of each domain. The drawing at the top represents a side view of the Fv, while the drawing at the bottom represents an end view.

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

87

E. Suqace of Complementarity-Determining Regions

The CDRs form a continuous surface, and the nature of this surface is determined by the physicochemical properties of the amino acids that contribute to its formation. In view of the variation in the lengths of the CDRs, especially of CDR1-L and CDR3-H, the CDR surfaces have varied topographies, as illustrated in Fig. 9. The wide diversity in antigen binding specificities is directly attributable to this variation in the CDR surface. The CDR surface is on average 2800 A‘ in area, or about one-third of the total surface of the Fv. The topography of the combining site complements that of the antigenic determinant so that protrusions from one fit into depressions in the other (see later discussion). Antibodies directed against flat regions on an antigen would also have flat combining sites, and antibodies against protruding loops or haptens would be expected to have grooves or pockets in the CDR surfaces. Some clear examples of these cases are presented in Fig. 9. Thus, the antibodies to globular protein antigens, e.g., the antilysozymes and, especially, the antineuraminidase NC4 1, have relatively flat CDR surfaces, while the antipeptide antibodies and those that bind to nucleotides have very pronounced grooves. It appears that for smaller ligands, a more complete envelopment is needed for stronger binding. Although the CDR surfaces are portrayed as static in Fig. 9, they are in reality plastic arid can be reshaped to varying degrees. Simple rotation of side chains can change the surface; larger changes can be accomplished by the movement of CDR loops and, even more, by whole-body movements of the variable domains. Some of these changes may lead to an induced fit (discussed later). The CDRs are unusual in that many aromatic residues, even the very hydrophobic ones, namely, phenylalanines and tryptophans, are frequently found exposed to solvent (Padlan, 1990). When in the framework, these amino acids are mostly buried, as would be expected in a watersoluble protein. It has been argued that this exposure of aromatics, made possible by the strength of the bilayer P-sheet structure, makes the CDR surface “sticky”; i.e., it has an enhanced capacity for binding ligands (Padlan, 1990). V. X-RAYCRYSTALLOGRAPHY OF COMPLEXES OF ANTIBODIES WITH SPECIFIC LIGAND

The first crystallographic analysis of an Fab complexed to specific ligand was of the murine phosphocholine-binding plasmacytoma protein McPC603, first at 4.5 L% resolution (Padlan et al., 1973) and later at 3.1 A

88

D1.3

EDUARDO A. PADLAN

RyHEL-5

LSYK16

n6 6

17.11

3D6

50.1

TE33

4DS

Dll.16

H52

NC41

ncw

c3

1710

2819

J639

59.1

5.1101

11312

9.155-4

FO 13 7

D44.l

YcPCOO3

4.4.20

nio o

31.71

40-60

CHAZ66

NC1 I)

1F7

KoI

nil

PO1

1

AN02

28.10

CNJ206

MOPCII

NW .

FIG.9. CDR surfaces of antibodies for which atomic coordinates are available from the Protein Data Bank.

resolution (Segal et al., 1974), using heavy-atom derivatives. It was found that the hapten was bound in a deep pocket, with salt bridges and hydrogen bonds formed where possible. This was the first demonstration of the complementarity between antibody and ligand in their shape and in their

89

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

physical and chemical properties. Since then, the structures of many other complexes have been elucidated by X-ray crystallography and the complementarity between antibody and ligand has been confirmed time and again. The various antibody-ligand complexes, for which atomic coordinates are available from the Protein Data Bank, are compared in Table VI. Included in Table VI are the surface areas on both antibody and ligand that are buried in the complex, the total number of interatomic contacts, the number of contacts involving main-chain atoms, the number of hydrogen bonds formed, the number of hydrogen bonds involving main-chain atoms in the antibody and, in those cases where the ligand is a polypep-

TABLE VI Characteristics of VariousAntibody-Ligand Complexesa

Antibody D1.3 HyHEL-5 HyHEL-10 D44.1 D11.15 F9.13.7 Je142 NC41 c3 1719 2619 59.1 50.1 TE33 B1312 R45-45-11 BVO4-01 Jell03 Se155-4 McPC603 4-4-20 AN02 26-10 DB3 40-50 CHA255 NC6.8 1F7 a

Surface buried 537 744 716 626 600 753 624 889 492 484 506 473 531 539 503 565 523 253 283 151 338 363 350 289 393 343 390 258

Ligand

Surface buried (A) vdW m.c.vdW H.b. m.c.H.b.

Chicken lysozyme Chicken lysozyme Chicken lysozyme Chicken lysozyme Pheasant lysozyme Guineafowllysozyme E. coli HPr Neuraminidase Poliovirus peptide Hemagglutinin peptide Hemagglutininpeptide HIV-I gp12OV3loop HIV-lgp120V3100~ Cholera toxin peptide Myohemerythrinpeptide Cyclosporin A Trinucleotide Inosine diphosphate Trisaccharide Phosphocholine Fluorescein DNP-spin label Digoxin Progesterone Ouabain In(II1)-EOTUBE NC174 sweetener Transition state analog

541 741 759 613 569 734 654 861 418 405 436 419 485 492 439 511 443 191 228 138 247 230 274 229 335 286 298 189

110 145 180 132 107 147 115 180 102 150 150 116 127 143 113 116 184 69 72 54 107 129 76 74 107 102 132 66

18 25 21 29 15 31 40 22 23 36 38 27 16 46 27 39 48 5 9 4 36 5 9 37 9 0 37 17

14 13 19 11

7 14 10 13 9 14 17 6

7 11 13 5 12 11 4 3 3 2 0 3 4 7 6 3

4(2) 1 4(1) 4(3) 2 (1) 3 (1) 5(1) 3 2 3 (1) 4(1) 2(2) 2 (2) 4 (1) 4(2) 2 (2) 5 1

1 0 1 0 0 1 1 0 2 2

vdW, Van der Mals contacts; m.c., main chain; H.b., hydrogen bonds; I.P., ion pairs.

' Values are for the first complex in the entry.

PDB 1.p. code 0 3 1

3 2 3 1 0 2 1 1 1

2 1 2 0 1 4 0 1 2 0

o 0 0 1 2 0

lFDL 2HFL 3HFM lMLCb 1JHL lFBIb lJEL lNCA lFPT IIFH IFRG lACY ~ G G I ~ ITET 2IGF IIKF lCBV IMRD IMFA PMCP 4FAB lBAF IIGJ~ IDBB lIBG lIND 2CGR IFIG

90

EDUARDO A. PADLAN

tide, the number of hydrogen bonds involving main-chain atoms in both antibody and ligand and the number of salt links formed. In the complexes involving whole antigens, the surfaces buried range from about 540 to about 890 A2, between about 400 and about 560 2 for complexes involving peptides, and less for smaller ligands. The number of main-chain atoms involved in the contacts is small in all cases. The complexes involving whole antigens permit visualization in three dimensions of the interaction of the antibody with its specific ligand. The availability of those complexes also allows delineation of the paratopes and the epitopes with precision. As predicted by Wu and Kabat (1970), the antigen binding site is primarily constructed from CDR residues, but there is occasional involvement of framework residues. The part of the CDR surface used for antigen binding differs from antibody to antibody, although the center portion of the surface is found to always be involved. The surface that interacts with ligand in the various complexes of known structure is presented in Fig. 10. Even in those complexes that involve whole antigen, only a small fraction (one-fifth to one-third) of the total CDR surface is actually utilized in the contact with the antigen (Fig. 10). The complexes that involve intact antigens include the murine monoclonal antibodies D1.3, HyHEL-5, HyHEL-10, D44.1, D11.15, and F9.13.7, all of which have been elicited against hen egg white lysozyme. In the crystal structures, D1.3, HyHEL-5, HyHEL-10, and D44.1 are complexed with their specific antigen, chicken lysozyme, whereas F9.13.7 is complexed with guinea fowl lysozyme and D1 1.15 is complexed with pheasant lysozyme. The sequence differences between chicken and guinea fowl lysozymes do not occur in the region that binds to F9.13.7, so the F9.13.7 epitope on chicken lysozyme may in fact be this region; we will assume that to be the case. The binding of D 11.15 to pheasant lysozyme is heteroclitic, so the region on pheasant lysozyme to which D1 1.15 is found to bind may or may not correspond to its epitope on chicken lysozyme. This correspondence for D1 1.15 will also be assumed. The epitopes for the antilysozymes and for the other antiprotein antibodies for which atomic coordinates are available from the Protein Data Bank are presented in Table VII, and the paratopes of the six antilysozymes are collected in Fig. 11. The structure of the complex of the murine monoclonal antibody Je142 and the histidine-containing phosphocarrier protein (HPr) of Escherichia coli is also available, as well as those involving the murine monoclonal antibodies NC41 and NClO and influenza virus neuraminidase. In addition, three idiotope-anti-idiotope complexes have been described in the FIG. 10. Areas in the CDR surfaces which directly contact the ligand in complexes of known structure.

N

f

P

rl t

N 0

xI

0

t

W

r

0

f

s

a:

r

n c

r

LL I .

OD (D

0

n

m9

r

t

0 n

0

a

N

0

0

I

=

m

r

p!

E

t

f

n

r c

m

0 t

?

c

el 3

n

n

0

n

x

t

3-

0

c

t

N

a

a

r

0

7 e n

W

z i E

7 I

I”

? r n

92

EDUARDO A. PADLAN

TABLE VII

Epitopesfor Antibodies 01.3, 0 1 1 . 1 5 , HyHEL-5, 0 4 4 . 1 , HyHEL-10, F9.13.7, Je142, NC41, and NClO Antibody

Antigen

D1.3

Chicken lysozyme

D11.15

Guinea fowl lysozyme

HYHEL-5

Chicken lysozyme

D44.1

Chicken lysozyme

Hy HEL- 10

Chicken lysozyme

F9.13.7

Pheasant lysozyme

Je142

E. coli histidine-containing protein (HPr)

NC41

Influenza virus neuraminidase

NClO

Influenza virus neuraminidase

a

Epitopef Asp-18, Asn-19, Gly-22, *Tyr-23, Ser-24, Asn-27, Lys-116, Gly-117, Thr-118, Asp-1 19, Val-120, Gln-121, Ile-124, Arg-125 *Arg-21, Gly-22, Tyr-23, Asp-103, Asn-106, Arg-112, LYS-113,LYS-116,Gly-117, *Thr-l18, Asp-1 19, Asn- 12 1 Gln-41, Thr-43, *Asn-44, Arg-45, Asn-46, Thr-47, Asp-48, Gly-49, Thr-5 1, Tyr-53, Gly-67, Arg-68, *Thr-69, Pro-70, Ser-8 1, Leu-84 Gln-41, Thr-43, Arg-45, *Asn-46, *Thr-47, *Asp-48, Gly-49, *Ser-50, T h r d 1, Tyr-53, Gly-67, Arg-68, Pro-70, Pro-79, Ser-81, Leu-84 *Arg-14, *His-15, Gly-16, Tyr-20, Arg-21, Trp-63, Arg-73, Leu-75, Thr-89, Asn-93, Lys-96, Lys-97, *Ile-98, Ser-100, Asp-101, Gly-102 His-15, Gly-16, Tyr-20, Arg-21, Trp-62, Trp-63, Gly-71, Arg-73, Leu-75, Asn-77, Thr-89, Asn-93, Lys-96, Lys-97, Ser-100, Asp-101 Met-I, Phe-2, Glu-3, Gln-4, Thr-34, Thr-36, Ser-41, Ser-64, Glu-66, Gly-67, Glu-68, Glu-70, Gln-71, Glu-75 Ile-149, Pro-326, *Arg-327, Pro-328, Asn-329, Gly-343, Asn-344, Asn-345, Asn-347, Ile-366, Ser-367, Ile-368, Ala-369, Ser-370, Ser-372, Leu-399, Asn-400, Thr-401, *Asp-402, Trp-403, Pro-43 1, Lys-432 Pro-328, Asn-329, Asp-330, Pro-331, Thr-332, Tyr-341, Gly-343, Asn-344, Ile-366, Ile-368, Ala-369, Ser-370, Asn-400, Thr-401, Trp-403

Asterisk (*), only main-chain atoms contribute to the epitope.

literature. Structural data for complexes involving a variety of smaller ligands, including peptides, polysaccharides, polynucleotides, and small haptens, are also available (Table VI). Instead of describing all those complexes here, the discussion will be limited to the complexes involving whole antigens and to a few involving

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

93

D1.3

011.15

HyHEL-5

D44.1

HyHEL-10

F9.13.7

FIG. 11. Stereo drawing of the paratopes of the six antilysozyme antibodies of known three-dimensional structure viewed end-on.

smaller ligands. Many of the features of the antibody-ligand interactions are common to all complexes so that generalizations can be made, and some of the details are from Padlan (1994b).

94

EDUARDO A. PADLAN

A. Complexes Involving Whole Antigen 1. Complex of Antibody Dl .3 with Chicken Lysozyme Antibody D1.3 binds to chicken lysozyme with an affinity constant of 4.5 x lo7M-'. The binding of D1.3 to lysozyme, based on the Fab:lysozyme complex (Fischmann et al., 1991) (PDB entry lFDL), is illustrated in Fig. 12; the residue contacts are summarized in Table VIII. There is good complementarity in the shapes of the D1.3 combining site and its epitope (Fig. 13). There are 110 van der Waals contacts between antibody and antigen and 14 hydrogen bonds. Six of the hydrogen bonds involve main-chain atoms from the antibody, and two of these bonds involve main-chain atoms from both antibody and antigen (Table VI). A few water molecules are found buried in the antibody-antigen interface where they mediate the interaction between D1.3 and lysozyme or fill in the gaps in places where the complementarity between the interacting surfaces is not precise. The D1.3 epitope contains 14 residues from two segments of the antigen, one near the NHz and the other near the COOH terminus (Table VII), so that the epitope is conformational, i.e., discontinuous. Three residues, two of which are glycines, contribute only through their main-chain atoms. The epitope contains several different structural motifs: Asp-18 and Asn-19 are part of a bend; Gly-22, Tyr-23, Ser-24 and Asn-27 are in an extended

FIG. 12. Stereo drawing of the Ca trace of the D1.3 complex with chicken lysozyme (PDB entry 1FDL) viewed from the side. The interacting side chains are shown in full. The antigen is on top.

TABLE VIII Contacts between Antibody and Ligand an Dl.3-Chicken 12ysozyme Complex (PDBEntly IFDL) Antibod$ Light chain Lysozyrne D18 N19 G22 Y23 s24 N27 K116 (3117 TI 18 D119 v120 Q121 I124 R125 Totals

Y32

Y49

Y50

T53

Heavy chain F91

W92

S93

G31

Y32

W52

G53

D54

D97

Y98

R99

5h 1

4

2h

1

3h

1

3

2

2

1 1 1

Sh

Ih 4

12

4h

4h 4h

9

Ih

7h

2 6

1

10

8

2

9

2

4

16

1

Presence of at least one hydrogen bond in the interaction is indicated by h.

5

1

14

6

5

15

17

5 7 5 2 11 3 3 11 5 16 4 29 3 6

3'1 3

Totals

3

110

96

EDUARDO A. PADLAN

FIG. 13. D1.3 paratope and epitope surfaces. The epitope is pulled 14 A away from the paratope for clarity.

configuration; Lys-116, Gly- 117, and Thr-118 are in a tight B-turn; and Asp-119, Val-120, Gln-121, Ile-124, and Arg-125 are in an a helix. The D1.3 paratope consists of 15 residues emanating from all six CDRs; 1 anrigen-contacting residue comes from the framework. Seven residues with aromatic side chains contribute to the binding: five tyrosines and two tryptophans, which together are responsible for 63% of the interatomic contacts. Three charged side chains are in the paratope, two aspartic acids and one arginine, but none forms a salt link with the antigen. No conformational changes were observed in either the Fab or the lysozyme on complex formation (Fischmann et al., 1991). Crystallographic analysis of the isolated D1.3 Fv, however, showed a slight shift in the relative orientation of the VL and VH, suggestive of an induced fit (Bhat et al., 1994). The observation of a conformational change in the Fv, but not in the Fab, may simply be a reflection of the difference in the resolution of the two X-ray analyses, 2.5 8, for the Fab vs 1.8 8, for the Fv. On the other hand, it may be due to inherent differences between Fabs and Fvs. Indeed, when the antibody-antigen contacts are computed based on the Fv:lysozyme complex (Bhat et al., 1994) (PDB entry IVFB), some differences are observed (Table IX, compare with Table VIII). For the D1.3 Fv:lysozyme com-

TABLE IX

Contacts between Antibody and Ligand i n D l AChicken Lysozyme Complex (PDB Entq 1 VFB) Antibody' ~

Light chain Lysozyme

H30

D18 N19 G22 Y23 S24 N27 G102 K116 G117 T118 D119

Y32

Y49

Y50

T53

~

~~~

Heavy chain F91

W92

S93

G31

Y32

"52

G53

D54

R96

D97

Y98

R99

Sh 1 2

4

2h

4h

lh

2

$ 3h

2

Zh

2 3

6 3 5 13

5h

21

5

Ih

4 7h

f

v120 Q121 I124 R125 L129

6 1 2h

Totals

2

9

4h

3

1

3

2

4

1

8 1 8

Qh

7

8

5

Presence of at least one hydrogen bond in the interaction is indicated by h.

5

6

5

2

15

23

4

Totals 9 7 7 2 13 3 2 8 12 9 20 5 30 2 13 2 144

98

EDUARDO A. PADLAN

plex, 17 residues constitute the paratope (vs 15 in the Fab complex), while 16 amino acids are in the epitope (vs 14 for the Fab), and there are 144 interatomic contacts between antibody and antigen (vs 110 for the Fab). There is also a difference in the number of hydrogen bonds found to be formed between antibody and antigen: 16 in the Fv vs 14 in the Fab complex. 2. Complex of HyHEL-5 with Chicken Lysozyme HyHEL-5 binds to lysozyme with an affinity constant of 2.5 x lo9 A t ' . The interaction is illustrated in Fig. 14 and the residue contacts are summarized in Table X. There is a close complementarity between paratope and epitope surfaces in this complex (Fig. 15), with no water molecules found in the interface (Sheriff et al., 1987). There are 145 atom pairs in van der Waals contact, with 13 hydrogen bonds. Only one hydrogen bond involves mainchain atoms. In this complex, three salt bridges are formed between two arginines, Arg-45 and Arg-68, from the lysozyme, and two glutamic acids, Glu-35 and Glu-50, from the heavy chain of HyHEL-5. Surrounding the salt bridges are the side chains of three tryptophans: Trp-91 from the light chain and Trp-33 and Trp-47 from the heavy chain. The environment surrounding the salt bridges is largely hydrophobic.

FIG. 14. Side view of the HyHEL-5 complex with chicken lysozyme.

TABLE x Contacts between Antibody and Lignnd in HyHEL-5-Chicken Lysozyme Complex (PDB Entry PHFL) Antibody'

Lysozyme Q41 T43 N44 R45 N46 T47 D48 G49 T 51 Y53 GG7 RG8 TG9 P70 S8 1 L84

Totals a

Light chain

Heavy chain

N31 Y32 Y34 D50 W91 G92 R93 P95

W33 E35 W47 E50 L52 S54 G55 ,556 T57 N58 G95 N96 Y97 2 2

11

4h

2 1

12h gh 2

3

5

1

3 6

2

6 17 2 39 5 3 2

7h 2

4s

2

3

3 1 5h

7 5

2

5

1

1

9

2"

lS

4

1

5 6 5 7h

1 5 5 30 5 16 1 5

4

1 2 3

145

3

3

2

1

Totals

7 1 7

5

17

1

3

6

1 1 2

3 5

1 1 1 0

2

9

Presence of at least one hydrogen bond in the interaction is indicated by h; presence of a salt bridge in the contact by 5.

100

EDUARDO A. PADLAN

FIG.15. HyHEL-5 paratope and epitope surfaces.

The epitope for HyHEL-5 on lysozyme is discontinuous, consisting of 16 residues from three segments of the antigen (Table VII). There are two P-strands in the epitope: Gln-41, Thr-43, Asn-44, Arg-45, Asn-46, and Thr-47 are in one strand, and Gly-49, Thr-51 and Tyr-53 are in the other, with Asp-48 in the bend between the two strands; Gly-67, Arg-68, Thr-69, and Pro-70 are in a loop, and Ser-81 and Leu-84 are in a helix. The HyHEL-5 paratope (Table X) is composed of 2 1 residues of which 4, including 2 glycines, contribute only through their main-chain atoms. One framework residue, Trp-47 from the heavy chain-an almost invariant residue-contributes to the contact with the antigen. All six CDRs are involved in the binding. Six aromatic residues are involved: three tyrosines and three tryptophans, and these contribute 48% of the contact. The HyHEL-5 paratope features a wide depression at the bottom of which sit the two glutamic acid side chains that form salt bridges with the antigen. 3. Complex of Antibody 0 4 4 .I with Chicken Lysozyme

Antibody D44.1 binds to lysozyme with an association constant of 1.4 x lo7 M-'. In the crystal structure reported by Braden et al. (1994) (PDB

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

101

entry lMLC), there are two D44.1:lysozyme complexes present; only the first complex in the PDB file will be considered here. The complex between D44.1 and lysozyme is presented in Fig. 16. There is good complementarity between the D44.1 paratope and its epitope on lysozyme (Fig. 17), with a few water molecules improving the fit. The contact, summarized in Table XI, features 132 van der Waals contacts and 12 hydrogen bonds, ofwhich 4 involve main-chain atoms from the antibody and 2 involve main-chain atoms also from the antigen (Table VI). Three salt bridges are formed between D44.1 and lysozyme and, as in HyHEL-5, they involve the arginines at positions 45 and 68 in lysozyme and the glutamic acids at positions 35 and 50 in the D44.1 heavy chain. The structures of both complexed and uncomplexed forms of D44.1 Fab have been elucidated by X-ray crystallography and there appears to be a conformational change on binding the antigen (Braden et al., 1994). The D44.1 epitope on lysozyme consists of 16 residues, of which 6, two glycines included, contribute only through their main-chain atoms. The D44.1 epitope is very similar to the HyHEL-5 epitope (Table VII), but the antigen in the D44.1 complex is rotated approximately 14" relative to that in the HyHEL-5 complex (with the Fvs maximally superimposed). The D44.1 paratope (Table XI) is composed of 2 1 residues with all six CDRs contributing to its construction; one residue from the framework is

FIG. 16. Side view of the D44.1 complex with chicken lysozyme.

102

EDUARDO A. PADLAN

FIG 17. D44.1 paratope and epitope surfaces.

involved in the contact with the antigen. Five residues with aromatic side chains, t h e e tyrosines and two tryptophans, are in the paratope and these contribute 55% of the contact with the lysozyme. Seven residues, which include three glycines, contribute to antigen binding only through their main-chain atoms. Three tryptophans also contribute to the environment of the salt bridges: Trp-94 from the light chain and Trp-33 and Trp-47 from the heavy chain. However, only the salt links formed by Glu-50 are surrounded by the three tryptophans; the salt link involving Glu-35 is not and, moreover, the guanidinium group of Arg-96 from the light chain is in close proximity to this latter salt link. Even further, the environment of the salt links in the D44.1:lysozyme complex is noticeably more polar than in the HyHEL-5:lysozyme complex. Thus, the salt bridges appear to be in a region of lower dielectric constant in the HyHEL-5-lysozyme complex than in the D44.1 :lysozyme complex. This may explain the 1000-fold difference in the affinity of these antibodies for the antigen.

TABLE XI Contncts between Antibody aim?Ligand in 044.I-Chtcken Lysozyme Complex (PDB Ently IMLC) Antibodyn Light chain Lvsozvme

Heavy chain

N32 Y50 S91 N92 S93 W94 R96

S30 1’31

Y32 W33 E35 E50 L52 S54 G55 S56 Y58 G95 D96 G97

Totals ~

Q41 T43 R45 N46 T47 n48 G49 S50 T5 1 Y53 G67 R68 P70 P79 S8 1 L84

Totals

Qh

2

5 2 36

2 lh 5’&

1

18 2

3

5’

10

4

3h

1

4

4h

2 2 711

1

4 5

1

1

15

4’

5’

3

1 4

3

1 1

2

1

3 1

1

1 1 3

1 3 3

1

2

1

4 2 5

9

5

2

6

2 2

4

1

0

3

3

5

5 3 9 2 2 8 5 41 1 1 3 5 132

‘These values are for the first complex in the Protein Data Bank entry. Presence of at least one hydrogen bond in the interaction is indicated by h; presence of a salt bridge in the contact by A .

104

EDUARDO A. PADLAN

4. Complex of HyHEL-10 with Chicken Lysoryme

HyHEL-10 binds to lysozyme with an affinity constant of 1.5 x lo9M-'. The interaction is shown in Fig. 18 and summarized in Table XII. There is close complementarity between paratope and epitope surfaces (Fig. 19) and no water molecules were seen in the interface (Padlan et al., 1989). The interaction between HyHEL-10 and lysozyme includes 180 van der Waals contacts and 19 hydrogen bonds. Four of the hydrogen bonds involve main-chain atoms from the antibody, and two of the bonds involve main-chain atoms from both antibody and antigen (Table VI). The epitope for HyHEL-10 on lysozyme (Table VII) consists of 16 residues; 5 of these, including 3 glycines, contribute only through their mainchain atoms. Here also, the epitope is discontinuous, with contributions from four regions of the antigen, and contains various structural motifs: Arg-14 is at the end of a helix; His-15 and Gly-16 are in an interhelical bend; Tyr-20 and Arg-21 are in a p-bend; Leu-75 is part of another pbend, as is Trp-63; Arg-73 is in an extended chain; Gly-102 is part of a loop; while Thr-89, Asn-93, Lys-96, Lys-97, Ile-98, Ser-100, and Asp-10 1 are in an a-helix. Five charged residues-two arginines, two lysines, and one aspartic acid-are in the epitope, but only Lys-97 may be in a salt bridge with the antibody and only weakly at that (there is a 3.6 fi separation between the charged groups of Lys-97 of lysozyme and Asp-32 of the heavy chain of HyHEL-10 and the groups are exposed to solvent). The HyHEL-I0 paratope (Table XII) consists of 20 residues from all six CDRs; 1 residue comes from the framework. Eight residues with aromatic

FIG. 18. Side view of the HyHEL-10 complex with chicken lysozyme.

TABLE XI1

Contacts between Antibody and Ligand in HyHEL-10-Chicken Lysozyme Complex (PDB Entry 3HFM) Antibody’ Light chain Lysozyme R14 H15 GI6 Y20 R2 1 W63 R73 L75 T89 N93 K96 K97 I98 SlOO DlOl GI02 Totals

Heavy chain

G30 N31 N32 Y50 Q53 S91 N92 W94 Y96

3

1 8 6

T30 S31 D32 Y33 Y50

S52 Y53 S54

8 10 12 21 6 16

Ih

3

gh

4 4h

2

gh

6

gh

12h

1

4 2

5 1

4

7

19h

2

gh 2h

3 11 18 10 3 11 39

7

25

2

7

1

3 4h

1

4 13

7h

1

5 1 7 1 0

5

8

2

3

12

6

2

1

Bh

gh 1 3 3 1 9

Totals 1

16

5h

11

~~~

a

S56 Y58 W95

Presence of at least one hydrogen bond in the interaction is indicated by h.

1 3 5h

4

15

5

7 180

106

EDUAKDO A. PADLAN

FIG.19. The HyHEL-I0 paratope and epitope surfaces.

side chains, six tyrosines and two tryptophans, participate in the interaction and contribute 53% of the contact. All the amino acids in the paratope contribute side-chain contacts to the interaction, except for the one glycine. 5. Complex of F9.13.7 with Guinea Fowl Lysozyme

Antibody F9.13.7 had been raised against chicken lysozyme but also binds guinea fowl lysozyme. The binding of F9.13.7 to this latter antigen has been studied crystallographically (Lescar et al., 1993) and is illustrated in Fig. 20 and summarized in Table XIII. There are 147 van der Waals contacts and 14 hydrogen bonds. Three of the hydrogen bonds involve main-chain atoms from the antibody, and one of the three also utilizes a main-chain atom from the antigen. Three salt links are formed between F9.13.7 and the ligand. Here also, there is close complementarity between the interacting surfaces (Fig. 2 1). The F9.13.7 epitope on guinea fowl lysozyme is similar to the HyHEL10 epitope (Table VII). It consists of 16 residues all of which, except for 2 glycines, contribute through side-chain atoms. The F9.13.7 paratope consists of 17 residues, including 1 from the framework (Table XIII). Here, the second CDR from the light chain makes no contribution to the interaction. Four aromatic residues, three tyrosines

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

107

FIG.20. Side view of the F9.13.7 complex with guinea fowl lysozyme.

and one tryptophan, are in the paratope and together contribute 32% of the contact with the lysozyme. Three residues in the F9.13.7 paratope, which include two glycines, contribute only through their main-chain atoms. Essentially the same region on the antigens constitutes the epitopes for HyHEL-10 and F9.13.7 (Table VII). However, the mode of association of F9.13.7 with antigen is dramatically different from that of HyHEL-10 (compare Figs. 18 and 20). In fact, the antigen in the F9.13.7 complex is rotated about 172" compared to that in the HyHEL-10 complex (with the Fvs maximally superimposed). As a further difference, the two lysines in the F9.13.7 epitope form strong salt links with the antibody. Differences are found also in the paratopes of HyHEL-10 and F9.13.7 (compare Tables XI1 and XIII). HyHEL-10 has more aromatics than F9.13.7 (eight vs four), while F9.13.7 has more charged residues (three vs one). 6. Complex of D1 1.15 with Pheasant Lysozyme

Antibody D11.15 had been raised against chicken lysozyme but displays cross-reactivity with various other avian lysozymes. In fact, D11.15 has a higher affinity (four times higher) for pheasant than for chicken lysozyme. Elucidation of the crystal structure of the complex between D1 1.15 Fv with pheasant lysozyme was performed in order to determine the structural basis for the heterocliticity (Chitarra et al., 1993). The binding of D11.15 to pheasant lysozyme is illustrated in Fig. 22 and summarized in Table XIV. There are 107 van der Waals contacts, including 7 hydrogen bonds; 2 of the latter involve main-chain atoms from the antibody and 1 of them

TABLE XI11 Contacts between Antibody and Ligand in F9.l?. 7-Guinea Foul Lysozyme Complex (PDR EntT IFRI) Antibody' Light chain Lysozyme H15 G16 Y20 R21 W62 W63 G7 1 R73 L15

Y32

G91

Y92

Heavy chain

T93

L94

T30

S31

E50

D52

S53

D54

Y56

N58

G99

T l O O SlOOa

1Sh 1

2

1

2 2

3 1 2 1

14h

1

llh

Qh

1

2 2

N77

5s

3

5h 3

3h

1

6'

1

1

2

3

4

1

3

5

6

6

7

2

6

15

6

Totals

18 2 6 3 1 2 1 31 4

7

1 14

2 6 15

2h 1

5h

T89 N93 K96 K97 SlOO DlOl

Totals

W33

8

7 7h 2 19

7h 10

1 19 11 17 9 15 147

a These values are for the first complex in the Protein Data Bank entry. Presence of at least one hydrogen bond in the interaction is indicated by h; presence of a salt bridge in the contact by s.

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

FIG.21. The F9.13.7 paratope and epitope surfaces.

FIG.22. Side view of the D11.15 complex with pheasant lysozyme.

109

110

EDUARDO A. PADLAN

TABLE XIV

Contacts between Antibody and Ligand in D l 1.15-Pheasant Lysozyme Complex (PDB Entry IJHL) Antibody'"

Lysozyme

Light chain

Heavy chain

S30 N92 E93 Y94 W96

S31 W33 Y52 D54 Y56 D95 N97 Y98

R2 1 G22 Y23 D103 N106 R112 K113 K116 G117 T118 D119 N121

3

Totals

3

2" 5h 2

1 5 6

6h 3 1

4" 1 9

2' 8

2 3

5

6 2

7 14h

8 2 1

5'

8

2

2

2

15

12

2

8

5

10

14

Totals 4 1

15 6 11 10 8 20 22 4 3 3 107

'" Presence of at least one hydrogen bond in the interaction is indicated by h; presence of a salt bridge in the contact by s.

involves main-chain atoms from the antigen also (Table VI). The interaction includes two salt links. As in the other complexes, there is good complementarity between the two interacting surfaces (Fig. 23). The D11.15 epitope on pheasant lysozyme is similar to D1.3 to chicken lysozyme (Table VII) in that both consist of elements near the NHn and COOH termini of the antigens. Twelve amino acids constitute the D 11.15 epitope, of which four, including two glycines, contribute only through the main-chain atoms. Amino acid differences between the two lysozymes occur at two positions in the D11.15 epitope: at position 113, where chicken lysozyme has an asparagine while pheasant lysozyme has a lysine, and at position 121, where chicken lysozyme has a glutamine while pheasant lysozyme has an asparagine. The D1 1.15 paratope (Table XIV) is composed of 13 residues from five of the six CDRs; CDR2-L does not contribute. Six aromatic residues are in the D 11.15 paratope, four tyrosines and two tryptophans, which together contribute 67% of the contact with the antigen. Two aspartic acids from

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

111

FIG.23. The D11.15 paratope and epitope surfaces.

the D11.15 form ion pairs with a lysine and an arginine from the lysozyme. The structural basis for the heteroclitic behavior of D 11.15 toward pheasant lysozyme is not obvious. Attempts to model a binding configuration that would explain the stronger binding to pheasant lysozyme were not convincing (Chitarra et al., 1993). It should be noted, however, that a fourfold increase in binding affinity represents less than 1 kcal per mole of energy, or less than the energy associated with an ordinary hydrogen bond, and so a very subtle structural difference may be enough to account for the observed heterocliticity.

7. Complex of Je142 with Histidine-Containing Phospho-Carrier Protein of Escherichia coli The structures of the Fab of Je142, uncomplexed and complexed with its antigen, histidine-containing phospho-carries protein (HPr), have been elucidated (Prasad et al., 1993). The antigen is somewhat ellipsoidal and Je142 binds near one end. The interaction is shown in Fig. 24 and summarized in Table XV. The CDR surface of Je142 has a depression into which HPr binds (Fig. 25). There are 115 van der Waals contacts between Je142 and HPr and 10 hydrogen bonds, including 5 that involve mainchain atoms from the antibody and 1 that involves main-chain atoms from

112

EDUARDO A. PADLAN

FIG.24. Side view of the Je142 complex with HPr.

both antibody and antigen (Table VI). No large conformational change was noted on antigen binding. The Je142 epitope on HPr consists of 14 amino acids from three segments of the antigen. Interestingly, the epitope is highly charged, with 5 of the 14 epitope residues being glutamic acids (Table VII). One glutamic acid side chain is in a position to form a salt bridge with a histidine on the antibody if the latter is positively charged. The epitope contains /3-sheet, a-helical, and loop elements. The Je142 paratope (Table XV) is constructed from 18 residues from five of the six CDRs; CDR2-L does not contribute to the binding. One fi-amework residue is part of the combining site. Three residues, two of which are glycines, contribute through their main-chain atoms only. Five aromatic residues, four tyrosines and one histidine, contribute 33% of the contact. 8. Complex of NC41 with Injluenuz Virus Neuraminidase

Antibody NC41 had been raised against the neuraminidase from influenza virus (subtype N9 isolated from tern) and binds to the antigen with an association constant of 1.2 x lo' M-'. The structure of the complex of NC41 Fab with tern N9 neuraminidase has been elucidated by X-ray crystallography. The interaction is presented in Fig. 26 and summarized in Table XVI. The head region of influenza virus neuraminidase is a tetramer of identical subunits and NC41 Fab was found to bind mostly to one subunit, but there is in addition some contact of the Fab with carbohydrate

TABLE XV

Contacts between Antibody and Ligand in Jel42-HPr Complex (PDB Entv IJEL) Antibodya Heavy chain

Light chain

H Pr M1 F2 E3 Q4 T34 T36 S4 1 S64 E66 G67 E68 E70 Q71 E75 Totals a

H27d G27e N28

Y32

5

Y96

T30 T31

Y32

A33

L50

S52 P52a S53

S54

Y56 M96 G97

E98 WlOO

4h

5 2

3s

5

1

3 14

5

2 3

4h

4

Qh

3 4

1

2h 1

0

7

5

9

1

15 10 4

lh 1 1 5h

Totals

2

1

1

6

1

6

Sh

2 1 3

8

2

8

2

Presence of at least one hydrogen bond in the interaction is indicated by h; presence of a salt bridge in the contact by s.

7

3h

6 6 1 7 1 0 1 0

14 6 1 5 2 11 3 4 27 6

4

1 1 1 5

114

EDUARDO A. PADLAN

FIG.25. The Je142 paratope and epitope surfaces.

FIG.26. Side view of'the NC41 complex with influenza virus neuraminidase.

TABLE XVI

Contacts between Antibody and Ligand an NCII-Neuramanidnse Complex (PDAEntry INCA) Antibody* Neuraminidase

Y4Y W50 S52 T53 H55 I56 H91 Y92 S93 P94 W96 -

a

T30 N31 Y32 N52 N53 E96 D97 N98 F99 SlOOa 1.100b

6 4 1

2

3

2

2 6 2 6 3 12 14 14 6 8 4 19 20 4 22 7 12 180

2 4h

2 6

2

1 10h

2

Sh 2

1

9’1

2 Sh 3

1

13

23

2

10

2

Totals 1 6 4 5

1

I149 P326 R327 P328 N329 G343 N344 N345 N347 I366 S367 I368 A369 S370 S372 L399 N400 T40 1 D402 w403 P43 1 K432 Totals

Heavy chain

Licrht chain

6 2

1

2 2

9

1

4

1

4

1

Presence of dt least one hydrogen bond in the interaction IS indicated by h

7

4

7

7

5h

gh 4 1 7h 1

1

12

4

21

13

37

5

2 2

2

116

EDUARDO A. PADLAN

from an adjacent subunit. Only the interactions of NC41 with the protein part of the epitope will be described here. The interaction buries about 890 A' of surface area on NC41 and about 860 A* of the neuraminidase (Fig. 27)-the largest area of interaction in all the antibody-antigen complexes of known structure (Table VI). There are 180 interatomic contacts, including 13 hydrogen bonds. Of the latter, three involve main-chain atoms of the antibody. Although both epitope and paratope have charged residues, no salt links are formed between NC41 and the neuraminidase. The epitope for NC41 on the neuraminidase consists of 22 residues from six widely separated (in sequence) segments (Table VII). These residues are mainly in loops connecting /3 strands in the antigen. Two residues contribute to the interaction through their main-chain atoms only. The NC4 1 paratope (Table XVI) is made up of 2 1 residues from five of the six CDRs; CDR1-L does not participate in the binding. Two antigen-

FIG.27. The NC41 paratope and epitope surfaces.

X-RAY CRYSTALLOGKAPHY OF ANTIBODIES

117

contacting residues are from the framework, one from the heavy chain and the other from the light chain. Side chains from seven aromatic residuesthree tyrosines, two tryptophans, one phenylalanine, and one histidineinteract with the neuraminidase; together, these aromatic residues are responsible for 32% of the interatomic contacts. 9. Complex of NClO with Influenza Virus Neuraminidase

Antibody NClO had been raised against the neuraminidase from influenza virus (subtype N9 isolated from whale) and binds to it with an association constant of 2 x lo7M’. The crystal structure of NClO Fab complexed to neuraminidase has been elucidated (Malby et al., 1994). Atomic coordinates for the structure are not yet available from the Protein Data Bank at the time of this writing, and so a comparative analysis of the NC41 and NClO complex structures cannot be made here. The description that follows is adapted from Malby et al. (1994). Their summary of the interaction of NClO with its antigen is reproduced in Table XVII. The binding of NClO to neuraminidase buries 697 A* of the surface of the antibody and 7 16 k‘of the antigen. Three water molecules are found in the interface. There are 85 interatomic contacts between antibody and antigen, including 12 direct hydrogen bonds. Only four of the six CDRs contribute to the contact; CDR2-L and CDR1-H do not participate at all. The NClO epitope on the neuraminidase (Table VII) consists of 15 amino acids from four polypeptide segments. Carbohydrate from a neighboring subunit contributes to the epitope. The NC 10 paratope is constructed from 14 residues, including four tyrosines. Despite the presence of charged residues in both epitope and paratope, no salt links are formed between NC 10 and neuraminidase. NC41 and NClO bind to overlapping epitopes (Table VII), but one is rotated 72” relative to the other (with the antigens in the two complexes maximally superimposed). There are some differences also in the nature of the paratopes: NC41 has more aromatics than NClO (eight vs four) but fewer charged residues (two vs four) (compare Tables XVI and XVII). 10. Idiotope-Anti-idiotope Complexes

It has been proposed that an anti-idiotypic antibody may bear an internal image, i.e., a molecular mimic, of the (external) antigen (Jerne, 1974). Crystallographic studies on three idiotope-anti-idiotope complexes have been reported in the literature, and so the proposal can now be substantiated. The first to be analyzed was the complex between the Fabs of the antilysozyme D1.3 and the anti-idiotypic E225 (Bentley et al., 1990). E225 had been raised against D 1.3 and was found to react to other antilysozymes, as well as to a “humanized” version of D1.3, suggesting that E225 is directed

118

EUUAKDO A. PADLAN

TABLE XVII

Contach between Antzbody and Lzgand an NCl 0-Neuraminzdase Complex Antibody"

Neuraminidase

Light chain

Heavy chain

S30 Y32 D91 P92 T93 L94

Y52 G53 N54 D56 Y99 YlOOa

P328 N329 D330 P33 1 T332 Y341 G343 N344 I366 I368 A369 S370 N400 T40 1 W40 3 Totals

5 4"

1"

7 3h

2 2h

2 Ih 1

2h 4h 1

7 1

3 4h 2" 3

3

9

1

11

8

1

5

8

4h 7

4

1 1 1

8

1

Totals 9 11 4 2 1 1 2 4 1 7 4 4 10 8

11

9 1 2

79

Presence of at least one hydrogen bond in the interaction is indicated by h

against the combining site. The Fabs of D1.3 and E225 were found to associate end to end in the complex. E225 interacted predominantly with the VL, with 9 of the 13 residues in the epitope coming from the light chain. Five of the six CDRs of D1.3 and a nearby VL loop constitute the idiotope, while all six CDRs of E225 contribute to the paratope. Approximately 800 k of surface area in each Fab are buried in the complex. A comparison of the combining site of E225 and the epitope of D1.3 on lysozyme showed that the E225 paratope is not a structural mimic of the antigen. This is probably because D1.3 is directed against an epitope on lysozyme which is partly made up of helices-structures that cannot be easily assumed by most of the CDR loops. The second was the complex involving the Fabs of the anti-idiotypic monoclonal antibody 409.5.3 and of the antibody 730.1.4 (Ban et al., 1994).The antigen for 730.1.4 was the E2 peplomer, a large glycoprotein,

119

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

of feline infectious peritonitis virus. In this complex also, the two Fabs were found to bind end to end. All six CDRs of 409.5.3 were found to contribute to the construction of the paratope, while only five of the 730.1.4 CDRs are found in the idiotope. The surface area buried by the interaction is 860 A2 for 730.1.4 and 890 for 409.5.3. In the absence of the structure of the original antigen, it is not possible to assess whether the anti-idiotope mimics the antigen. The third was the complex between the Fabs of YsT9-1, a monoclonal antibody specific for the lipopolysaccharide A antigen of Brucella abortus, and of its anti-idiotopic antibody T91AJ5 (Evans et al., 1994). Here also, the two Fabs were found to associate end to end. In this case, all six CDRs in both Fabs were found to be involved in the contact. The surface area buried by the interaction is 730 812 for YsT9-1 and 760 for T91AJ5. A structure for antigen-bound YsT9-1 is not available and so a direct comparison of the structures of the anti-idiotope and the original antigen cannot be made here. Nonetheless, the CDR surface of YsT9-1 has been found to have a deep groove with dimensions consistent with the expected structure of the polysaccharide antigen. In the idiotope-anti-idiotope complex, T91AJ5 was found not to completely cover the putative antigen binding groove and so antigen mimicry in this case is not expected. The ability of the immune system to produce anti-idiotypic antibodies that bear an internal image of the original antigen must depend on the nature of the antigen (Amzel et al., 1994). The combining sites of antibodies are constructed from polypeptide segments mainly in the form of loops, whereas any molecular architecture may constitute an antigenic determinant. Indeed, it would not be easy, and probably would be impossible, to construct a combining site that is an exact mimic of a lipid, a carbohydrate, or a polynucleotide, since the chemical groupings in these molecules are not present in naturally occurring amino acids. Protein antigens are probably the easiest to mimic. However, as the example of the D1.3:E225 complex illustrates, helical structures in an antigen may already be difficult to reproduce in an anti-idiotope combining site. Nevertheless, it may be possible to generate the internal image of smaller substructures in an antigen. The structure of a very interesting complex has been elucidated, which involves an anti-anti-idiotypic antibody and the original antigen (Garcia et al., 199213). The monoclonal antibody MAbl31 had been raised against an antibody that had been raised against an antibody to angiotensin 11, an octapeptide hormone. MAbl3 1 binds angiotensin I1 with high affinity (Ka = 7.4 x 109M-'),and the hormone was found to bind in a deep cleft in the CDR surface of MAb 131. A compact structure was found for the ligand, with the NH2 and COOH termini of the peptide in close proximity. Indeed, the conformation of the peptide was found to closely resemble the

x2

x2

120

EDUARDO A. PADLAN

structure of a CDR3-L loop, suggesting that the structural mimic of the antigen in the anti-idiotypic antibody may have been a single CDR loop, possibly its CDR3-L (Garcia et al., 1992b).The amino acid sequences of the original anti-angiotensin I1 antibody, MAbl10, and of the anti-antiidiotypic antibody, MAb131, show a very high degree of similarity, and these antibodies have identical antigen binding properties (Garcia et al., 1992a). This then appears to be an example of structural mimicry in an idiotypic network. B. Complexes Involving Smaller Molecules

1. Complexes of 1 7/9 with Hemagglutinin Peptide Antibody 17/9 was raised against a 36-amino-acid synthetic peptide corresponding to residues 75-1 10 of influenza virus hemagglutinin and binds to peptide with high affinity (dissociation constant 2 x lO-'M). The structure of 17/9 Fab has been elucidated by X-ray crystallography in both complexed and uncomplexed forms (Rini et al., 1992; Schulze-Gahmen et al., 1993). One complex involved a 7-mer peptide (acetyl-Asp-Val-ProAsp-Tyr-Ala-Ser-amide)and another involved a 9-mer peptide (Tyr-AspVal-Pro-Asp-Tyr-Ala-Ser-Leu-amide). The crystals of the uncomplexed Fab contain two molecules in the asymmetric unit, and so two independent views of 17/9 Fab are available. Three crystal forms of the complexed Fab were studied and one contained two liganded Fabs in the asymmetric unit, thus providing four pictures of 17/9 Fab complexed to peptide. The two uncomplexed Fabs are very similar to each other, as are the four complexed structures in the different crystal forms. There is a groove in the 17/9 CDR surface in which peptide binds (Fig. 28). In the complex with the 7-mer peptide (PDB entry lIFH), 18 residues constitute the paratope and contacts are made to all seven amino acids in the ligand. Six of the paratope residues, of which three are glycines, contribute only through their main-chain atoms. There are 150 van der Waals contacts and 14 hydrogen bonds, including 3 that involve main-chain atoms in the antibody and 1 that involves a main-chain atom in the ligand also (Table VI). One salt link is formed between antibody and peptide. Four tyrosines are in the 17/9 paratope, although one contributes only through main-chain atoms; the remaining three are responsible for 27% of the interatomic contacts. In all four complex structures, the NHZ-terminal residues of the peptide were found to be in an extended conformation, the rest being in a tight/?-turn. The conformation of the peptide as bound to 17/9 is different from that found in intact hemagglutinin.

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

121

FIG.28. End view of the 17/9 CDR surface and bound peptide ligand (PDB entry 1IFH).

Slight differences are found in the relative disposition of the V Land ~ VH (Table V), but these are not significant. The differences in the elbow bends are most probably not correlated to the ligand state of the Fab and simply reflect the flexibility of the Fab. A large structural difference is observed in the CDR3-H of complexed and uncomplexed Fabs. The movement of this hypervariable loop is such as to promote peptide binding. Thus, this conformational change has been interpreted as an induced fit (Rini et al., 1992). 2. Complexes of Se155-4 with Carbohydrate

Antibody Se155-4 binds to the polysaccharide O-antigen from pathogenic Salmonella of sero group B; the antigen is built from repeating units of the tetrasaccharide aD-Gal(1-+2)[a~-Abe( 1+3)]a~-Man( 1+4)a~-Rha. The association constant for the binding of Se155-4 to the tetrasaccharide and to the analogous trisaccharide lacking rhamnose is 2.0 x lo5 M-'. X-ray structures are available for complexes of Se155-4 Fab with dodecasaccharide, heptasaccharide, and trisaccharide units of the antigen, as well as for a complex of Se155-4 Fv with a trisaccharide (Table I). It is found that the CDR surface of Se155-4 has a pocket approximately 8 A deep and 7 A wide into which the abequose moiety of the ligand binds (Fig. 29). Interestingly, this pocket is lined almost entirely with aromatic residues. The complex buries 283 A2 of the antibody and 228 A2 of the carbohydrate, computed on the basis of the Fv:trisaccharide complex (PDB entry 1MFA) (Table VI). The abequose contributes approximately half of the buried surface area. There are 72 van der Waals contacts, including four hydrogen bonds of which one involves a main-chain atom of the antibody. The aromatic residues are responsible for 88% of the interatomic contacts.

122

EDUARDO A. PADLAN

FIG 29. The CDR surface of Se 155-4 and bound trisaccharide (PDB entry 1MFA).

Some differences are found in the binding of trisaccharide to Sel55-4 Fab or Fv. In the complex involving the Fab (PDB entry lMFD), 297 of the antibody surface are buried in the complex, as well as 248 A2 from the ligand; there are 73 interatomic contacts, including four hydrogen bonds of which one involves a main-chain atom of the antibody. These numbers, especially the latter, are essentially the same as those for the complex involving the Fv. However, there is one more amino acid residue in the paratope in the Fv compared to the Fab complex (11 vs 10).

Az

3. Complex of BV04-01 with d(pT)3

Antibody BV04-01 is an autoantibody with specificity for singlestranded DNA. The structure of BVO4-01 Fab has been determined by X-ray crystallography with and without bound d(pT)3, a trinucleotide of deoxythymidylicacid (Herron et al., 1991). The CDR surface of BV04-01 is found to have a groove approximately 12 A wide at its widest, and the trinucleotide is found to bind in this groove (Fig. 30). The ligand binding site is formed by 20 residues from five of the six CDRs of BV04-01; CDR2-L does not contribute to the binding. Five of the epitope residues have aromatic side chains and together contribute 57% of the interatomic contacts. There are 184 van der Waals contacts between antibody and trinucleotide, including 12 hydrogen bonds, of which 5 involve main-chain atoms of the antibody, and 1 salt link (Table VI). The middle base of the trinucleotide is sandwiched between a tyrosine side chain and that of a tryptophan, an example of n-n stacking. Comparison of the liganded and unliganded forms of the Fab reveals a slight change in the VL:VHmode of association (Table V). This rearrangement of the quaternary structure of the Fv and conformational changes in CDR1-L and CDR3-H appear to have made possible a more comple-

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

123

FIG.30. The CDR surface of the DNA-binding autoantibody BV04-01 with bound d(pT)3.

mentary interaction with the ligand. This was interpreted as an example of induced fit. 4. Complexes of Catalytic Antibodies with Transition State Analogs

The ability of the immune system to produce antibodies against virtually any structure (if presented properly) has opened up the possibility of generating antibodies with enzymatic properties by using transition state analogs as immunogens Uencks, 1969). Many catalytic antibodies have been obtained (reviewed by Lerner and Tramontano, 1988; Schultz, 1988; Benkovic, 1992) and crystal structures for a few have become available. The first is antibody IF7 which catalyzes the conversion of chorismate to perphenate. The crystal structure of the Fab of IF7 has been determined in a complex with a transition state analog (Haynes et al., 1994). The hapten was found to bind in a small indentation in the CDR surface (Fig. 3 1). The hapten binding site is formed by all three CDRs of the heavy chain and the third CDR of the light chain. The site is basically hydro-

FIG 3 1. The CDK surface of the catalytic antibody 1F7 with bound transition state analog.

124

EDUARDO A. PADLAN

phobic and there is good shape complementarity. Three hydrogen bonds are formed between antibody and transition state analog, but there are no salt bridges. When compared to the known structure of the complex between the same transition state analog and chorismate mutase from B . subtilis, it was found that the opposite face of the hapten was bound to the antibody relative to the enzyme. Further, the transition state analog was more tightly bound to the enzyme, with more hydrogen bonds formed and the enzyme presenting a larger number of charged residues for ligand binding. The difference in the interaction may account for the 10,000-fold greater catalytic efficiency of the enzyme compared to that of the antibody. The Fab structure of a second catalytic antibody, 17E8, with a bound transition state analog has been reported (Zhou et al., 1994). This antibody, which had been raised against a norleucine phosphonate transition state analog, catalyzes the hydrolysis of norleucine and methionine phenyl esters. The hapten was found to bind in a deep cleft between the CDR3 of the light and heavy chains. Fourteen amino acids contribute to the antibody-ligand contact, mostly from the first and third CDRs of the two chains but also including four from framework regions. The phenyl ring and the n-butyl side chain of the hapten were found in hydrophobic sites. Interestingly, the active site of 17E8 contains a serine and a histidine, which appear to play the same role as the corresponding residues in the catalytic triad of serine proteases. Moreover, the site also contains a lysine side chain that could stabilize oxyanion formation. It appears that, in this case, the immune system has converged on an active site structure that has been selected after eons of natural enzyme evolution (Zhou et al., 1994). The structure of the Fab of another catalytic antibody, CNJ206, has been reported (Golinelli-Pimpaneau et al., 1994) but without a bound transition state analog. This antibody catalyzes the hydrolysis of p-nitrophenyl ester and was raised against a phosphonate hapten linked to keyhole limpet hemocyanin. The CDR surface was found to have a long groove which is hypothesized as being part of the combining site. The third CDR of the heavy chain and the framework region immediately after it are disordered in the crystal structure. A thorough assessment of the structure of this antibody must await a higher-resolution study of the molecule and the structure of its complex with a transition state analog. Several murine myeloma proteins bind phosphocholine (Potter, 1972) and some have been demonstrated to have esterolytic properties (Pollack et al., 1986; Pollack and Schultz, 1987). The phosphocholine-binding protein McPC603, the structure of which was one of the earliest to be determined crystallographically (Padlan et al., 1973; Segal et al., 1974),has been shown to have this catalytic activity (Pollack and Schultz, 1987). In the complex of McPC603 Fab with phosphocholine, the phosphate group of

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

125

the hapten, which has a configuration that mimics the transition state, is in close electrostatic contact with the guanidinium group of an arginine and forms a strong hydrogen bond with the hydroxyl of a tyrosine. The hapten fits tightly in a deep pocket with the phosphate more on the outside and the positively charged trimethylammonium group in a salt link with an aspartate at the bottom of the pocket (Padlan et al., 1985). The McPC603 residues involved in the interaction with the phosphocholine were also found to be present in other molecules with the same binding specificity (Padlan et al., 1976), and so these other antibodies may also have similar catalytic properties.

V1. CONCLUSIONS The available crystallographic data on antibodies point to a common motif in the three-dimensional structure of the individual domains, in the quaternary association of the domains, and in the overall architecture of the molecules, regardless of class, isotype, or origin. Most of the structural work has been on rodent antibodies because these molecules are more easily obtained. Nevertheless, the close similarity of all the known antibody structures suggests that conclusions can be drawn with confidence and that generalizations can be made that most likely apply to all. In regard to antigen binding, the crystallographic results show that (1) the combining site is constructed from CDR residues as predicted (Wu and Kabat, 1970), with an occasional involvement of framework residues; (2) only a small fraction, about one-third or less, of the total CDR surface is actually utilized in antigen binding; (3) there is complementarity between paratope and epitope, especially in shape; (4) the combining site is plastic and may change on ligand binding; ( 5 ) side chains contribute a major portion of the interaction with ligand; (6) amino acids with aromatic side chains play a significant role in binding; and (7) solvent molecules may be involved in antibody-antigen interactions. The very first studies on antibody structure showed that segments with identical amino acid sequences can adopt different conformations depending on the environment [i.e., they are deformable (Schiffer et al., 1973; Edmundson et al., 1974)] and that this deformability can lead to induced fit on ligand binding (Edmundson et al., 1987). More recently, more conformational changes in antibodies, suggestive of induced fit, have been noted. The changes may be in the disposition of side chains, e.g., in the D1.3:E225 idiotope-anti-idiotope complex (Bentley et al., 1990), in the structure of loop segments, e.g., in the binding of Fab 17/9 to peptide (Rini et al., 1992; Schulze-Gahmen et al., 1993), or in the

126

EDUAKIIO A. PADIAN

relative disposition of the variable domains, e.g., in D1.3 Fv (Bhat et al., 1994). The last mentioned is further evidence for the relatively weak interaction between Vr. and V H , which may serve a useful purpose as an added mechanism for fine-tuning antibody specificity (Colman et al., 1987). The biggest change so far in the mode of association of the VL and VH on ligand binding was observed in the antibody 50.1 in which the pseudo dyads relating V1. to VH differ by more than 8" between the liganded and unliganded forms of the Fab (Table V); this difference is portrayed in Fig. 32. The V1,:VH module may be even more deformable in the absence of the CL:CHl (one function of which may be to strengthen the VL:VHinteraction by increasing its probability). This portends the possibility that the binding properties of isolated Fvs may differ from those of intact molecules and Fabs. The plasticity of the CDR surface and of the combining site has serious implications for certain antibody applications, e.g., in the proposed use of antiidiotypic antibodies as vaccines (Nisonoff and Lamoyi, 1981) and of antitransition stage-analog antibodies as enzymes (Jencks, 1969). Thus, the deformability of the CDR surface makes production of an anti-idiotypic antibody that mimics the structure of the original antigen less likely. In the case of catalysis, deformability may help by moving distant groups closer to the site of the reaction; on the other hand, a plastic combining site may be unable to produce strain in a substrate to aid in the conversion to product. Higher-resolution crystallographic studies of antibody-antigen complexes are becoming feasible, and they allow the location of solvent molecules, especially those trapped in the interface. Bound water can have a significant role in the specificity and affinity of antibody binding to antigen. Solvent molecules can improve complementarity by acting as fillers in places where the fit between paratope and epitope is not precise. Solvent molecules can also mediate hydrogen bond formation. On the other hand,

FIG.32. End view of the liganded (thinner bonds) and unliganded (thicker bonds) forms of 50.1 illustrating the possible relative movement of the variable domains on ligand binding. In the drawing, the Vl. domains had been maximally superimposed.

X-RAY CRYSTALLOGRAPHY OF ANTIBODIES

127

the trapping of water results in a decrease in the entropy of the system, thereby contributing negatively to the interaction. Further, trapped water molecules could result in decreased binding affinity by their effect on the dielectric constant in the interface region between antibody and antigen. The dielectric constant in a pure hydrocarbon environment is 2; in the interior of a protein the dielectric constant is usually assigned a value of -2 to 4, while in pure water it is 80 (Honig and Nicholls, 1995). It may not be possible to know precisely the change in the dielectric constant when water is trapped at the antibody-antigen interface, but it is probably safe to assume that an increase in the constant will result. This may explain the 1000-fold decrease in the binding affinity of HyHEL-5 for lysozyme in which an arginine, which forms a salt bridge with a glutamic acid in the antibody, is replaced with lysine. In the structure of the HyHEL-5 complex with the mutated antigen (Chacko et al., 1995), a water molecule is found to occupy the added space resulting from introduction of the smaller lysine. As described previously, the binding of HyHEL-5 to lysozyme is dominated by the salt bridges between two glutamic acids from the antibody and two arginines from the antigen, and the immediate environment of these ion pairs probably has a low dielectric constant which would enhance the electrostatic interactions. An increase in the polarity of this environment, e.g., by the introduction of water, could lead to a significant decrease in the strength of the salt bridges. X-ray crystallography has permitted identification of the antibody residues that are in actual contact with the antigen, in other words, the specificity-determining residues (SDRs). It is found that these antigencontacting residues are mostly located in the center portion of the CDR surface (Padlan, 1994a). It is also found that the SDRs mostly emanate from positions that display high sequence variability (Abergelet al., 1994; Padlan et al., 1995).It appears that the boundaries of the CDRs need to be redefined. Identification of the SDRs, by crystallographic means or by examination of variability plots, can facilitate the design of protein engineering studies that attempt to modify the ligand binding properties of an antibody, as well as the humanization of nonhuman antibodies (rendering them nonimmunogenic while preserving their ligand binding properties) since only the SDRs may need to be altered, or preserved, as the case may be. We now know a great deal about antibody structure, yet much more needs to be done. For example, the Fc structure is known only for IgG and only to medium resolution at that. Because the effector fimctions of an antibody reside in the Fc, it is imperative that high-resolution studies of this fragment from all antibody classes be undertaken. A detailed structure for the Fc of IgE, for example, will add to understanding of the binding of this fragment to mast cell receptors and help in the design of molecules for

128

EDUARDO A. PADLAN

the treatment of allergic disease. Further, many antibodies have been generated, often in nonhuman hosts, that have potential uses in human therapy, e.g., antibodies with antitumor activity, and three-dimensional data on the antigen binding regions of these antibodies will greatly aid in attempts to humanize these molecules. The need for high-resolution X-ray structures for antibodies and other medically important molecules cannot be overemphasized.

ACKNOWLEDGMENTS I thank Drs. Susan Chacko, David R. Davies, and Birgit A. Helm for comments and discussions, and Hitomi Kuho and Atul Nair for help with the figures.

REFERENCES Ahergel, C., Tipper, J. P., and Padlan, E. A. (1994). Res. Zmmunol. 145,49-53. Abola, E. E., Bernstein, F. C., Bryant, S. H., Koetzle, T . F., and Weng, J. (1987). In “Crystallographic Databases-Information Content, Software Systems, Scientific Applications” (F. C. Allen, G. Bergerhoff, and R. Severs, eds.), pp. 107-132. Data Commission of the International Union of Crystallography, Bonn, Germany. Alzari, P. M., Spinelli, S., Mariuzza, R. A., Boulot, G., Poljak, R. J., Jarvis, J. M., and Milstein, C. (1990).EMBOJ. 9,3807-3814. Amzel, L. M., Garcia, K. S., and Desiderio, S. (1994). Res. Zmmunol. 145, 53-55. Amzel, L. M., Poljak, R. J., Saul, F., Varga, J . M., and Richards, F. F. (1974).Proc. Natl. Acad. Sci. U.S.A. 71, 1427-1430. Arevalo, J. H., Stura, E. A,, Taussig, M. J., and Wilson, I. A. (1993a). J . Mol. Biol. 231, 103-118. Arevalo, J. H., Taussig, M. J., and Wilson, I. A. (1993b).Nature 365, 859-863. Arnold, E., Jacobo-Molina, A., Nanni, R. G., Williams, R. L., Lu, X., Ding, J., Clark, A. D., Jr., Zhang, A,, Ferris, A. I.., Clark, P., Hizi, A., and Hughes, S. H. (1992). Nature 357, 85-89. Ban, N., Escobar, C . , Garcia, R., Hasel, K., Day, J., Greenwood, A,, and McPherson, A. (1994).Proc. Natl. Acad. Sci. U.S.A. 91, 1604-1608. Benkovic, S. J. (1992).Annu. Rev. Biochem. 61, 29-54. Bentley, G. A., Bhat, T. N., Boulot, G., Fischmann, T., Navaza, J., Poljak, R. J., Riottot, M.-M., and Tello, D. (1989). Cold Spring Harbor Symp. @ant. Biol.54, 239-245. Bentley, G. A., Boulot, G., Riottot, M. M., and Poljak, R. J. (1990).Nature 348, 254-257. Bernstein, F. C., Koetzle, T. F., Williams, G. J . B., Meyer, E. F., Jr., Brice, M. D., Rodgers, J. R., Kennard, O., Shimanouchi, T., and Tasumi, M. (1977).J. Mol. Biol. 112, 535-542. Bhat, T. N., Bentley, G. A., Boulot, G., Greene, M. I., Tello, D., Dall’Acqua, W., Souchon, H., Schwarz, F. P., Mariuzza, R. A,, and Poljak, R. J. (1994). Pror. Natl. Acad. Sci. U.S.A. 91, 1089-1093. Bhat, T. N., Bentley, G. A,, Fischmann, T. O., Boulot, G., and Poljak, R. J. (1990). Nature 347,483-485. Blundell, T. L., and Johnson, L. N. (1976). “Protein Crystallography.” Academic Press, New York.

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INSIGHT INTO ANTIBODY COMBINING SITES USING NUCLEAR MAGNETIC RESONANCE AND SPIN LABEL HAPTENS By HARDEN M. McCONNELL and MARIA MARTINEZ-YAMOUT Department of Chemistry Stanford University Stanford, California 94305

I. 11. 111. IV. V. VI . VII. VIII. IX. X. XI.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . AntibodiesANOn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . DiEerence Spectra . . . . . . . . . . . . . . . . . . . . .

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Distance Titrations Combining Site Dynamics and Reaction Kinetics . . . . . . . . . . . . . . . . . . . . . . . . Crystal Structure of AN02 .......................

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Synopsis and Outlook .................. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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It is possible to obtain novel and useful structural and dynamic information on antibody combining sites using high-resolution nuclear magnetic resonance (NMR) spectroscopy together with suitable nitroxide free radicals called spin labels (SL). The purpose of this article is to describe this approach in terms that are convenient for biochemists or immunologists, rather than in the technical language of the physical chemist or NMR spectroscopist. The methods are illustrated with work performed in this laboratory on the Fab fragment of the A N 0 2 antibody which has specificity for haptens containing the dinitrophenyl (DNP) group. A great deal of pioneering work on the application of NMR and spin labels to antibody structure was carried out by Dwek and collaborators (Dower and Dwek, 1979). They studied mouse myeloma proteins with specificity for dinitrophenyl haptens and reached a number of conclusions concerning antibody structure and reaction kinetics that are similar to those described here. In retrospect their progress in this area was remarkable, considering that at that time there was a paucity of X-ray structural data on antibodies ADVANCES I N PROrEIN CHEMISTKY, Vol. 49

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and that neither hybridoma nor single-site mutagenesis technology had been developed. Deuteration of tryptophan in myeloma proteins was accomplished by feeding a mouse deuterated tryptophan! (Gettings and Dwek, 1981). Much of our work on A N 0 2 was carried out before the crystal structure of this Fab fragment was determined, and before single-site mutations made definitive signal assignments possible. Nevertheless, in the absence of a crystal structure and definitive signal assignments, uncertainties can accumulate to an unacceptable degree if detailed structural and kinetic information is needed. [Applications of two-dimensional NMR methods to structure determination of lower molecular weight proteins and peptides are described by Wiithrich (1986). For such problems deuteration, singlesite mutations, and spin labels are usually not needed. For related references see Berliner and Reuben (1989) and Jardetzky and Roberts (1981).] Because Fab fragments can be crystallized, and the practice of X-ray crystallography has improved to the point that structures can be determined quite rapidly, one may ask whether specialized NMR techniques such as those described in this article warrant the effort they require. Our conservative view is that in special cases where very detailed information on combining sites is required, this effort can be rewarding, as for example when antibodies are to be tailor-made for therapeutic or diagnostic use or when they exhibit enzymatic activity and the structural basis of this activity is of interest. It will be seen that NMR spectra of antibody combining sites can reveal details of structure and dynamics that are not available from X-ray structures. It should be borne in mind that unlike X-ray diffraction, NMR spectroscopy can be regarded as a time domain technique. An NMR spectrum is the Fourier transform of a relaxation spectrum, the free induction decay (Abragam, 1961; Ernst et al., 1987). The determination of even a static protein structure using NMR can thus be expressed in terms of time-dependent processes. In the event that an antibody-hapten complex has a structure that itself varies in time, these time-dependent processes are compounded. Thus, the observed NMR spectrum or relaxation spectrum in principle provides views of both structure and dynamics. 11. ANTIBODIES ANON Antibodies ANOn, where n = 1,2, ..., 12, were produced by hybridomas secreting IgG antibodies against the paramagnetic hapten DNP-SL depicted in Fig. 1. AN02 was derived from mice immunized with keyhole limpet hemocyanin conjugated with the 5-fluoro analog of DNP-SL. The specificity of these antibodies is largely directed against the dinitrophenyl

137

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group, and thus they also bind the haptens DNP-SLH, DNP-Gly, and DNP-Glyn shown in Fig. 1. These antibodies have been sequenced and characterized by Leahy et al. (1988). Most of the NMR studies were carried out on Fab fragments of AN02. The X-ray crystal structure of AN02 complexed with DNP-SL has been determined (Brunger et al., 1991).

0

il

o'Na II

N A H

on

DNP-Gly2

on

on

DNP-Gly

FIG. 1. Dinitrophenyl haptens that bind to the monoclonal antibodies ANOn. DNP-SL is the paramagnetic nitroxide spin label hapten. The unpaired electron is strongly localized on the nitrogen and oxygen atoms of the nitroxide group. The diamagnetic hapten DNP-SLH is produced by gentle chemical reduction of the nitroxide group. The haptens DNP-Gly and DNP-Gly2 were obtained by reaction of fluoro- and difluorodinitrophenyl with glycine. See Theriault et al. (1991).

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HARDEN M. McCONNELL AND MARIA MARTINEZ-YAMOU?

111. DIFFERENCE SPECTRA An Fab fragment of an IgG antibody contains thousands of protons, which is a major obstacle to the application of 'H NMR spectroscopy because of the overlap of the many resonance signals. Some simplification is achieved in the case of antibody combining sites in that this region typically contains a high proportion of aromatic residues (Davies et al., 1990). In A N 0 2 there are 11 tyrosines and 6 tryptophans in or adjacent to the complementarity determining regions of the light and heavy chains. The spectral positions of the aromatic residues are well separated from the aliphatic residues, and to a lesser degree well separated from one another. Even so, the problem of overlapping resonance signals is overwhelming and requires special strategies in order to simplify the spectra sufficiently to obtain signal assignments. One method for spectral simplification is the use of deuterated amino acids, discussed later. The second method for spectral simplification involves the use of paramagnetic (spin label) haptens and the calculation of NMR difference spectra. The electron has a magnetic moment that is about a thousand times larger than the magnetic moment of the proton, and even larger than the magnetic moments of other nuclei. When the nitroxide spin label hapten binds in the binding site of A N 0 2 , all protons within about 20 A of the unpaired electron are subject to the magnetic field produced by the spin magnetic moment of this electron. As a result, their proton NMR resonance signals are broadened. By spectral subtraction, (NMR spectrum of Fab without a spin label) minus (NMR spectrum of Fab with a spin label hapten bound), one obtains a dijfference spectrum that gives proton resonance signals for the protons within 20 A of the odd electron in the free radical. This difference spectrum provides a snapshot of what is loosely referred to as the antibody combining site region. See Fig. 2 for a schematic illustration of this principle. An example of an NMR difference spectrum for tyrosine residues in A N 0 2 is given in Fig. 3. This is the aromatic region of the spectrum, where all aromatic amino acid proton signals except that of tyrosine are removed by deuteration, as discussed later. The NMR difference method described here is not limited to antibodies derived from mice immunized with a paramagnetic hapten; any hapten that can be modified by a paramagnetic nitroxide group is a candidate for this type of analysis.

IV. SELECTIVE DEUTERATION Proton difference spectra for antibody combining sites contain so many resonance signals that it is dificult to resolve the resonance line of individual protons in amino acids. Difference spectra can be significantly simpli-

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139

Hapten

Unpaired electron

A 2

Fab comdex with b p i n label hapten

=L Difference spectrum

FIG.2. Schematic representation of the technique for obtaining NMR difference spectra using a spin label hapten. Nuclear magnetic resonance spectra from two protons, A and B, are shown for the Fab fragment. Below this spectrum is the NMR spectrum of the Fab fragment complexed with a paramagnetic spin label hapten. The resonance spectrum of proton A in the combining site region is strongly broadened by the magnetic field of the unpaired electron, whereas the spectrum of the more distant proton B is comparatively unaffected. The third spectrum is the difference spectrum and shows essentially only the resonance of proton A in the combining site region.

fied by amino acid deuteration (Anglister, 1990). Antibody-secreting hybridomas can be grown on selectively deuterated amino acids, and these amino acids can be incorporated to a level of over 95% in the secreted antibody (see Anglister et al., 1984a,b; see also Gettings and Dwek, 1981). In a number of studies, partially deuterated tyrosine residues, illustrated in Fig. 4,have been employed. Partial deuteration of antibody proteins sometimes provides a second advantage, significantly decreasing the NMR line widths of the remaining proton signals. The proton signals in Fig. 3 arise from the protons in tyrosine that are next to the hydroxyl group. When there is rapid flipping of the tyrosine aromatic side chain, the two protons on a given residue are equivalent on the NMR time scale and give resonance signals at the same position. Flipping of the tyrosine aromatic ring at a rate of 210 sec-' produces this equivalence. As a rule, solvent-exposed tyrosine residues undergo this rapid flipping. V. NUCLEAR MAGNETIC RESONANCE SIGNAL ASSIGNMENTS

For many applications of the methods discussed here it is important to have signal assignments, i.e., to know which NMR signal corresponds to which amino acid proton. With a known antibody sequence, model building, various magnetic resonance technical strategies, and selective deuter-

140

HARDEN M. McCONNELL AND MARIA MARTINEZ-YAMOUT

7.15

6.90

6.65 PPm

6.40

6.15

5.90

FIG.3. Illustrative spin label difference spectra of the Fah fragment of the monoclonal antibody AN02. The aromatic region of the 500-MHz proton difference spectrum ofANO2 with perdeuterated tryptophan, phenylalanine, and partially deuterated tyrosine (H-3,5Tyr). Spectra were recorded at 37°C with 100-150 p M Fah and excess hapten. Resonances A through I arise from 11 tyrosine residues within -20 6; of the spin label. The various difference spectra are (A) Fah-FahSL, (B) FabCly-FahSL, (C) FahClyz-FabSL, and (D) FahSLHFabSL. [From Martinez-Yamout and McConnell (1994).]

ation, it is sometimes possible to make plausible assignments. However, the greatest confidence in NMR assignments is obtained from single-site mutagenesis. The assignment methodology for tyrosine resonances in AN02 is illustrated in Fig. 5 , which shows spectra employed to assign

INSIGHT I N T O ANTIBODY COMBINING SITES

OH

DJ$c

I

H

:D H * CH2

I

CH

NH~’

141

’

CH

‘COOH

H-3,5-tyrosine

NH2

‘COOH

H-2,6-tyrosine

FIG.4. Partially deuterated tyrosine. Spectra reported here arise from H-3,5-tyrosine.

proton resonance G to the light chain tyrosine (LY31) by mutating this residue to phenylalanine (LY31F). Signal assignments using point mutations in the antibody sequence have been successful because conservative mutations at one site usually do not produce large shifts in the resonance positions of the proton signals of other residues, especially for tyrosine residues on the surface of the protein. This is clearly illustrated in the spectra in Fig. 5 . Nonconservative mutations produce larger shifts in the resonance positions of other residues, but these shifts themselves are sometimes helphl in making signal assignments (Martinez-Yamout, 1994). Most of the tyrosine resonances in the combining site region give sharp resonances because they undergo rapid motion on the surface of the protein. Two buried tyrosine resonances are not observed in the difference spectra and have been identified as LY34 and LY36 by elimination. It is likely that the flipping rate of these tyrosines is low. All 11 tyrosine resonance signals seen in the difference spectra for A N 0 2 have been assigned.

VI. DIAMAGNETIC HAPTENS

Three diamagnetic haptens are illustrated in Fig. 1, DNP-SLH, DNPGly, and DNP-Gly2. These haptens have dissociation constants on the same order of magnitude as the paramagnetic hapten, DNP-SL, on the order of micromolar. These haptens are useful in studies on the kinetics of hapten-antibody reactions (discussed later) and also in obtaining certain difference spectra. The difference spectrum, (NMR of Fab) minus (NMR spectrum of Fab with DNP-SL bound), yields the NMR spectrum of the combining site region free of hapten. In contrast the difference spectrum, (NMR of Fab with DNP-SLH bound) minus (spectrum of Fab with DNP-SL

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HARDEN M. McCONNELL AND MARIA MARTINEZ-YAMOUT

7.15

6.90

6.65 PPm

6.40

6.15

5.90

FIG. 5 . Spin label difference spectra of the LY3lF mutant. Spectra of AN02 are also shown for comparison. Signals G and G' are missing in the spectra of LY31F since these signals arise from tyrosine-31 on the light chain of AN02. (A) Ly31F Fab-FabSL, (B) FabFabSL, (C) LY31F FabGly-FabSL, (D) FabGly-FabSL, (E) LY3lF FabSLH-FabSL, and (F) FabSLH-FabSL.

bound), yields the NMR spectrum of the occupied binding site region. It can be seen in Fig. 3 that, as a first approximation, the resonance spectra of these combining sites are similar. However, the differences are significant and interesting, especially for signal G (due to LY31), as discussed later.

INSIGHT INTO ANTIBODY COMBINING SITES

143

VII. DISTANCE TITRATIONS

The proton line broadening depicted schematically in Fig. 2 depends strongly on the distance between the NO group of the nitroxide free radical and the proton on the protein. When the rate of binding and dissociation of the paramagnetic hapten is fast and reversible, the hapten-induced line broadening can be used to measure this distance. One employs a “spin label titration,” measuring protein proton line widths at different spin label concentrations (Anglister et al., 1984b). Such distance measurements were particularly helpful in early studies on AN02, before the crystal structure was determined. Detailed comparisons between crystal structure distances and distances given by spin label titrations are given by Thierault et al. (199 1) and Martinez-Yamout and McConnell (1994). The titration distances proved quite useful in making preliminary signal assignments. In some cases they are significantly shorter than the crystal distances. This is expected since the titration distances are derived from the average of a l/(distance)6 dependence of the electron spin-enhanced nuclear relaxation rates, where this distance is measured between the position of the odd electron and the position of the proton. Thus, structural fluctuations tend to exaggerate the shortest distances.

VIII. COMBINING SITE DYNAMICS AND REACTION KINETICS

Surprising information on antibody combining sites has been obtained through a study of antibody-hapten reaction kinetics. These reaction kinetics can be measured even when the hapten-antibody reaction kinetics are rapid, as is usually the case when the equilibrium dissociation constants are in the micromolar range. As an example, the hapten DNP-Gly2 binds to A N 0 2 with an equilibrium binding constant of 1.7 x lo6 M-’ at 37°C. The sharp resonance of a proton at position 3 in this hapten (see Fig. 1) is broadened in the presence of the AN02 antibody, and this broadening permits determination of the dissociation rate constant. From this measurement it is possible to deduce the on-rate constant, k,, = 7.1 x lo8M-’ sec-’. [For earlier related work, see Haselkorn et al. (1974) and Sutton et al. (1977) and references therein.] This reaction rate constant can also be deduced from resonance line widths of tyrosine resonances in the combining site region (Anglister et al., 1984b). Thus, local conformation of the tyrosine (assigned to LY3 1) must follow closely the binding and dissociation of the hapten, which occurs roughly 1000 times a second in these experiments.

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HARDEN M . McCONNELL AND MARIA MARTINEZ-YAMOUI

IX. CRYSTAL STRUCTURE OF A N 0 2 The crystal structure of the Fab fragment of AN02 complexes with DNP-SL was determined by Brunger et al. (1991). A space-filling drawing of this structure is given in Fig. 6, in which the tyrosine residues are displayed in yellow. In the upper part of Fig. 6 the DNP-SL hapten is shown in red, and in the lower part of Fig. 6 the hapten has been removed without changing any protein coordinates. All of the 11 observed tyrosine signals have been assigned to these various residues. As mentioned previously, two tyrosine residues, LY34 and LY36, that are in the back of the binding site (Fig. 6, lower) do not give detectable resonance signals. The putative larger line widths are doubtless related to a low flipping rate. The tyrosine LY36 has the proper orientation (Baker and Hubbard, 1984) to form a hydrogen bond with glutamine-89. Tyrosine LY34 forms one part of one face of the binding pocket, and its rotation is hindered by tryptophan 91, tyrosine 32, and aspartate 50, with whose carboxy group it may also form a hydrogen bond. [A role for tyrosine residues in myeloma M 3 15 has been discussed by Leatherbarrow et al., (1982).] In this crystal structure, the dinitrophenyl ring is stacked between two tryptophan residues, LW91 and HW96. [For a discussion of the contributions of tryptophan rings to dinitrophenyl hapten binding, see Jackson and Dwek (198I).] The aromatic side chain of light chain tyrosine LY31 is positioned above and perpendicular to LW91. The resonance of the protons of this tyrosine gives rise to signal G or, when two coexisting conformations are present, signals G’ and G”. The resonance position of this particular tyrosine is particularly sensitive to ring current shielding effects from LW91, and to a lesser degree from the aromatic ring of the hapten (see Theriault et al., 1991). For a discussion of ring current shifts, see Johnson and Bovay (1958). The resonance of this tyrosine led to discovery of the conformational heterogeneity of the AN02 Fab-DNP-Glyn complex, as mentioned later. The light chain tyrosine LY31 is the only significant difference in the complementarity determining loops between AN02 and the germline antibody, which has a serine at this position (Theriault et al., 1989). It has been shown that there is no significant effect of the mutation LY31S on dinitrophenyl-hapten binding (Yamout-Martinez and McConnell, 1994). The intercalation of the dinitrophenyl ring between two tryptophan residues (LW91 and HW96) in the case of the AN02 complex with DNPGly, was established by means of nuclear magnetization transfer before the structure of AN02 DNP-SL was determined (see Anglister et al., 1987). [Intra- and intermolecular nuclear magnetization transfer has also been used extensively by Anglister et al. (1993) to study the structure and kinetics of antibody-antigenic peptide complexes.]

INSlGHT INTO ANTIBODY COMBINING SITES

145

In examining the structure of the AN02 complex with DNP-SL as given in Fig. 6, one might wonder to what extent the reported tyrosine ring orientations for this complex apply to the solution structure, bearing in mind that there is rapid flipping of the tyrosine rings in solution and that there are doubtless intermolecular forces in the crystals. In selected cases (e.g., HY27 and HY33) studies have been made of both nuclear magnetization transfer between tyrosine residues and mutual ring current shifts, all of which support the crystal structure conformations (see Theriault et al., 1991).

X. CONFORMATIONAL HETEROGENEITY

In general, both antigens and antibodies may be conformationally heterogeneous before they react, and the product of their reaction may or may not be conformationally heterogeneous. An interesting example of the effects of Fab combining site heterogeneity on the binding reaction was obtained through an NMR determination of the binding rate of DNPGly2 to the Fab fragments of ANOl and AN02. The association of this hapten with AN02 is close to the diffusion-limited rate (109M-' sec-I), and the on-rate constant increases with increasing temperature. The activation energy for the binding reaction (5.1 kcal/mol) is close to the activation energy for molecular diffusion in water (Theriault et al., 1991). In contrast, the rate of DNP-Gly2 binding to the ANOl Fab fragment decreases with increasing temperature (Theriault et al., 1993). The explanation of this anomalous kinetic behavior is that the combining site has thermally excited structures that do not bind hapten. As discussed later, this interpretation is confirmed by molecular modeling calculations in which a portion of the heavy chain hypervariable D loop of ANOl forms structures that inhibit access of the hapten to the combining site. There is high sequence homology between antibodies ANOl and AN02. The heavy chains have 77% sequence identity, and the light chains 88% sequence identity, where most of the differences are due to conservative replacements (Leahy et al., 1988; Theriault et al., 1991). A significant difference between the two antibodies is that an additional four residues are found in the hypervariable D region of the heavy chain of ANO1. A computer model of ANOl suggests that these additional residues form a loop that partially blocks the hapten binding site. This may account for the fact that the on-rate constant for binding of DNP-Gly2 to ANOl is about 100 times slower than the on-rate constant for binding to AN02. Moreover, molecular dynamics calculations on AN0 l and AN02 show that the D region of ANOl assumes multiple conformations at high temperatures and fewer conformations at low temperatures. In contrast, this same re-

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HARDEN M. McCONNELI. A N D MARIA MARTINEZ-YAMOUI

gion of AN02 has essentially the same conformation throughout the entire temperature range. For tyrosine residues the ‘H NMR spectra are consistent with this conformational heterogeneity in AN0 1. A tyrosine signal exists as a doublet in the absence of hapten and as a single resonance in the presence of DNP-Glyn. This temperature-dependent conformational heterogeneity thus provides an explanation for the apparent negative activation energy for hapten binding to AN01 (Theriault et al., 1993).The conformational heterogeneity described here may be related to that found by Lascombe et al. (1992) in their study of two distinct crystal structures of the Fab fragment of a monoclonal antiarsenate antibody. Even though the binding rate constant for DNP-Glyn to AN02 is close to the theoretical limit of that of a diffusion-controlled reaction, NMR data show clear evidence for complexity even for this reaction. It is not simply that the hapten undergoes diffusion, experiences a collision, and then sticks in the combining site. Difference spectra provide clear evidence for two coexisting conformations of the AN02 Fab-DNP-Glyn complex. These conformations are revealed by a doubling of resonance signals of the protein, as well as by a doubling of resonance signals from the bound hapten. The formation of the two complexes can be represented by the reactions

+H Fab + H Fab

--L

(FabH)’

-L

(FabH)”

[see Theriault et al. (1991) and Yamout-Martinez and McConnell (1994)l. Under specified experimental conditions, proton signals from a tyrosine residue (LY31) are split into two signals (G’ and G”), each corresponding to a distinct conformation. Nuclear magnetization transfer between the signals G’ and G” can he used to measure the rate at which structures (FH)’and (FH)” interconvert. The rate of interconversion of these conformations is found to be limited quantitatively by the preceding dissociation and reassociation reactions. In other words, the rate of direct interconversion of the structures (FH)’ and (FH)” is too slow to be measured and requires dissociation and reassociation of the hapten. The crystal structure of AN02 Fab DNP-SL has been used to model the two structures of AN02 DNP-Glyz, namely, (FH)’ and (FH)” (see Fig. 7). One of these structures (lower) stabilizes an otherwise unstable conformation of the hapten. In this conformation of the hapten there is a twist of the glycine residue relative to the plane of the aromatic ring to give a conformation that is unfavorable by about 2 kcal/mol. However, this twisted conformation avoids the charge repulsion that is otherwise present between the carboxylate of the glycine hapten and the light chain aspartate side-chain carboxylate anion. Mutating the LD50 residue to threonine or serine removes this charge repulsion and increases the binding energies of

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147

DNP-Gly:, by about 2.4 and 3.2 kcal/mol, respectively. These mutations yield more than a 100-fold increase in affinity. The haptens DNP-SLH and DNP-Gly’, for which this charge repulsion is absent, do not show NMR spectra corresponding to more than one conformation of the Fab-hapten complex. However, for all three Fab-hapten complexes, the NMR spectra provide compelling evidence for a substantial change in the conformation of at least one of the tryptophans in the combining site. The resonance signal from the aromatic ring protons of LY3 1 undergo a large (-200-Hz) upfield shift on hapten binding, a shift that is almost certainly due to motion of LW91 to accommodate binding of the dinitrophenyl ring. The tryptophan motion considered here may be similar to that reported in X-ray studies on the binding of steroids to Fab DB3 (see Arevalo et al., 1993).

AND OUTLOOK XI. SYNOPSIS

When our NMR studies on the antibodies ANOn (n = 1, 2, 3, ..., 12) were undertaken in 1984, it was by no means clear that any useful information would be obtained, even with the strategy of using spin label difference spectra, deuteration, and single-site mutations. A favorable combination of circumstances made these studies possible. They include (1) the narrow line widths of most of the aromatic proton resonances in the combining site region, (2) the high efficiency of incorporation of deuterated amino acids in the antibodies, and (3) the relatively minor perturbations in spectral resonance positions brought about by conservative singie-site amino acid mutations, making possible definitive signal assignments. These conditions will probably hold for most antibody Fab fragments. It is now clear that the combination of a crystal structure, nuclear magnetic resonance, and single-site mutagenesis can provide a wealth of detailed, suggestive information about antibody combining sites. As just one example, in our work the doubling of a resonance line led to the question of why a hapten should be in two conformations in an antibody combining site when one intramolecular hapten conformation is itself energetically unfavored. A theoretical model of this structure led to the conclusion that this result might be related to unfavorable electrostatic interactions between the more stable intramolecular conformation of the hapten and an antibody residue. To test this hypothesis the residue was mutated to a neutral residue, resulting in an improvement of antibody-hapten binding of more than a factor of 100. This result illustrates the point made in Section I: Given an objective such as increasing the affinity of an antibody for a specific hapten, the detailed structural and kinetic information provided by a combination of NMR and X-ray crystallography can prove to be rewarding.

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ACKNOWLEDGMENTS This work was supported by the Army Research Office and by the Office of Naval Research (contract NO00 14-90-5-1407).

KEFERENCES Abragam, A. (1 961). “Principles of Nuclear Magnetism.” Oxford University Press, London. Anglister, J., Frey, T., and McConnell, H. M. (1984a). Biochemistvy 23, 1138-1 142. Anglister, J., Frey, T., and McConnell, H. M. (1984b). Biochemistvy 23, 5372-5375. Anglister, J., Bond, M. W., Frey, T., Leahy, D., Levitt, M., McConnell, H. M., Rule, G. S., Tomasello, J., and Whittaker, M. (1987). Biochemistry 26, 6058-6064. Anglister, J., Scherf, T., Zilher, B., Levy, R., Zvi, A,, Hiller, R., and Feigelson, D. (1993). FASEBBJ. 1154-1 162. Arevalo,J. H., Stura, E. A., Taussig, M. J., and Wilson, I. A. (1993).J. MoZ. Biol. 231, 103-1 18. Baker, E. N., and Hubbard, R. E. (1984). Pmg. Biophys. Mol. Bid. 44, 97-179. Reuben, ed.), Berliner, L. J., and Reuben, J. (1989). In ”Biological Magnetic Resonance” Vol. 8. Plenum Press, New York. Brunger, A. T., Leahy, D. J., Hynes, T. R., and Fox, R. 0. (1991).J. Mol. Biol. 221, 239-256. Davies, D. R., Padlan, E. A., and Sheriff, S. (1990).In “Annual Review of Biochemistry” (C. C. Richardson, ed.), Vol. 59, pp. 439-474. Annual Reviews, Palo Alto, CA. Dower, S. K., and Dwek, R. A. (1979). In “Magnetic Resonance in Biology” (R. Shulman, ed.), pp. 271-303. Academic Press, New York. Ernst, R. R., Bodenhausen, G., and Wokaun, A. (1987). “Principles of Nuclear Magnetic Resonance in One and Two Dimensions.” Clarendon Press, Oxford. Gettings, P., and Dwek, R. (1981). FEBS Lett. 124, 248-252. Haselkorn, D., Friedman, S., Givol, D., and Pecht, I. (1974). Biochemistry 13, 2210-2222. Jackson, W. R. C., and Dwek, R. A. (1981). Mol. Immunol. 18, 499-506. Jardetzky, O., and Roberts, G. C. K. (1981). “NMR in Molecular Biology.” Academic Press, New York. Johnson, C. A., and Bovey, F. A. (1958).J. Chem. Phys. 29, 1012-1014. Lascombe, M.-B., Alzari, P. M., Poljak, R. J., and Nisonoff, A. (1992). Proc. Natl. Acad. Sci. U.S.A. 89,9429-9433. Leahy, D. J., Rule, G. S., Whittaker, M. M., and McConnell, H. M. (1988). Proc. Natl. Acad. SCZ. U.S.A. 85, 3661-3665. Leatherbarrow, R. J.,Jackson, W. R. C., and Dwek, R. A. (1982). Biochemistry 21, 5124-5129. Martinez-Yamout, M. (1994a). Thesis, Stanford University, Stanford, CA. Martinez-Yamout, M., and McConnell, H. M. (1994b).J. Mol. Bid. 244, 301-318. Sutton, B. J., Gettings, P., Givol, D., Marsh, D., Wain-Hohson, S., Willan, K. J., and Dwek, R. A. (1977). Biochem.J. 165, 177-197. Theriault, T. P., Rule, G. S., and McConnell, H. M. (1989). In “Proceedings of the 10th Ettore MajorandNATO Summer Institute on Protein Structure and Engineering” (0. Jardetzby, ed.), pp. 367-376. Plenum Press, New York. Theriault, T. P., Leahy, D. J., Levitt, M., McConnell, H. M., and Rule, G. S. (1991).J. MoZ. Biol. 221, 257-270. Theriault, T. P., Singhal, A. K., Rule, G. S., and McConnell, H. M. (1993).J. Phys. Chern. 97, 3034-3039. Wuthrich, K. (1986). In “NMR of Proteins and Nucleic Acids.” Wiley, New York.

u.

COMPUTATIONAL BIOCHEMISTRY OF ANTIBODIES AND T-CELL RECEPTORS By JlRl NOVOTNY and JURGEN BAJORATH Departments of Macromolecular Modeling and Molecular Structure BristoCMyers Squibb Research Institute Princeton, New Jersey 08540 and Seattle, Washington 98121

I. Background

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A. Gross Immunoglobul

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A. VL-VH Interface 3 / Barrel

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d Monte Carlo Methods

A. Thermodynamics of Binding B. Lock-and-Key or Induced Fit C. Empirical Gibbs Functions

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B. What Is a Protein Epitope?

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Copyright B 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.

IX. Antibody Engineering . . . .

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E. Heterospecific Polyvalent Constructs, “Miniantihadies” . . X. T-cell Receptor Modeling arid Engineering. . . . . . . . . . . . . . . . . . . . . . . . . . . .

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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In vertebrates, the immune system has evolved to specifically recognize any foreign antigen (a macromolecule, virus, bacterium, or cancer cell) and to destroy it. The key attributes of immunity-its precise specificity, the seemingly endless diversity of the immune repertoire, and the ensuing unique molecular “self ’-identity of each vertebrate organism-are all mediated by antibodies and T-cell receptors. In the past two decades it has become possible to relate immune functions to immunoglobulin and T-cell receptor structures. However, with protein molecules ranging in size from 50,000 to 1,000,000 Da, the challenges of structural analysis are enormous. Aids such as molecular models, calculations, simulations, and computer graphics are indispensable. Their technical and conceptual complexities have led to the emergence of a specialized field called computer modeling. The term cornpuler modeling is being used profusely, if vaguely, to describe different types of activities. It can mean anything from just looking at three-dimensional structures on a computer screen to application of complex and involved mathematical concepts and manipulations to obtain new insights into the structure-function relationship. “Computational immunology” became a necessity once the X-ray crystallographic structures of immune molecules emerged. Antibody-antigen complexes have immediately presented us with a challenge: Given all the exquisite atomic detail of the two molecules interacting in three dimensions, can we understand the chemical origin of affinity and specificity to a point where, e.g., accurate predictions of the effects of point mutations will be possible? Such an understanding, it soon turns out, goes beyond a mere detailed description. It requires biophysical interpretation of crystallographic reality. Necessarily, one has to stop and ponder many questions, and search (and perhaps even err in the course of the search) for a conceptual framework that allows understanding.

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A. A Touch of Metascience: Description and Understanding,

Rigor and Empiricism It seems obvious that a mere collection of all the experimental facts assembled by molecular immunologists (the specificity and binding data, the structures of antibodies and their antigenic complexes, the plethora of amino acid and nucleic acid sequences) cannot, per se, answer the fundamental questions of the field. Abstract concepts are needed to connect all the functional and structural data, and to develop formalisms capable of extrapolation to novel situations and predictions. It may be useful to spend a little time on relevant metascientific thoughts. Questions are omnipresent in our work and thinking: Does a single unifying (bio)physical principle govern molecular phenomena? Is there a single correct way to proceed toward understanding these phenomena? In an abstract sense, yes; practically, however, no. Ultimately, antibodies are chemicals-macromolecules-described by the same physical principles as, e.g., hydrogen gas. A rigorous, deductive approach to their structure from the very first principles (quantum mechanics) would be hopeless, not only because of the practical impossibility of solving the Schrodinger equation for tens of thousands of atoms, but also because of the essential and unavoidable limitation of any logical system of axioms. In 1931 Kurt Godel (Fig. 1) showed that mathematical number theory is deeply and incurably inconsistent, in that any finite set of axioms can be proven to be incomplete. That is, there is always at least one statement whose veracity cannot be deduced from the initial set of postulates (Godel, 1931; Nagel and Newman, 1958). If this is true for the central discipline of mathematics, it is even more true for all the less formal scientific disciplines: physics, chemistry, and biology. Thus, attempts to deduce the ultimate truth from a set of first principles will always be limited to uncertain outcomes (see, e.g., Yun-yu et al., 1993). On the other hand, induction from experimental data and abstraction from observables have long been an efficient and fertile way of doing science (e.g., Darwin, 1859, 1871). Induction processes usually lead to an emergence of alternative scientific disciplines, each with its own specific, truthful description of reality. This does not necessarily mean that we cannot see the most general relations, or that we are not able to guess at an overreaching relationship between anything and everything else in nature. However, alternative descriptions of phenomena (“paradigms,” Khun, 1970), either exact or approximate, may coexist for long periods of time. A case in point is quantum mechanics. Equivalent formulations exist, based on matrix calculus (Heisenberg, 1925; Born and Jordan, 1925), wave mechanics (Schrodinger, 1926), and path integrals (Feynman and Hibbs, 1962; Feynman, 1972);group theory (Weyl,

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FIG. 1 . Kurt Godel. (Courtesy of the Institute for Advanced Studies, Princeton, NJ.)

1928) and the conjecture of “hidden variables” (Bohm, 1952) provide additional, conceptually independent perspectives. What message does this leave us regarding molecular immunology? Overall, we think, it justifies an empirical and pragmatic approach to immune phenomena and structural science, as opposed to a rigorous but limiting purism. Approaching very complex phenomena and observables (e.g., structural determinants of antigenic specificity), one needs to propose simple and approximate explanations first. Only afterward, if proven useful, can the approximate concepts be refined into something more exact. Richard Feynman (1967) observed: The only utility of science is to go on and try to make guesses. We always must make statements about regions we have not seen, or the whole business is of no use. In order to avoid simply describing experiments that have been done, we have to propose laws beyond their observed range. There is nothing wrong with that, despite the fact that it makes science uncertain. If you thought before that science was certain-well, that is just an error on your part.

Similarly, Max Planck (1933) wrote: In every science it occasionally happens that there arises a conflict between two classes of people whom I may designate respectively as purists and

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pragmatists. The former strive always after a perfect coordination of the accepted axioms, submitting them to even more and more rigid analysis, for the purpose of eliminating every contingent and foreign element. On the other hand, the pragmatists try to amplify the accepted first principles by the introduction of new ideas and thus send out feelers in all directions for the purpose of making progress. They do not mind if the mongrel be mated with a pure-bred, provided something can be achieved through the combination, which otherwise could not be achieved. The purist sticks to his logical weapons. He takes his stand on logical deductions from the accepted principles of science, whereas the pragmatist scientist is striking out into new ground; and in order to open that up he must break away from the logical line of the old ideas. The pragmatist must face failure again and again, and is always open to jibes of the orthodox “I told you so.” What the puritan objects to is the introduction of new ideas from outer sources. Now, no theorem or working hypothesis can arise ready-made. Every hypothesis which eventually has proved to be useful and to have led to valuable discoveries at first occurred only vaguely to the mind of its inventor.

B. Scope of the Article, Nature of Structural Data

In this article, we discuss the diverse computer-aided techniques that have been applied to analysis of the immune structure-function relationship, and put the main results obtained with these methods in a broader perspective. As such, our article is necessarily a personal account of these analyses and another scientist would have written a different overview (some of them, in fact, have: Padlan, 1994;Webster et al., 1994). However, we have striven to make the presentation balanced enough so that the reader can form his or her own opinion on the matter. Structural data are the bedrock on which computational immunology stands and we start with general comments on the nature of the data. The three-dimensional structures come to us as Cartesian coordinates of molecules determined by X-ray crystallography or, more recently, multidimensional (hetero)nuclear magnetic resonance (NMR) spectroscopy [e.g., the solution structure of an isolated VL domain by Constantine et al. (1994)l. These protein and DNA structures (available through the Brookhaven Protein Data Bank; see Bernstein et al., 1977) represent atomic models best fit to electron density (X-ray) or interatomic distance (NMR) data. These models can be gauged as to their accuracy and precision. Accuracy is a measure of the closeness with which a calculation reproduces the true structure. Precision, on the other hand, is a measure of the reproducibility of measurements (e.g., distance constraints) or calculations (e.g., simulated annealing). Nominal resolution, the crystallographic residual factor (R

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factor), and the B factor’ (Ladd and Palmer, 1985) are values describing crystallographic accuracy and precision, which may approach fractions of angstroms for well-resolved structures (less than 2.0 A nominal resolution). Estimates of the precision and accuracy of NMR-determined protein structures (Zhao and Jardetzky, 1994) put the accuracy of a family of simulated annealing-derived coordinates at about 1 even if the errors in distance constraints are smaller than 1 A. The precision of the structures appears to be nearly insensitive to the quality of NMR data and is, at best, on the order of 1-2 A, although a precision of 0.4-0.7 A is technically attainable. The X-ray and NMR structures represent thermodynamic equilibrium average structures, or what Gregorio Weber (1975)would call a “bulk’ protein:

-

The time-average structure observed by X-ray diffraction is something of an abstraction, since it is not itself widely-or even sparsely-represented at any given time in the population of molecules. I mean by this that if we were to take an instantaneous picture of the molecular population showing us all the coordinates of the atoms for each individual molecule we would have difficulty in finding one that will match the average in all respects, although most of the molecules will have most features in common with it. Indeed the protein molecule model resulting from the X-ray crystallographic observations is a “platonic” protein, well removed in its perfection from the kicking and screaming “stochastic” molecule that we infer must exist in solution. The great importance of the former lies in that it has permitted us to see the origin of the “bulk properties” of the protein, which result from averaging over the whole population.

As will become apparent (Sections II,C, and VI,B), the results of certain computer experiments (least-squares superpositions in particular) may vary according to the nominal resolution of the structures under study. Common sense dictates that greater credence is due the results obtained with high-resolution structures (less than 2.0 A resolution).

11. TOOLS OF COMPUTER ANALYSIS

Protein structures being sets of three-dimensional Cartesian coordinates (x,y,z) of thousands of N, C , S, 0, and H atoms, any convenient and meaningful manipulation of these structures can be achieved only on a computer. This is true both for simple translations, rotations, and zoom-

’

Nominal resolution gives the shell radius, in the reciprocal space, to which the diffraction data (reflections) were collected and used to calculate the electron density. The R factor gives the fraction of electron density unaccounted for by the final structural model. The (isotropic) B factor (Debye-Weller, temperature factor) gives the apparent size of a spherical atom and becomes larger with increasing fuzziness of the diffraction image of an atom.

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ing in real space, and for more abstract, involved operations such as generation and examination of molecular surfaces, simulation of atomic movements, least-squares superposition of molecules, and other molecular modeling procedures per se. One can speak of three levels of computer modeling approaches. On the most basic level, computers provide a convenient viewing interface for scientists contemplating atomic details of a set of least-squares-superposed molecules as, e.g., in the works of Lesk and Chothia (1982).The next level consists of software programs that allow structure manipulations “by hand” (e.g., building up immune molecules from homology as, e.g., Pumphrey did in 1986). The third level provides for computational evaluation of protein energetics and stereochemistry via a potential function or a force field, i.e., a set of equations that define the optimal state of a protein polymer (e.g., Bruccnleri and Karplus, 1990).Although calculations per se are better defined and more objective than hand manipulation of molecules, it does not necessarily mean that the less precise methods are less useful. Even the highest precision means nothing if the physical concepts embodied in the software are not sound, or are not appropriate for the situation at hand. All physical models are approximations and the user should well understand their limitations. “Garbage in, garbage out,” is the notorious adage of computer scientists. One of the goals of this article is to make the inherent conceptual limitations of our methods more explicit. A . Protein Potential Energy

In order to build and manipulate protein structures in a computer, the chemical and geometric aspects of the structure, such as bonds, angles, torsions, and atomic radii, have to be mathematically expressed and encoded in a program. The field dealing with the development and usage of such programs has become known as molecular mechanics. Molecular mechanics has its origin in X-ray diffraction of proteins. The Fourier transformed diffraction data yield an electron density map that needs to be fitted with an amino acid sequence. The crude three-dimensional protein model is then refined, its stereochemistry regularized and poor atomic overlaps corrected, etc. For the purpose of model refinement, Levitt and Lifson (1969) developed a set of formulas that explicitly describe the potential energy of an atom in a protein. The total energy of the system can be obtained by summing over all the atoms. First and second derivatives of this empirical energy potential can be calculated from the formulas, and the total energy of the molecule minimized by moving all the atoms along the potential energy gradient. It is important to realize that the potential energy function of Levitt and Lifson, and the other early force fields-ECEPP (Warme and Scheraga,

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1974), Hagler’s formulations (Hagler et al., 1974) embodied in DISCOVER, Hermans and McQueen (1974), MM2 (Allinger, 1977), CHARMM (Brooks et al., 1983), AMBER (Weiner et al., 1986), GROMOS (van Gunsteren and Berendsen, 1987), and OPLS potentials Uorgensen and Tirado-Rives, 1988)-were merely a means of building an abstract wire model of a molecule. The potential specifies how long (do) the wires representing atomic bonds are, how strong they are (Kbond)and how they stretch with Brownian thermal motions (harmonically, for mathematical convenience): Ebond

= Khond(d

- HdO)‘

(1)

Also specified are the correct values of angles connecting three atoms and how soft these angles are (Kangle):

(Zo)

= Kangle (6 -

(2) as well as how easy it is to turn the torsions (4) and where the torsional minima lie: Emglc

Etorslon

= &( 1 - cos @).

(3)

The molecular mechanics force field also makes sure that double bonds are planar and that the correct values for the other, “improper” torsions, w (e.g., chiral atom stereochemistry), are enforced: Elmpn,per

= KO(@

- wo)*

(4)

It specifies how big the “balls” (defined by radii, r ) representing atoms are and how hard they are: EvdW

=

A,

rv

B, rg

(5)

--

Equation (5) implies that nonbonded atoms interact by painvise LennardJones potentials. In Eq. (5), rIJstands for the distance separating the ith and thejth atoms. Their interaction consists of a weak attraction [London dispersion forces falling off with the sixth power of distance (London, 1930)] and a steep repulsive van der Waals (vdW) barrier (the term). Painvise interactions are also used to describe electrostatic interactions between electrically charged atoms and formally neutral but dipolar groups with measurable partial atomic charges,

a,a:

where E is the dielectric constant. It was quickly realized that the utility of the potential energy function was much broader than a mere real space

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refinement. Via energy minimization and, better still, Monte Carlo conformational searches (Tanaka and Scheraga, 1975), researchers hoped to arrive at the natural structure of protein models; after all, the natural structure is the lowest energy structure. Taken at face value, an exact potential energy function and powerhl computers could calculate correct structures and, implicitly, the biological properties of proteins (Levitt and Warshel, 1975). After more than 20 years, the challenge and excitement of this proposition is still with us and it remains essentially unsolved. What is missing from the molecular mechanics approach? First, the potential energy of a protein in vucuo is not a very good approximation of the free energy of the biological system: the protein in physiological solution. The molecular mechanics force field was really meant to describe a mechanical ball-and-stick model built by crystallographers: impenetrable spheres of atoms with rigid bonds and somewhat more flexible angles, and with rotatable torsional degrees of freedom. No account of protein-solvent interactions is given. Second, even if the potential energy function is correct, the problem of finding the global energy minimum is an enormous one. Much activity has focused on the development and testing of free energy potentials that would be more realistic measures of the stability of a folded protein in an aqueous environment (Novotny et al., 1984; Eisenberg and McLachlan, 1986; Sippl, 1990; see Section VI1,C). Another approach is to include water molecules in the system explicitly and simulate properties of the complete solvent-solute ensemble. This approach, however, is very demanding on computing power, requiring the manipulation of tens of thousands of atoms, and always faces the fundamental question of reaching a good equilibration and accomplishing a sampling of states sufficient to represent a rigorous thermodynamic average (Chandler, 1987). B. Surfaces and Rlumes

Computer-based analyses of protein surfaces and volumes (Richards, 1977) greatly contributed to our understanding of protein structure and function in general. Specific immunochemical applications included the identification of effector sites (see Section V,A), the determination of molecular correlates of antigenicity (Section VIII), and binding energy estimates (Section VI1,C). In a landmark paper, Lee and Richards (1971) introduced the concept of solvent-accessible and contact surfaces, as defined by a spherical probe that rolls over the protein surface (Fig. 2). Thus, the accessible and contact

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FIG 2. Accessible surface algorithm. A planar section of protein surface is shown, with atoms exposed to the outside solvent numbered from 1 to 12. Two spherical probes with different radii, RS > Rl are rolled over the surface and define the accessible surfaces as (continuous) lines traced by their centers. Their contact surfaces are the (discontinuous) lines of contact with the individual atoms. Their reentrant surfaces are the (discontinuous) lines that fail to make contact with the probe. Together, the contact and reentrant surfaces define the (continuous) molecular surface. Note that, as the probe radius goes to inifinity, so does the accessible surface while the contact surface converges to a small value. (Reproduced with permission from Richards, 1977. Annu. Rev. Biophys. Bioeng. Vol. 6. 0 1977 by Annual Reviews, Inc.)

surfaces of the same protein, effectively defined by differently sized probes, may vary and may have somewhat different properties. Large probes ( r = 10 A) that can sample, by direct contact, only the most protruding parts of a protein surface, “see” a surface with an atomic compositio? rather different from that seen by a smaller, water-sized probe (r = 1.4 A) (Table I). The concept of solvent accessibility inspired a large body of work. The studies by Chothia (1974) and others established proportionality between the Lee and Richards solvent-accessible surfaces and the magnitude of the hydrophobic effect of the solute. The Lee and Richards (1971) algorithm also became the basis of various programs for the display of molecular surfaces (Fig. 3), most notably the dot surface diagrams due to Connolly (1983) and the “plaster” surface approximations of the program GRASP

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TABLE I

Accessibility ofAmino Acid Residues to Probes ofDzfferent Radii" Probe radius = 1.4 8,

Probe radius = 11.4 8,

Accessibility

Accessibility

Amino acid

(A")

Amino Acid

(AZ)

'4% LYS Gln Glu Asn Tyr ASP Pro Thr Ser His Trp Ala Gly Val Leu Met Ile Phe cys

101 103 79

Lys k g Gln Asn Glu ASP Pro Ser TYr Thr His Ala Gly Val Leu Met Ile TrP CYS Phe

223 219 152 1 I5 115 104 92 79 77 74 40 36 33 22 20

66 65 61 59 53 46 43 41 32 28 25 25 22 22 20 18 13

14

14 14 5 5

Adapted from Novotny et al. (1987). The values represent averages of calculations performed on 11 single-domain proteins.

(Nicholls, 1992). Richmond (1984) presented an analytical surface representation employing differential geometry and allowing for some measure of surface minimization. More recently, Pascual-Ahuir and Silla (1990), in their program GEPOL, gave us a tool for the generation of a molecular surface (see Fig. 2) and proposed that it is a more direct correlate of hydrophobicity than the solvent-accessible surface is (Tufion et al., 1992). Richards (1974) and Finney (1975) described computer algorithms that partitioned the space occupied by a protein into atomic volumes based on Voronoi polyhedra (Fig. 4). This allowed the local packing density of proteins to be determined as -0.75, a very high density indeed, approaching that of closely packed ideal spheres. Volume (Connolly, 1985, Stouch and Jurs, 1986) and surface partitioning is an important component of various computerized docking procedures (Kuntz and Crippen, 1979; Connolly, 1986; Gregoret and Cohen, 1990, 1991; Jiang and Kim, 1991; Cherfils

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.

B

FIG.4. Volumes occupied by protein atoms (lioronoi polyhedra). (A) A two-dimensional sketch of the Voronoi algorithm. Points show centers of atoms. Vectors are drawn from an atom to all its neighbors within a sphere of 8 A radius. Planes perpendicular to the vectors, and normal to the van der Waals radii of the contacting atoms, are constructed, defining the smallest polygon (a polyhedron in three dimensions, the Voronoi polyhedron) that encloses the central atom. The ratio of the atomic van der Waals volume to that of the Voronoi polyhedron is the packing density of the atom. (B) The Voronoi polyhedron of the Oy atom in a serine residue. Atoms are shown as spheres with radii one-quarter of their van der Waals radii. [Reprinted with permission from Harpaz et al. (1994).

et al., 1991) that determine the best shape complementarity in protein-

ligand pairs. The importance of inter- and intraprotein packing to protein function and stability has been hotly debated, with the focus on the following issue: Is tight packing of complementary side chains the decisive determinant of protein folds [i.e., the “jigsaw puzzle” or “watchmaker” paradigm of Harpaz et al. (1994)], or could tight packing be readily achieved with any nonspecific assemblage of side chains [e.g., the “nuts-and-bolts-in-a-bag” paradigm of Bromberg and Dill (1 994)]? Evolutionary evidence seems to favor the latter view. Side-chain-side-chain contacts in proteins of similar threedimensional structure show high variability (Russel and Barton, 1994), often with as few as 12%common contacts and virtually no conservation of energetically favorable side-chain-side-chain interactions. Gerstein et al. (1994) analyzed volume changes in side chains occurring in protein evolution and found that only about half of the protein cores strongly conserved their volume (to within 10% variation). The rest of the positions showed various degrees of variation that, in some core sites and in nearly all surface sites, approached random variation (28% and more). An inspection of interfaces in protein-protein (Krystek et al., 1993) and, particularly, in antibody-

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antigen (Lawrence and Colman, 1993) complexes revealed relatively loose complementarity and enough empty space to suggest that, on the whole, the main role of (approximate) shape complementarity may be expulsion of water from hydrophobic interfaces and/or modulation of interprotein interactions by surface-prebound water molecules (see Section VII,C,3), rather than precisely engineered atomic interactions and steric repulsions.

C. Structural Superpositions Statistical analysis of the available Brookhaven Protein Databank entries has indicated that there may be no more than about 1000 distinct proteinfold families (Chothia, 1992), and that the many millions of protein amino acid sequences may merely repeat the same folding motifs over and over again. Although the three-dimensional dissimilarity of two proteins parallels their sequence diversity (Chothia and Lesk, 1986), proteins with no sequence similarity may still share the same fold. Three-dimensional similarities that persist in proteins despite sequence differences accumulated in evolution can be quantitatively analyzed by pairwise structural superpositions. The measure of overall corespondence of the two compared sets of atoms is the root-mean-square (rms) deviation (A):

McLachlan (1972), Diamond (1976), Kabsch (1976), and Rossmann and Argos (1975,1976) introduced formalisms for finding the best rotation to fit a given set of atoms to a target set of coordinates. Structural motifs (sets of backbone and/or side-chain atoms) are first identified in the two structures being compared, for example, residues participating in heme binding in globins and in cytochromes. These are then used to carry out the best rigid-body rotation and translation that matches the Cartesian coordinates of one atomic set (the source) to those of the other atomic set (the target) such that the (weighted) sum of squared deviations is minimized. In the McLachlan (1972) formulation, given the two sets of N coordinate vectors hba(a = 1, ... N)we seek an orthogonal rotation matrix R and a translation t that convert the coordinates aza(i = 1,2,3) to

and minimize the residual

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where w, is an arbitrary weight. Note that the formula implies equivalence of predefined pairs of atoms in the two structures. Several powerful algorithms were developed that find the best fit for two sets of atoms (structures) through systematic application of rotations and translations in the three-dimensional Cartesian space (Rossman and Argos, 1975; Diamond, 1976; Lesk, 1991). It is important to realize that there is no a przorz correct way of equivalencing protein structures and parts thereof. In current practice, the selection and definition of groups of superposed atoms implicitly contain a hypothesis of the cause of structural similarity; at the same time, the hypothesis is being tested by the superposition and the ensuing analysis of the results. For example, in order to measure differences in relative orientation of the Vr*and VH domains in different antibodies, it is possible to equivalence Ca atoms of one domain (e.g., V,) by least-squares superpositions, and to calculate the rotational-translational matrix required to best superpose the other domain pair (e.g., VH). However, given the existence of the invariant motifs at the VL-VH interface (Section IV,A), we may argue that a more meaningful way of equivalencing pairs of dimeric VL.-VH modules would be to least-squares superpose the six aromatic rings of the conserved “herringbone” cluster and the pair of Gln residues forming interdomain side-chain hydrogen bonds, rather than the complete domain backbones (Novotny and Sharp, 1992; Bajorath et al., 1995). It is reasonable to assume that the solvent-exposed /3 sheets are unimportant in formation of the interface and that by their excessive sequence (mass) variations, they may obscure the best alignment of the key interface-forming segments.

111. SmucruKEs, SEQUENCES, AND SUPERFAMILIES The relationship between amino acid sequence and three-dimensional structure is often described as a stereochemical code that transposes primary protein structures into tertiary protein structures (Epstein, 1964, 1966). The code is degenerate: Although the chemical structure (amino acid sequence) of the protein is known to determine the three-dimensional structure (Anfinsen and Haber, 1961; White, 1961), many different sequences can adopt the same fold. From the point of view of the stereochemical code, structural variability of immunoglobulin polypeptide chains offers an interesting, well-studied example of structural degeneracy exploited by nature for generation of the immune repertoire. It is generally accepted that each immunoglobulin sequence represents a unique antigenic specificity. Indeed, by refolding a denatured immune Fab and

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demonstrating that it had regained its original specificity, Haber (1964) showed for the first time that the information of immune specificity resides in the amino acid (and, implicitly in the DNA) sequence alone. In this section, we will consider sequence similarity from the general perspective of polymer solubility and from the point of view of an immunoglobulin superfamily of structures.

A . Gross Immunoglobulin Structure It is of functional significance that immunoglobulins have a modular design (Hill et al., 1966; Singer and Doolittle, 1966; Edelman, 1970; Fig. 5). Both the light (25,000 Da) and the heavy chains (50,000 Da) are composed of several domains, each of which consists of approximately 110 amino acid residues. The antigen binding function is concentrated in the amino terminal, the so-called variable domains of both the light and heavy chains (Hilschmann and Craig, 1965; Titani et al., 1965). It has been demonstrated experimentally that the isolated variable domains can refold without changing the rest of the polypeptide chain (Hochman et al., 1973). Antibody modules share the same architectural motif as noncovalently formed domain dimers. The domains themselves are formed by two antiparallel P sheets closely packed face to face (Richardson, 1981; Lesk and Chothia, 1982; Novotny et al., 1983; see Section II1,C). The basic building blocks of immunoglobulin domains are therefore P-strand segments and reverse loops connecting these strands. The domains are linked together by rather extended “hinge” or “switch” peptides long enough to permit the movement of domains with respect to each other. Comparison of currently available X-ray structures of Fab fragments shows clearly that the “elbow” angle between the long axes of the VL-VH and CL-CHl dimeric modules can vary from essentially extended (180”) to quite sharp (100”). Flexibility of the hinge between the Fabn and the Fc is well documented, e.g., by the electron microscopic studies of Valentine and Green (1967) and the hydrodynamic studies of Tanford and co-workers (Noelken et al., 1965; Fig. 5). Some immunoglobulin subclasses (e.g., the mouse IgG2.J are more flexible than others (e.g., the relatively rigid mouse IgGl) and the polypeptide segments crucial to flexibility have been mapped by domain swap experiments (see Section IX,A) to the hinge and the CHI loop 131139 (Schneider et al., 1988). Contrast-matching, small-angle scattering of neutrons determined the mean antigen-antigen distance between the and IgGnb molecules as 11.7-12.4 nm, with a bivalent mouse IgC,, IgCZA, large variance (-4 nm, Sosnick et al., 1992). For all three subclasses, the scattering data could be fitted only with a distribution of distances rather

Fv

Fab

-45m-

FIG.5. Various models of a complete I@ molecule. (hj) a sketch of covalent structure showing the light (L) and heavy (H) chains, interchain disulfide bonds (SS), and approximate dimensions of the Fab and Fc fragments. Variable domains are hatched. (Middle)Model derived from hydrodynamic studies by Noelken et al. (1965).A and B chains refer to the H and L chains, respectively; fragments I and I1 are the Fab fragments, and fragment I11 is the Fc fragment. (Rzght)a-Carbon tracing of a complete I g C molecule (Harris et al., 1992). Light line, L chain; heavy line, H chain.

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than with a single distance. Thus, antibody molecules in solution sample a large selection of hinge and elbow angles at any given moment, a structural trait undoubtedly important for efficient antigen engagement. B. Polymer Solubility and Amino Acid Sequence Variability

The conformational states of a polymer in solution (random coil or folded, compact or extended) depend on a relative balance of polymerpolymer and polymer-solute interactions (Flory, 1969). The fact that in proteins many different sequences adopt the same compact fold strongly suggests that there is one gross (solubility)property of natural amino acids that overwhelmingly determines the structure of the folded state (Dill, 1990). Polypeptide chains that may have only 1 or 2 amino acids out of 10 in common, but conserve the sequence distribution of hydrophobic and hydrophilic residues, retain the same fold (Bashford et al., 1987), suggesting that the hydrophobicity pattern of an amino acid sequence is the most likely determinant of protein structure. The computer experiments of Chan and Dill (1990), enumerating the complete conformational spaces of two-dimensional polymers composed of two types of residues (black and white, hydrophobic and hydrophilic), reproduced many of the features of folded proteins, in particular the existence of unique compact structures attainable by different sequences, the families of related sequences, and the secondary structure patterns. It is often asked whether the native protein structure is the one of global free energy minimum, and whether kinetic aspects of protein folding are not equally important (Baker and Agard, 1994). Although no definitive answer is currently available, some recent results emphasize the importance of a thermodynamic minimum in the determination of native folds. Sippl (1990), Bryant and Lawrence (1991), Bowie et al. (1991), and others developed pseudo potentials that capture, in numerical form, important features of the known protein structures, e.g., the averages and distributions of pairwise residue-residue distances, solvent exposures of all 20 amino acids, distances (and implicitly, electrostatic interactions) of formally charged residues, and the character of the immediate neighborhood of side chains in various folds. Native amino acid sequences examined with these pseudo potentials virtually always show a distinct energy minimum associated with only one, the native, fold. Energies obtained with misfolded structures (i.e., fits of the sequence into alternative folds of other proteins) are distinctly less stable. Likewise, the computer folding experiments of Sali et al. (1994), with proteinlike simplified polymers on a threedimensional lattice, seemed to imply that the sole criterion for a fast folding step toward compact, nativelike structures (molten globules) was the existence of a deep global minimum in the free energy landscape.

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C. Immunoglobulin Superfamily

Lesk and Chothia (1982) were the first to define the core of immunoglobulin domains (VK,VA, Vy, CZ, Cyl, Cy2, Cy3) on the basis of leastsquares comparisons of available X-ray structures. Although the core of each of the domains consisted of about 35-36 homologous residues, forming two p sheets packed face to face, only 3 residues were common to all the domains: 2 cysteines that formed a disulfide bridge between the p sheets, and a tryptophan that packed against them (Fig. 6). The other interior residues tended to retain hydrophobic character but varied greatly in size. Williams and Barclay (1988), Harpaz and Chothia (1994), and others defined groups of amino acid sequences designated the immunoglobulin superfamily (IgSF). In the superfamily, sequence similarity ranges from a clear homology, virtually guaranteeing an identical fold (-4040% identical residues), to weak similarities (10-1 5%), and a putative three-dimensional structure for the more controversial members of the family was debated for some time. For example, a folding motif radically different from that of immunoglobulins was proposed for the CD2 antigen: the (ap fold of this molecule (Clayton et al., 1987) was seemingly favored by circular dichroism measurements showing a significant proportion of a helix in the CD2 extracellular domain(s), whereas Williams et al. (1987) argued CD2 similarity with immunglobulins on the basis of sparse, conserved sequence motifs. X-ray (Jones et al., 1992) and NMK studies (Driscoll et al., 1991, Withka et al., 1993) confirmed the presence of an immunoglobulin fold in the CD2 leukocyte antigen. Given the marginal sequence similarity of CD2 to immunoglobulins, elucidation of this structure constituted strong support for the concept of an immunoglobulin superfamily. It appears that, within the immunoglobulin family, the number of constituent p strands may vary but the general folding topology, i.e., the Greek key motif (Richardson, 1981), remains conserved. According to Harpaz and Chothia (1994), the current superfamily tree can be subdivided into sets, i.e., clusters of domains that are structurally more similar to each other than to a member of any other set. Sets are distinguished by the number ofp strands in the two individual sheets and their length (Fig. 6). An antiparallel p sandwich is one of the commonest protein folds observed, and Bork et al. (1994) used the computer program DALI to carry out a complete three-dimensional classification of the known P-sheeted structures. The common structural core of four p strands, B, C, E, and F, was found to be shared by nine distinct families. Subclass distinctions arose as additional /3 strands were appended to the core. Disulfide bridges were not necessarily invariant in number and location within the subclasses. The four major topological subtypes were described as (1) the c-type, i.e., classical seven-stranded, Ig constant-domain topology; (2) the s-type, a

FIG 6. Folding motifs of the immunoglobulin superfamily (Williams and Barclay, 1988; Harpaz and Chothia, 1994). (Top left) V domain fold (the VH domain of the McPC 603 Fab fragment) with two four-stranded /3 sheets. (Top rzght) C1 domain fold (the CI, domain of the McPC 603 Fab fragment), a p sandwich with a four-stranded and a three-stranded p sheet with the strand topology A-B-D-E and C-F-G. The core of the immunoglobulin domain (Lesk and Chothia, 1982), i.e., the intradomain disulfide and a tryptophan side chain packed against it, is also shown. (Bottom) C2 fold (the fourth extracellular domain of CD4) is essentially the C 1 fold with the D strand missing. See Bork el al. (1994) for a more encompassing definition of the immunoglobulin fold. [Graphics by Molscript (Kraulis, 1991).I

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seven-stranded “switched” type with strand topology E-B-A and G-F-C-C’; (3) the h-type, a hybrid between (1) and (2) where the strand C’/D is kinked and hydrogen-bonds to the strand C; and (4) the v-type, a nine-stranded type typified by variable domains. In this broad definition, the immunoglobulin fold comprised proteins as diverse as the growth hormone receptor domain 2, fibronectin, neuroglian domains 1 and 2, fungal galactose oxidase domain 3, the PapD protein domain 1, and cyclodextrin glycosyltransferase domain D. In all these folds, the core motif of four antiparallel 4, strands conserved its tight packing, strand curvature, and sheet-sheet angle.

ANATOMY OF ANTIBODY BINDING SITE IV. MOLECULAR Primary structures of different light and heavy chain variable domains and V H ) contain segments conspicuously variable both in length and amino acid composition (Wu and Kabat, 1970). There are three such segments in both VL and V H , and their positions within the domain sequences are homologous. It has been hypothesized that these hypervariable loops, designated L1, L2, L3, H1, H2, and H3, are responsible for antibody specificity and form the surface of the antigen combining site. Accordingly, they are also known as complementarity-determining regions (CDRs). X-ray crystallographic structures of many Fab fragments indeed confirmed that, by noncovalent association of the VL and VH domains, all six loops come into close contact and form a contiguous area on the surface of the VL-VIj dimer from which the binding site (the paratope in serological parlance) is constructed (Fig. 7). (VL

A . VL-VH Interface /3 Barrel Domains from different chains associate by noncovalent forces to form domain heterodimers. Each domain can be viewed as having two /3-sheet surfaces, and in the complete immunoglobulin molecule one of the /3 sheets faces the solvent, whereas the other mediates contact with the other domain of the pair. The principal difference between a VL-VH type of dimerization and constant-constant domain pairs lies in the fact that the /3 sheets involved in the domain interface are different in the two domain types (Edmundson et al., 1975). It has been noticed that /3 sheets are not flat, as originally suggested by Pauling and Corey (1951), but twisted (Chothia, 1973). The VL-VH contact /3 sheets are not only twisted but also strongly curved, giving an impression of being wrapped counterclockwise around an elliptical-hyperboloidal surface (Novotny and Haber, 1985). Thus, the VL-VH interface seems to

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give rise to a third p barrel formed by walls of the two interacting p barrels of the VL-VH domains. Structural fingerprints of this unique fold are (1) the two /3 bulges in the edge p strands G of the VL and VH domains, with sequences Phe-Gly-Gly-Gly and Trp-Gly-X-Gly, respectively; (2) an aromatic ring cluster of at least six Tyr/Phe residues forming a second layer of side-chain interactions in the VL-V, interface; and ( 3 ) a pair of Gln residues forming a pair of hydrogen bonds across the VL-VH interface (see Fig. 7; Novotny and Haber, 1985). The conserved features of antibody binding sites are worth recounting in greater detail. The VL-VH interface forms a close-packed, twisted p barrel characterized by cross-sectional dimensions 1.04 x 0.66 nm (10.4 x 6.6 A) and a top-to-bottom twist angle of 212". The geometry of the interface is preserved via the invariance of about 12 side chains, both inside the domain and on their surface. Buried polar residues form a conserved hydrogen-bonded network that has a similar topological connectivity in the two domain types. The two hydrogen bonds contributed by invariant Gln side chains extend across the interface and anchor the p sheets in their relative orientation. Invariant aromatic residues close-pack at the bottom of the binding site p barrel with their ring planes oriented perpendicularly in the characteristic herringbone packing mode. About 18 nm2 of protein surface is buried between the domains and about 3040% of this contact surface is contributed by the hypervariable regions (Novotny and Haber, 1985). The p sheets that form the interface have edge strands that are strongly coiled by /3 bulges. As a result, the edge strands fold back over their ownp sheet at two diagonally opposite corners. In the VL-VH dimer, residues from these edge strands form the central part of the interface, resulting in what we call three-layer packing; i.e., there is a third layer composed of side chains inserted between the two backbone side-chain layers that are usually in contact. This three-layer packing (Chothia et al., 1986) is different from the common aligned or orthogonal /3-sheet packing found in other P-sheeted proteins (Chothia and Janin, 1981, 1982). Conservation of the geometry of the VL-VH interface strongly contrasts with the variability of the CDR loops that provide connections between the /3 strands of the interface barrel. A schematic diagram of the binding region is shown in Fig. 7. It is interesting to note that one of the p strands in each of the domains corresponds to the J gene segment and is encoded separately from the rest of the variable-region gene (Early et al., 1980; Bernard and Gough, 1980; Newel1 et al., 1980). The region of the V geneJ gene junction maps into the L3 and H3 hypervariable loops, with additional amino acid sequence variablility generated by frame shifting the splice point between the two gene segments. In the heavy chain segments,

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there is a third short gene segment, D, that becomes inserted in the V-J junction (Early et al., 1980; Siebenlist et al., 1981); the D segment corresponds exactly to the H3 loop. The overall picture that emerged from structural analysis is that of a conserved structural scaffold or framework (the Vl,-VH interface p barrel) to which the various hypervariable regions can be attached. This structural concept has been supported by the loop swap experiment of Jones et al. (1986) whereby a transfer of antigenic specificities, via gene splicing and protein expression, was accomplished between two different antibody V region scaffolds (see Section IX,D). It is obvious that amino acid sequence variations in the hypervariable loops change the shape of the outer parts of the binding site. However, many examples of antibody specificity modulation can be mapped to amino acids participating in formation of the bottom of the binding site and inaccessible to solvent or antigen (Stevens et al., 1980; Horne et al., 1982). Side chains of residues Leu L96, Glu H35, and Asp H101, known to be important to the specificity of phosphorylcholine-binding myelomas (Rudikoffet al., 1981; Cook et al., 1982, Rudikoffet al., 1982; Chothia et al., 1992), are either totally or partially buried in the V,-VH interface. Other hypervariable residues, such as C-terminal parts of L1 and H1 and Nterminal parts of J gene segments, also form part of the VL-VH contact surface. The calculated residue free energy contributions to the stability of antibody-antigen complexes (AGrc,,due;see Section VI1,C) also emphasized the importance of the bottom part of the binding site. For example, Tulip et al. (1994) and Rauffer et al. (1994) found that, as a rule, the highly destabilizing mutations of the N9 neuraminidase-NC4 1 antibody complex occurred at rigid residues, just as protein folding is more destabilized by mutations in the core than by mutations at mobile residues (Alber et al., 1987). B. Binding Potential of Surface Cavities In virtually all known protein structures, binding sites have the shape of cavities or grooves. In antibodies, the antibody binding site is located at the generally concave interface between the light and heavy chain variable domains. In one case, a small hapten (phosphorylcholine) enters deeply into the interdomain pocket (Satow et al., 1986), in another case the principal residue of a protein antigen (glutamine-121 of hen egg white lysozyme) is buried in the interface while the rest of the antigen-antibody contact area is rather flat, if irregularly undulated ( h i t et al., 1986). It is natural for the curvature of binding site cavities to match that of the antigens: Binding sites that accommodate small ligands have high curvatures and appear as pockets; those directed toward large protein antigens

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have a low curvature, being more akin to valleys and grooves than to deep crevices (de la Paz et al., 1986). Why should the concave surface be favored as a specific combining site? Although no definitive answer is available at present, at least four good reasons can be cited. First, diffusion away from cavities is significantly slower than from flat surfaces or through the solvent. Primitive binding properties of simple concave organic molecules such as crown ethers and cavitands demonstrate this very clearly (Cram, 1983). Second, electrostatic fields are enhanced or focused in cavities, even though solvent quenches the field at other, flat or convex parts of the protein surface (Zauhar and Morgan, 1985; Klapper et al., 1986). Third, the hydrophobicity of a surface is a function of its curvature relative to the size and curvature of a water molecule, and concave surfaces are more hydrophobic than flat or convex surfaces (Sharp et al., 1991; Nicholls et al., 1991). Fourth, a hydrodynamic drag that develops at concave sites as a ligand molecule approaches may give rise to a a steering torque that forces the ligand into the pocket. The magnitude of this torque force is estimated to be significant, even larger than the electrostatic torque (Brune and Kim, 1994). The dielectric enhancement of an electrostatic field at cavities is illustrated in Fig. 3A. There the negative field generated by a pair of carboxyl groups embedded in a low-dielectric ( E =2) protein (with no other charges present) is compared to that generated by the same groups in water (i.e., a dielectric constant continuum of 80). The low dielectric of the protein not only allows the field to extend into a larger region of space but also modifies the field according to the shape of the dielectric boundary. The field enhancement inside the binding site cavity is striking (Novotny and Sharp, 1992). Computer simulations of antigen diffusion toward the antibody HyHEL-5 (Kozack and Subramaniam, 1993) suggested that the electrostatic field generated by charged amino acids at the binding site increases reaction rates, and effectively steers the antigen molecule into the site. The precise matching of charged groups with charged groups of the opposite sign is an example of chemical complementarity between antibody and antigen which, in addition to shape complementarity, determines the specificity of interaction. Complex specificity imposed by this charge distribution can, however, be achieved only by paying a price in free energy of desolvation which decreases complex stability (see Section VI1,B). C. Side-Chain Compositional Bias

It has been noted that antigen combining sites of antibodies have an unusual amino acid composition (Padlan, 1990). There is a statistically significant preference for aromatic rings and dipolar side chains, in partic-

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ular Tyr and Asn. A similar side-chain bias emerges from empirical free energy calculations that make it possible to rank, in a semiquantitative manner, the combining site residues according to their binding signifiNovotny et al. 1989). cance (AGres,due, Is the side-chain bias seen in antibody combining sites shared by recognition sites of other proteins? A comparison with enzymes (Krystek et al., 1993) reveals substrate binding sites of neutral proteases populated by amino acids very different from those of antibody binding sites: small, rigid side chains that incur no conformational-entropic penalty on complex formation (Pro, Ala, Cys) or Gly, which has no side chain. Hence enzymes and their inhibitors on the one hand, and antibodies and their antigens on the other hand, employ different strategies for harnessing the free energy of binding in their respective complexes. Neutral proteases bind uncharged substrate molecules, and the nonentropic side chains in their binding sites (1) serve a better purpose than charged and dipolar amino acids, and (2) contribute favorably to binding energies by minimizing the stiff conformational entropy penalty. By analogy, the aromaticdipolar residue bias in antibody combining sites is likely to reflect the nature of antigenic surfaces. The majority of antigenic epitopes consist of loops where charged and dipolar amino acids are very common (Section VII). It seems that in the antibody combining sites the best binding surfaces are constructed with formally charged side chains carrying charges opposite those displayed by the antigens. Indeed, charge matching is frequently seen in antigen-antibody complexes, but it may be difficult to generate a perfect charge-charge match to sufficiently stabilize the complex. Further, (free) energy needed for charge desolvation on complex formation represents a large energetic penalty, so large that it may actually destabilize the complex (Section IV,D). From these points of view, aromatic rings stabilizing buried charges via “aromatic hydrogen bonds,” i.e., charge-ring n electron interactions (Levitt and Perutz, 1988), may represent a good alternative to charge neutralization and burial. Dipolar (amide) side chains represent, next to the formally charged and aromatic residues, another possible tool of charge neutralization. D. Electrostatic Perspective

Novotny and Sharp (1992) analyzed electrostatic fields generated by antibodies and their antigens, and discussed their importance in binding. For convenience, their conclusions are briefly summarized here. (1) The calculated field contours corresponded closely to the distribution of formally charged side chains on the surface. (2) By and large, the sign of the field at the binding site was found to be opposite that of the hapten. For dipolar (zwitterionic) molecules, the field dipole helped to

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orient the ligand. Binding sites to neutral molecules may have measurable fields (menadione, galactan), or may be neutral (digoxin). The fields did not extend very far (i.e., beyond -4A) into the solvent. Outside the binding site region, the electrostatic potentials were complex and seemingly uncorrelated with the antigen binding. (3) Although there were local regions of electrostatic complementarity for large antigens, absolute complementarity was not a prerequisite for complex formation (e.g., D1.3lysozyme). (4) Fields at the 4-4-20 binding site specific for fluorescein suggested an electrostatically guided, lateral, two-dimensional diffusion of the ligand along the antibody surface into the site. ( 5 ) The HyHEL-5 and HyHEL- 10 antibodies against lysozyme had large negative fields complementing large positive fields of the antigen. In HyHEL-10, side chains that did not contact the antigen acted through space to augment the field and increase antibody affinity for the antigen. V. INSEARCH OF EFFECTOR SITES An antibody is a dual-purpose molecule: The antigen binding site allows for recognition of a virtually unlimited range of antigenic structures, and the constant domains mediate interactions with molecules belonging to the effector systems participating in antigen elimination. The y chain CH2 domain in particular plays an important role by engaging the Clq component of complement. The triggering event in the classical complement pathway is the binding of the first component of complement, C 1, to the Fc region of immunoglobulins aggregated in immune complexes. The structure of Clq, proposed by Reid and Porter (1975), has the appearance of a bunch of tulips: 18 chains, each about 200 amino acid residues in length, are linked in threes in the base and stalk regions to form collagen-like triple helices. Each of the six superhelices terminates with a globular head region thought to contain the Fc binding site. Apparently, the single Fc binding sites are of relatively low affinity ( K s 100-1000 M P ) and only the aggregation of several Fc fragments on immune complexes affects tight C l q binding due to multivalency mediated by the six C l q heads. Identification of the C l q binding site on IgG antibodies represents an early example of successful computer-aided structural analysis.

-

A. C l q Banding Site on Fc Fragment Burton et al. (1980) argued that the residues of the CH2 domain involved in interaction with C l q should fulfil two criteria. First, they should be accessible for C l q binding, that is, not buried in the interior of the

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domain. Second, they should be highly conserved in those immunoglobulin molecules that bind Clq; this followed from the observation of crossspecies reactivity of C l q and IgG antibodies. Starting with the crystallographic structure of the Fc fragment (Deisenhofer, 1981), residues of the CH2 domain in contact with solvent were identified using the Lee and Richards (197 1) algorithm and a water-sized probe (radius 1.4 A). Of the 104 residues of the cH2 domain, 72 were found to be accessible to water. An inspection of contiguous, solventexposed hydrophobic patches identified 27 residues clustered into four large patches (> 100 Az),and 8 other residues found in two small patches or as isolated side chains. The location of three of the large patches made it unlikely that they were involved in C 1 q binding. Analysis of interspecies residue conservation then helped to eliminate all the patches but one. The sequence conservation analysis employed human and mouse myeloma proteins, and rabbit and guinea pig heavy chains, some of which did and some of which did not activate complement. Some invariant positions could be readily eliminated from being involved in Clq binding by being buried, covered with the carbohydrate, or affecting sugar attachment. Of the remaining positions, the invariance of some could be understood on structural grounds without invoking functional significance. All these considerations led to emergence of the continuous residues on the C-F-G /?-sheet face as a potential binding region composed of exposed, highly conserved, and mostly charged (five Lys, two Glu) residues. These residues were proposed to form the C l q binding site (Fig. 8). In 1988, Duncan and Winter systematically altered surface residues in the mouse IgG2, isotype and localized the binding site for C l q to essentially three side chains, Glu-318, Lys-320, and Lys-322, contained within the originally proposed seven residues of the CH2 C-F-G/?-sheet face. B. Fc Receptor Binding Sites and Rheumatoid Factor-Reactive Sates

The solvent accessibility-sequence conservation argument previously outlined was also used by Woof et al. (1986) to propose location of the Fcy receptor binding site to the hinge-link region of the CH2 domain (Woof FIL 8. Effector sites of the Fc fragment. (To$ lefl) Fc fragment (Deisenhofer, 1981). p Strands are shown as ribbons, and the oligosaccharide at the c H 2 / c H 2 interface as ball-andstick. T h e p hairpin predicted by Burton et nl. (1980) to be the C l q binding site is shown in heavy lines. (To$ right) Detail of the C"2 domain. Residues mutated in the F /3 strand by Duncan and Winter (1988). are also shown. (Lower left) Fc fragment with the residue Pro-238 highlighted. The Fc receptor binding site was localized to the polypeptide N-proximal to residue 238. This peptide, however, is not visible in the crystallographic structure of the human Fc fragment. (Lower rzght) Detail of the CH2 domain with the residue Pro-238 highlighted. [Graphics by Molscript (Kraulis, 1991).]

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\/

\\

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et al., 1986; Burton, 1985). Duncan et al. (1988) engineered a single amino acid change in a mouse IgGeb antibody, E235L, which enabled the antibody to bind the high-affinity FcyRI receptor with a 100-fold improvement in affinity. Finally, Chappel et al. (1991), through the use of recombinant IgG1/IgGphybrids and site-directed mutagenesis, localized the essential receptor binding activity to the CH2 sequence Glu-Leu-Leu-Gly-Gly-Pro (residues 233-238) (Fig. 8). A rather complex effector system is that of immunoglobulin E and its various cellular receptors: the high-affinity FceRI, the low-affinity FceRII (also known as CD23), FceRIII, and complement receptor 2 (CR2, also known as CD21; see Sutton and Gould, 1993). The three-dimensional structure of IgE is unknown, but the amino acid sequence of the E chain suggests an overall structure similar to that of other classes of antibodies, in particular, a p chain with an additional constant domain in place of the hinge region. The two C-terminal domains of IgE were computermodeled on the basis of the crystallographic structure of the human IgG Fc fragment (Padlan and Davies, 1986). Highlights of the IgE model were (1) a disulfide bridge linking CLto CE1, and (2) two SS bridges linking the two Ce2 domains of the pseudo symmetry-related heavy chains. The predicted fold of the C Eand ~ C Edomains ~ assumed Asn-394-linked oligosaccharide chains to lie in between the Ce3 domains. With the use of recombinant peptides and domain exchange techniques, a segment of E chain sequence at the N terminus of the Ce3 domain (residues 330-335 of the E sequence) has been implicated in F e R I receptor binding. In order to localize rheumatoid factor (RF)-reactivesites on human IgG molecules, Peterson et al. (1995) used overlapping heptapeptides derived from the C H domain ~ sequence as competitors in RF-binding assays. To design the heptapeptides, they relied on the calculated, large-probe accessible “antigenic epitopes” postulated in the IgG CH3domain by Novotny et al. (1986a; see Section VIILA). About 10 residues were identified as critical for rheumatoid factor binding, clustered in the two segments between amino acids 343-354 and 401-439 of the human H chain sequence. C. Conserved Elbow Joint in Fab Fragments

Although not an effector site per se, the elbow joint described by Lesk and Chothia (1988) is an intriguing molecular device that is localized in a small region of the antibody molecule and mediates segmental domain flexibility (see Section 111,A). Based on computer graphics inspection of several Fab fragments with different elbow angles, Lesk and Chothia

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(1988) concluded that movement of the VL-VH dimer relative to the CLCHI dimer involved interactions of three VH and two CHI residues that formed the molecular equivalent of a ball-and-socket joint, plus a few additional contacts that varied from structure to structure. Residues 11, 110, and 112 in VH packed against residues 149 and 150 in CHI, and the three VH residues belonging to the P-sheet framework contacted the two adjacent, turn-located CHI residues. The extent of the shift between members of any pair of Fab structures was estimated by superposing the CHI residues in different Fab fragments and calculating the mean position differences of the VHresidues. In one case, the VHresidues were displaced by a translation of 4.4 A and a rotation of 36". Inspection of space-filling models showed that the relative movement of the residues resembled that occurring in a ball-and-socketjoint, with the CHI residues forming the ball and the VHP-sheetresidues forming the socket (Fig. 9). VI. PROTOCOLS FOR THREE-DIMENSIONAL MODELING OF BINDING SITES Basic information about the nature and dimensions of antigen combining sites was derived in the precomputer age by solution chemistry and serology. Combining sites were probed by series of chemically similar haptens in the early works of Landsteiner (1962), Pressman and Grossberg (1968), Karush (1962), Kabat (1970), Haber (Haber et al., 1967, 1976), and Schechter (1971), to name but a few. The approximate dimensions of binding sites were such as to accommodate about six monosaccharide units or about three or four peptide units. In favorable cases, ingenious resonance transfer and chemical modification studies provided more detailed atom-atom distance information (e.g., Rosenstein and Richards, 1976). A. N M R Spectroscopy Combined with Computer Model Building In chemistry, it is common to derive structural formulas of compounds from spectroscopic methods such as nuclear magnetic resonance, spin resonance, circular dichroism, and infrared. The same methodology has been applied to proteins, and particularly to antibodies. If an atomic detail-level model is sought, the complexity of the task also calls for the use of computational methods. Some of the first atomic details of antibodyligand interactions emerged from a combination of NMR spectroscopy and computer-aided model building in the work of Dwek's group (Dwek et al., 1975, 1976; Sutton et al., 1977; Willan et al., 1977; Dower et al., 1977; Wain-Hobson et al., 1977) These studies paved the way for similar analyses

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FIG.9. Ball-and-socketjoint at the elbow of the Fah fragment McPC 605. VH domain is at the upper left, arid CFI1 domain is at the lower right. The VH side chains 1 1, 110, and 1 12 are shown in sp;ice-filling representation (heavy lines), and the C k ~ lspace-filling side chains 149 and 150 are shown as dashed lines. These side chains form a mechanical equivalent of a ball-and-socketjoint, facilitating Fah elbow movements. [Graphics by Molscript (Kraulis, 1991).]

on anti-spin label monoclonal antibodies (Anglister et al., 1984, 1987; Levy et al., 1989; Zilber et al., 1990) and on the anti-2-phenyloxazolone Fv fragments (McManus and Riechmann 1991). Dwek and co-workers used then state-of-the-art magnets (270 MHz) and various spin-labeled haptens to deduce that the combining site of the MoPC 315 myeloma protein for dinitrophenyl was a (hydrophobic) cleft with overall dimensions 11 x 9 x 6 A. The use of lanthanide ions allowed

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the exact equilibrium binding constants for dinitrophenyl haptens to be measured (- 1 p M ) . Dinitrophenyl was buried in the site to about 11 A depth, and interacted closely with the A r g side-chain VL 95 and an “aromatic box” of residues Trp L93, Phe H34, and Tyr L34. Asn L36 contributed hydrogen bonds to the nitro groups of the hapten. Reference to the computer-built model of Padlan et al. (1977) allowed the assignment of three nearby histidine residues, H 102, L97, and L44. Eventually, inclusion of chemical modification data (Dwek et al., 1977) and NMR spectroscopy on selectively nitrated tyrosine residues (Leatherbarrow et al., 1982) led to a refined model that accounted for the binding experimental data from a large range of cross-reacting haptens (Fig. 10). B. General Stratagems

Computer-aided analyses of antibody combining sites (Section IV,A) formulated the concept of a conserved framework with hypervariable loops implanted on it. Since 1986, it has become possible, via gene cloning (Jones et al., 1986), to create chimeric proteins with CDR loops grafted onto foreign frameworks that carry antigen-binding capacity essentially indistinguishable from that of the parent antibody. If indeed it is possible to manipulate antigenic specificities at will, then accurate modeling of structures of arbitrary loops will become an important practical goal. To derive the structure of an antigen binding site from its amino acid sequence, one is faced with the problems of (1) finding the most appropriate three-dimensional Fv framework (the template) among the existing X-ray crystallographic structures, and (2) replacing the six CDR loops of the crystal structure with loops in conformations corresponding to those of the amino acid sequences at hand. A successful loop swap experiment requires (a) a modeling protocol generating natural loop conformations from amino acid sequences, (b) an exact definition of the boundaries between the framework and the N and C termini of each loop, (c) knowledge of the best possible succession in which the loops are built back onto the framework, and (d) identification of any framework residue that influences CDR conformations. These critical residues must be carried over from the template to the framework of the newly constructed antibody. Different approaches have been developed to accomplish these tasks. C. Knowledge-Based Methods

Knowledge-based (homology) modeling methods (see, e.g., Greer, 1991; Bajorath et al., 1993; Bajorath and Aruffo, 1994; and Sali, 1995, for concise overviews) allow one to construct an approximate three-dimensional

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H!

c

66

L3 . n

FIG. 10. Three-dimensional structure of the MOPC 315 antigen binding site, as derived by NMR spectroscopy and computer modeling (see Section VI,A for details). (Reproduced with permission from Dwek et al., 1977. Nature 266, 31-37. 0 1977 Macmillan Magazines Ltd.)

model of a protein from its amino acid sequence, and atomic coordinates of a similar protein structure. Jones and Thirup (1986), in their analysis of protein structures from the Brookhaven Protein Data Bank, pointed out that loops with similar N- and C-terminal end points and identical length

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often had similar conformations. The conjecture that CDR loops with identical length and different sequences may adopt similar conformations formed the basis of early antibody modeling protocols (Kabat and Wu, 1972; Padlan et al., 1977; Feldmann et al., 1984; de la Paz et al., 1986; Roberts et al., 1987; Smith-Gill et al., 1987). Independently, structural classification of loops in proteins (Sibanda and Thornton, 1985; Ring et al., 1992) also facilitated modeling, particularly of the P-hairpin loops L2, L3, H2, and H3. This type of structure-based modeling was automated by Levitt (1992) with his segment matching algorithm: Given a loop sequence, the Protein Data Bank can be searched for short, homologous backbone fragments (e.g., tripeptides) which are then assembled and computationally refined into a new combining site model. A milestone event in knowledge-based modeling was introduction of the canonical CDR structure concept by Chothia, Lesk, and colleagues (Chothia and Lesk, 1987; Chothia et al., 1989). They found that five of the six CDR loops (all except the H3) adopted only a limited repertoire of backbone conformations that were readily predictable from the sequence. These canonical conformations were determined by specific packing, hydrogen bonding interactions, and stereochemical constraints of only a few key residues (structural determinants). Examples of canonical motifs are presented in Fig. 11. In its most general form, the canonical structure concept assumes that (1) sequence variation at other than canonical positions is irrelevant for loop conformations, (2) canonical loop conformations are essentially independent of loop-loop interactions, and (3) only a limited number of canonical motifs exist and these are well represented in the database of currently known antibody crystal structures. Every one of these assumptions may fail in isolated practical instances. In their definition of the five canonical CDR loops, Chothia and Lesk (1987) and Chothia et al. (1989) described the CDR loops as overlapping, but not identical to, the hypervariable regions of Kabat et al. (1977).When a large number of antibodies were scanned for the presence of canonical sequence motifs in their CDR loops and frameworks, 50%-95% (depending on the particular loop) of murine and human sequences were found to contain one. Chothia et al. (1992) also showed that the vast majority of VH domains in antibodies display one of the seven different canonical H 1 and H2 conformations. The canonical repertoire of CDR loop Ll was enriched by Wu and Cygler (1993) who analyzed the crystal structure of a murine antibody with a 1 light chain (Cygler et al., 1991). Canonical features are also thought to determine conformations of loops in proteins other than immunoglobulins (Tramontano et al., 1989; Tramontano and Lesk, 1992). Structural determinants of canonical CDR loops include residues in the framework regions. The side chain of the heavy chain residue 71, in the

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@-strandE, determines the conformation of the CDR loop H2 (Tramontano et al., 1990). A critical role for other framework residues in preserving productive antibody-antigen interactions was demonstrated in the mutagenesis experiments of Foote and Winter (1992). 1. Results: Canonical Loop Modeling of Binding Sites The canonical loop concept has met with success in structure prediction of several antibody binding sites. Chothia and colleagues predicted all six CDR loop conformations in the lysozyme-binding antibody D1.3 (Chothia et al., 1986) and five canonical loop conformations in four other antibodies (HyHEL-5, HyHEL-10, NC41, and NC10) before their crystal structures were known (Chothia et al., 1989). In the early D1.3 prediction conformations of four CDR loops (Ll, L2, H2, and H3) were accurately described with backbone rms deviations (including @ carbons) 0.5-0.9 A from the X-ray structure. Subsequently, backbones of 14 out of 19 canonical loops were predicted with an accuracy of better than 1.0 A rms (but in no case worse than 1.4 A rms). A level of accuracy of -0.7 A was achieved by Eigenbrot et al., (1993) and Essen and Skerra (1994) in single canonical loop predictions. Several papers reported the construction of models for which crystallographic structures do not exist and whose accuracy cannot be evaluated yet. The study of Roberts et al. (1994), on model building of the catalytic (esterolytic-amidolytic) NPN43C9 antibody included a careful selection of the framework based on an inspection of various VL-V, interfaces. The model correctly predicted previously unknown binding and catalytic hnctions of the Arg residue L96, and suggested a mechanism by which the antibody stabilized high-energy transition states during catalysis. Chothia et al. (1989) observed that even correctly predicted CDR loops may be spatially misplaced (rigid-body shifts) by up to 3 A relative to their crystallographic counterparts. Such effects are critical for accurate modeling of antibody binding sites, as they may substantially alter the shapes of binding sites. In this sense, assessment of the accuracy achieved in individual CDR loop predictions may be misleading. The often reported backbone, or even all-atom rms values obtained by direct least-squares fit of isolated individual loops, do not take into account the rigid-body misplacements of whole loops, and the actual accuracy of the complete binding site model may be lower (Bajorath et al., 1995). As the database of high quality crystal structures has grown, some canonical motifs have become well established. In other cases (e.g., the H2 loop), the ensemble of observed and classified canonical conformations may still be incomplete. Unusually long L1 loops, whose tip portions are not very well defined conformationally and probably sample several different backbone configurations, also may not be accurately predictable. Fur-

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thermore, an assignment of sequence motifs to canonical conformations may remain ambiguous in a few instances, e.g., when conformationally “odd” amino acids, such as multiple prolines or glycines, are found in antibody sequences. In general, however, the canonical structure concept provided the model building of combining sites with an excellent tool. For the many newly determined antibody sequences it is highly likely to find, in the Brookhaven Protein Data Bank, templates (frameworks) with very high sequence similarity; more than 80% identity is not unusual. Such templates often include one or more CDR loops of the same canonical class as the loops to be modeled. In this case loop splicing is not necessary and the template loop can be directly copied into the model. At the current rate of Brookhaven Data Bank growth (close to a new antibody X-ray structure every month), and the number of antibody Fab structures currently available (more than 50), knowledge-based modeling will only become easier and even more reliable. Automatic loop search procedures, such as the distance matrix-based methods of Jones and Thirup (1986)will help to identify loops with sequences identical, or nearly identical, to those of loops with unknown conformations. Fast fetching algorithms for structure comparison (Holm and Sander, 1994) and relational databases (Bryant, 1989) will allow efficient handling of the rapidly growing numbers of antibody structures and sequences. 2. Framework-Loop Relationship

Having determined canonical backbone motifs of selected CDR loops, one is faced with remaining problems such as (1) how to model conformations of noncanonical loops, (2) how to place side chains on CDR loop backbones, and (3) how to combine CDR loops with the best framework model. Routinely, it is assumed that side-chain conformations of homologous residues are similar (Summers et al., 1987). Thus, the side-chain conformations most frequently observed at the corresponding positions in other CDR loops of the same canonical conformation are selected in the model. Libraries of preferred side-chain rotamer conformations assembled from databases can also be consulted (Ponder and Richards, 1987). The generality of these procedures, however, has frequently been questioned (see, e.g., Schrauber et al., 1993). As the best way of splicing loops onto the framework, Tramontano and Lesk (1992) suggested placing loop backbones on the end points of the framework after a weighted, least-squares superposition of four framework residues N- and C-terminal to the loop. This suggestion, however, does not eliminate differences in framework structures, and in the resulting rigid-body shifts in relative loop positions. An example will illustrate this point. Seven crystal structures of antibody combining sites, refined to

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better than 2.0 A resolution, were superimposed with average rms shifts of 0.4-0.6 A on the backbones, a very good agreement indeed (see Fig. 12 and Table I1 for details). In order to assess how well the individual loops of the same canonical class agreed in the context of the frameworks, two different rms deviations were calculated (Bajorath et al., 1995). The conventional value (rms) was calculated after direct least-squares superposition of only the loop backbone atoms and directly reflects the differences in the backbone conformation of the loops. The other value, called here spatial rms (s-rms), was calculated for the loops afier superposition ofthe conserued Fv framework segments as described in Table 11. The s-rms values reflected not only the conformational differences in various loops, but also their different orientations with respect to the conserved framework (the “takeoff’ angles resulting in rigid-body shifts). A comparison of two CDR loops that have a similar conformation but are spatially displaced via rigid-body shifts would therefore result in a low rms value and a high s-rms value. As an example, we limited our comparison to the H1 and L2 loops (Fig. 12), all of which are of the same respective canonical structure type. The average backbone rms deviation for the pairwise H 1 loop comparisons (seven residues long; see Table 11) was 0.5 A, however, the s-rms deviations were much greater, 1.6 A. For the L2 loop, the average backbone rms shift of the seven L2 loops (three residues long) was 0.2 A, but their average s-rms deviation was 1.2 A. These observations are generally valid for all canonical CDR loops (Novotny and Bajorath, unpublished observations). That is, isolated loop conformations always superpose much better than loops in the context of their individual frameworks. For example, three of the seven L3 loops shared canonical structure type 3, and the backbone conformations of these loops were remarkably similar. In contrast, their relative spatial positions were quite different (see Fig. 12). Examination of the superimposed p strands supporting the CDR loops shows that the positions of the framework termini differ and that their average painvise difference is typically larger than 1.0 A. The central strands of the p sheets essentially diverge at the very ends but edge strands (such as C”) show greater structural differences throughout. To a large extent, CDR loop displacements correspond to differences at the CDRframeworkjunctions. The definition of the framework-loop junctions is, to some extent, subjective and arbitrary and a judicious selection of loop splice points may have a major impact on the quality of the final model. For example, the CDR loop H2 of the 5539 Fab fragment, when implanted on the HIL framework, would result in an s-rms deviation of about 2.5 A, despite the fact that the H2 loop conformations in 5539 and HIL are essentially identical (0.3 A rms).

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COMPUTATIONAL BIOCHEMISTRY OF ANTIBODIES

'TABLE 11

Painvise ms Comparisons of Seven H I CDR Loops of Same Canonical Type Root-mean-square deviation Fv Fragments superimposed" 4-4-20 to KOL H52 to KOL D1.3 to KOL D1.3 to 5539 D1.3 to 4-4-20 H52 to 4-4-20 H52 to Dl .3 H52 to 5539 KOL toJ539 Se155-4 to 4-4-20 HIL to D1.3 5539 to 4-4-20 HIL to KOL HIL to 5539 Sel55-4 to KOL Se155-4 to HIL 4-4-20 to HIL H52 to HIL Se155-4 to D1.3 Se155-4 to H52 Se155-4 to 5539

rmsb

s-rms'

0.6 0.4 0.9 0.9 1.2 0.6 0.8 0.5 0.2 0.7 0.8 0.6 0.2 0.3 0.4 0.3 0.6 0.3 0.6 0.3 0.5

0.9

(4

(4

0.8

1.4 1.4 1.7 1.1 1.4 1.2 1.2 1.9 2.0 1.8 1.4 1.6 1.8 1.a

2.1 1.8 2.3 2.1 2.7

' 4-4-20, Mouse monoclonal antifluorescein Fah (Herron et al., 1989), PDB code 4FAB; KOL, human myeloma Fah (Marquart et al. 1980), PDB code 21G2; D1.3, mouse mnooclonal antilysozyme Fah (Fischmann et al., 1991), PDB code 1 FDL; 5539, mouse monoclonal antigalactan Fah (Suh etal., 1986), PDB code 2FBJ; H52, humanized mouse myeloma antiCD18 Fv (Eigenbrot et al., 1994), PDB code IFGV; HIL, human Fab (Saul and Poljak, to be published) PDB code SFAB; Se155-4, mouse monoclonal antioligosaccharide Fah (Cygler et al., 1991), PDB code 1MFE. To obtain the rms values listed, all the atoms of the two H I loop backbones (residues H26-H32) were least-squares superimposed. ' To obtain the s r m s values, backbone atoms of the conserved VL-VH interface-forming residues (H36-H40, H94-H96, L35-38, and L86-88; see Novotny and Sharp, 1992) in each of the two Fv fragments were least-squares superimposed. The operation brought the complete antigen combining site regions (i.e., parts of the inner /3 barrel and all the CDR loops) of the two Fv fragments into equivalent positions. Thus superimposed, the root-mean-square deviation between the pair of the H1 loop backbones was calculated as the s-rms value.

185

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Changes in the spatial relation of CDR loops may provide, in addition to sequence and length variability, a means of increasing the repertoire of shapes available for antigen recognition. From this point of view, antibody sequences must include determinants not only of CDR loop conformation but also of CDR loop position. The canonical CDR loop library consists of an overlapping and, in general, smaller set of residues than that for hypervariable regions (Kabat et al., 1977). Backbone segments, which on the basis of canonical loop definitions are classified as frameworks, include sequence variability which may modulate interactions among adjacent loops and may account for some or all of the effectsjust described. One way of addressing this framework bias in practical modeling may be to select frameworks not only on the basis of overall sequence similarity (currently the most common procedure) but also on the basis of conserved patterns of residues in the regions adjacent to the CDR loops (see Section IX,D). D. Conformational Searches and Monte Carlo Methods

Protein conformation is determined by values of backbone and sidechain torsional angles @ (C-N-Ca-C),11, (N-Ca-C-N), and x (N-Cu-C/?-Cy, Ca-C/?-Cy-CG,and so on). Three-dimensional modeling involves finding specific values for all these torsional degrees of freedom. A particularly promising approach is therefore to use automatic computer algorithms that uniformly sample the complete conformational space of a polypeptide chain segment (Bruccoleri and Karplus, 1987; Shih et al., 1985; Snow and Amzel, 1986; Moult and James, 1986; Fine et al., 1986; Amzel, 1992). Ideally, all the backbone and side-chain conformations compatible with the rest of the protein structure can be generated. The lowest energy conformation should correspond to the naturally occurring one. In practice, technical problems associated with an exhaustive sampling of conformational space restrict searches to short polypeptide segments only. The CONGEN program (Bruccoleri and Karplus, 1987) represents an efficient realization of this modeling stratagem. Given an accurate Gibbs function and a short loop sequence, reliable structural prediction using CONGEN appears to be remarkably easy: Generate all the stereochemically acceptable structures of the loop, calculate their energies, and take the one with the lowest energy. In practice, however, two major problems must be overcome first: Loops are not always short, and accurate energy functions do not yet exist. In the case of antibodies, most loops are sufficiently short that a complete search is feasible given modern computer workstations. The second problem presents a more fundamental hurdle (see Section VI1,C).

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In its most general form, a conformational search is a set of nested iterations of the degrees of freedom (e.g., torsional angle values on a preselected grid, say, 30") in the system. In CONGEN, the generation of backbone coordinates depends heavily on the Go and Scheraga (1970) chain closure algorithm as modified by Bruccoleri and Karplus (1986). Given stereochemical parameters for construction of the polymer and six adjustable torsion angles between the two fixed end points, the algorithm calculates values for the six torsional angles needed to perfectly connect the (rigid-angle) polymer from one end point to another. T o generate conformations of loops with more than three residues, the backbone torsion angles of all but three residues are systematically sampled, and the Go and Scheraga procedure is used to close the backbone. Bruccoleri and Karplus (1986) allowed for small variations in the peptide bond angles which greatly improved the efficiency of chain closure. CONGEN sampling of backbone torsion angles is done with the aid of a conformational energy map. A set of maps giving energies as a function of discrete values of q5, q, and o corresponding to grids of 60" down to 5" has been precalculated. Typically, a 30" sampling is sufficent to include the natural torsion and to guarantee good results. The backbone can be searched either forward from the N terminus or backward from the C terminus, and both cis and trans peptide bond angles can be sampled. After the backbone has been constructed, side chains can be placed by a variety of methods, each allowing complete freedom in sampling the complete side-chain conformational space. In 1987 a seven- to eight-residue loop was often too long to be searched exhaustively, particularly if it contained amino acids with many torsional degrees of freedom (glycine backbones, lysine side chains). With present-day computers, and their increasing speed of computation, it has become possible to search loops with 10 or more amino acids exhaustively, and the limit is steadily increasing (Table 111). Random searches of backbone conformations is an alternative way of producing a library of possible CDR loop structures. The random tweak method of Fine et al. (1986) consists of Monte Carlo simulation in loop torsion angles followed by energetic minimization of the randomly generated starting conformations. Random torsion angles are forced to satisfy geometric constraints of the framework and splice into the remainder of the molecule. The constraints are applied as a set of Lagrange multipliers in a computationally fast iteration scheme [one inversion of a 4 x 4 matrix is required per iteration (Bajorath and Fine, 1992)l. The tweak method has been implemented in two programs, Levinthal's PAKGRAF and the HOMOLOGY/INSIGHT program commercially available from Molecular Simulations Inc. (San Diego, CA). Higo et al., 1992 (see also Gibrat et al.,

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TABLE 111

Computer Workstation Speed in CONGEN Conformational Searches CPU speed Year

Computer

1987 1990 1994 1994 1995

MicroVaxII" IRIS 4D/706 ONYX, 1 processor6 ONYX, 10 processors" CHALLENGE, 10 processors"

'I

MHz 1.5 16 150 -1300 -2600

Search time per residue'

nsec

(set)

667 62 6.7 -0.8 -0.4

200 10 1 0.1 0.05

Digital Equipment Corporation, Maynard, MA.

' Silicon Graphics, Inc., Mountain View, CA.

' Averages obtained from constructions of six CKD loops of various lengths and amino acid sequences; see e.g., Bruccoleri et al. (1988), Novotny et al. 1991), Bassolino-Klimas et al. 1992).

1992) described a different Monte Carlo protocol for CDR loop modeling. It combines the Metropolis et al. (1953) search algorithm, and weights applied to potential energy terms (forcing potentials), in a simulated annealing scheme (Kirkpatrick et al., 1953) to generate loops that satisfy the framework constraints. In order to identify the native conformation in the (often vast) number of all those that are stereochemically possible (including side-chain rotamers), one has to rely on a free energy criterion. Indeed, it is the free energy of the complete system, rather than its potential energy in vacuo, that determines the native fold. In the past, the calculated in vacua potential energies (Brooks et al., 1983) were unable to distinguish between correctly and incorrectly folded protein structures, whereas modified potentials with nonbonded interactions including solvent-exposed (surfacedependent) terms could discriminate between the two types of structures (Novotny et al., 1984). An approximate representation of solvent effects was incorporated into the loop selection algorithm by Bruccoleri et al. (1988). The generated loops were first ranked by the in vacuo potential, and then solvent-accessible surfaces of the loops in the lowest potential energy window of 1 kcal (4.2 kJ) were calculated; the loop with the least accessible surface was then selected. Alternative approximations to free energy developed and reported over time were (1) a complete exclusion of intramolecular van der Waals interactions from the potential (Martin et al., 1989), and (2) ranking on the basis of the electrostatic energy obtained from a finite difference solution of the Poisson-Boltzmann equation (including the solvation term), and

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189

atomic solvation parameters (Smith and Honig, 1994). None has been completely satisfactory. If indeed loop-loop contacts are important for correct binding site structure prediction, then both the knowledge-based methods and automatic computer algorithms will eventually need a robust free energy functional to gauge the nativeness of the completed assemblies of all six loops. In CONGEN construction, the lowest free energy partial solutions may continuously be selected as the buildup of the loops progresses. In knowledge-based procedures, once the correct backbones are found, the Gibbs function may be used to guide side-chain construction. 1. Results Obtained with Conformational SearcheslMonte Carlo Methods

The first use of the CONGEN program involved an automated protocol that constructed two antibody binding sites, one for the small hapten phosphorylcholine, McPC 603, and the other for the protein antigen (antilysozyme HyHEL-5). Reasonable accuracy was achieved in both cases (1.4-1.6 A s-rms for all CDR backbones, 2.4-2.6 total), with the best results obtained for the McPC 603 L3 loop (six residues, 0.8 A backbone rms, 1.4 A total) and the McPC 603 H1 loop (five residues, 0.7 A backbone rms, 1.7 A total) and the HyHEL-5 L2 loop (six residues, 0.8 A backbone rms, 1.7 A total). Significant side-chain misplacements occurred on isolated aromatic rings and formally charged residues in the L3 and H3 of HyHEL-5 (total rms 14.1 A and 2.7 A, respectively; backbone rms 1.1 A in both cases) and the H3 in McPC 603 (total rms 2.9 A, 1.1 A on the backbone). The exceptionally long L1 loop in McPC 603 had to be built in several successive runs, each constructing only part of the 100~1,and also showed a large rms deviation from the X-ray structure (2.6 A on the backbone, 3.0 A total). However, the tip of this long loop showed relatively high backbone B factors in the crystal and its electron density was difficult to interpret unequivocally (Satow et al., 1986; see also comments in Brookhaven Protein Data Bank entry 1MCP). Several CONGEN computer modeling experiments were carried out using antibody sequences whose three-dimensional structure became available only later. Nell et al. (1992) reported construction of the binding site of an anti-insulin antibody 123, based on its homology with HyHEL-5 antilysozyme antibody. In the case of the antidinitrophenyl antibody AN02 (Bassolino-Klimas et al., 1992), the backbone rms shift of the six loops (43 amino acid residues) was 2.6 A. The shortest loop was 6 residues long, and the longest 9 residues long. Due to the length of the loops, several side-chain misplacements occurred (total rms 3.9 A). The antidigoxin antibody 26-10 (Bruccoleri and Novotny, 1992)was modeled from the McPC 603 framework and only five loops were built by conformational searches. The H1 loop backbone was copied directly from the crystal-

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lographic template because the only sequence difference in the definition of the loop was Glu H35 to Asn. This turned out to be a mistake: When the X-ray structure of the 26-10 antibody became known (Jeffrey et al., 1993), it was found that the H1 loop conformation was substantially different from the template for residues 28-30, outside the range of the loop as initially defined for the CONGEN run. As a result of this, and of the sequential construction of the loops, the H3 and H2 loops were constructed incorrectly. The fact that polypeptide segments with essentially identical sequences may differ substantially in conformation (Kabsch and Sander, 1984) presents a major challenge to all protein modeling protocols. In the first application of the random tweak method, Fine et al. (1986) generated conformations for four loops, H1, H3, L2, and L1, from the binding site of McPC 603. Starting from random structures, a large number of conformations for the loop backbones were generated, followed by either minimization or molecular dynamics to find minimum energy conformations for both the backbone and loop side chains. The same method was used to construct the entire antigen combining site of the CEA antibody specific for a carcinoembryonic antigen, a known colon cancer cell marker (Mas et al., 1992). Gibrat et al. (1992) reported backbone rms agreements in the range 0.9-2.6 A on reconstruction of the complete HyHEL-5 binding site with the Metropolis-simulated annealing Monte Carlo method. 2. Single-Residue Mutants, Indirect Effects on Binding CONGEN calculations were also used to supply a structural rationale for experimentally produced single-residue mutations and their effects on antigen binding. In the antidigoxin antibody 40-150 (Novotny et al., 1990; Ping et al., 1993), a spontaneous mutant 40-150 A2.4 carried a replacement Ser-+Argin its heavy chain (H94) and had altered specificity.A secondorder mutant, 40-150 A2.4P.10, lacked two residues at the N terminus of its H chain and had a specificity profile approaching that of 40-150 antibody. The N terminus and the position H94 were distant from the antigen binding site of the antibody, and the structural basis of the specificity changes was not immediately apparent. Approximate structures of the 40-150 antibody and its mutants were constructed by the computer, based on atomic coordinates of the homologous mouse antibody McPC 603. The torsional spaces of the polypeptide backbone and side chains around position H94 were uniformly sampled and the lowest energy conformations were analyzed in detail. The results indicated that, when Arg H94 is substituted for Ser, Arg H94 can hydrogen-bond to side chains of Asp H101, Arg L46, and Asp L55 (Fig. 13).This resulted in a change in the surface of the combining site which may account for the affinity changes. Deletion of the two N-terminal residues increased solvent accessibility of Arg H94.

COMPUTATIONAL BIOCHEMISTRY OF ANTIBODIES

191

The solvation may have caused a hydrogen bond between Arg H94 and Asp HlOl to be lost, restoring the structure to one similar to that of 40-150. The preceding structural hypothesis was tested by Ping et al. (1993) who prepared genes coding for N-terminally deleted heavy chains with both the Ser H94 and Arg 94 side chains, respectively, in the position H94. When antibody activity of the engineered and reconstituted antibodies was measured, N-terminal deletion had little effect on binding of the Ser H94 structure, whereas two-residue truncations increased affinity approximately 40-fold for the Arg H94 mutant, consistent with the hypothesis. Chien et al. (1989) described computational analysis of a single residue mutation similar to that in 40- 150. In their work Asp H 101, when replaced with Ala, totally abolished the phosphorylcholine-binding capability of the antibody S107. Computer-aided analysis of this effect highlighted the importance of Arg H94, and the salt bridge between the residues Arg H94 and Asp H101, in maintaining proper conformation of the H3 loop. RuffJamison and Glenney (1993) used the CONGEN program to build a model of another phosphorylcholine binding Fv fragment, Py20, and to simulate binding site mutants on a computer. In the course of their work, they discovered two mutations (V, Tyr-105-tAla and VH Tyr-1064Ala) with a moderately increased affinity for the antigen. In mutagenesis experiments on the antidigoxin antibody 26-10, CONGEN computer modeling of mutated side chains helped to rationalize diverse mutagenesis data, e.g., at hapten-contacting residues Asn H35 and Tyr-50 (Schildbach et al., 1991, 1993a, 1994). Modulation of antibody affinity by side chains in the hapten-distal position H52 was also analyzed by Schildbach and co-workers (1993b). Several mutant side chains were modeled using the crystal structure as a starting point. The results suggested that diverse residues could be accommodated within the antibody without substantial structural rearrangement, and that none of the substituted side chains were able to contact hapten. At the same time, the modeled H52 mutant conformations suggested plausible ways in which noncontact residues could modulate affinity indirectly through their impact on the orientation of the hapten-contacting side chains. E. Issues, Combined Protocols, Future Improvements

Several relatively accurate methods are currently available for modeling loop structure from its sequence. An inherent accuracy limit of the canonical concept is a fraction of an angstrom if backbones are considered in isolation, and -1.5 A for all atoms. Automatic loop construction via uniform conformational sampling or random tweaking essentially always contains the native loop structure in the set of the generated loops but, as mentioned

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JIRl NOVDTNY AND JURGEN BAJORAlH

earlier, the key problem here is to have a reliable Gibbs function to identify the native loop correctly. In many cases, the calculated free energy of the loop will be correct only if all the (potentially manifold) interloop interactions are correctly modeled, too. This raises the question of accurate modeling of the complete binding site, i.e., an ensemble of six interacting loops. Even if knowledge-based methods successfully find every single loop, one will still need a reliable procedure for correctly assembling the backbones in the context of the site, and adding side chains in their correct native conformations. Reflection on all these complexities of construction seems to favor a hybrid knowledge-based-conformationalsearch protocol, perhaps in the form of an automatic construction and database selection of every single loop, and an iterative loop combination-side-chain placement algorithm that would then completely assemble the site. Such a general protocol has not been developed yet, although the Martin et al. (1989) procedure (now commercially available from Oxford Molecular, Ltd.) represents the best attempt so far to combine CONGEN conformational searches with database loop selection methods. Pedersen et al. (1992) described an assembly of the complete D1.3 antilysozyme binding site using a combination of database searches for the corresponding canonical templates for five loops, side-chain construction by CONGEN, and CONGEN construction of the complete H3 loop, for which no canonical template was available. Very good rms values were reported for all the individual loops. One of the successful applications of a combined, knowledge-basedconformational search protocol is construction of the binding site of the anticancer antibody BR96 (Bajorath, 1994). In this work, framework regions were combined from VL and Vw domains of two different X-ray structures, 4-4-20 and 17/9 (Rini et al., 1992). This allowed the conformations of CDR loops L2, L3, and H1 to be directly included in the model. The splicing of the remaining CDR loop backbones on the framework was accomplished by superposing five residues N- and C-terminal to the loop and the framework end points, respectively. The unusually long CDR loop L1 in BR96 (12 residues) shared length and canonical determinants, but only limited sequence similarity, with the corresponding loop in 4-4-20 and was modeled based on the 4-4-20 structure. CDR loop H2 in BR96 represented another ambiguous canonical motif. Its sequence was consistent with the H2 canonical structure type 3 characterized by a glycine and exceptional torsion angles at position 54, but it had two glycine residues at positions 53 and 54, making it difficult to predict its conformation. The canonical conformation, with the glycine at position 53 in regular torsions, and the glycine at position 54 in exceptional torsions, was retained in the model as one possibility, and an alternative conformation was generated using CONGEN conformational searches. The best CONGEN-generated conformation, in fact, contained exceptional backbone torsions at position

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COMPUTATIONAL BIOCHEMISTRY OF ANTIBODIES

53 and the glycine at position 54 with @ and 1/, angles in the allowed region of the torsional space. To model the H3 loop, the most common conformation at the base of the loop was assumed, and the residual portion of the loop was obtained from complete CONGEN conformational searches in the presence of the other loops. Crystal structure of the BR96 Fab fragment, determined and refined to 2.5 A resolution, was reported by Jeffrey et al. (1995). Table IV summarizes the rms and s-rms deviations between the BR96 X-ray structure and the model, as originally reported by Bajorath and Sheriff (1995). Overall, a good agreement exists for the backbone rms of all the loops (see Table IV). The largest rms was obtained for the L1 loop which also shows rather high B factors in the crystal. Also, as in other models, the s-rms values for all the loops were higher than the rms values. In the future, as computers become faster (approximately doubling the speed of the central processing unit every 10 months), computer time will become less of an issue in modeling, and all the stereochemically acceptable conformations of long loops can be fully sampled. In automatic modeling methods (CONGEN, random tweak), it is important to avoid situations where a small imprecision in, say, positioning a side chain of one loop, is amplified into a gross error in modeling the neighboring loop (see examples in Section IV,D,l). For a complete combining site buildup, Bruccoleri et al. (1988) developed a sequence of loop constructions based on the relative positions of the loops in the local frame of reference provided by the /3 sheets of the VL-VH domain interface. The three shorter loops, L2, L3, and HI, are placed “low” (closer to the midpoint of the P-barrel interface) than the others (Fig. 7B). They do not interact with each other and provide a natural basis for construction of the remaining “high” loops, H2, H3, and L1. Thus, the low loops are built first, e.g., in the order L2, H1, L3, followed by H2, H3, and L1. TABLL IV

CDR Loop Cornpanson: BR96 Model ~

~~

~

rms deviation

~~

(A)

71s

BR96 X-ray‘ ~~

s-rms deviation (8,)

Loop

Backbone

All atoms

Backbone

All atoms

L1

1.6 0.2 0.3 0.3 0.3 1.5

2.9 0.4 0.9 0.6 0.9 3.3

2.0 0.3 1.0 0.9 1.4 2.9

3.2 0.5 1.:3 1.0 1.8

L2 L3 H1 H2 H3

At 2.5 8, resolution.

3.8

194

JlRI NOVOTNY AND JURGEN BAJORAlH

VII. BINDING AFFINITY

AND

SPECIFICITY

The question of antibody specificity is central to molecular immunology. Even problems seemingly unrelated to specificity, such as the immune repertoire and maturation of the antigenic response require, for their full understanding, a reference to antigen binding and affinity changes in the process of clonal selection. What are the main physical components of binding and specificity? Do antibody and antigen structures change on complexation, and, if so, by how much? What is the atomic origin of affinity and, implicitly, of specificity? Only recently, with the emergence of dozens of X-ray structures of antigen-antibody complexes including both low- (- 1pM) and highaf€inity ( 1 nM-10 pM) ones, have we had an opportunity to explore these questions in precise atomic terms. Our explorations have been met with a stiff challenge. In the structures of the complexes, there are hundreds of atoms in intimate interactions: van der Waals, hydrogen bonding, salt bridging. It is not a simple task to relate this molecular jungle to experimental observables (equilibrium binding constants, KM). The most basic biophysical concepts necessary for formulation of any binding theory are still being debated, and there are those who doubt whether atomic origins of binding specificity will ever be fully understood (Mark and van Gunsteren, 1994; Janin, 1995). Rigorous calculations of binding constants may currently be unattainable, however, the situation is not so hopeless that any meaningful insight into the attribution of binding energies would be denied us. As we hope to demonstrate in this section, qualitative and semiquantitative estimates of binding energy attribution are possible in many cases, and can be directly compared to experimental perturbations of binding (AAG values obtained from site-directed mutants of antibodies and/or antigens). Gradually, a conceptual framework for the rationalization of binding data is emerging and will be refined, with time, into a truly quantitative tool. The current situation may remind us of the empirical and semiempirical quantummechanical calculations used in chemistry. They, too, provide a valuable insight into structures of compounds by aproximating, rather than rigorously solving, the Schrodinger equation for many electron molecules.

A. Thermodynamics of Binding Concepts such as binding specificity and complex stability (affinity) have their origin in the thermodynamics of bimolecular reactions. For example, in the reaction Antigen

+ Antibody = Complex

COMPUTATIONAL BIOCHEMISTRY OF ANTIBODIES

195

molar concentrations of the three molecular species are measured at equilibrium, and the strength (specificity) of the complex is estimated from its relative concentration, i.e., the ratio KAS = [complex]/[antibody][antigen]. The experimentally measured KAs relates to the Gibbs free energy of complex formation, AG, as AG = RT log KAS (where R, the gas constant, is the product of the Boltzmann constant, k, and the Avogadro constant, L, and is equal to 8.314 kJ mol-' K-', and T is the temperature in kelvins). Changes in Gibbs free energy, a thermodynamical quantity, can in principle be obtained from atomic structures of all the molecules involved in the reaction, provided all the physical forces responsible for the complex formation are accurately known. The specificity of protein-ligand interactions comes from a large difference between binding constants characterizing the binding of specific and nonspecific ligands. Thermodynamically, the higher binding constants for specific ligands arise from stronger overall forces (Gibbs free energy differences) between the antibody and the antigen. Most of the forces responsible for binding are distinctly short-range: Van der Waals-London dispersion forces (London, 1930), hydrophobic force [i.e., a difference in surface solvation] (Kauzmann, 1959), and hydrogen bonds (Pauling, 1960) have vanishingly small values at distances greater than 3 4 A, a local distance even on an atomic scale. While the first two types of forces can be said to be isotropic (spherically symmetric), hydrogen bonds are strictly directional and require orientation of the participating groups. Electrostatic forces act at a distance but the high dielectric constant of water effectively limits their reach. Thus, the burial of charged atoms at a protein-protein interface distinctly increases their effective electrostatic field, but only at the expense of the energetically unfavorable desolvation of charged groups. A consequence of all this is that the two molecular surfaces, the antibody paratope (i.e., the binding site) and the antigenic epitope, will enter into a stable complex only if they have complementary molecular shapes over a large area, and their surface charge distribution is such that the interaction of opposite charges on the epitope and the paratope provides sufficient Coulombic attraction to stabilize the complex (Novotny et al., 1987). These attractive contributions are counterbalanced by conformational entropy losses of side chains immobilized at the antigen-antibody interface. In the omnipresent thermal motion at room temperature, torsions of free side chains tend to rotate randomly and distribute themselves equally in the three lowest energy conformational states, trans (180") and f gauche (k60"). On complex formation, only one of these states becomes locked in the tightly packed interface. Enforcement of this torsional preference over the natural equalizing tendency of the Brownian motion costs energy, and some of the Gibbs free energy of complex formation must be expended on it.

196

JIRI N O V O T N Y AND JUKGEN UAJORATH

Although the quantitative aspects of these biophysical components of binding are still debated, estimates have been summarized as follows (Novotny and Sharp 1992). (1) Van der Waals or dispersion-repulsion (London) interactions probably constitute most of what is termed shape complementarity in binding, in that they penalize intermolecular contacts that provide either overlap of atoms, or cavities, either directly or through induced strain. Well-packed contact regions at antigen-antibody interfaces, though, are probably not much more favorable than the antibodysolvent and antigen-solvent contacts experienced by the free molecule in the complex. Surface tension data from organic liquid-water systems show that the work of adhesion between hydrocarbon and water interfaces is essentially the same as that between two hydrocarbon interfaces (Nicholls et al., 1991, Adamson, 1976). Furthermore, dispersion forces are relatively small in magnitude, and their possible differences amount to even smaller magnitudes. ( 2 ) The hydrophobic effect is the major stabilization factor of complex formation contributing, according to various estimates, between 25 and 7 2 cal (6 and 17 J) of Gibbs free energy stabilization per 1 of protein-protein contact area (Chothia, 1974; Chothia and Janin, 1975; Sharp et al., 1991b). (3) Electrostatic effects accompanying complex formation involve the following. (a) Creation of new clusters of charged atoms in the low dielectric constant ( E = 2) environment at the protein-protein interface of the complex; these charge-charge interactions can stabilize the complex through Coulombic attraction, the net effect being proportional to the atomic charges. (b) Desolvation of charged groups; this is proportional to the square of the atomic charge, and so the desolvation process is always unfavorable, and often stronger, than the net Coulombic attraction (see Section VI1,A). (4) On complex formation, immobilization of a freely rotatable torsional degree of freedom (a side chain exposed to solvent) carrying a free energy penalty of about 0.6-0.7 kcal ( 2 . 5 kJ; Privalov, 1979; Novotny et al., 1989; Nicholls et al., 1991; Pickett and Sternberg, 1993).

x2

B . Lock and Key or Induced Fit Do antigens andlor antibodies change structure on binding [induced fit hypothesis, first explicitly proposed for antibodies by Pauling (1940)l or is the binding essentially an association of two rigid bodies [the lock-and-key paradigm of Fischer (1894)l. The X-ray crystallographic structures, in fact, reveal both binding modes. Examples of lock-and-key complexes, currently much more numerous, include the McPC GO3 antiphosphorylcholine myeloma (Satow et al., 1986); D1.3 antilysozyme (Amit et al., 1986; Bhat et al., 1994); NC41 and NClO antineuraminidase (Tulip et al., 1994;

COMPUI’AI‘IONAI. BIOCHEMISI‘KY OF ANTIBODIES

197

Malby et al., 1994); 4-4-20 antifluorescein (Herron et al., 1989); and 26-10 antidigoxin ueffrey et al., 1993). The best examples of large induced fits on complexation are the antipeptide antibodies 17/9 and 50.1 where the whole H3 loop pivots as if on two anchor points (Stanfield et al., 1990, 1993; Rini et al., 1992; Schulze-Gamen et al., 1993). On complex formation, either lock-and-key or induced fit, one of the possible surface side-chain conformers is always selected and “rigidified” at the antigen-antibody interface. Because of this generality, and because its energetic cost can be well estimated, this shift from a preformed conformational equilibrium need not be considered an induced fit. The simplest case of a backbone-induced fit may also involve stabilization of a disordered loop segment in one of the thermally available conformational states, introducing a shift in the preexisiting equilibrium (Fersht, 1984). Given the relatively high cost of conformational entropy (-0.6 kcal per aliphatic side-chain torsion or 0.4 kcal per backbone torsion; see Section VII,A), it may well be that those antigen-antibody systems where tight binding is required evolved toward rigid (lock-and-key)binding. Can the induced fits be operational in cross-reactivity?The only structurally well-documented case of antibody cross-reactivity, that of the highaffinity (- 1 &) mouse monoclonal antiprogesterone DB3 which binds four different progesterone-like steroids (Arevalo et al., 1993, 1994), involves no structural changes in the antibody on engaging the various ligands. Cross-reactivity was accompanied by two distinct modes of hapten orientation (i.e., the steroidp ring with two methyl groups) with respect to the Trp side chain H50, one of the major hapten-contacting residues. Incomplete binding surface complementarity between the haptens and the antibody seemed to be the key structural feature promoting cross-reactivity. Bruccoleri and Karplus (1990), Hoffren et al. (1992), and de la Cruz et al. ( 1 994) reported molecular dynamics simulations of hypervariable loops that may provide us some idea of the shape variations the binding site undergoes with thermal fluctuations. The Bruccoleri and Karplus (1990) simulations were carried out at different temperatures in vacuo, and with the goal of sampling the complete conformational space of each loop. Comparison with the results of CONGEN searches revealed that molecular dynamics sampled the loop conformational space less completely, and less efficiently, than the CONGEN uniform searches. De la Cruz et al. (1994) simulated dynamics of a free and a complexed antibody binding site (Fv fragment of the antirhinovirus serotype 2 heptadecapeptide) at room temperature and with an explicit solvent. They reported average rms deviations of up to 1.4 for the free hypervariable loops of the Fv fragment, and less so for those complexed with antigen. A systematic drift from the X-ray positions was also observed that, e.g., for the

198

JIRI NOVOTNY AND JURGEN BAIORATH

CDR H2 loop approached 3 A after a 100-psec dynamics run (in the presence of an explicit solvent). This may have been an artificial by-product of the particular technical conditions of the simulations (the GROMOS potential, nonbonded interactions evaluated with a cutoff of 8 A, and a longer cutoff of 15 applied every fifth step). By comparison, other work (Kitson et al., 1993) showed that, under different conditions (class I1 DISCOVER potential, cutoff 25 with no switching function or employing Ewald summation),2 the average structure simulated by molecular dynamics did not differ from the X-ray structure by more than a fraction of an angstrom. This is indeed to be expected if the solvated protein structure represents a natural system at Boltzmann equilibrium with itself.

C. Empirical Gibbs Functions As early as 1975, Chothia and Janin used the rule of proportionality between hydrophobic effect and solvent-accessible surface area (Chothia, 1974) to estimate hydrophobic stabilizations of bovine pancreatic trypsin inhibitor (BPTI), hemoglobin a/3 dimer, and insulin dimer. After a correction for conformational entropy loss on complex formation, a good correlation between the solvent-accessible protein-protein contact areas and the measured K M was achieved. Nevertheless, the concept of accessible surface area as the only measure of the Gibbs free energy change in complex formation was an oversimplification. For example, the areas of contact between trypsin and BPTI (Huber et al., 1974) and between the immunoglobulin Fc fragment and the fragment B of staphylococcal protein A (Deisenhofer, 1981) are identical (13.9 nm2), while the affinities of these two complexes differ by at least six orders of magnitude (0.1 pM in the case of the trypsin inhibitor and -1pM or less in the case of Fc fragmentfragment B). By now, approximations of binding constants have been refined by including empirical estimates of all the atomic thermodynamic contributions deemed to be important in the attribution of binding energy (Section VI1,A). Empirical Gibbs (free energy) functionals, in the form of simple

'

Evaluation of nonhonded (van der Waals and electrostatic) interactions is timeconsuming during molecular dynamics simulations; often the painvise interactions are neglected beyond an arbitrary cutoff distance. Switching functions are sometimes added to the potential around the cutoff distance to smooth the abrupt truncation of interactions, hut this practice was shown to generate large artificial forces and unwanted perturbations to the system. Ewald (1921) summation allows calculation of all the electrostatic interactions of a set of charges to inifinity faster than simple summation of all the painvise interactions can.

COMPUTATIONAL BIOCHEMISTRY OF ANTIBODIES

199

formulas, were proposed by Novotny et al. (1989), Williams et al. (1991), Nicholls et al. (1991), Wilson et al. (1991), Horton and Lewis (1992), Murphy et al. (1993), and Abagyan and Totrov (1994). The many simplifications necessarily adopted in these estimates (see Section VII,C, 1) require that the results not be interpreted too finely, and various improvements are being explored (Pickett and Sternberg, 1993; Jackson and Sternberg, 1994; Vajda et al., 1994). Nevertheless, the present forms yielded reasonable estimates in many cases and showed predictive power where sitedirected mutagenesis results distinguished between residues important and unimportant for binding. Research now focuses on (1) elimination of technical errors in electrostatic calculations such as, e.g., poor treatment of charge desolvation effects on complex formation (see Bruccoleri et al., 1996), (2) refinement of surface scaling constants (Novotny, Bruccoleri, Davis, Sharp, manuscript in preparation), and, where applicable, ( 3 ) a proper account of interface-bound water and its impact on the energetics of complexation (see Section VII,D). 1. Functional Forms and Limits of Approximation

The treatments of Novotny et al. (1989), Murphy et al. (1993), and Abagyan and Totrov (1994) are the only ones systematically applied to antigen-antibody interactions and are discussed here in detail. In the Novotny et al. (1989) method, atomic coordinates of an antibody-antigen complex are the only data on which the calculation is based. By using the Gibbs functional as detailed in the following discussion, the atomic free energies are calculated for each molecule, first for the uncomplexed form and then for the complex. The difference between these two values gives the atomic Gibbs free energy differences on complex formation, AG,,,,,, values. These are the sums of the individual contributions due to hydrophobic, electrostatic, and side-chain conformational entropy effects. From the atomic values, the AGresidurcontributions and the complete AG of the reaction are obtained by further summations. In this empirical scheme, and assuming rigid macromolecules, (1) the hydrophobic effect, AGHB, is directly proportional to the contact solvent-accessible area (in square angstroms) (Lee and Richards, 1971)between the two molecules (Chothia, 1974):

AGHB = (contact area) x 25 cal

(10)

(1 cal = 4.2 J), and (2) electrostatic (Coulombic) interaction between the two molecules, AGEL,is empirically “screened” by an effective dielectric constant:

200

JIRI N O V O T N Y A N D J U R G E N BA J O M I ' H

where QJ is the partial atomic charge, r is the distance between the ath and jth atoms, and E is the effective dielectric constant. Hydrogen bonding is treated as an electrostatic phenomenon, included in Eq. (1 1). Equation (11) approximately reproduces the differential strength of protein-protein hydrogen bonds compared to protein-solvent hydrogen bonds, as estimated by Fersht et al. (1985) in site-directed mutagenesis experiments. These usually attractive interactions are counteracted by a loss of conformational entropy of surface side chains immobilized at the contact surface (Privalov, 1979; Rashin, 1984): -TAS( = NRT log 3 = 0.6N kcal

(12)

where R is the gas constant, T , the temperature, equals 300 K, and N is the number of side-chain torsional degrees of freedom lost. Equation (12) implies that each torsion has approximately three equienergetic states available in free solution (i.e., trans and 2 gauche) but becomes locked in one conformation on the formation of a complex (hence the log 113 = -log 3 term. Finally, for the absolute AG value calculations, estimates are made for the cratic and translational-rotational entropy changes (AS(R and A S T R , respectively) that accompany complex formation (see Novotny et al., 1989): TASCR= 2 kcal

(13)

TASIK= 9 kcal

(14)

Murphy et al. (1994) and Finkelstein and Janin (1989) offered somewhat different treatments and values for both the cratic and translationalrotational entropy terms. Assumptions implicit in Eq. (9-14) are that (1) the solute-solute van der Waals interactions are essentially of the same magnitude as the solutesolvent van der Waals interactions and effectively cancel out (see Section VII,A), and (2) that changes in vibrational entropy between the two free proteins and the protein-protein complex are likewise unimportant. Indeed, the largest changes are expected to occur in low-frequency, collective modes of vibrations [e.g., lobe opening and closing, as suggested by, e.g., Tidor and Karplus (1994), which are known to be effectively damped in aqueous solutions (Cusack et al., 1988). 2. Culculutaons on Indavaduul Antagen-Antabody Complexes

Calculations carried out to date include those for about 10 antibodyantigen complexes and are summarized in Tables V-VII. Overall, the absolute AG are in the range of experimentally observed values, with two exceptions (HyHEL-5 and NC41) due to a poor electrostatics approximation [Eq. (1l)]. Experimentally determined AAG values characterizing the effects of single-residue mutations on binding are available for the NC 10

20 1

COMPUTATIONAL BIOCHEMISTRY OF ANTIBODIES TABLE V

Empirical Free Energy Calculationsfor X-ray Structures of Antibody-Antigen Complexes ~A

A G (kcdl)

Complex

~ G ~ (kcal)

D1 .3-lysozymer Hy HEL-5-lysozyme HyHEL-10-lysozyme NC4 1-N9 neuraminidase NC 10-N9 neuraminidase McPC603-phosphorylcholine

-11.4 -14.2 -13.0 -9.7 -10.8 -6.6

-9 -3 2 -13 -22 -13

36.7 1-phenyl arsonate 4-4-20-fluorescein

-4 -12.3

-7 -16

' The experimentally

~~

~

~ Refs.

~

~

Novotny et al. (1989) Novotny et al. ( 1 989) Novotny (1991) Tulip et ul. (1994) Tulip et al. ( 1994) Novotny et al. (1989); Novotny (1991) See Table VI See Table VII

4

determined AG value.

* The calculated AG value.

' The original calculation reported by Novotny et al. (1989) was carried out on the Amit et al. (1986) X-ray coordinates. Crystal structure has since been refined and several water molecules were found at the antigen-antibody interface, however, empirical AG calculations have not yet been repeated on the refined coordinates.

TABLE VI Phenyl Arsonate-36-71 Fab Complex: Calculated &&p,dUp ~

~

~~

Contact surface

and Experimental AAG Valuesa ~~

Residue

(A2)

AGH$

AGEL'

N, torsion

Asn H35 Ser H99 Trp H47 Tyr H50 Ala H59 Phe H 108 Tyr H106 Arg L96 Leu L94

0.8 0.8 0.6 32.4 3.4 1.6 25.9 17.0 15.9

0 0 0 -0.8 -0.1 0 -0.6 -0.4 -0.4

-0.7 -0.7 -0.4 -0.2 0 0 -0.1 -4.1 0

0 0 0 1.5 0 0 2.0 1 1

- T A S L F ~ Total

0 0 0 0.9 0 0 1.2 0.6 0.6

-0.7 -0.7 -0.4 -0.4 -0.1 0 +0.2 -3.9 +0.2

AAGEx~ >-3.5 -3.4 -2.3 -3.5

-3.1

' Values in kcalimol. The experimental A A G E x ~values (Sompuram and Sharon, 1993) represent the measured differences between the AG of the wild type and that of the Ala mutant at the same position. Phenyl arsonate partial atomic charges were derived from STO-3G Gaussian90 calculations (T. Stouch and J. Novotny, 1991, unpublished results); the arsonate group was assumed to be monoionic (Pressman and Grossberg, 1968). Residue numbers are consecutive through the polypeptide chain. h The hydrophobic term; see Eq. (9). The electrostatic term; see Eq. (10). The TASC:F(conformational entropy) term; see Eq. (1 1).

202

JIRI NOVOTNY AND JURCEN BAJORATH

TABLE VII

Fluorescein-4-4-20 Fab Complex: Calculated AGrcsidueand Experimental AAG Valuesa Contact surface Residue

(A*)

Gly H104 Trp H33 Arg H52 Arg H74

6.5 48.1 0 0 29.6 0 0 39.9 16.2 5.5

TyrH103 Lys H54 Lys H67 Tyr H56 Tyr H102 Ser HlOl Asp H31 Arg L39 Lys H55 His L 31 Gln L33 Ser L96 Ser L94 Trp LlOl Phe L103 Tyr L37

5.4

4.2 0 32.1 6.9 8.6 5.0 17.9 5.7 36.5

N, A G E L ~ torsion

-0.2 -1.2 0 0 -0.7 0 0 -1.0 -0.4 -0.1 -0.1 -0.1 0 -0.8 -0.2 -0.2 -0.1 -0.4 -0.1 -0.9

-0.8 -0.1 -0.7 0 -0.9 0 0 0 -0.2 -0.2 0.8 -3.3

0

-2.2

0 1 0 2 0

0 0 -1.2 0 -0.1 0 0.5

1 0 0

2 0

0 2 2

2 1 0

1 1

2

-TASCF~ Total 0-1.0 0.6 0

0 1.2 0 0 1.2 1.2 1.2 0.6 0 0 0.6 0 1.2 0 0.6 0.6 1.2

-0.7 -0.7 -0.5 -0.4 -0.3 -0.2 +0.2 +0.6 +0.9 f1.3 -3.4 -2.2 -0.2 -0.2 -0.2 -0.1 +0.1 +0.5 +0.8

AAGEXP

-2.2 0

-2.4

a Values in kcal/mol. The experimental AAGEXP values (Denzin et al., 1993) represent the measured differences between the AG of the wild type and that of the Ala mutant at the same position. Fluorescein partial atomic charges were derived from STO-3G Gaussian90 calculations (T. Stouch and J . Novotny, 1991, unpublished results). Residue numbers are consecutive through the polypeptide chain. In this crystal structure of the 4-4-20 complex, one molecule of the solvent 2-methylpentane-2.4-diolis found in a cavity inside the Fv fragment beneath fluorescein but makes no contact with the hapten. The KO of complex formation in methylpentanediol is different (lower) from that in physiological solution (Herron et al., 1989). The mcthylpentanediol molecule was present in the empirical AG calculation. The hydrophobic term; see Eq. (9). The electrostatic term; see Eq. (10). The TASCF(conformational entropy) term; see Eq. (11).

and NC4 1 antineuraminidase complexes, antiphenylarsonate 36-7 1 (Table VI), antiphosphorylcholine McPC 603, and the antifluorescein 4-4-20 (Table VII) complexes. Often, the relative ranking of residues agrees in the experiment and the calculations but the absolute values differ, sometimes by as much as 3 kcal (e.g., Table VI). The calculated AGresidueof Tyr H106 in the 36-71 antibody, Tyr-H33 in McPC 603, and Trp LlOl in 4-4-20 are all in error due to an overestimation of the side-chain con-

COMPUTATIONAL BIOCHEMISTRY OF ANTIBODIES

203

formational entropy term. These side chains were probably constrained to a limited set ofXl torsions even prior to complex formation. On the other hand, some agreements of the calculated residue contributions with experimental AAG data are notable. Kam-Morgan et al. (1993), working on the HyHEL- 10 complex, measured AAG values for several mutants in the Arg-2 1 and Asp- 101 positions and compared them with the AGresiduecontributions calculated by Novotny (199 1). Mutagenesis of Asp101 was well rationalized by the calculated AGHB,AGELand TASCFterms. The Arg-2 1 AGresiduccontribution, originally calculated as -11 kcal/mol, was measured to be only about -2 kcal/mol. Tulip et al. (1994) compared binding energy attributions in complexes of the influenza N9 neuraminidase with those of two different antibodies, NC41 and NC10. In this work, mutations at the energetically important positions (i.e., side-chain substitutions at sites for which the calculated AGresiduec -1 kcal/mol) did not bind the antibody, while neutral mutations (at sites where AGr,,idue > -1 kcal/mol) had no effect on binding, as tested against the binding data reported by Nuss et al. (1993) and Webster et al. (1987). The trend was valid for NC41 in 19 out of 27 cases at 13 neuraminidase sites, or 24 out of 27 if steric clashes and backbone hydrogen bonds, immutable by sidechain replacements, are taken into account. It was valid for NClO in five out of seven neuraminidase sites [corrected experimental data of Gruen et al. (1994) as opposed to the seven out of seven correlation originally reported by Tulip et al. (1994)l. Describing the effect of mutations made in the D1.3 antilysozyme combining site, Hawkins et al. (1993) noted that “much of the energetics of interaction seems to be driven by contacts from . . . the segment G117 to Q121 of lysozyme,” and that, in the antibody, VH residues T30, Y32, R99 and VL residues Y50, T53, and S93 were less important. These rankings are in a good overall accord with those given in Novotny et al. (1989). In the most recent coordinates of the D1.3 complex (Bhat et al., 1994) water molecules were found at the interface that were not considered in the earlier calculations. The question of water-mediated binding is discussed separately in Section VII,D. Hawkins et al. (1993) also remarked that “the number of contacts appears to be at least as reliable a guide to predicting the energetics of the interaction of the D1.3 antibody and lysozyme as semi-empirical calculations.” However, in the Tulip et al. (1994) calculations, retention of binding in the I368R mutant, at the spatial center of the epitope, was successfully predicted while, e.g., the K432N mutation at the edge of the interface markedly reduced binding, an effect expected from the calculations. Perhaps the most important effects suggested by the calculations and subsequently borne out by experimental evidence were those involving (1)

204

JIRI NOVOI‘NY AND JUKGEN BAJOKATH

the existence of an “energetic epitope” (Novotny et al., 1989; Jin et al., 1992), more fully discussed in Section VIII, and (2) the very different attribution of binding affinities in the two overlapping neuraminidase epitopes (also see Section VIII). Later calculations employ a significantly improved formula for electrostatics (Bruccoleri et al., 1996), a hydrophobicity term based on scaling contact molecular surfaces and on conformational entropy estimates enumerated by uniform conformational sampling of all the side chain torsional degrees of freedom in CONGEN. A blind test of the method attempting to reproduce AAG values measured on 10 lysozyme singlechain mutants that affected binding of the HyHEL-10 antibody Kirsch, University of California, Berkeley, personal communication; Novotny, Bruccoleri, Davis, and Sharp, manuscript in preparation) yielded encouraging results, as shown in Fig. 14.

u.

3. Binding Energies from Calorimetric Data

Murphy et al. (1993) carried out a calorimetric study of complex formation between the Fab fragment of the antibody 13. l and its antigen, angiotensin 11. Association of the two molecules was accompanied by an enthalpy change (AH) of -8.9 2 0.7 kcal mol-’ and a heat capacity change (AC,) of -240 2 20 cal K-I. From these values, the free energy change of the reaction, AG, at 30°C was estimated as -1 1 kcal mol-’ with a AS component of 6.9 cal K-’ mol-’ (TAS 22.3 kcal). Thus, complex formation was favored both enthalpically and entropically. Structural interpretations of AC, and AH changes invoked proportionality between accessible polar (AApo1) and apolar (AA,,)contact surface areas calculated from the structure of the complex, and the AC, and AH values (Murphy and Freire, 1992; Privalov and Makhatadze, 1990; Spolar et al., 1992). Thus,

-

AC, = 0.45AAap- O.26AAp,I

(15)

The enthalpy change was related to the temperature at which the apolar contribution was assumed to be zero, T*H - 100°C:

AH

= AH*

+ (Acap+ h c , , ~ )( T - T*H)

(16)

AH* = 35AAp,,

(17)

Here,

To derive KM from the X-ray structure of the complex, no structural changes were assumed in the antibody binding site, and an arbitrary extended conformation of angiotensin was used to estimate the intramolecular surface changes accompanying the assumed change in angiotensin conformation on complex formation.

205

COMPUTATIONAL BIOCHEMISTRY OF ANTIBODIES

I

I

I

I

I

I

I

I

/I

I / /

OKWD

12.0

/ /

-

/

/

10.0

-

/ / /

- correl. cosi

/

8.0

R21E

0

8.0

-

/ /

'OKWG

,,

without K98M: correl. coef. 0.78

-

/

4.0

0.68

/

(ave. error

2.8 kcal)

/

/

-

2.0 0.0 /'

-2.0

,ti: 0

-

OKSEM

-

ODlOlK

/

-4.0

w62y

/

(9

-

R21K

W83Y

/

-6.0

I

I

I

I

I

I

I

I

I

Experimental AAG values [kcal]

FIG.14. Empirical Gibbs free energy estimates on 10 single-residue hen egg lysozyme mutants complexed with the HyHEL-10 antibody. (The experimental data are courtesy of J. Kirsch, University of California Berkeley.) The calculated AAG values (mutant-wild type) are based on CONGEN-generated coordinates of the respective mutants starting from the X-ray crystallographic coordinates of the wild-type lysozyme-HyHEL- 10 complex [e.g., in the W63Y mutant the lysozyme Trp-63 was replaced by Tyr, etc. (Novotny, Bruccoleri, Davis, and Sharp, manuscript in preparation)]. The calculations employed a scaled molecular surface ([contact area]*70). as the hydrophobic term, a finite difference Poisson-Boltzmann algorithm with dielectric boundary and charge smoothing-antialiasing as the electrostatic term, and conformational entropy estimates carried out by the exhaustive CONGEN enumeration of the trans and gauche torsional degrees of freedom. The correlation coefficient for all the data points is -0.6; it is -0.8 if the K96M mutant is ignored (the lysozyme wild type Lys-96 is exceptional in that it participates in buried intramolecular hydrogen bonds and its substitution for Met is likely to lead to global structural changes). The average error for the latter nine AAG values, comparing the experiment and the calculation, is *2.8 kcal.

Based on Eq. (15), a AC, value of -250 cal K-' mob' was obtained, in close agreement with the experimental results, and the A H estimate, with the use of Eq. (15), yielded -8.4 kcal mol-I, compared to the experimentally determined AH of -8.9 kcal mol-I, a remarkable result considering that the angiotensin conformation in free solution was not well known and its total surface areas, A, and LP,had to be approximated.

206

JIRI NOVOTNY AND JURCEN BAJORATH

The entropy change in the complexation was assumed to be related to the heat capacity change as

AS = AS*

+ (AC,., + Ap,pol)In (T/T*s)

(18)

where T*s, the temperature at which the apolar contribution to the entropy change is zero, equals 112”C,and AS*, the residual entropy change, is interpreted as consisting of configurational and “other statistical” contributions to AS:

AS* = AS,,,

+ ASsc + AS,,

(19)

where AS,,, is the change in backbone torsional degrees of freedom, ASSC is the change in side-chain torsional degrees of freedom, and AS,,, is the change in the number of particles in solution. The values of the entropy estimates, i.e., the terms of Eq. (19), were substituted from literature data and the overall AS estimate fell in the range 7-9 cal K-’ mol-’, in good agreement with the experimental value of 6.9 cal K-’ mol-’. These results were interpreted as showing both the loss of configurational entropy and a larger entropy gain from solvent release due to the hydrophobic effect on complexation. Enthalpically, binding was also favored by hydrogen bonding. It can be said that the main focus of the Murphy et al. (1993) work was on finding structural correlates of the extensive thermodynamic functions of state rather than approximating the absolute AG of the reaction from its atomic components. Structural interpretations of protein thermodynamics (Kauzmann, 1959) have had a long and fruitful tradition (Privalov, 1979), however, some of its important issues are still unresolved (Sturtevant, 1994; Naghibi et al., 1995). For example, the hydrophobic effect is considered to be a manifestation of water entropy changes induced by solutes but, depending on the reference state with respect to which the effect is measured (aliphatic alcohol, vacuum) and the theoretical framework used (classical or Flory-Huggins theory; Sharp et al., 1991; Sitkoff et al., 1994; Chan and Dill, 1994), differences in solute-solvent interactions vary in magnitude, contain varying amounts of enthalpic and entropic (mixing volume) contributions, and may enter into the free energy balance with different significance. Electrostatic interactions, on the other hand, are mostly considered to be of enthalpic origin, yet they involve desolvation of charges on attainment of compact solute states (folded protein, proteinprotein complex). Solvation-desolvation events are accompanied by changes in the entropy of water (electrostriction) so large that they almost certainly overshadow the hydrophobic effect encountered at nonpolar surfaces. Efforts trying to relate any macroscopic theory (thermodynamics) to the microscopic, atomic description of matter are essential for an understand-

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207

ing of biological specificity, however, the phenomenological gap that must be overcome is very wide indeed. Thus, the development of empirical atomic rules of specificity may have a better chance of success when focusing on the interpretation of just one-the major- experimental observable (AG and the binding constant, KD) rather than dissecting this observable into its individual macroscopic parts (calorimetric enthalpy and entropy). This is because every thermodynamic quantity of state represents an equally bewildering mix of microscopic events, each of them as complex in its atomic origins as the parent one and each involving mixtures of solute and solvent effects. Thus, by dividing the problem, one may paradoxically make it more and more complex, in proportion to the number of functions of state being considered. All the (unobservable) microscopic states and their transitions manifest themselves to us only indirectly, as macro observables. The interfacial tension, for example, is not only a direct measure of hydrophobicity, reflecting, in ensemble, all the events happening on solute-solvent mixing, but also a quantity proportional to the solute molecular surface. Molecular surface is a straightforward attribute of structure and, as such, is readily amenable to measurement and analysis. The advantage of simple empirical rules such as the correlation between the hydrophobic effect and solute surface is in circumventing the microscopic complexity of the solution and substituting an aspect of solute structure instead. In this way, quantitation of hydrophobicity can be easily carried out based on the structure of the solute alone. 4. Antigen-Antibody Docking

One way of probing intermolecular interactions is to carry out antigenantibody docking simulations in a computer. A successful computer docking experiment requires (1) a rapid and ef€icient generator of the many sterochemically acceptable contact orientations of the two molecules, and (2) a robust Gibbs functional that can correctly identify the native complex among the many antigen-antibody pairs generated in the course of orientational sampling. Because of the important role of the Gibbs functional, the docking problem is similar in spirit to the theories of binding energy attribution discussed previously. However, the importance of shape complementarity has been highlighted by the work of Norel et al. (1994) who reported successful docking on the basis of surface shape matching alone. Building on the earlier work of Connolly (1986), they represented molecular surfaces by “critical points” describing prominent holes and knobs as minima and maxima of a shape function. Their automatic algorithm considered the entire molecular surfaces of 16 protein pairs from the known

208

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complexes, but no additional information about the structure of the binding sites. Fifteen complexes were successfully docked, including the antibody-lysozyme complexes HyHEL-5 and HyHEL-10. The most ?ccurate ab initio prediction of antibody-antigen association, to within 1.6 A of the X-ray structure, was reported by Totrov and Abagyan (1994) for lysozyme and the HyHEL-5 antibody. Their docking algorithm used an original, “biased probability,” Monte Carlo procedure. The Metropolis et al. (1953) Monte Carlo algorithm is a succession of random steps in the generalized coordinate space followed by energy evaluation of the new state, E , and its acceptance in proportion to the Boltzmann factor,

AE kT In the biased method, the random step and its acceptance are modified by a probability function that favors the energetically most preferred regions of the configurational (coordinate) space. The biased algorithm does not waste much time sampling the forbidden regions of the energetic landscape, the main problem associated with Metropolis Monte Carlo searches. Another important innovation introduced by Abagyan et al. (1993) was consistent use of the internal coordinate space, rather than the Cartesian coordinate space, for configurational sampling. The Gibbs functional used to evaluate the calculated antigen-antibody configurations was that of Abagyan et al. (1993) and Abagayan and Totrov (1994). It consisted of three terms: (1) surface energy, (2) electrostatic polarization free energy, and (3) side chain entropy. Although conceptually similar to the Gibbs functional described in Section VII,C,l [Eqs. (10)(12)], its formal implementation was different. Thus, surface terms employed the Eisenberg and McLachlan (1986) solvation parameters to scale the solvent exposed and/or contact surfaces. To this term a precomputed conformational entropy term was added that approximated side-chain conformational entropy changes in the individual side-chain types. Sidechain entropy estimates were made on the basis of preferred conformational zones, essentially rotamer libraries:

u=l

where P is the probability of the vth state and R is the gas constant, corrected if necessary for an additional number of states: Sadd

= -R 1%

(Nadd)

(21)

where N is the number of additional states. The electrostatic term, the

COMPUTA?’IONAL BIOCHEMISTRY OF ANTIBODIES

209

modified image electrostatics, makes use of (1) a rigorous analytical solution to dielectric boundary effects for an ideal spherical body (Kirkwood, 1934; Friedman, 1975), and (2) a fast approximation (a surface projection) of this solution to the irregular shape of a protein. The final electrostatic equations were of the Coulombic type and contained, in addition to the partial atomic charges, Qi, the fictitious image charges, Qi””,created at the dielectric boundary:

where E,,, and E~ are solvent and protein dielectric constants, R is the spherical protein radius, and xi is the distance from the ith atom to the center of the sphere). Cherfils et al. (1991), in their docking of the lysozyme-HyHEL-5 complex, employed simplified protein models with one sphere per residue and simulated annealing algorithms driven by a pseudo energy function proportional to the protein interface area. Docked complexes were subjected to conformational energy refinement with full atomic detail. Although a near-native complex configuration was generated and identified as a low-energy one, some other nonnative complexes could not be rejected based on the criteria used. Jiang and Kim (1991) developed a “soft” docking algorithm utilizing a cubical grid and a full molecular mechanics potential. When applied to the lysozyme-HyHEL-5 antibody complex, the correct docking solution was found to be among the top 500 configurations out of about 20,000 generated. Independently, Walls and Sternberg (1992) developed a soft algorithm that allowed for structural changes during docking. Docked structures were evaluated quantitatively based on protein surface complementarity and a simple electrostatic model that screened out unfeasible interactions. When applied to the HyHEL- 10, D1.3, and HyHEL- 10 antibody-lysozyme complexes, the method identified between 15 and 40 possible docking orientations with the native structures being ranked 3rd, 5th, and 30th. Pellegrini and Doniach (1993) reported on computer docking experiments involving lysozyme complexes with D1.3, HyHEL-5, and HyHEL10 that employed rigid structures and a two-step approach. First, a coarsegrained painvise atomic potential of the Sippl (1990) type was used to bring the two molecules together. The configurations obtained were then refined with use of the all-atom OPLS potential of Jorgensen and TiradoRives (1988) and a distance-dependent dielectric function. The native configuration was consistently found to be the preferred solution for all three complexes. Friedman et al. (1994) docked epitopic fragments (heptapep-

210

JIRI NOVOTNY AND JURCEN BAJORATH

tides) to the binding site of the antipeptide antibody B1312 (both the free and complexed X-ray structures), using the Metropolis Monte Carlo docking program of Goodsell and Olson (1990). The peptides Pro-His and Val-Pro-His, which contain residues experimentally identified as important for binding, docked correctly to both antibody structures, but all larger peptides docked correctly only to the complexed Fab, even when torsional flexibility was allowed in the ligand. 5. Hypothesis of Functional (Energetic) Epitopes

Immunochemists often observed that a small portion of an antigenic determinant was of crucial importance in defining its specificity. The term immunodominant (Sela, 1969, quoting Heidelberger) has commonly been used to describe this phenomenon. Does immunodominance have an identifiable molecular basis? The empirical Gibbs free energy calculations for antibody-antigen (Novotny et al., 1989; Novotny, 1991; Tulip et al., 1994) and enzyme-inhibitor (Krystek et al., 1993) complexes consistently indicated that only a small number of amino acids, approximately 30% of the total contact surface area, contributed actively to binding energetics. In the antibodies, the bottom part of the antigen binding cavity often dominated the energetics of binding, whereas in lysozyme, the energetically most important residues defined small (2.5 to 3 nm2) energetic epitopes. Thus, a concept of protein antigenicity emerged that invoked the active, attractive contributions mediated by the energetic antigenic epitopes and the passive surface complementarity contributed by the surrounding contact area (see also Section VIII). The concept offered resolution of an apparent paradox: on the one hand, a multitude of side-chain-side-chain interactions at the interface [-16 side chains in the antibody as well as in the antigen; see, e.g., Amit et al. (1986)J and, on the other hand, the experimentally derived size of the binding site as four to six amino acids (Haber et al., 1967; Sela, 1969; Schechter, 1971; Kabat, 1970). A number of experimental data consistent with the hypothesis of an energetic epitope have accumulated, including those obtained on antibodies to human growth hormone (Jin et al., 1992; Cunningham and Wells, 1993),3human placental lactogen (Lowman et al., 1991), the A repressor (Breyer and Sauer, 1989), the antilysozymes HyHEL-10 (Lavoie et al., 1992) and D1.3 (Hawkins et al., 1993), the anti-N9 neuraminidase NC41 (Nuss et al., 1993), anticytochrome c (Mylvaganam et al., 199l), and anticyclosporin (Rauffer et al., 1994) antibodies. Smythe and von Itzstein (1994) accepted the concept of a functional epitope as a starting point for their synthesis of

Jin et al. (1992) suggested the termfinctional eptiope instead of energetic epitope.

COMPUTATIONAL BIOCHEMISTRY OF ANTIBODIES

21 1

a biologically active, constrained cyclic peptide that mimicked the NC4 1 antineuraminidase antibody. The size of the functional epitope varies somewhat according to the criterion used for its definition. Jin et al. (1992) found that, per epitope, the number of alanine substitutions causing a >2- or >20-fold effect on binding affinity was on average eight and three, respectively, which is more in accordance with Nuss et al. (1993) than with the CONGEN calculations (Tulip et al., 1994; Novotny et al., 1989). Part of the discrepancy may arise because the large negative AGreslduc values of some residues in the CONGEN functional epitopes are due to favorable contacts made by main-chain atoms only (Arg-327 in N9-NC41) and can be “invisible” to mutagenesis. In the utmost limit of low molecular weight haptens with no formal charges and only one or two functional groups (e.g., digoxin; see Near et al., 1993), the functional epitope concept may not be applicable (Webster et al., 1994). In the calculations reported by Novotny et al. (1989) and Tulip et al. (1994), charged residues were high on the list of energetic residues. Jin et al. (1992), Kelley and O’Connell (1993), and Cunningham and Wells (1993) also reported that charged residues played a prominent role in most functional epitopes and that out of the average number of 8 residues causing a >2-fold reduction in affinity, on the average 2.8 are charged. The functional epitopes are mostly discontinuous (Jin et al., 1992; Tulip et al., 1994).As for predictions that some of the contact residues act in a repulsive manner and destabilize the complex, further experimental data are required to confirm that this is the case. The alanine scan of Jin et al. (1992) sometimes identified side chains that hindered antibody binding. Getzoff et al. (1988) reviewed the evidence indicating that, in heteroclitic antibodies, the contributions of some residues to binding affinity can be increased. D. Water-Mediated Binding

The complex of D1.3 antibody with hen egg white lysozyme is currently one of the best resolved antigen-antibody complexes, at 1.8 A (Bhat et al., 1994). At this resolution, about 50 water molecules were reported at or near the interface, with few of them actually trapped at the interface. The structure of the lysozyme complexed with the D1.3 mutant W92D (VL domain) was also solved (Ysern et al., 1994). Titration calorimetry of W92D mutant complex formation showed that the AAG of the reaction (--4 kcal, wild type-mutant) could be attributed to a smaller negative binding enthalpy (3.8 kcal) with few net changes in binding entropy. In the structure of the mutant, two water molecules occupied the space created by the smaller size of the Asp side chain compared to Trp.

212

FIR1 NOVUI‘NY AND ,JLiRC,EN BAJORATH

The phenomenon of water-mediated binding has been most extensively discussed for the trp receptor-operator system (e.g., Shakked et al., 1994). There, the specificity of DNA-protein interaction could be explained not only by direct hydrogen bonding but also by water-mediated hydrogen bonds. Comparison of the X-ray structures of the free and bound states of the DNA operator regulatory sequence made it clear that “the three hydration sites used to mediate protein contacts to the three critical bases of the operator half-site sequence are already fully occupied in the free DNA. The water molecules can thus be regarded as non-covalent extensions of the DNA bases which may be used as stereospecific recognition elements of the DNA target sequence” (Shakked et al., 1994). A full account of water-mediated interactions in antigen-antibody complexes requires knowledge of whether any given water molecule was bound to a protein prior to complex formation, or whether it became passively trapped at the interface. In the first instance, a prebound water molecule can be looked at as another protein side chain, and its interactions in the complex can be evaluated in a straightforward manner based on its protein contact and its partial atomic charge (see Section VI1,C). In the second instance, the protein-water-protein complex becomes a ternary complex of a “solute” water molecule and two protein molecules. In this case, it is necessary to estimate correctly the entropy decrease of the system due to imprisonment of the water molecule at the interface. A water molecule bound to protein may acquire new, productive waterprotein interactions (hydrogen bonds, van der Waals contacts) at the expense of those existing in bulk water prior to complex formation. One of the four possible water-protein hydrogen bonds would stabilize the complex by a varying amount, depending on the quality of the bond and the partial charge of the participating protein atom. In bulk water at room temperature, there are -3.5 hydrogen bonds per molecule (Lemberg and Stillinger, 1975) and the average hydrogen bond energy of liquid water is probably in the range 2-3 kcal/mol (Eisenberg and Kauzmann, 1969). Thus, to recover the bulk interaction energy, a protein-entrapped water molecule should gain at least -8 kcal in hydrogen bonding to protein groups, i.e., nearly -3 kcal per H bond if, as reported by Williams et al. (1994), three H bonds per molecule is the most common form of waterprotein interaction. The entropic cost of the transfer and complete immobilization of a water molecule from the liquid to the protein has been estimated to be -2 kcal/mol (Dunitz, 1994).In most situations, the free energy associated with entrapment of water in the compIex is expected to carry a AG close to zero at best, and would probably be unfavorable in many cases. This may be the reason why, in tight protein-protein complexes, intersurface-bound water is a relatively rare phenomenon.

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VIII. MOLECULAR BASISOF P R O T E I N ANTIGENICITY

The early serological experiments of Landsteiner (1962) and others showed that virtually any chemical structure attached to a protein molecule can elicit an antigenic response. The early era of hapten research has given way to the current age of antigenicity research on peptides and proteins. The comparison of properties of antibodies elicited with protein antigens, on the one hand, and their mimics, short peptides, on the other hand, has formed most of our views (Sela, 1969; Benjamin et al., 1984; Tainer et al., 1985; Novotny et al., 1987; Getzoff et al., 1988; Colman, 1988) on the molecular origin of antigenicity. In discussing the molecular basis of antigenic response, it is important to distingiush between the terms antigenicity and immunogenicity (Benjamin et al., 1984). Antigenicity refers to the ability of a protein surface region to be potentially antigenic, while immunogenicity refers to the ability of any antigenic site to elicit such a response under particular experimental conditions such as the immunization protocol, and the genetic constellation of the organism [an “immunopotent” determinant according to Sela (1969)]. However, bona fide antigenic sites may not be immunogenic in certain experimental situations (“immunosilent,” Sela, 1969). Identification of antigenic epitopes can be based only on indirect experimental procedures, such as methods involving the comparative strength of binding of the same specific antibody to homologous proteins with a small number of amino acid replacements (Benjamin et al., 1984); NMR hydrogendeuterium exchange experiments (Paterson et al., 1990); and X-ray crystallography of antibody-antigen complexes ( h i t et al., 1986). Antiprotein antibodies sometimes specifically recognize short peptides (tetra- to hexapeptides), and such antibodies can be elicited by synthetic peptide antigens. Often a single native conformation of a peptide is recognized, such as the disulfide-bonded loop peptide of lysozyme: antiloop antibodies do not react with peptides in which the disulfide bond has been reduced (Amon et al., 1971). The majority of antigenic sites in proteins, however, seem to consist of amino acids that are not contiguous in the amino acid sequence (composite or discontinuous epitopes). This is simply a consequence of the large contact area between antibodies and antigens (- 800 A*), and the low probability that such a large surface would be contributed by a contiguous polypeptide segment (Barlow et al., 1986). Based on a long history of experimental work, some researchers concluded that several discrete antigenic sites exist on protein surface (e.g., Atassi, 1975, 1978), implying that certain surface regions are more antigenic than others. Other researchers have argued that many more mutually overlapping epitopes exist on protein surfaces and that the whole protein surface is antigenic (Benjamin et al., 1984).

214

J l K I N O V U I N Y AND JUKGEN BAJOWI'H

A. Segmental Flexibility and Surjace Exposure Westhof et ul. (1984) and Tainer et al. (1984) noticed a correlation between the average backbone crystallographic B factors and locations of antigenic sites and proposed that segmental flexibility (assumed to be associated with the cause of high B factor values) is an important component of antigenicity (Tainer et al., 1984, 1985). Implicit in this proposal was the notion that most antigen-antibody interactions are accompanied by an induced fit in the antigen, and that antigenic epitopes frequently rearrange their conformations to maximize productive noncovalent (electrostatic, van der Waals) interactions with binding sites (Geysen et al., 1987, Getzoff et al., 1987). An alternative antigenic theory was suggested by Padlan (1985) who proposed that the antigenic potential of a polypeptide segment was a simple additive function of atomic properties such as surface exposure and polarity. The segmental flexibility theory of antigenicity was challenged by several groups (Novotny et al., 1986b; Fanning et al., 1986; Thornton et al., 1986) on the grounds that ( 1 ) B factors represented parameters combining the effects of thermal mobility and static crystalline disorder into one measure, often making it dificult to correlate them unequivocally with either the static or the dynamic aspects of the structure; and that (2) molecular properties other than segmental flexibility (in particular, surface protrusion) were also correlated with protein antigenic sites, and the average backbone B factors. For example, the prominent antigenic epitopes may simply be the most protruding parts of the surface, easily accessible to the large antibody molecules. In fact, correlation among surface protrusion (static accessibility), segmental flexibility, and antigenicity was so strong that it was difficult to design experiments that would isolate the relative importance of these various properties. In this context, analysis of flexibility and antigenicity properties in scorpion neurotoxins, small molecules of 46 amino acids containing four disulfide bridges (Fig. 15), was particularly illuminating. The experimental work oFEl Ayeb et al. (1983, 1984) and Bahraoui et al. ( 1986) established four antigenic epitopes in the Androctonus australis neurotoxin and localized them in the amino acid sequence. Novotny and Haber (1986) calculated large-probe (r = 10 A, comparable in size to antibody domains) accessibility profiles of the Centruroides sculpturatus neurotoxin, a molecule closely similar to the of A. australis neurotoxin, using the X-ray coordinates of Almassy et al. (1983). Six prominently exposed regions were identified, clustered in four surface patches that were identical to, or overlapped with, the experimental antigenic epitopes. Next, Novotny and Haber (1986) carried out molecular dynamics simulations on the C. sculpturatus structure, computed average backbone B fac-

COMPUTATIONAL BIOCHEMISTRY OF ANTIBODIES

215

FIG 15. Ribbon diagram ofthe scorpion neurotoxin fold. Disulfide bonds are shown as light sticks and large probe-exposed loops (antigenic regions). are highlighted in a dark color. The N terminus of the polypeptide chain is approximately in the middle of the figure and the C;-terminal Cys is at the lower left. Two turns of an a helix are visible at the upper right, and beneath the a helix is a three-stranded /3 sheet.

tors from the simulation, and compared results with the X-ray-derived B values. Most of the neurotoxin structure and, in particular, three out of the four antigenic sites, were found inflexible, asjudged both by the computed and the crystallographic B factors (Fig. 16). The remaining flexible epitope was associated with only marginal above-average maxjma of backbone B values, corresponding to rms displacements of 0.5 A. It thus appeared that, at least in this molecule, antigenicity was determined by an exceptional surface exposure of relatively short loop segments, and that segmental flexibility was not an essential component of antigenicity. These conclusions were supported by a later study (Granier et al., 1989) based on the crystal structure of the A. australis toxin determined at 1.8 resolution (Fontecilla-Campset a,l., 1988).On refinement to 1.3 A resolution (Housset et al., 1994), the average backbone B factor of the A . australis toxin structure remained exceptionally low: 10 A2,with a maximum at 16.2 A2 and a minimum at 7.2 .k2.

216

JIRI NOVOTNY AND JURCEN BAJORATH

7.

8.

1.

0.

10

20

30

40

60

e0 .

Sequence number

FIG. 16. Large-probe accessibility contact surface and crystallographic B factor profiles for the A. australis scorpion neurotoxin molecule. Heavy line represents the smoothed accessible contact surface calculated with a spherical probe 10 %, in radius, light line represents B factors. Antigenic peptides (see Section VIII,A) are delineated by small squares at the top of the figure.

It seems significant that the calculated energetic epitopes cluster along the most exposed regions in the two proteins whose antigenicity has been studied most thoroughly: hen egg white lysozyme and influenza neuraminidase (Fig. 17). Similarly, the complete antigenic analysis of human growth hormone (Jin et al., 1992) showed the epitopes to correlate well with the most protruding regions of the molecule. It is interesting that both the experimental data of Jin et al. (1992), and the calculated frequency of side chains occurring in protein surfaces accessible to large spherical probes (Novotny et al., 1987), show a prominence of long, formally charged or dipolar side chains (Arg, Lys, Glu, Gln, Asp, Asn; see Table VI). Antibodies themselves can become antigens of other antibodies and Novotny et al. ( 1986a) investigated a correlation between immunoglobulin antigenic epitopes (i.e., locations of the idiotypic, allotypic, and isotypic serological markers) and large-probe accessibility profiles of selected antibodies. The experimental epitopes always corresponded to convex parts of an antibody surface made by reverse turns. The computed protruding surfaces occurred in homologous positions in all the immunoglobulin chains for which the computations were carried out, and most of the Bsheet surfaces of the domains were found to be poorly antigenic. The C H ~

217

COMPUTATIONAL BIOCHEMISTRY OF ANTIBODIES

A 7.

D1.3. Hy-10

Hy-5

Hy-5. Hy-10

Hy-10

D1.3

e.

c (

H

5.

X

"8

4.

5 ti

3.

8

2.

s 1.

0.

LO

20

30

60

50

40

90

80

70

110

100

120

13C

Sequence number

B I

I

m

4.

-

0

0

2

3.

X

"!

5 f;

2.

sI .Id

0

1.

0.

l!L 320

I

I

o

ym

I

I 0

rn

I 0

I

I

NClO epitope

m

:II 380

400

I

I

420

Sequence number

FIG. 17. Large-probe accessibility contact surface profiles for (A) lysozyme and (B) influenza neuraminidase. Positions of the energetically most important residues (the functional epitopes) are highlighted by vertical bars and squares and circles at the top of the figure.

218

JIRI N O V O T N Y AND J U R G E N BAJORATH

and CH3domains had many more calculated antigenic sites than the Fab fragment. Variable-domain epitopes (idiotopes) involved both hypervariable and framework residues, and only about 25% of the hypervariable residues were strongly antigenic. Pedersen et al. (1994) have carried out a statistical analysis of all the surface-accessible residues in human and murine Fv domains. They found that precise patterns of exposed residues were different in the two species, and that most surface positions had strong preferences for a small number of residue types. These observations have practical implications for the humanization of murine antibodies (see also Section IX,E). A large body of indirect evidence seems to indicate that surface protrusion is an important characteristic of antigenic sites in proteins. Side-chain polarity and higher-than-average backbone B factors also correlate well with antigenicity, but a causal link between these properties and antigenicity is less straightforward than that between protrusion and antigenicity. The conjecture that antigenicity is mostly determined by surface protrusion provides a natural link between the two extreme antigenicity theories (“distinct antigenic epitopes exist” vs “the whole surface is antigenic”) by introducing the concept of antigenic probability which varies along the surface. B. What Is a Protein Epitope?

“An antigenic epitope” is an operational definition whose factual content differs depending on whether we emphasize energetics of complex formation, complementarity of antigen-antibody surfaces, or other phenomena. According to the method used to define the epitope, one may thus arrive at different conclusions about antigenicity (Geysen et al., 1987; Laver et al., 1990; Greenspan, 1992). In addition to crystallographic epitopes and functional (energetic) epitopes, we also have NMR epitopes defined by the extent to which bound antibody prevents deuteriumhydrogen exchange on the backbone segments of the antigen (Paterson et al., 1990; Benjamin et al., 1992) and mutational epitopes deduced from the effects of single-residue substitutions (either synthetic or natural) on the strength of binding (Smith-Gill et al., 1987; Smith and Benjamin, 1991; Smith et al., 1991; Prasad et al., 1993). The mutual relations of these various definitions are only now beginning to be delineated. Sheriff et al., (1987), Padlan et al. (1989), and Prasad et al. (1993) compared the X-ray structures and epitope mutational data on the HyHEL-5, HyHEL-10, and phosphocarrier protein HPr-Jell42 antibody complexes. By and large, the crystallographic and mutational epitopes overlapped well. The limitations of the mutagenesis approach became apparent when, of the 14 amino acid

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residues of the HPr protein found in contact with the antibody binding site, 9 were correctly assigned by the mutagenesis studies, 1 could not be altered by mutations, 2 appeared to be critical for the protein fold, and 2 other peripheral side chains had a minimal effect on antibody binding. Interestingly, 4 amino acids adjacent to the epitopic residues were incorrectly assigned to the Jell42 epitope. The concept of a functional (energetic) epitope (see Section VI1,D) provides an additional perspective on antigenicity. The calculated energetic epitopes (Novotny et al., 1989; Novotny, 1991; Tulip et al., 1994) clustered along the most exposed regions in the two proteins whose antigenicity has been studied the most thoroughly, i.e., hen egg white lysozyme and influenza neuraminidase (Fig. 17). The complete antigenic analysis of human growth hormome gin et al., 1992) also showed the functional epitopes to correlate best with the most protruding regions of the molecule. Both the experimental data of Jin et al. (1992) and the calculated frequency of side chains occurring on protein surfaces accessible to large spherical probes (Novotny et al., 1987) showed a prominence of long, formally charged or dipolar side chains (Arg, Lys, Glu, Gln, Asp, Asn; see Table I) in the functional epitopes. At the same time, however, the size of the crystallographic epitope indicates that a surface area larger than the functional epitope must be complementary to the antibody surface. C. Cross-Reactivity in Proteins: Influenza Neuraminidase How cross-reactive are individual protein epitopes? How degenerate are proteins as antigens? The fact that a delimited patch of protein surface can support several overlapping, different epitopes has by now been well established (Darsley and Rees, 1985; Malby et al., 1994; Lescar et al., 1995; Bottger et al., 1995). In the two cases where cross-reactive epitopes were studied in atomic detail, degenerate binding of the same antigenic motif (Malby et al., 1994), or two different antigenic motifs by the same antibody (Lescar et al., 1995), did not require any chemical similarities between the different epitopes or different binding sites. In the N9 neuraminidase complexes, -80% of the NC41 and NClO antibody epitopes overlap (Malby et al., 1994), and one might expect about two-thirds to threequarters of the energetic neuraminidase residues to be identical, and to contribute comparable binding energies, in the two complexe~.~ This was clearly not the case, however, as established both by experiment (Malby This was the situation invariably found with enzyme-inhibitor complexes such as, e.g., the eglin inhibitor in complex with chymotrypsin and with subtilisin. See Krystek et al. (1993) for more details.

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et al., 1994; Nuss et al., 1993; Webster et al., 1987) and by calculations (Tulip et al., 1994). The two antibodies, NC41 and NC10, engaged different side chains of the same neuraminidase surface to create stable complexes (Table VIII). Is an area of protein surface a single antigenic epitope, or is it a multitude of different overlapping epitopes? The term epitope being an operational one, the answer to this question may also be formulated operationally. About 50-60% of protein surfaces is made of polar atoms including those that are formally charged. The charged atoms occur mostly at prominent surface convexities where they are most efficiently solvated. The Asp, Glu, Lys, and Arg side chains are not only preferentially located in loops but are themselves the longest side chains. Naturally, protrusions and their polar atoms constitute the best anchor points for a firm attachment of antibodies but, depending on the topography of the larger, adjacent surface area and relative dispositions of the multitude of surrounding polar atoms (both capable of making, and when in the complex required to make, hydrogen bonds) many alternative solutions exist for approximately complementary binding site surfaces. Thus, the antigenic code, akin to the stereochemical code of protein structures (Section III,B), may be degenerate (Malby et al., 1994) in the sense that many different surface shapes can complement an antigenic determinant. The degeneracy of both the stereochemical and antigenic codes may not be accidental. Protein-protein interactions follow the same physical rules as protein folding events, and approximately similar phenomenology can be expected in both types of interactions. IX.

ANTIBODY

ENGINEERING

The modular three-dimensional architecture of immunoglobulins (Section II1,A) and T-cell receptors lends itself well to protein engineering schemes that shuffle, transpose, and reconnect the domains into chimeric proteins with hybrid structures and novel properties. The rapid development of antibody engineering has been stimulated by three important technological advances: ( 1) Rapid development of gene cloning technologies and the advent of the polymerase chain reaction (PCR), allowing subcloning of eukaryotic genes into bacterial plasmids (Boss et al., 1984; Cabilly et al., 1984). Nevertheless, the expression of chimeric immunoglobulins in transformed lymphoid cells such as myeloma or hybridoma (Rice and Baltimore, 1982; Oi et al., 1983; Ochi et al., 1983; Rusconi and Kohler, 1985) has remained a powerful experimental tool. (2)Progress in the controlled expression of proteins from plasmid-inserted genes in bacteria and other organisms, i.e., yeast (Wood et al., 1985) and baculovirus

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TABLE VIII

AGresduem Calculated for N 9 Neuraminidme Epitopes (-80% Overlapping) in NC41 and NCI 0 Antibody Complexesa NC41 Antibody complex Residue Attractive LYS-463 Lys-432 Ala-369 Asn-400 Thr 401 Arg 327 Ile 368 Pro 43 1 Ser 367 Lys 435 Neutral Asn 329 Pro 328 Leu 399 Pro 326 Gly 343 Trp 403 Ser 370 Asn 345 Man 200D Asn 344 Man 200F Ile 149 Asn 347 Ile 366 Ser 372 Asp 434 Repulsive Asp 402 Glu 433

NClO Antibody complex Residue

-4.8 -4.0 -3.4 -2.6 -2.4 -1.9 -1.8 -1.4 -1 .o -1 .o -0.8 -0.7 -0.6 -0.5 -0.5 -0.5 -0.3 0.0 0.0 0.1 0.2 0.3 0.3 0.5 0.7 0.7

1.5 2.0

AGresidue

Attractive Lys.432 Asn-329 Man 200F Ala-369 Thr 401 Pro 328 Gly 343 Ser 370

-3.6 -2.2 -2.0 -1.6 -1.5 -1.3 -1.0 -1 .o

Neutral Pro 331 Pro 342 Trp 403 Man 200E Man 200D Asn 400 Ile 368 Thr 332 LYS-336 Ile 366 Val 333 Ser 367 Asp 330 Asn 344

-0.6 -0.6 -0.6 -0.5 -0.3 -0.2 0.0 0.0 0.0 0.2 0.2 0.3 0.9

Repulsive Tyr 341 Ser 372

1.1 1.1

a Data in kcal/mol; see Tulip et al. (1994) for details. Amino acids set in boldface type are those mutated by Nuss et al. (1993) and Webster et al. (1987).

and plant cells (Hiatt et al. (1989). Proteins were obtained either as secreted, refolded, soluble species or as insoluble, denatured intracellular aggregates, inclusion bodies, that were easy to isolate but had to be solubilized and renatured before a functional protein was obtained. (3) Computer-

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aided structural design techniques, supported by the numerous X-ray crystallographic coordinates of diverse antibodies. In this section, we briefly discuss chimeric antibodies and T-cell receptors, covalent Fv fragments (single-chain or disulfide-bonded), heterospecific bifunctional constructs, and various domain humanization schemes (Neuberger et al., 1984; Riechmann et al., 1988) with a focus on computeraided structural design. A . Chimeric Antibodies via Domain Interchange Some of the first synthetic chimeras were mouse antigen binding domains and V,) implanted on human constant-region domains (Boulianne et al., 1984; Morrison et al., 1984; Takeda et al., 1985);VH domains spliced onto CLdomains giving rise to functional, antigen-specific, VH-CJVI.-CL L chainlike dimers (Sharon et al., 1984); recombinant mouse antibodies with novel effector functions engineered via H chain constant domain swaps (Neuberger et al., 1985; Schneider et al., 1988); and domain deletions or insertions to produce shortened antibody-like molecules (Igarashi et al., 1990) and antibodies with altered oligomerization states. As a rule, the structural design of these hybrids was straightforward (i.e., genes coding for complete domains were swapped, by subcloning, between molecules). More-ambitious examples of antibody engineering included the replacement of selected immunolgobulin domains with foreign proteins [e.g., enzymatically active bacterial P-lactamase (Goshorn et al., 1993; De Sutter and Fiers, 1994)l. Highlights of these constructions include (1) CD4 and CTLA4 immunoadhesins (proteins composed of IgG constant domains, the Fv modules being replaced with two extracellular domains of the CD4 receptor (Capon et al., 1989) or the CTLA4 marker (Linsley et al., 1991) for use in acquired immunodeficiency syndrome (AIDS)therapy; (2) immunoligands such as the interleukin-2 molecule fused to IgG constant regions (Landolfi, 1991); (3) an exogenous peptide epitope implanted in lieu of the H chain third hypervariable loop (Sollazzo et al., 1990); (4) metal coordination sites engineered into an antibody binding pocket (Roberts et al., 1990); and divalent molecules combining the complete class I major histocompatibility complex (MHC) molecule with an immunoglobulin heavy chain (Dal Porto et al., 1993). Finally, various chimeric constructs consisting of T-cell receptor (TCR) C domains and antibody V domains, or TCR-antibody polypeptide chain aP or yd heterodimers, were also assembled and shown to carry functional traits characteristic of both parent molecules (Gascoigne et al., 1987, Gross et al., 1989, Mariuzza and Winter, 1989; Becker et al., 1989; Goverman et al., 1990; Schearman et al., 1991; Gregoire et al., 1991; Eilat et al., 1992). (VL

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B. Single-Chain Fv Fragments, “Diabodies, Fv-Toxin Congugates ”

The production of large quantities of stable Fv fragments in bacteria was seriously hindered by the fact that two polypeptide chain segments, VL and VH, had to be separately refolded and reformed into a noncovalent dimer. The problem has been circumvented by the design and successful construction of a single-chain Fv where the C terminus of a VH (alternatively, V,) domain was connected to the N terminus of the VL (VH)domain by a polypeptidic linker. The following issues had to be considered in the design of the linker: (1) connection polarity, i.e., the question of a possible preference for leading the linker from the C terminus of the Vr. domain to the N terminus of the VH domain, or vice versa; ( 2 ) the minimal, and possibly the maximal, length of the linker; (3) the nature, i.e., the detailed amino acid sequence, of the linker, with special reference to protein folding and proteolysis. Two different single-chain Fv designs were described in 1988, both involving the use of computer modeling to design the molecule but approaching the preceding questions in different ways. In the work of the HarvardJ Creative Biomolecules group (Huston et al., 1988), the order of domain connection was deemed unimportant in view of the pseudo symmetry of the Fv fragment, and the polarity chosen was VH+VL. In the work of the Genex group (Bird et al., 1988) the polarity was VL+VH. The success of both designs immediately proved the functional equivalence of both solutions. The HarvardKreative Biomolecules group obtained the distance to be spanned by the linker from Fab crystal stryctures as -3.5 nm which, considering the length of a peptide unit (3.8 A), would require at least 11 amino acid residues. To interfere minimally with refolding of the two immunoglobulin domains, and also to maximize the flexibility of the linker, a sequence rich in glycines, (Gly-Gly-Gly-Gly-Ser)3,was chosen. Such a sequence should also be rather resistant to proteases. The design philosophy of the Genex group relied on searches through the Brookhaven Protein Data Bank for peptides of proper molecular dimensions to bridge the interdomain distance and to introduce correct peptide bond angles at the N and C termini of the prospective linkers. Alternatively, linkers were designed by an incremental addition of short peptides from the C terminus of the VL to the N terminus of the VH. Some linkers were designed to minimize interactions with the Fv, whereas others were designed to fit into a groove on the back of the Fv structure primarily with the use of alternating glycine and serine residues and Glu and Lys included to enhance solubility. Thus, one of the successhl linkers had the sequence EGKSSGSGSESKST. Since the original studies, dozens of papers have been published describing the use of single-chain Fv fragments for various diagnostic and

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therapeutic purposes, and in investigating various aspects of the design (see, e.g., Huston et al., 1991, and Pluckthun, 1992, for reviews). It seems that many amino acid sequences can satisfy the purpose of the linker, although some were claimed to be superior from the point of view of bacterial secretion (Takkinen et al., 1991). Argos (1990) published a detailed survey of oligopeptide linkers in natural multidomain proteins and recommended candidates for general gene fusion work. He concluded that, for the linker to be optimally extended, it should contain small (Gly) and polar (Ser, Thr) amino acids. Thus, e.g., the improved linker described by Adams et al. (1993) and Hilyard et al. (1994) had the sequence (Ser-Ser-Ser-Ser-Gly)3,while that used by Whitlow et al. (1993) had the sequence GSTSGSGKPGSGEGSTKG. For single-chain Fv fragments, the critical length requirement for the linker seems to be 12-13 residues, as 10-residue linkers did not sterically allow the VL-VH domain dimer formation. This observation was cleverly exploited by Holliger et al. (1993) and Hudson et al. (1994) in the design of “diabodies,” i.e., small bivalent and bispecific antibody fragments. By using a linker too short to allow pairing between the two domains of the same chain (either 5 or 10 residues of linker length), the VL and VH domains were forced to pair with the complementary domains of another chain to create two different antigen binding sites. An efficient domaindomain packing at the two contacting ends of the dimeric Fv modules was investigated by computer graphics (Holliger et al., 1993), and it was found that it might be possible to join the C terminus of the VH domain directly to the N terminus of the VL domain and dispense with the linker polypeptide. Indeed, fragments with no linker proved to be dimeric and bispecific when expressed in bacteria and the X-ray structure of the diabody L5MK16, specific for phosphatidylinositol, turned out to be very similar to that predicted by modeling (Perisic et al., 1994). According to Desplancq et al. (1994) and Whitlow et al. (1994), single-chain Fv fragments have a natural tendency to form heterobivalent dimers and perhaps even higher oligomers. Thus, heterodimers of antifluorescein and antitumor scFv fragments 4-4-30 and CC49, respectively, formed with a linker as long as 12 residues (Whitlow et al., 1994). Bivalent dimers of the antitumor antibody B72.3 were obtained even with a linker 30 residues long, and better activity was observed with the domain arrangement VL-linker-VH compared to VH-linker-VL (Desplancq et al., 1994). NMR data from the McPC 603 single-chain Fv fragment using the (GGGGS)s linker (Freund et al., 1993) indicated relative independence of the linker from the rest of the structure, and confirmed its high flexibility. Two X-ray crystallographic structures have been reported for single-chain Fv fragments (Kortt et al., 1994; Zdanov et al., 1994). In both, including the

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1.7 A resolution structure of the carbohydrate-binding antibody Se155-4 (Zdanov et al., 1994) single-chain Fv complexed with the antigen, the linker was largely invisible due to crystalline disorder. Antibody binding sites, with their unique specificities, can be used to target proteins (enzymes, toxins) to cells and tissues. An example of this approach to human therapy is antibody-targeted dissolution of infarctionrelated blood clots by proteolytic enzymes (Fab urokinase, Haber et al., 1989). The single-chain Fv technology has been particularly successful in supporting bacterial production of effective immunotoxins. Thus, singlechain Fv of antitumor specificity with a modified Pseudomonas exotoxin (PE40) attached to its C terminus is a powerful and specific anticancer agent (Chaudhary et al., 1989). An extensive literature, exploring various aspects of targeting, toxin structure, optimal expression, and other aspects of this topic exists by now, and is not reviewed here in detail. One practically relevant bifimctional construction was the antidigoxin single-chain Fv fragment with the -40-residue fragment B of the staphyloccocal protein A attached to its N terminus (Tai et al., 1990). The fragment B effector domain, through its affinity for the immunoglobulin Fc fragment, simplified purification (via affinity chromatography) of the Fv construct. The single-chain technology has also been applied successfully to T-cell receptors and MHC proteins. Fv-like, soluble single-chain T-cell receptor V P a fragments were expressed in bacteria and shown to possess essentially the same antigen specificity as the parent receptor (Novotny et al., 1991; Ward, 1992; So0 Hoo et al., 1992; Schodin and Kranz, 1993; Kurucz et al., 1993). Functional, soluble MHC-like proteins were prepared by tethering the three extracellular domains (al,a2and a3)of the mouse H-2 class I a chain to the p2 domain (Mottez et al., 1991, Mage et al., 1992). Finally, Eshhar et al. (1993) designed and constructed chimeric genes composed of a single-chain Fv domain linked with y or 5 chains, the common transmembrane, signal-transducing subunits of the immunoglobulin, and T-cell receptors. The chimeric genes were expressed as functional cell surface receptors in a cytolytic T-cell hybridoma, and they triggered interleukin-2 secretion from the cells on encountering antigen to which the single-chain Fv specificity was directed (the hapten trinitrophenyl). Such chimeric receptors can provide T cells and other lymphocytes with antibody-type recognition coupled directly to cellular activation. A diagrammatic summary of Fv fragment-based single-chain constructs is given in Fig. 18.

C. Disuljide-Bonded Fv Fragments It is known that Fv fragments of different specificities, and different amino acid sequences, vary widely in stability (Padlan, 1994).Although the

226

FIG 18. Protein engineering of antibody binding sites: a schematic diagram. VH and VI. domains are shown as open circular sections, peptide linkers as thick lines, leucine zippers (a helical dimers) as filled rectangles, and cell toxins, enzymes, etc., as filled circles. (Tol,) From left to right, a single-chain Fv fragment (scFv), a disulfide-bonded Fv fragment (SSFv), a bivalent diabody, and a bivalent, disulfide-bonded scFv dimer. (Bottom) From left to right, an scFv attached to an effector molecule (e.g., Pseudomonas PE40 cellular toxin), a bivalent scPv-leucine zipper construct, and a bivalent scFv chimera with three scFv fragments chained together by a flexible linker. Both homo- and heterodimeric leucine zipper sequences are known, allowing in principle a noncovalent assembly of homobivalent and heterobivalent antibody-like chimeras. Similarly, homo- and heterobivalent, linker-chained scFv constructs are possible. Bivalent scFv chimeras based on four-helix bundles (the ROP dimer of the a helix-turn- helix motif). were also described (see Section IX,F) but are not shown. Note also that antigen combining sites (i.e., the three hypervariable loops in the VH and V1, domains) can be transferred from an Fv framework to another uones et al., 1986), and different pairs of VH and V1- domains can be recombined to give novel antigen binding sites.

critical interdomain side-chain contacts accomplishing the “three-layer” P-sheet-P-sheet packing are conserved in the variable domains of antibodies and T-cell receptors, about 40-50% of the domain-domain interface is contributed by hypervariable loop residues, suggesting that the strength of domain-domain contacts may be modulated considerably. Quantitative information is scarce, but one of the most stable VL-VH

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dimers may be that of the antidigoxin antibody 26-10 (Anthony et al., 1992), approaching the V r P H association constant of 1 nM. At the other extreme, the McPC 603 Fv fragment was found to be only marginally stable (Glockshuber et al., 1990), with an estimated domain-domain association constant of less than 1 p M . According to Glockshuber et al. (1990), three different strategies, namely, (1) chemical cross-linking, (2) introduction of disulfide bonds, and (3) generation of a single-chain protein, all stabilized the Fv fragment in a comparable way. To introduce disulfide bonds into the Fv fragment, Glockshuber et al. (1990) used the computer program of Pabo and Suchanek (1986) that systematically scans intra- or intermolecular residue pairs and selects those with the Cp-Cp distance close enough to support a SS bridge (-4-5 A). The two disulfide bridges Glockshuber et al. (1990) introduced into the McPC 603 VH and Vr domains were relatively close to the third CDR loop: V1.55 and VH108 (L chain and H chain, respectively), and G56C and T106C (L chain and H chain, respectively). Jung et al. (1994) used molecular graphics and computer model building tools to identify two possible interchain disulfide bond sites in the framework region of the Fv fragment, distal from the antigen combining site (Fig. 19). Of the two sites identified, i.e., VH44-vL105 and vH111VL48, the former was tested by constructing a chimeric protein composed of a truncated form of Pseudomonas exotoxin and the Fv fragment of the monoclonal anticancer antibody B3 (Brinkmann et al., 1991; see also Webber et al., 1995). The chimeric toxin was found to be just as active as the corresponding single chain counterpart and considerably more stable. Reiter et al. (1994a) then showed that the latter disulfide site, VH11 l-Vl~48, could also be used to generate a functional disulfide-bonded B3 Fv fragment. Reiter et nl. (1994b) extended the disulfide-bonded constructs to two more Fv fragment-Pseudomonas toxin chimeras, generating cytotoxic proteins with full activity, improved stability, and a good yield in bacterial expression. Thus, SS-bridged Fv fragments may be more useful than single-chain Fv immunotoxins as therapeutic and diagnostic agents where inexpensive production and large quantities of refolded material are required, The single-chain Fv fragments may retain their usefulness in applications such as recombinant membrane-bound Fv receptors (Eshhar et al., 1993), phage surface display of complete binding sites, and heterospecific bifunctional miniantibodies.

D. Humanization of Mouse Monoclonals Monoclonal antibody therapy has become an attractive alternative in the cure of several disease states, such as allergy (Kolbinger et al., 1993) and cancer. Immunoglobulin-doxorubicin conjugates (Trail et al., 1993)

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FIG.19. Disulfide bond engineered into the Fv fragment. The Molscript ribbon diagram shows the VL (heavy lines) and the VH (light lines) domains. Carbons of side chains H44 and L100, which were replaced with cysteines by Jung et al. (1994), are shown as van der Waals radii spheres.

and single-chain Fv-Pseudomonas toxin chimeras are currently in human clinical trials. One of the major potential drawbacks of prolonged administration of mouse hybridomas, or fragments thereof, is onset of an immune response against the mouse framework antigenic determinants. To diminish this problem, murine monoclonals can be humanized by protein engineering. In therapy based on complete antibodies or Fab fragments,

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most foreign determinants can be eliminated by grafting the mouse VLand VH domains onto the human constant domains (Sahagan et al., 1986, Sun et al., 1987). More fundamentally, the six murine hybridoma hypervariable loops forming the antigen combining surface can be implanted onto a human VdV, framework, producing functional chimeric Fvs that retain the original antigenic specificity (Jones et al., 1986; Riechmann et al., 1988; Verhoyen et al., 1988).This fine molecular surgery is not always successful. As discussed in Section VI,C,2, the relative orientations of the CDR loops and their conformations are supported by several framework residues. Experience has shown that these side chains must be transplanted together with the loops in order to retain the full antigenic activity of the chimera. Computer-aided structural analysis of framework-CDR loop interactions helped to rationalize humanization protocols. Aspects of this analysis have been discussed in Section VI, but a few additional comments are given here. Difficulties encountered in CDR loop grafting are illustrated, e.g., by the work of Kao and Sharon (1993) on a hybrid antibody consisting of the anti-p-azophenyl arsonate framework (hybridoma 36-65) and antidextran CDR loops (hybridoma 26.4.1). Without the use of structural analysis or modeling, and with the Kabat et al. (1977) definition of CDR loops, all attempts failed to produce a functional chimera with VH and VL 36-65 frameworks and 26.4.1 CDR loops, although a partial chimera, constructed from a hybrid H chain and the native antidextran L chain, was fully active. The humanized anti-Tac antibody (with antiinterleukin-2 receptor activity) was prepared by Queen et al. (1989) with the use of human frameworks that maximized homology with the anti-Tac framework sequences. In addition, a computer model of the anti-Tac antibody, built with the ENCAD program of Levitt (1983), was used to identi5 several framework positions (H chain 27, 30, 48, 67-68, 98, and 106, L chain 47 and 59) which were likely to interact with the CDR loops or antigen. The humanized antibody retained about one-third of its affinity for the antigen, compared with the wild-type antibody. In the trial-and-error approach of Gorman et al. (199 1) a chimeric form of an anti-CD4 antibody, based on the framework of the human myeloma KOL, possessed essentially native antigen affinity,while a chimera based on the NEW antibody framework showed only a poor affinity. The most successful humanization CDR loop grafting protocols documented in the literature employed computer-built models of the chimeric Fv fragments. Typically, these studies report a judicious choice of frameworks, transfer of the critical loop-supporting residues from the wild-type antibody, and the canonical loop structure approach to model generation. In one case (Nakatani et al., 1994) the CDR loops were grafted on, and

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QUANTNCHARMm homology models were built for, as many as nine different frameworks. Each construct was assessed for biological affinity. One of the humanized anti-IL-2 (B-B10) receptor antibody variants, M5, showed nearly the same activity as the mouse wild type. Some of the best documented examples of the humanization of a group of antibodies were reported by the Genentech group (Carter et al., 1992; Kelley et al., 1992; Presta et al., 1993) who also reported crystal structures of three humanized fragments, one Fv and two Fab (Eigenbrot et al., 1993, 1994). The crystallographic structures represented different variants of the 4D5 antibody against a proto-oncogene HER2 gene product p185. The X-ray structures attested to an excellent accuracy of model building: The average rms deviation of the computer-built models from the X-ray structures was within the range of those observed among the X-ray structures themselves. The modeling protocol of the Genentech group relied on the generation of consensus coordinates based on the crystal structures of seven different Fab fragments. The consensus structure is believed to have eliminated inappropriate structural idiosyncrasies that may be present in a single structure. Derivation of the consensus framework, with use of the program INSIGHT (Molecular Simulations, Inc.), involved ( 1) independent definition of the p-sheeted segments; (2) least-squares superposition of the consensus p strands from all the structures onto the same template structure; (3) redefinition (filtering) of consensus segments based on a Ca-Ca distance criterion (i.e., only a carbons closer than 1 A to the template were retained in the template; generally, p strands passed this test, whereas many loops did not); (4) calculation of average Cartesian coordinates for all the consensus backbone atoms; (5) addition of conserved side chains to the consensus structure; and, finally, (6) addition of the modeled CDK loops to the consensus structure, based on the Chothia et al. (1989) classification of canonical loops. Often, no antibody template could be found for the H3 loop. In that case, loops of the same length were imported from nonimmunoglobulin structures and the resulting models energy-minimized in the DISCOVER (Molecular Simulations, Inc.) or CHARMm (Molecular Simulations, Inc.) program. The humanization procedure reported by Hsiao et al. (1994) likewise relied on the comparison of several immunoglobulin frameworks. The most homologous sequences were selected as structural templates and the consensus framework was generated by superposition of invariant residues at the VL-VH interface (Novotny and Haber, 1985; Novotny and Sharp, 1992). Where possible, the Chothia et al. (1989) canonical loops were utilized; alternatively, the loop selection procedure of Jones and Thirup (1986) was employed to extract approximate loop conformations from the

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Brookhaven Protein Data Bank. Then, with the use of computer graphics, side chains were compared residue by residue to identify framework positions potentially critical for the structural integrity of the combining site. For such positions, the murine residues were retained in the final model. In an attempt to develop a general Fv humanization algorithm, Studnicka et al. (1994) classified each amino acid position in the variable region according to the benefit of achieving a more humanlike antibody vs the risk of decreasing or abolishing specific binding affinity. With use of the Chothia et al. (1987,1989) definitions of CDR loop end points, knowledge of Fv solvent accessibility (Novotny et al., 1986a; Padlan, 1991), VL-VH interface conservation (Novotny and Haber, 1985, Chothia et al. 1986), and the conservedP-sheeted motifs (Lesk and Chothia, 1982), a consensus table was developed to identify, in a semiquantitative manner, low-risk positions (exposed to solvent but not contributing to binding or antibody structure), moderate- and high-risk positions (directly involved in antigen binding, CDR stabilization, or internal packing). The consensus table was tested experimentally by humanizing the anti-CD5 antibody H65 whose binding activity was greatly reduced by two previous “blind” attempts at CDR grafting. The new humanized H65 antibody, with 20 low-risk human consensus substitutions, retained the full binding avidity of the wild type. Another engineered antibody with 14 more moderate-risk substitutions had unexpectedly three- to seven-fold-enhanced avidity. The Studnicka et al. (1994) “position-risk scheme” is similar in spirit to the solvent accessibility analysis reported by Pedersen et al. (1994) (see Section VIII).

E. Heterospecijic Polyvalent Constructs, “Miniantibodies” The conceptually simplest bivalent, bispecific single-chain construct is the one where two single-chain Fv fragments of different specificities were connected by a C-terminal, disulfide bond-forming Gly4Cys or Cys5Hisj extension (Adams et al., 1993; Kipriyanov et al., 1994), or by means of designed Gly- and Ser-rich linkers (Mallender and Voss, 1994; Mallender et al., 1994; Hayden et al., 1994; Mack et al., 1995; Kurucz et al., 1995). A more complicated design of heterofunctional “miniantibodies” consisting of a single-chain Fv fragment, a flexible IgG3 hinge and an amphiphilic a-helical segment (leucine zipper), was reported by Pack and Pluckthun (1992) (Fig. 18; see also Pack et al., 1993). The dimer-forming propensity of the a helices drives spontaneous generation of a noncovalent, bifunctional, heterospecific chimera. When expressed in Escherichia coli, the bivalent fragments associated readily and were able to bind to surface-bound antigen under conditions in which bivalent but not monovalent antibody fragments bind. Packet al. (1993) reported that two single-

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chain Fv fragments with a C-terminal hinge followed by a helix-turn-helix motif formed bivalent noncovalent dimers in vivo with significantly higher avidity than those based on the leucine zipper-containing constructs. The improved avidity may have resulted from the greater stability of the fourhelix bundle formed on association of the helix-loop-helix motifs, from the antiparallel orientation of the Fv binding sites, or from both. Better still, tetravalent miniantibodies were assembled on a parallel, four-bundle a-helical scaffold (Pack et al., 1995; Fairman et al., 1996). A similar dimerization motif, i.e., the Fos and Jun leucine zipper genes fused to VH and CH1domain genes, was used to bring together Fab‘ fragments with two different specificities (Kostelny et al., 1992) in a mammalian expression system. Initially, bivalent, monospecific Fab’ fragments were expressed individually in the myeloma cell line Sp2/0 from plasmids containing genes for the hybrid H chains and those encoding the complete L chains. When these homodimers were reduced at the hinge region and their mixture reoxidized, mostly Fab’-zipper heterodimers formed and could be readily isolated. One of the exciting developments of antibody engineering has been the advent of combinatorial libraries of immunoglobulin polypeptides, and their expression on the surface of filamentous phage vectors (see, e.g., Winter and Milstein, 1991, or Marks et al., 1992, for review). One of the components of this design is use of the single-chain Fv fragment for phage surface expression. In principle, the method may supersede hybridoma technology and facilitate a mass production of antibodies with desired specificities. In practice, the recovery of rare “original” L and H chain pairs constituting a potent antibody depends on an efficient screening of very large (> lo8) combinatorial libraries. Screening of V gene repertoires becomes very efficient when single-chain combinations of VL and VH genes are cloned into a filamentous fd phage vector in its gene I11 or gene VI proteins. Modified phages display functional single-chain Fv modules on their surfaces and readily bind to antigen in a specific manner. Phage variants as rare as lo-‘ can be isolated in a single affinity chromatography step. X. T-CELLRECEPTOR MODELING AND ENGINEERING Before March 1995, when the X-ray crystallographic structure of the T-cell receptor chain was published by Bentley et al., all our structural knowledge of thie receptor had been derived indirectly, from analyses of T-cell receptor amino acid sequences, homology modeling, and sitedirected mutagenesis of T-cell receptor binding sites.

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A . Outline Structure Based on Sequence The first nucleotide sequences of T-cell receptor a and P chain genes (Chien et al., 1984; Hedrick et al., 1984; Saito et al., 1984a,b; Yanagi et al., 1984) indicated that these polypeptides corresponded in size to immunoglobulin L chains and were distantly related to immunoglobulin chains. The initial comparisons of small numbers of P chain variable domains (Patten et al., 1984) emphasized either similarities or differences between immunoglobulins and led, accordingly, to different conclusions about their functions. For example, Patten et al. (1984) hypothesized, purely on the basis of a sequence variability index, that VP segments had more hypervariable regions than the three CDR segments of immunoglobulins. The three additional nonimmunoglobulin hypervariable segments might be involved in interactions of T-cell receptors with polymorphic MHC determinants. On the other hand, Arden et al. (1985) suggested, on the basis of sequence analysis of 19 Va genes, that variable domains of T-cell receptors and immunoglobulins are similar in structure, and that it is unnecessary to postulate any special sites, apart from the classical antigen binding site, for binding properties of T-cell MHC-restricted antigen receptors. Amid these conflicting claims, Novotny et al. (1986~) analyzed sequence similarity of immunoglobulins and T-cell receptors from the point of view of structural fingerprints known to be conserved in antibody domains and in the antigen combining site (Lesk and Chothia, 1982; Novotny ef al., 1983; Novotny and Haber, 1985; Chothia et al., 1986; see Section IV). Based on these conserved sequence patterns, the T-cell receptor a, P, y, and CD8 chains were postulated to fold into immunoglobulin-like domains consisting of multistranded antiparallel P-sheet bilayers. Since the invariant side-chain motifs mediating domain-domain interactions were also found to be conserved T-cell receptor chain^,^ it appeared that the binding site of the T-cell receptor was fundamentally no different than the conventional binding site of an antibody. Thus, a/?receptors and immunoglobulins were likely to accommodate, in their respective binding sites, antigens in the same size range. If there was a single T-cell receptor binding site (as opposed to separate sites, one for the antigen and the other for the presenting MHC molecule), and if the binding sites of T-cell receptors and antibodies were fundamentally no different, what was the structural basis for the difference in antigen recognition between B and T cells? The answer to this question was likely The crystallographic structure of the CD8 extracellular domain reported by Leahy et al. (1992) confirmed that CD8 associated into a Fv-like homodimer.

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to be found in the structure of the antigen recognized, rather than in the binding sites themselves. The epitopes recognized by binding sites of antibodies were derived entirely from antigen, while those recognized by T-cell receptors may have been derived in part from the nominal antigen and in part from the restricting MHC element. Fundamentally a restatement of the “altered self’ hypothesis (Zinkernagel and Doherty 1974), the preceding conjecture accommodated the experimental evidence for complex formation between an immunogenic peptide and an MHC class I1 molecule (Babbitt et al., 1985). In the Ca and C/3 T-cell receptor domains, the segments corresponding to A-B-D-E /3 sheets showed a higher degree of conservation than their putative solvent-facing C-F-G /3-sheets, consistent with a dimeric Va/V/3 (VJVH-like) and CalCp (CLJCHl-like) domain modules. However, the interface of the C domains in the T-cell receptors resembled most the corresponding interface of the antibody CH3 domains which is relatively rich in electrically charged residues. Stable P-sheet-P-sheet contacts involving buried charges required formation of neutralizing ion pairs. The net charges of the putative Ca/C/3 domain dimers suggested favorable domaindomain electrostatic interactions, whereas some other domain-domain pairs were electrostatically less favorable (Novotny et al., 1986~). This observation further justified the search for a missing chain compatible with the Cy domain. Indeed, the 6 chain was identified by Brenner et al. (1986) and Bank et al. ( 1 986). Chothia et al. (1988) developed an outline structure of the T-cell a/3 receptor, based on a large set of amino acid sequences and assuming that the VaVp dimer has a framework structure very close to that of immunoglobulins. The loops that formed the antigen binding site were found to be similar in size to those commonly found in immunoglobulins, although perhaps with different conformations, and only limited sequence variability was found in the a I and PI hypervariable loops, suggesting that they mainly interacted with the constant parts of the MHC proteins. Claverie et al. (1989) built a complete model of the VaVp dimeric module, with use of the FRODO program and the Fab backbone as the starting point. The model was optimized by energy minimization with CHARMm and CONGEN, and was used to investigate various alternative arrangements of the receptor and the MHC molecules in putative antigenic complexes. The main conclusions were that the a and /3 chains were functionally equivalent, and that the third hypervariable loops of both chains may mainly interact with the antigen. The first and second regions were in positions favorable for making contacts with residues pointing up from the two a helices of the MHC structure. Similar suggestions about the relative MHC-peptide-receptor orientations were put forward by Davis and

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Bjorkman (1988). It was comforting to see many of the previously mentioned predictions (e.g., the immunoglobulin fold and the character of the Cp interdomain surface) to be confirmed by the X-ray structure of the p chain (Bentley et al., 1995). An interesting observation was made by Jores et al. (1990) in their studies on sequence variability in T-cell receptor /3 chains. In addition to the three hypervariable loops homologous to those of antibodies, the /3 chains possessed a distinct fourth hypervariable loop between residues 70 and 74, intermediate to the p strands D and E. In the antibody-like model of the T-cell receptor, the four hypervariable regions formed a contiguous surface area available for contacts with putative antigens. B. Engineering and Mutagenesis of T-cell Receptor Binding Site

If indeed the T-cell receptor structure is very similar to that of antibody, equivalent engineering designs, such as construction of a soluble Fv-like fragment, should be possible with the receptor. A strategy for the production of such small, soluble, single-chain T-cell receptor fragments was reported by Novotny et al. (1991). A gene encoding the RFL3.8 receptor, specific for the hapten fluorescein in the context of major histocompatibility complex class I1 and composed of the Va and Vp domains joined by a flexible peptide linker, was assembled in an E. coli plasmid. Subsequently, the protein was produced in a bacterial expression system, purified, refolded, and found to be poorly soluble at neutral pH in aqueous buffers. An inspection of the computer-generated Va-Vp model showed several surface-exposed hydrophobic residues. When these were replaced by polar side chains via site-directed mutagenesis of the corresponding gene, a soluble protein resulted and was shown to have antigen-binding properties equivalent to those of the intact receptor of the RFL3.8 T-cell clone (see Section IX,B for complete references on single-chain VaVp constructs). The computer-generated model of the RFL3.8 antifluorescein receptor served as a starting point for mutagenesis aimed at identification of its antigen-contacting residues (Ganju et al., 1992). To localize the potential antigen-contacting residues in the model, advantage was taken of the fact that the crystallographic structure of an antifluorescein antibody, the murine monoclonal 4-4-20, has been solved (Herron et al., 1989). Using atomic coordinates of the 4-4-20 antibody, the most conserved parts of its Vr-VH interface were superimposed on the corresponding parts of the RFL3.8 model. On this superposition, the fluorescein molecule bound to the 4-4-20 antibody was found close to a conspicuous cavity on the surface of the RFL3.8 model. The cavity was surrounded by V a and Vp hypervariable loops and was therefore a promising candidate for the RFL3.8

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antigen binding site (see Fig. 3B). Strikingly, side chains chemically similar to those comprising the most important hapten-contacting residues of the 4-4-20 antibody (Trp H33, Tyr L37, Ser L94, Arg L39) were found at the surface of the putative RFL3.8 fluorescein-contacting cavity (Tyr-31, Tyr166, Ser-227, Arg-94) despite the fact that the amino acid sequences of the 4-4-20 and RFL3.8 hypervariable loops showed little similarity to each other. This chemical similarity extended to the layer of aromatic residues directly under the bottom of the binding site cavity. All these observations suggested that similar chemical motifs may be used by antibodies and T-cell receptors to engage the same antigen. Altogether, six potential amino acid contacts with the antigen were selected for alanine-scanning mutagenesis. The mutated single-chain T-cell receptors were expressed in E. coli, purified, refolded, and assayed for fluorescein binding (Ganju et al., 1992). Five out of six mutations resulted in a loss of detectable binding. These RFL3.8 antigen combining site residues were distributed among the p3, al and a:! CDR loops. Given that fluorescein is one of the smallest T-cell antigens available, it seems reasonable to expect that the majority of receptors use multiple CDR loops to contact antigen in combination with the MHC proteins.

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CATALYTIC ANTIBODIES By EDWARD M. DRIGGERS and PETER G. SCHULTZ Howard Hughes Medical Institute Department of Chemistry University of California Berkeley, California 94720

I. Introduction. . 11.

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111. IV. V. VI . VII. VIII. Conclusion . . . References . . .

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I. INTRODUCTION

The humoral immune system is perhaps the best single example in which large, diverse libraries of molecules are generated and screened for a specific biological function. One of the first examples in which the chemical potential of large libraries of this sort was exploited was the use of transition state theory to select catalysts from among the large population of antibody molecules (1). Since these early experiments, which involved relatively simple transformations, the reactions catalyzed by antibodies have increased in complexity and degree of difficulty (2). At the same time strategies for generating antibody catalysts have become increasingly sophisticated. Structural and mechanistic studies show that the chemical notions used to generate catalytic antibodies are indeed reflected in their active site structures (3-5). Today, there is interest in screening libraries not only of antibodies but also of Fab fragments (6), RNAs (7), peptides (S), synthetic organic molecules (9),and even solid state materials (lo), for interesting new properties and functions. This article surveys advances in the field and lessons that have been learned from the study of antibody catalysis.

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11. IMMUNOLOGICAL EVOLUTION OF CATALYSIS In contrast to the situation for enzymes, the binding affinity and selectivity of antibodies evolve rapidly, through a process involving genetic recombination of variable (V),joining and diversity (D) genes followed by affinity maturation events. The net result is that tremendous molecular diversity can be screened in a period of weeks for a desired specificity ( 1 1 ) . Although immunological and natural selection both afford selective, highaffinity binding sites, enzymes generally evolve to maximize catalytic efficiency and are therefore selected based on affinity for high-energy transition states (12),whereas antibodies evolve to maximize affinity for molecules in their ground state. Consequently, in order to tap the catalytic potential of antibodies, the immune system must be provided with information relating to the rate-limiting transition state of a particular reaction. One strategy employed successfully to generate catalytic antibodies is the use of a stable analog of the transition state (TST) as the immunogen (1). This effectively directs immunological evolution along the same pathway as enzymatic evolution; the end result is an antibody with catalytic activity. To what degree can one reproduce the natural evolution of enzymes using these ideas? Consider, for example, the enzyme ferrochelatase, which catalyzes the insertion of Fez+ into protoporphyrin as part of the heme biosynthetic pathway (13). A potent inhibitor of this enzyme is the bent porphyrin N-methylprotoporphyrin (14),which is thought to resemble the transition state for porphyrin metallation in which distortion of the macrocyclic ring system forces the nitrogen lone pairs into a geometry better able to bind the incoming metal ion. If this hypothesis is indeed correct, then antibodies generated against a bent N-alkylmesoporphyrin should act as a ferrochelatase. In order to test this notion, monoclonal antibodies were generated against the mesoporphyrin derivative 1 (Fig. 1) (15). In the case of antibody G1-A12, catalysis was observed with a variety of transition metals including Zn(II), Co(II), Cu(II), and Mn(I1). The catalytic properties of this antibody are similar to those of the enzyme ferrochelatase. The reported Michaelis constant, K,, values for the enzyme ferrochelatase range from 10 to 70 p M , compared to 50 p M determined for the antibody (Cu"), and both enzyme and antibody have comparable affinities for the N-methylporphyrin (13-15). The enzyme and antibody insert a variety of divalent transition metals into porphyrins, with similar turnover numbers (L). A calculated value of k,,, for ferrochelatase with Zn(I1) is 800 hr-', and the experimentally determined value of k,,, for the antibody is 80 hr-' (15). Clearly in this case, immunological evolution against a transition state analog produced a catalytic antibody with properties quite close to those of

u),

CATALYTIC ANTIBODIES

263

1

FIG.1. Antibody-catalyzed porphyrin metallation reaction.

the corresponding enzyme (13-1 5). Moreover, the similarity between the antibody and the enzyme strongly support the hypothesis that the enzyme has evolved to bind a distorted heme structure. Among the most ubiquitous and well-characterized enzyme-catalyzed reactions are the acyl transfer reactions. A number of novel mechanisms have evolved for these enzyme-catalyzed reactions, including the formation of acyl-enzyme intermediates, direct acyl transfer between two substrates, and metal-dependent acyl transfer (16).These reactions have been an attractive target for antibody catalysis and many examples have been documented in the literature, including stereo- and regioselective ester hydrolysis (17) and amide bond hydrolysis (18). One can again ask, To what degree can immunological evolution recapitulate the properties of enzymes for this important class of biochemical reactions? Consider, for example, the antibody-catalyzed transesterification reactions illustrated in Fig. 2 (structures 2-9). Antibodies raised against phosphonates 2 or 3 were expected to bind the corresponding substrates in a reactive orientation and thereby catalyze the bimolecular reaction by acting as “entropy traps” (19,20). In addition, the dipole of the P=O bond reflects the developing negative charge on the carbonyl oxygen in the transition state. The fact that the antibodies are complementary to tetrahedral phosphonate esters should be reflected in lower affinities for the trigonal reaction products.

264

EDWARD M. DRIGGERS AND PEI'ER G. SCHULTZ F)

NCCHzO+

n

YJo

0

6

AO-Ph O

H 5

I

+

FIG.2 . Antibody-catalyzed transacylation reactions.

Antibodies generated to each hapten were found to be remarkably efficient catalysts for the corresponding transesterification reactions. The effective molarity for the antibody-catalyzed transesterification of thymidine 4 with the alanyl ester 5 is approximately 5 x lo4M (20). The transesterification reaction of the vinyl ester 7 with racemic 2-phenethyl alcohol 8 is estimated to have an effective molarity on the order of 105-106 M (19). These values, which represent very large rate enhancements for these bimolecular reactions, underscore the importance of entropic factors in biological catalysis. The efficiency and selectivity of these reactions are reflected by the fact that neither antibody catalyzes acyl transfer to water to

CATALYTIC ANTIBODIES

265

any appreciable extent, even though water is present in both cases at a concentration approximately 1O5 times that of the more hindered secondary alcohol. This ability to exclude water from participating in reactions is characteristic of many enzyme-catalyzed reactions. The two antibodies were found to function via different mechanisms. In the case of thymidine aminoacylation (20), the differential binding affinity of the antibody to the phosphonate diester relative to substrates appears to account for a large fraction of the catalytic advantage. This result is consistent with the classic notion of transition state complementarity in enzymatic catalysis put forth by Haldane and Pauling (12). In contrast, the second transesterification reaction was found to proceed through a PingPong mechanism involving a covalent acyl-antibody intermediate ( 19). Moreover, formation of the acyl intermediate appears to depend on an induced fit phenomenon. The preceding results suggest that these two catalytic antibodies can in fact be viewed as primitive enzymes following two distinct evolutionary pathways. The ideas used to generate these catalytic antibodies have recently been extended to the generation of antibodies that catalyze peptide bond formation (21,22). One such antibody has been shown to catalyze this bimolecular reaction with an effective molarity of roughly 1000 M , without catalyzing the hydrolysis of the peptide product or racemization of the ester substrate (Fig. 3) (22). These results raise the intriguing possibility of using antibodies as tools for polypeptide synthesis.

u 0. -0

FIG.3. Antibody-catalyzed peptide bond formation.

266

EDWARD M. DKICGERS AND PETER G. SCHULTZ

111. STRUCTURAL STUDIES

Structural studies support the notion that catalytic antibody active sites evolve in response to the mechanistic information contained in the structure of the immunogen (3-5). Consider, for example, the antibody 17E8 which was raised to phosphonate 10 (Fig. 4,structures 10-12) (4).This antibody catalyzes hydrolysis of the corresponding formyl norleucine phenyl ester 11 with a k,,, of 223 min-' and a rate acceleration lIcaJlcuncatof 2.2 x lo4. The X-ray crystal structures of the antibody-transition state analog complex and the Michaelis complex (in which an amide analog of the substrate is bound) (4,23) reveal a recognition pocket in the active site for specific binding of the side chain of the amino acid substrate as well as a light chain lysine residue (Lys-97L)which likely functions to stabilize the negatively charged transition state, much like the oxyanion hole found in serine proteases. A comparison of the structures of the Michaelis complex and the transition state analog complex clearly shows the increased binding interactions that occur as the reaction progresses toward the transition state configuration. The antibody active site has a Ser-His catalytic dyad proximal to the phosphorus of the bound hapten, resembling the Ser-HisAsp catalytic triad of the serine proteases. The positions of the antibody and enzyme side chains relative to the acyl group undergoing nucleophilic addition are virtually superimposable (Fig. 5), suggesting that the antibody resembles in many respects a primitive serine protease. Steady-state

FIG.4. Antibody-catalyzed ester hydrolysis.

CATALYTIC ANTIBODIES

267

FIG. 5 . The active site of antibody 17E8 superimposed on the active site of trypsin complexed with BPT14.

hydroxylamine partitioning experiments lend support to a catalytic mechanism involving rate-limiting formation of a covalent acyl-antibody intermediate. By introducing additional catalytic groups, such as an aspartate or glutamate in close proximity to the histidine, one might be able to further enhance the activity of this catalytic antibody. For example, it has been shown previously that mutagenesis of T ~ r - 3 to 3 ~histidine in the phosphorylcholine binding antibody S 107, which catalyzes the hydrolysis of choline esters, results in a 10-fold increase in the esterolytic activity of this antibody (24,25). Another comparison between enzyme- and antibody-catalyzed reactions can be made in the case of the conversion of chorismic acid 13 to prephenic acid 14 which is catalyzed by the enzyme chorismate mutase. This 3,3-sigmatropic rearrangement, which is a key step in the biosynthesis of

268

EDWARD M. DKIGGERS AND PEI'EK G . SCHULTZ

aromatic amino acids in plants and bacteria, is known to proceed through an asymmetric chairlike transition state (26, 27). One might expect that an antibody combining site complementary to the conformationally restricted transition state would accelerate this rearrangement, again by acting as an entropy trap. Antibodies 1F7 and 2E11, elicited to derivatives of a bicyclic transition state inhibitor of chorismate mutase, have been shown to increase the rate of the rearrangement 10'-fold (hapten 15) (28) and lo4fold (hapten 16) (29), respectively, over that of the uncatalyzed reaction (Fig. 6, structures 13-16), compared to the approximately 106-foldacceleration (k,,Jk,,,,,) of the enzyme chorismate mutase. Both antibodies, like the enzyme, display high specificity for the (-)-isomer of chorismate. Antibody 2E11 (29) functions primarily by increasing the entropy of activation for the reaction (AS++= -1.2 eu, AH++ = 18.3 kcal/mol), antibody 1F7 (28) primarily decreases the enthalpy of activation (AS++= -22 eu, AH++= 15 kcal/mol), and the enzyme affects both (AS++= 0.0 eu, AH++= 15.9 kcal/mol) (27). The X-ray crystal structures of the enzyme and antibody 1F7 have been solved (3). Structural data suggest that the enzyme and the antibody stabilize the same conformationally restricted chairlike transition state (Fig. 7). The overall shape and charge complementarity between the combining sites and the transition state analog result in binding of the correct enantiomer of chorismate in the conformation required for reaction. Differences in the number and nature of specific interactions available for restricting conformational entropy and stabilizing the highly polarized transition state may account for the observed lo4 times lower activity of the antibody 1F7 relative to that of the natural enzymes.

OH

OH 13

14

FIG.6. Antibody-catalyzed Claisen rearrangement of chorismate to prephenate.

269

CATALYTIC ANTIBODIES

\

0 ' 'U

A

0'

h H 3 3

Cys75J

FIG.7 . Schematic diagram comparing the hydrogen bonding and electrostatic interactions of the transition state analog with relevant side chains of 1F7 (A) and Bacillus subtilis chorismatr mutase (B). Dashed lines indicate hydrogen bonds. (3)

The X-ray structures just described show that the properties of catalytic antibodies do reflect the mechanistic information contained in the hapten structure, and other mechanistic studies also bear this out. For example, it has been shown that by raising antibodies to positively charged hapten 19, one can generate an antibody (43D4-30D3) with a complementary negatively charged residue in the combining site (Fig. 8, structures 17-22) (30). This residue, which has been identified as Glu-43" by affinity labeling and mapping techniques, is positioned to abstract the proton a to the carbonyl group in substrate 17, leading to p-elimination of HF with a rate acceleration 105-foldover the second order rate constant for the acetate-catalyzed reaction (31). Hilvert and co-workers have exploited charge complementarity to generate very efficient catalytic antibodies that also operate via general base catalysis (32).An antibody specific for hapten 22 was found to catalyze the decomposition of substituted benzisoxazole 20 to give 2cyanophenol 21 with greater than 108-foldrate accelerations. In addition to demonstrating the large catalytic advantages that can be realized with antibodies, this experiment also began to define the degree to which optimally positioned general bases and acids can contribute to enzymatic catalysis. Although in each example described here the catalytic antibody evolved in response to a synthetic immunogen, some reports suggest that the immune system can produce catalytic antibodies in the absence of such immunogens (33,34). For example, autoimmune antibodies isolated from patients with systemic lupus erythematosus were found to hydrolyze DNA with a /@' value of 14 min-' and a K, value of 43 nM (33). These kinetic constants, which were obtained using highly purified Fab fragments, are remarkably close to those of restriction enzymes such as EcoRI. Unraveling the mechanism by which these antibodies are generated during the im-

270

EDWARD M. DRIGGERS AND P E E R G. SCHULTZ

Jyp_,,-C^"a 17

+

HF

18

FIG.8. Antibody-catalyzed elimination reactions.

mune response could prove extremely useful in the development of other effective antibody catalysts for biological and biomedical applications.

Iv. EVOLVING FUNCTIONS N O T Y E 1 FOUND IN NATURE Because the immune system responds rapidly to a given set of chemical instructions, one can attempt to evolve antibodies that catalyze reactions for which enzymes have yet to be found. Concerted pericyclic reactions, which include cycloaddition reactions, sigmatropic rearrangements, and electrocyclic ring closure reactions, represent one such opportunity. These reactions have not only received a greal deal of theoretical and mechanistic attention from chemists, but have also found many applications in organic synthesis (35).There are few examples of pericyclic reactions catalyzed by enzymes (27). Consequently, pericyclic reactions represent an ideal target for testing the degree to which catalytic antibodies can be generated for reactions that are rare or do not occur in nature.

27 1

CATALYTIC ANTIBODIES

The first such reaction to be considered was the Diels-Alder reaction, which in its simplest form consists of the reaction between butadiene and ethylene to yield cyclohexene (36). The transition state involves a highly ordered cyclic array of interacting orbitals in which carbon-carbon bonds are broken and formed in a single concerted step (Fig. 9). As a result of the stringent alignment of orbitals in the bimolecular transition state, an unfavorable entropy of activation (AS$) on the order of -30 to 4 0 eu is generally observed. The design of a hapten for generating catalytic antibodies for this reaction must address two issues: (1) an entropy sink must be provided such that the two substrate molecules are oriented in a reactive conformation on binding, and (2) a mechanism must be included for avoiding product inhibition because the product of a condensation reaction might be expected to bind more strongly than either substrate. Hilvert and co-workers were successful in designing a bicyclo[2.2.1]hapten, 23, that satisfies both criteria (37). The Diels-Alder reaction they chose to investigate was the addition of tetrachlorothiophene dioxide 24 to N-ethylmaleimide 25 which gives rise to an initial bicyclic Diels-Alder adduct (Fig. 10, structures 23-30). This adduct spontaneously extrudes sulfur dioxide, resulting in the dihydrophthalimide product 26 which has significantly less structural similarity to the hapten than the initial DielsAlder adduct, thereby minimizing product inhibition. An antibody raised to hapten 23 that resembles the transition state for the addition reaction was an efficient catalyst with an effective molarity of 100 M . At the same time, a second, more general strategy for catalyzing the Diels-Alder reaction was developed (38). In this case the reaction involved cycloaddition of the acyclic diene 27 to N-phenylmaleimide 28 to yield the cyclohexene product 29 (Fig. 10). Hapten 30 is based on a bicyclo[2.2.2]octene skeleton in which the ethano bridge locks the cyclohexene ring into a conformation resembling the Diels-Alder transition state. Because the

R

7 Diene

+

'R'

R' Dienophile

Product Transition state FIG.9. Diels-Alder reaction of a diene and a dienophile to yield a cyclohexene product.

272

EDWARD M. DRIGGERS AND PETEK G. SCHULTZ

24

P

0

FIG 10. Antibody-catalyzed Diels-Alder reactions.

reaction product does not contain this hydrophobic bridge and has a conformation distinct from that of the hapten, it was expected to bind less tightly in the antibody combining site. In fact, an antibody generated to hapten 30 catalyzed the formation of the Diels-Alder adduct with a k,,K,, value of 900 M-' sec-' (diene); product was a bound with KO of 10 p M , which can be compared to a K O of 126 nM for the hapten. Another well-studied pericyclic reaction for which enzymatic catalysis has yet to be demonstrated is the Cope rearrangement (39). In order to generate catalysts for this reaction, antibodies were raised against the diphenyl-substituted cyclohexane derivative 3 1. This hapten was expected to mimic the six-membered ring transition state for this concerted rear-

CATALYTIC ANTIBODIES

273

rangement (Fig. 11, structures 31-33) (40). Four antibodies were isolated that catalyze the oxy-Cope rearrangement of diene 32 to 33, one with a kcaJkuncatvalue of 5300. NMR analysis of this antibody by transferred NOE studies in accord with the hapten design indicates that it does in fact constrain the substrate in a cyclic conformation (unpublished results). These studies on the Diels-Alder and oxy-Cope reactions underscore the ability of the immune system, when guided by carefully defined mechanistic criteria, to evolve catalysts for a wide range of chemical transformations, some of which have heretofore been unknown in nature.

v.

UNNATURAL COFACTORS

Many enzymatic reactions depend on a set of small nonpeptidyl cofactors such as hemes, flavin, pyridoxal, and nicotinamide. Chemists have developed their own set of chemical auxillaries including metal hydrides, transition metals, and Lewis acids, which perform similar functions. The large number and utility of the cofactors available to the chemist raise the question whether antibodies can be used to extend biological catalysis to reactions not normally considered within the purview of nature. Specifically, can antibodies be developed that use chemical “cofactors” in addition to the limited set of enzymatic cofactors (41)? One such example is the antibody-catalyzed oxygenation reaction of a sulfide to the corresponding sulfoxide (42). The monooxygenase enzymes responsible for this transformation use flavin or heme cofactors that typically require NADPH for cofactor regeneration (43). Hsieh and co-workers asked whether the inexpensive oxidant, NaI04, could be used to carry out this reaction. This eliminates the need for cofactor recycling, a significant

0

32

33

FIG.11. Antibody-catalyzed oxy-Cope rearrangement.

274

EDWARD M. DRIGGEKS AND PETER G. SCHULTZ

barrier to the use of many enzymes in synthesis (Fig. 12, structures 34-36). Hammett u-p studies, solvent isotope effects, and pH-dependent studies on sulfide oxidation by periodate (44) suggest that the transition state for this reaction resembles that depicted in Fig. 12. Consequently, aminophosphonic acid 34 was designed to generate antibodies that catalyze the conversion of sulfide 35 to sulfoxide 36. Because hapten 34 contains an amine that is protonated at physiological pH, antibodies specific for 34 were expected to stabilize the incipient positive charge on sulfur present in the transition state. A phosphonic acid moiety was introduced into the hapten to provide a binding site for the periodate ion. Antibody 28B4.2, which catalyzes the NaI04-dependent oxidation of sulfide 35 with a k,,, of 8.2 sec-l, was isolated, and no inactivation due to antibody oxidation was observed. The turnover number and catalytic efficiency of this antibody are comparable to those of the corresponding enzymes (43). A second example of antibody catalysts that use unnatural cofactors is the antibody-catalyzed reduction of ketones to the corresponding alcohols (45,46). The enzymatic reduction of carbonyl groups to alcohols usually requires the cofactor NADH or NADPH. Chemical reductions, on the other hand, are usually carried out with inexpensive and versatile metal hydrides, such as NaBH4 or LAlH4. In an effort to generate antibodies that catalyze the metal hydride dependent reduction of ketone 37,antibodies were generated against N-oxide 39 (Fig. 13).Antibodies raised against this hapten were expected to stabilize the tetrahedral transition state arising from nucleophilic attack of hydride on the carbonyl group, as well as to provide a site to accommodate the reductant. The chiral active site of an antibody

L

J

36

FIL. 12. Antibody-catalyzed, periodate-dependent oxygenation reaction.

275

CATALYTIC ANTIBODIES

NaCNBH,, Ig

QN

QN

37

38

FIG. 13. Antibody-catalyzed, borohydride-dependent ketone reduction. Ig, Immunoglobulin.

specific for one of the two enantiomers of hapten 39 should also discriminate between the enantiotopic faces of a prochiral substrate, affording high stereoselectivity.Antibody 378.39.3 was found to catalyze the reduction of substrate 37 to the corresponding alcohol 38 with a k,,JK, value of 1.9 x 103M-' min-' (R=C2H5)(46). As expected, the antibody stabilized one of two possible enantiomeric transition states to give the S-alcohol in 96%enantiomeric excess. The reduction of ketones containing branched and aryl substituents, including the highly symmetric l-nitrophenyl-3phenyl-2-propanone, also showed high enantioselectivity. This straightforward strategy may find general applicability in the regio- and stereoselective reduction of a broad range of compounds and may be useful for reactions not amenable to existing biological or chemical approaches. Other examples involving antibodies that use novel cofactors include the peroxycarboximidic acid dependent oxidation of unfunctionalized alkenes to yield epoxides (47). The enantioselectivity for this reaction was greater than 98%, and exceeds that which can be achieved with the hemedependent enzyme chloroperoxidase. VI. DIFFICULT CHEMICAL TRANSFORMATIONS The field of catalytic antibodies has begun to focus on catalytic transformations that are difficult to carry out using existing chemical methods. These include reactions that have been termed disfavored, i.e., kinetically controlled reactions in which the products arise not from the lowest energy transition state (favored) but from a higher energy transition state (disfavored). In practice it has proven difficult to discriminate chemically and to control the relative energies of these two transition states. Consider, for

276

EDWARD M . DRIGGERS AND PETEK G. SCHULFZ

example, the Diels-Alder reaction discussed earlier. In the case of a monosubstituted diene and dieneophile, eight products are possible. Four products correspond to the regio- and stereoisomers resulting from endo attack and four arise from exo attack (Fig. 14). For reactions under kinetic control the endo pathway is typically favored over the exo pathway as a result of secondary orbital interactions in the transition state. Gouverneur and co-workers asked whether the binding energy of antibodies could be programmed to selectively catalyze formation of the disfavored exo pathway (48). The reaction chosen for study was the cycloaddition between trans-lN-acylamino-1,3-butadiene 40 and N,N-dimethylacrylamide 41 (Fig. 15, structures 40-45). In the absence of a catalyst the reaction proceeds under aqueous conditions to give an 85: 15 mixture of the endo 42 to exo adduct 43. A bicyclo[2.2.2]octeneframework was again used to mimic the boatlike transition state for the pericyclic reaction. Hapten 44 mimics the endo approach in the transition state, because the amide group of the dienophile is oriented toward the n orbitals of the diene. Conversely, in the exo transition state, the dienophile substituent is oriented away from the n system. This geometry is mimicked by hapten 45, which should generate

endo approach

Re face

Ri

< + ' ! R2

Ri

em approach

Si face

ex0

approach Re face L

FIG. 14. Geometric features of the four transition states that control the endo/exo enantioselectivity of the Diels-Alder transformation.

277

CATALYTIC ANTIBODIES

’CONMe2 0

Y

NH

b

R

b

40

42

43

0

R

A

&

N&CONhle, H

CONMe2

NH

oAR 44

0 J--A 45

FIG.15. Antibody catalysis of an exo Diels-Alder reaction.

antibodies whose binding sites stabilize the exo transition state and catalyze formation of the corresponding trans adduct, 43. Antibody 7D4 (specific for hapten 44) and antibody 22C8 (specific for hapten 45) catalyze exclusive formation of the cis (endo) and trans (exo) adducts, respectively (48). The effective molarities for the antibody-catalyzed reactions were 4.8 M (7D4) and 18 M (2268). In each case the degree of enantioselectivity was greater than 98%. Another disfavored reaction that has been successfully catalyzed by antibodies is the 6-endo-tet cyclization of the epoxy alcohol illustrated in Fig. 16 (structures 46-49) (49). This antibody-catalyzed reaction is formally a violation of Baldwin’s ‘‘rules’’for ring closure reactions (50), which state that the preferred product arising from the 180”transition state geometry of an intramolecular nucleophilic substitution reaction is the 5-exo-tet product. In order to catalyze 6-endo-tet cyclization, it was necessary to generate an antibody that not only lowers the energy barrier for epoxide ring opening but also overcomes the entropic barrier and strain necessary to bring the hydroxyl group into a geometry that favors a six-membered (disfavored) vs a five-membered (favored) ring transition state geometry. It was anticipated that hapten 46 would generate a combining site that would stabilize both the developing charge in the breaking C-0 bond and the six-membered ring geometry (49). The difference in dipole between the hapten and the reaction product was expected to minimize product inhibition. Two antibodies generated against N-oxide 46 were found to catalyze the regioselective ring opening of epoxide 47 to form the six-membered ring

278

EDWARD M. DRIGGERS AND PETER G . SCHULTZ

~

FK. 16. Antibody catalysis of an anti-Baldwin cyclization reaction.

product 49. Comparison of the Ltvalue with that of the uncatalyzed reaction was not possible, because only the five-membered Baldwin ring closure product was formed in the absence of antibody. In addition, only the S,Sepoxide was a substrate for antibody-catalyzedpyran ring formation. Thus, the antibody controls both the regio- and the stereochemistry of this reaction. Another challenge in chemistry is the rational design of catalysts capable of complete regio- and stereoselective control over reaction products. For example, it would be difficult using known chemical methods to selectively reduce diketone 50 to afford only one of eight possible reaction products because all eight products arise from transition states that are expected to be similar in energy (Fig. 17, structures 50-53). However, it was shown that one antibody (37B39.3) generated against N-oxide 39 (see

OH H 02

E

'

H

3

NaCNBH,

- - .

52

50

OH

, 02Nd

/

I =H

3

53

FIG. 17. Regio- and stereoselective, antibody-catalyzed diketone reduction.

279

CATALYTIC ANTIBODIES

later discussion) catalyzed the reduction regioselectively with greater than 75:1 selectivity for one of the two nearly equivalent ketone moieties (46). Moreover, the reaction was highly stereoselective, affording the S enantiomer of hydroxy ketone 51 in 96% enantiomeric excess. In contrast, the nitrobenzyl carbonyl group was reduced more slowly than the methoxybenzyl carbonyl group in the uncatalyzed reaction (V,.el= 0.74).The overall yield of hydroxy ketone (S)-51 was 94%, which is significant in light of the fact that the background reaction produces all eight products. Another example in which antibodies were able to selectively stabilize one of a number of nearly equivalent transition states is a diasteroselective esterolytic reaction (51). Antibodies were generated against each of four diastereomeric phosphonate analogs of the transition states for the hydrolysis of the corresponding l-(benzyloxy)-2-fluoro-2-methyl-3-hydroxybutane esters 54. Each of the four esters was hydrolyzed in 2 97% enantiomeric excess and in greater than 23% overall conversion (theoretical yield, 25%) with the corresponding antibody (Fig. 18,structures 54-56). Given that at present no general chemical methods exist for generating catalysts of this sort, such antibodies might find applications in the chiral resolution of synthetic intermediates containing either acid or alcohol functionality. Regioselective esterolytic antibodies have also been reported that are able to selectively deprotect an acylated carbohydrate (52). Many other examples are appearing in which antibodies provide the chemist with a high degree of control over the outcome of chemical reactions. Antibodies can effectively exclude solvent from participating in reactions. Keinan and co-workers showed that an antibody generated against the quaternary ammonium ion hapten 57 was able to catalyze the cyclization of hydroxyethyl enol ether 58 to the corresponding ketal59 in water with high enantiomeric purity (Fig. 19,structures 57-60) (53).Ordinarily,

54

55

-

H 0 2 C m P < o + Me

I

NHAc

56

FIG.18. Diastereoselective antibody-catalyzedester hydrolysis reaction.

280

EDWARD M . DRIGGERS AND PETER G. SCHULTZ

50

Ar

,

59

FIG. 19. Exclusion ofwater from an energetic intermediate in an antibody active site

ketal formation does not occur under aqueous conditions; the oxocarbonium ion intermediate is rapidly trapped by water to yield a hemiketal and ultimately ketone 60. Antibodies have also been reported that control the syn/unti ratio of the oxime product that results from condensation of hydroxylamine with a ketone (54) as well as the formation of 3-hydroxyoxepane rings from simple hydroxy epoxides (55). Finally, antibodies generated against a quaternary ammonium hapten have been shown to catalyze the stereoselective hydrolysis of an enol ether under aqueous conditions to give the corresponding aldehyde with greater than 98% enantioselectivity (56).

VII. FUTURE DIRECTIONS

Antibody catalysis will undoubtedly be extended to many other interesting classes of reactions. For example, antibodies can catalyze a cationic cyclization reaction (57). Antibody 4C6, which was generated against hapten 61, was found to catalyze the cationic rearrangement of 62 to cyclohexene 63 (2%) and trans-2-dimethylphenylsilylcyclohexanol 64 (98%) (Fig. 20, structures 61-64). Such a narrow distribution of products is surprising because cationic cyclization reactions conducted under solvolysis condi-

28 1

CATALYTIC ANTIBODIES

0

I

63

64

62

-0

bNU H

OH

61

F I G20. Antibody-catalyzed cationic cyclization reaction.

tions usually yield a plethora of products. The almost singular production of the cyclized product, 64, was attributed to the ability of an antibody to both enforce a pseudocyclic transition state geometry and trigger the reaction under conditions so mild that there is no detectable background reaction. These studies will undoubtedly lead to efforts aimed at larger multiring cyclization reactions. We will also continue to see the development of new methods for generating catalytic antibodies. One promising approach involves the use of mechanism-based screens in which covalent modification by a hapten is used to identify antibodies from a phage display library with an appropriately positioned nucleophile group in the active site. For example, a semisynthetic combinatorial antibody library was successfully screened for antibodies containing a cysteine residue in the complementarity determining regions (58). Libraries were panned with a-phenethylpyridyl disulfide 65 attached to a solid support. This reagent undergoes efficient disulfide exchange with an appropriately placed thiol in an antibody combining site (Fig. 21, structures 65, 66). Out of 10 randomly picked clones, two antibodies contained an unpaired cysteine in the combining site. One of these was found to accelerate the hydrolysis of thioester 66, in which the electro-

282

EDWARD M. DRIGGERS AND PETER G. SCHULTZ

FIG 2 1. Mechanism-based selection for active site nucleophiles.

philic carbonyl occupied the same position as the reactive sulfur atom in 65 during selection. As expected, the reaction involves formation of an acylantibody intermediate. This result suggests that iterative mechanismbased selection procedures may prove quite useful in screening for antibodies with specific functional groups in the combining site. In addition to strategies involving synthetic immunogens, more biologically oriented approaches are being developed for generating catalytic antibodies. For example, the hydrolytic antibody 48G7 (see earlier discussion) has been efficiently expressed in Escherichia coli for use as a model system to demonstrate the feasibility of using genetic selections to enhance catalytic activity (59). Conditions were found that permit the secretion of active recombinant antibody into the periplasm of an E. coli strain deficient in biotin biosynthetic genes (Abio-gal).A number of substrates were synthesized that, upon hydrolysis by the antibody, yielded free biotin, a required nutrient for cell growth. These substrates and selections are being used to identifji mutants of the antibody with altered activities. This approach should be generalizable to a wide number of hydrolytic reactions including the selective cleavage of peptide, polysaccharide, phosphodiester, and ester bonds. Similar approaches are being developed for selecting antibodies with enhanced activity that catalyze biosynthetic reactions, such as the conversion of chorismic acid to prephenic acid (60), and the decarboxylation of orotate (61).For both reactions, antibodies have been found that complement auxotrophs lacking the corresponding biosynthetic enzymes. In the latter case, this complementation was used as the basis for screening a library of antibodies generated from a mouse immunized with a synthetic immunogen. Other interesting strategies have also appeared for generating catalytic antibodies, including the development of rapid plate assays for screening large numbers of antibodies directly for catalysis (62,63). For example, Green and co-workers used an antibody specific for the product of a reaction to screen hybridoma supernatants for catalysts (63).A second strategy involves the generation of transgenic mice that produce antibodies with a high percentage of metal ion-binding light chains (64). This approach

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283

may facilitate the generation of catalytic antibodies that utilize metal ions and other cofactors. Catalytic antibodies with cholinesterase activity have also been generated by immunizing mice with a monoclonal antibody directed against the active site of acetylcholinesterase (65). The catalytic efficiencyof this antibody (kLaJkuncar= 4 x lo8)is quite high, suggesting that this approach may prove useful for generating structural and functional variants of enzymes. It is likely that antibody catalysis will soon be applied to practical problems in chemistry and medicine. Already there have been reports in the literature of antibody-catalyzed cocaine hydrolysis (66) and antibodycatalyzed prodrug activation (67,68). In the latter case, the use of a catalytic antibody makes prodrug activation possible by reactions not catalyzed by endogenous enzymes. In addition, efforts are focusing on methods for efficiently generating polyclonal catalytic antibodies in the hope that someday researchers may be able to actively immunize and produce therapeutic catalytic antibodies (69). A demonstration that enantioselective conversions can be carried out by antibodies on a multigram scale (70), as well as efforts aimed at extending antibody catalysis to organic solvents (71), should facilitate the use of antibodies in organic chemistry. A report describes the use of a catalytic antibody to carry out the key synthetic step, the enantioselective protonolysis of an enol ether, in the total synthesis of (-)-a-multistriatin, the aggregation pheromone of the European elm bark beetle (72). This reaction, which was carried out in greater than 99% enantiomeric excess and 98% chemical yield, was followed by 10 chemical steps with all four asymmetric centers originating from the chirality achieved using the catalytic antibody. Finally, many of the ideas that form the basis for the work described in this article are being applied elsewhere (6-1 0). For example, the planar phenanthrene transition state analog 67 has been used to screen nucleic acid libraries for RNAs that catalyze isomerization of the substituted biphenyl 68 (Fig. 22, structures 67-69) (73). In addition, mechanism-based selections have been used to identify RNAs that undergo efficient selfalkylation reactions (74).Such experiments are extending RNA catalysis from phosphoryl transfer reactions to new classes of chemical transformations.

VIII. CONCLUSION Although tremendous progress has been made in the field of catalytic antibodies, major challenges still exist. Methods have to be developed to further improve the catalytic efficiencies of antibodies. Many classes of reactions also remain to be surveyed, and effective haptens must be de-

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FIG.22. RNA-catalyzed isomerization reaction.

signed to catalyze such reactions. Improved methods for expressing and screening antibodies need to be developed, and many practical problems associated with the use of antibodies in bioreactors must be solved. However, the progress made in the field in recent years suggests that these challenges will be met. Moreover, the success of chemistry in exploiting the molecular diversity of the immune system to generate selective catalysts points to the tremendous potential of combinatorial libraries. Indeed the lessons learned from the catalytic antibodies have recently found their way to the physics community with the report that libraries encompassing virtually the entire periodic table can now be screened for interesting new physical properties such as superconductivity and magnetism (10).

ACKNOWLEDGMENTS We are grateful for financial support for this work from the National Institutes of Health, the Ofice of Naval Research, and the US. Department of Energy under Contract No. DEAC03-76SF00098. PGS is a Howard Hughes Medical Institute Investigator.

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THE NATURE OF THE ANTIGEN By MICHAEL SELA and ISRAEL PECHT Department of Immunology Weizmann lnstltute of Science Rehovot 76100, Israel

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Antigen-binding molecules include antibodies and T-cell receptors (TCR), as well as class I and class I1 antigens encoded by the major histocompatibility complex (MHC). This article will define and illustrate the notion of antigens. Macromolecules, such as enzymes and hormones, have well-defined biological activities and are uniquely specific. The same is largely true for the previously mentioned biological macromolecules with the exception of antigens. Antigens may be small or large, may have other defined biological activities, or may be confined to their ability to react with antigen-binding molecules. Thus, defining and surveying antigens is difficult, as it could cover almost all facets of immunology. We will provide a concise message, and will refer primarily to reviews, key articles, and recently published papers, and we will use certain results as examples. We also had to make some arbitrary decisions: we will briefly describe tumor ADVANCES IN PROTEIN CHEMISTRY, Vol. 49

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antigens but will not discuss antigens used for vaccination against infectious diseases or those involved in autoimmune disease and allergy. We will address several more quantitative aspects of the interactions between antibodies and their respective epitopes. The remarkable recent increase in our knowledge of the three-dimensional structure of antibodies has led to an appreciation of conformational transitions that are induced on antigen binding. Earlier spectroscopic and kinetic evidence for the operation of an induced fit mechanism in antibodies has received detailed support from structural studies. Moreover, X-ray crystallography has provided crucial insights into the mechanisms by which antigenic epitopes are presented to T cells: Structures of both class I and class I1 MHC-encoded molecules in their peptide-bound states were combined with the results of an immense volume of immunological and biochemical studies to construct a detailed model of MHC-epitope interactions. Thermodynamic and kinetic studies have started to provide input to this relatively static structural outline. Most importantly, several investigations of the mechanism of binding interactions between recombinant soluble TCR and its ligand-MHC-peptide complexes have been carried out. These studies have begun to yield more quantitative information about this crucial process for selection of the T-cell repertoire and its activation. Undoubtedly, we are entering an exciting and promising phase in immunology in which a detailed molecular understanding of central cellular processes is emerging. 11. ANTIGENS, ANTIGENICITY,

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IMMUNOGENICITY

A . Definitions Antigen (Ag) is any substance (molecule) that provokes the production of a specific antibody or immunocyte (immune cell), or that interacts specifically with these products of the immune response, when penetrating the body of a vertebrate (Paul, 1993). The first part of this definition, namely, the capacity to provoke an immune response, is also called immunogenicity and the substance provoking such a response is called an immunogen (Sela, 1969). The second part, the specific interaction, is called antigenic specificity. A chemical or physical change in a molecule that results in an increased immune response enhances its immunogenicity, even though it may or may not change its antigenic specificity. It is the antigenic determinant (also called an epitope) that is responsible for the specificity. The notion of antigen also includes the capacity to induce specific immunological tolerance (e.g., Swat et d., 1994), or anergy, defined as

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a state of T-lymphocyte unresponsiveness characterized by the absence of proliferation (human T-cell clonal anergy, Gimmi et al., 1993). Immunogenicity is the capacity to provoke an immune response. When one refers to an immunogenic molecule, this means that the molecule is capable of triggering an immune response by itself, not when conjugated to another macromolecule. Thus, the term immunogenic peptide, for example, refers to a peptide that is immunogenic by itself, whereas a peptide that serves as an important epitope while attached to a macromolecule should be described as immunopotent or, if it is more immunopotent than related peptides, as immunodominant. The ability to mount an immune response ultimately depends on the interplay between the chemistry of the antigen and the physiological state of the host. Thus, immunogenicity is operationally dependent on the experimental conditions of the system, including parameters such as the antigen, the mode of immunization, the organism being immunized, and its genetic background, as well as the sensitivity of the methods used to detect a response. For thymus-dependent antigens, an eficient immune response necessitates the collaboration of T- and B-cell epitopes (reviewed by Milich, 1989; see also Sharma et al., 1993).A normal antibody response to T-cell-dependent antigens requires physical contact between antigenspecific B and T cells. It has been shown that the germinal centers in lymph nodes are an in vivo site where antigen-specific T and B cells interact (Fuller et al., 1993). It is worth stressing that we use the word antigen sometimes for a molecule, sometimes for a virus or a bacterium, and sometimes for an organ or a tissue, and that antibodies have a combining site (also defined as a paratope), with all its distinctive features, of a more or less similar size and cavity. These combining sites are not complementary to a complete bacterium or to a complete heart, but they are always complementary to a unique antigenic determinant which is of limited molecular size. Among the immunocytes we recognize B cells (the precursors of antibodyproducing cells) and T cells. The combining sites on B cells are essentially the same as those of the antibodies that their progeny will produce. On the other hand, the combining sites of T-cell receptors are distinct from those of antibodies. What is characteristic of T-cell receptors is that they recognize the antigen after it has been processed within a cell and presented to the T-cell receptor in conjunction with either class I or class I1 antigens. These are antigens defined by immune response genes that are part of the MHC. Most antigens are thymus-dependent, which means that they need to be recognized in this manner. A minority of antigens, called thymus-independent, do not need recognition by T cells and may lead to efficient antibody formation after interacting exclusively with B cells.

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The antigenic determinants may be parts of proteins, nucleic acids, polysaccharides, lipids or glycolipids, or other biological macromolecules. Very often they have unique steric conformations and are part of a native structure. We thus have to distinguish between sequential determinants (epitopes) and conformation-dependent (or conformational) determinants (epitopes) (Sela et al., 1967). The operational definition holds that if antibodies against a protein, for example, react well with a tetra-, penta-, or hexapeptide derived from that protein, then the antibody is against a sequential determinant. The antibody, on the other hand, is against a conformation-dependent determinant if it is made against a juxtaposition of atoms in space that results from a unique conformation of the macromolecule, and any peptide derived from such a protein cannot, after denaturation, react with the antibody. It is of interest that for most globular proteins and native nucleic acids, almost all the antigenic determinants are conformation-dependent, whereas for most polysaccharides, fibrilar proteins such as silk fibroin, and single-stranded nucleic acids the determinants are sequential. The use of homopolymers of amino acids or sugars and of peptidyl proteins as antigens has established that the determinant is composed of four to six amino acid or sugar residues which contribute unequally to binding with the antibody combining site. Not all antigenic determinants express themselves all the time: Some are more immunopotent than others. Some do not express themselves at all under a certain set of conditions and are called immunosilent, even though under other conditions they may provoke an efficient immune response. Thus a determinant may be immunosilent within a complete macromolecule but quite immunopotent when a segment of the macromolecule on which it is present is used for immunization. Situations are also known in which a determinant is immunosilent but becomes immunopotent in animals made tolerant to other parts of the immunogenic macromolecule of which the particular determinant is a part. We may thus define immunopotency as the capacity of a region of an antigen molecule to serve as an antigenic determinant and induce the formation of a specific immune response. The term hapten, in its strictest sense, designates any substance, large or small, that does not elicit an immune response by itself but can be shown to react with an antibody provoked by immunization with a complete immunogen of which the hapten forms a part. In practice, most investigated haptens are small chemical substances-smaller than a complete antigenic determinant. When attached to a protein, a hapten such as dinitrophenyl or penicilloyl might be defined as an immunodominant part of an antigenic determinant (an epitope). In studies on determinants of a polysaccharide or polypeptide nature, it is of interest to establish the immunodominant portion.

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Generally, an organism distinguishes between self (material that is its own) and nonself (any foreign material). The immune system of an organism reacts against any foreign compound (antigen) and is tolerant (unable to react) toward its own body components, which may be good immunogens in other organisms. This self-tolerance is acquired during fetal or neonatal development, and the immune system can be made tolerant to even foreign material or tissue introduced during this period. Such material, which can induce immunological tolerance or unresponsiveness, is called a tolerogen. Another phenomenon that should be mentioned here is antigenic competition (Taussig et al., 1973). This may occur between different antigens (intermolecular) or between different specificity determinants on the same antigen (intramolecular), in which case we define it as competition between antigenic determinants. This phenomenon may account for some determinants being immunosilent under certain circumstances. Antigenic competition may be defined as inhibition of the immune response to one antigen or determinant by the administration of another antigen or determinant. B. Molecules as Antigens

The two types of natural macromolecules most investigated as antigens are proteins and polysaccharides (Sela, 1973-1 987). These also include glycoproteins, nucleoproteins, lipoproteins, etc., as well as peptidoglycans, glycolipids, and other conjugates. Nucleic acids are also antigenic. Lipids are poor immunogens, but antibodies against them can be obtained, and liposomes play a role here, as they do in enhancing the immunogenicity of various other antigens. Synthetic antigens, especially synthetic polypeptides, have played an important role in elucidation of the molecular basis of antigenicity and many other immunological phenomena, and they will be discussed later in more detail. Other synthetic polymers have also been shown to be immunogenic (e.g., polyvinylpyrrolidone). All proteins are probably immunogenic, although individual proteins differ markedly in immunogenicity. Denatured proteins are often less immunogenic than the corresponding native proteins. Self-aggregation of a protein is usually associated with a negligible change in its antigenic specificity but with a considerable increase in immunogenicity. Like other antigens, proteins possess a continuous spectrum of antigenic determinants that correspond to discrete portions of the surface structure and are preferentially located in regions most exposed to the external environment. The relationship between structure and antigenicity is, however, more complex for globular proteins than for other antigens in that it depends to a very large extent on the overall conformation of the molecule. The exploration of antigenic regions on the surface of proteins has become easier

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with the advent of monoclonal antibodies and rapid methods of peptide synthesis.The antigenic sites may be described as surface domains composed of amino acid side chains that may be distant in sequence but close in space (conformation-dependent determinants). Such domains are probably overlapping and cover most of the protein surface. On the other hand, fibrous proteins possess sequential determinants, whose size may be determined with synthetic peptides to be in the range of three to six amino acid residues. Special attention has been given by immunologists to proteins that possess distinct and easy-to-measure biological properties. These include enzymes and enzyme inhibitors, protein hormones, toxins, and antibodies (i.e., immunoglobulins as antigens), as well as proteins composing viral coats. Immunological studies have also been most successful in following the evolution of proteins. In the case of enzymes, antibodies directed against them-depending on the site of the particular epitope against which they are derived-may lead to total or partial inhibition of the enzyme, form a complex with the enzyme that is fully active, cause enhancement of enzymatic activity, and in some cases even stabilize enzymatic activity at elevated temperatures (Amon, 1973). Polysaccharides are the other class of antigenic substances. Although complex, they nevertheless provide antigens of relatively simple structure through which many of the detailed structural aspects of antigenic determinants and antibody combining sites have been worked out. Microbial polysaccharides are located on the cell surface and are therefore of importance in recognition and immune responses of higher organisms to microbial infection. The simplest polysaccharide antigens are dextran, (a polymer composed entirely of glucose) and levan, composed entirely of fructose. Another important group consists of the capsular polysaccharides of pneumococci. Complex lipopolysaccharide antigens, endotoxins, are found in a large variety of microorganisms, notably in gram-negative Enterobacteriaceae such as Salmonella and Shagella. The polysaccharide determinants are predominantly sequential, consisting usually of four to six sugars, but some antibodies may have combining sites that are smaller. Blood group antigens are the other important category of polysaccharide antigens. They are gene-dependent structures expressing the individuality of cell surfaces, body fluids, and secretions. Chemical characterization of blood group structures has been fully developed. The chemical structures of ABH and Lewis antigens have been elucidated using watersoluble blood group substances isolated from secretions (ovarian cyst mucin, gastric mucin). These structures, when on erythrocytes and other cells, are part of more complete glycolipid or glycoprotein antigens. Antigenic functions of nucleic acids were recognized much later than those of proteins or polysaccharides. No immunogen has yet been pre-

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pared that is capable of inducing antibodies to double-stranded DNA in experimental animals. Such antibodies are, nevertheless, present in humans suffering from systemic lupus erythematosus, as well as in mice and dogs with similar diseases. Their sera usually contain antibodies to single-stranded, denatured DNA, as well as to RNA, double-stranded RNA, histone, and nucleoprotein. It is possible to induce antibodies to single-stranded RNA or DNA either by immunizing with them, complexed with a macromolecule of opposite electric charge, or by preparing conjugates of nucleosides, nucleotides, or oligonucleotides with proteins or synthetic polypeptide antigens and using them as immunogens. Complex formation of methylated bovine serum albumin with synthetic polynucleotides, including some that were double-stranded and triple-stranded, yielded a mosaic of antibodies, some of which definitely recognized the higher-order structure of these macromolecules. Progress in the field of lipid immunology is more recent, largely because of advances in lipid and membrane chemistry. This has led to a heightened awareness of lipids as important cellular antigens. Among the lipids, phosphatides (such as sphingomyelin and cephalin) and glycosphingolipids (such as galactocerebroside) are the most important immunologically. Antibodies against lipoidal extracts of various tissues appear during the course of syphilitic infection, which has led to a standard serological test for syphilis. Another lipid antigen is the Forssman antigen, which is mainly responsible for hemolysis of sheep erythrocytes in the presence of antiserum and complement. The greatest barriers to advancement in the field of lipid immunology have always been the chemical and physical properties of the lipids themselves, particularly water insolubility. The problem of reactivity of soluble antibodies with lipid antigens was partially overcome by including auxiliary lipids such as lecithin and cholesterol in the antigen suspension. Mixtures of lipids in the form of liposomes, consisting of concentric spherules of lipid bilayer membranes, can mimic precisely many of the immunological aspects of intact cell membranes. Liposome availability has permitted study of the immunogenicity of membrane-associated lipids. C. Immunoglobulins, Major Histocompability Complex Products, T-cell Receptors

Immunoglobulins are mentioned here exclusively in terms of their antigenicity. Immunological data usually preceded structural information, and they were crucial, e.g., in the discovery of allotypy and idiotypy. Today a detailed antigenic analysis of immunoglobulins (Ig) of every class and type is possible because of the availability of monoclonal antibodies (MAb).

296

MICHAEL SELA AND ISRAEL PECHl

The epitopes within one immunoglobulin molecule vary greatly in their relative immunopotencies. Thus, some determinants on the Fc fragment of an IgG are immunodominant compared with determinants on Fab, but when Fab is injected, in the absence of Fc, either by itself or as the dimer (Fab)2, antibodies are produced efficiently against epitopes on the Fab fragment of IgG. Antigenic analysis helped not only to distinguish among the various classes (IgG, IgM, IgA, IgE, IgD) and subclasses of immunoglobulins but also to define their phylogeny. Allotypes are immunologically detectable genetic differences in particular constant regions, whereas idiotypes are the unique antigenic determinants found on the variable regions of antigenbinding receptors; i.e., they represent paratopes of different specificities (idiotypes) in terms of their antigenic variation (Greenspan and Bona, 1993). Regulation of the immune system through idiotype-anti-idiotype interactions can be achieved without the presence of the antigen and thus is particularly well suited to the maintenance of steady states in lymphoid populations after the antigenic stimulus has been removed. Indeed, idiotypeanti-idiotype relationships have the potential to link diverse members of the immune system into a network, and so the activation of one set of clones within the system may have far-reaching and quite unanticipated effects elsewhere within the immunological network. All plant and animal cells possess antigens that can express themselves in a foreign host. Many animal and human antigens can trigger autoimmune phenomena. Some antigens may be organ-specific, whereas others are present essentially on all cells (e.g., histocompatibility antigens). The central role of the MHC in immune processes has been recognized and its antigenicity has been described (e.g., Klein, 1986; Rotzschke and Falk, 1991; Bradley et al., 1992). The MHC, a cluster of diverse genes that mediate and regulate a variety of immune mechanisms, appears to exist in all higher vertebrate species (HLA in humans; H-2 in mice). Genetic, structural, and functional studies on the multiple MHC products have defined three broad classes of genes and molecules. Class I products are glycoproteins expressed on the membranes of all nucleated cells (histocompatibility or transplantation antigens). These are the main targets of the graft rejection reaction, and they mediate the recognition and destruction of virus-infected or neoplastic cells. Class I1 products, defined by immune response (IT)genes, are expressed principally on the membranes of antigen presenting cells (e.g., macrophages, dendritic cells, B lymphocytes) and mediate the regulation, through so-called helper and suppressor effects, of a variety of humoral and cellular immune responses. When incompatible, these Ir gene products also play a potentiating role in trans-

THE NATURE OF THE ANTIGEN

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plant rejections. Class I11 genes determine the structures of several discrete components of the complement system that cause destruction and elimination of bacteria and other foreign cells. All the products of these genes are antigenic, and the antibodies they provoke have been investigated. Antibodies recognizing TCR or their component chains have been used extensively in their study. Some of the early investigations have been summarized by Marrack and Kappler (1986).

D. Complex Antigens Antigens of importance in practical immunology are generally cellular or multicellular structures, not dispersed molecules. Of course, the specificity is ultimately definable in molecular terms in all cases. Viruses, sometimes even crystallizable, are among the simplest of such structures, with most of the antigenic specificity residing in their coats which are sometimes purely protein but often include lipids or polysaccharides. In some cases, inner core proteins are also efficient antigens capable of providing a protective immune response. More has been learned about immunology from studies on bacteria than on any other group of natural antigens, and their antigenic determinants have been elucidated in great detail in many cases, most of them polysaccharide in nature but also involving proteins and teichoic acids. Lipids often participate in these specificities as well. Progress has been more limited in the investigation of mycoplasmas and chlamydiae. On the other hand, there has been tremendous progress in the immunology of parasite diseases, due to both helminths and protozoa, including the great antigenic variations characteristic of some agents. Fungi are another group of antigens that express an enormous number of antigenically different entities about whose molecular nature relatively little is known. Allergens are antigens that cause allergic reactions of either the immediate or delayed type. They may be of widely different origins such as dust, fungi, hair, pollen, bacterial proteins, food, or drugs. The immediate-type allergy is induced mainly through a mechanism triggered by IgE class antibodies, whereas the delayed-type allergy is T cell-mediated. No listing of natural antigens would be complete without mention of all the cellular markers, receptors, and tissue antigens. There is a growing number of immunologically and chemically defined antigens characteristic of various types of T cells, B cells, and macrophages. There are also the water-soluble cytokines, molecules produced in cells and spilled into body fluids, such as interleukins, interferons, and thymic and tumor factors. Tumor antigens, superantigens, and T-independent antigens will be discussed later in this article.

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MICHAEL SELA AND ISRAEL PECHT

111. MOLECULAR CRITERIA FOR h T I C E N I C I 7 Y The availability of synthetic antigens permitted a systematic approach to elucidating the role of various molecular aspects in antigenicity and immunogenicity (Sela, 1969; Novotny et al., 1987). Landsteiner first showed that small molecules (e.g., 2,4-dinitrophenol), when injected into animals, do not elicit antibody formation. However, dinitrophenyl proteins, in which dinitrophenyl is attached to a macromolecular carrier, elicit the formation of antibodies reacting specifically with the dinitrophenyl group. Such small molecules were termed haptens. Thus, a new antigenic specificity may be grafted on to an antigen. On the other hand, a limited enrichment of gelatin with tyrosine increased its immunogenicity without significantly changing its specificity. Thus, it is possible to change both immunogenicity and antigenic specificity by chemical modification. An increase in immunogenicity by means of appropriate adjuvants has developed significantly due to the availability of synthetic adjuvants which may also be attached covalently to the antigen. Synthetic polypeptides (polymers of amino acids), linear and branched, have been used extensively in immunological research, as their structures are both simple and well known. This permits the construction of hundreds of antigens for the purpose of elucidating the molecular basis of antigenicity, and later the molecular basis of manifold immunological phenomena. Knowing the chemistry of the copolymers made it possible to arrive at conclusions about the role of various structural features in their antigenic function. It was determined that the immunogenically important area of the molecule must be readily accessible and not hidden in the interior of the molecule. By chemical modification antigenic materials may be converted into nonantigens [e.g., by attachment of polyethylene glycol or by poly(o~-alanylation)],whereas nonantigenic materials may become immunogenic. Recent examples of a decrease in immunogenicity are described by Fuertges and Abuchowski (1990) and by Sasaki et al. (1993). An interesting example of increasing immunogenicity involves the insertion of a peptide from interleukin- 1 into poorly immunogenic recombinant proteins (Beckers et d., 1993). The presence of electric charges on a macromolecule is not a minimum requirement for it to be immunogenic. The overall shape of the molecule does not seem to be a crucial factor in immunogenicity, whereas the size seems to be important: Very few molecules of less than 2 kDa are immunogenic, and immunogenicity increases steadily with molecular size. The presence of aromatic amino acids increases the chance of a small molecule’s becoming immunogenic by itself. Generally, in our current understanding, such a small molecule will be

THE NATURE O F THE ANTIGEN

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immunogenic if it can serve both as a B-cell epitope and a T-cell epitope at the same time. Appropriately constructed polymers of D-amino acids may be immunogenic in a similar way to polymers of natural L-amino acids. To detect this antigenicity, however, it is necessary to immunize animals with very low doses, as in the dose range required to prove the immunogenicity of Lamino acid polymers, the D-polymers may induce immunological tolerance, also called paralysis. This is probably because they are metabolized very slowly, if at all. Through studies of structurally related immunogens, it was possible to establish that antigens, such as pneumococcal polysaccharides, Escherichia coli lipopolysaccharides and D-amino acid polymers, which possess repeating antigenic determinants and are slowly metabolized, are T-independent, i.e., they do not need the cooperation of helper T cells and B cells, whose progeny produce antibodies, for an efficient immune response. In contrast, most antigens, including L-amino acid copolymers, are T-dependent. The purely cellular immune response is limited to the T-cell population, of which many subpopulations are now known, and it probably involves the cooperation of helper T cells and effector T cells. Antigens leading to an immune response of essentially any desired specificity can be prepared synthetically, including the production of antibodies against peptides, oligosaccharides, oligonucleotides, tRNA, and lipids, as well as against haptens such as penicillin, prostaglandin, dinitrophenol, pyridoxal, and ferrocene. Similarly, antibodies have been obtained against many biologically active peptides such as angiotensin, bradykinin, and vasopressin. Moreover, totally synthetic immunogens, including peptide segments of viral coat proteins, e.g., MS2 bacteriophage, hepatitis virus, and bacterial toxins (diphtheria, cholera) have been produced, and they have led to the production of antibodies capable of neutralizing the virus or inducing protection against diphtheria and cholera in experimental animals, thus opening the conceptual door to the production of synthetic vaccines (for a review, see Milich, 1989). To give just one of the many examples where synthetic antigens were of crucial importance in detecting or elucidating a defined immunological phenomenon, the genetic control of immune response should be mentioned. The capacity to respond well or poorly to a certain antigenic stimulus is under strict genetic control. This observation has been made possible largely because of synthetic antigens (chemically simple) and inbred strains of animals (genetically simple). Using defined branched synthetic polypeptides, differing only in a limited manner in their antigenic determinants, it was possible to prove conclusively that genetic control of the

300

MICHAEL SELA AND ISRAEL PECHT

immune response is determinant-specific (McDevitt and Sela, 1965, 1967). McDevitt showed later that the immune response to these synthetic antigens was linked to the major histocompatibility locus of the species (McDevitt and Chinitz, 1969). The Zr genes and their products (Ia) have been extremely important in enabling us to understand the phenomena of immunity and resistance to diseases.

N . ROLEOF CONFORMATION IN ANTIGENICITY

Spatial folding of proteins plays an important role in determining their antigenic specificity, as is apparent from the poor reaction-or total lack of cross-reaction-between denatured proteins and antibodies to the same proteins in their native form (Sela, 1969; Todd et al., 1982; Novotny et al., 1987; Laver et al., 1990; Roberts et al., 1993; Ota et al., 1993). For example, antibodies to native bovine pancreatic ribonuclease do not react at all with the ribonuclease oxidized by performic acid, which is a randomly coiled chain devoid of disulfide bridges. Nor do antibodies to ribonuclease oxidized by performic acid react with the native enzyme (Brown et al., 1959). Similarly, antibodies prepared in goats against rabbit IgG do not react with the rabbit IgG after all its disulfide bridges have been opened by reduction (Freedman and Sela, 1966).This is undoubtedly due to changes in the conformation of the protein molecule, resulting in loss of the original antigenic determinants. Conformation here designates a particular arrangement of atomic positions in a molecule that can be achieved without the reorganization of chemical bonds. An antigen can provoke antibodies against many different determinants present in its molecule, and some of these antibodies may be overlapping. Thus, antisera against a protein antigen usually contain a population of antibodies of differing specificity, having as a common denominator the capacity to react immunospecifically with the antigen. There are many reported examples in which antibodies have been used for the detection of different conformations in proteins: Metmyoglobin forms a reddish-brown precipitate with antiserum to metmyoglobin. Antisera to apomyoglobin give white precipitates with apomyoglobin but also with metmyoglobin. The release of ferriheme from metmyoglobin must have been due in this case to a change in the conformation of the crossreacting antigen on reaction with antibodies to myoglobin (Crumpton, 1966). With synthetic models it has been possible to build, with the same peptides, immunogens that possess either exclusively sequential or conformationdependent epitopes. Thus, antibodies to the helical polymer (Tyr-AlaGlu), do not react with the peptide Tyr-Ala-Glu, nor do they react with

T H E NATURE OF T H E ANTIGEN

301

larger peptides in which the sequence Tyr-Ala-Glu is repeated several times. On the other hand, antibodies to the Tyr-Ala-Glu peptide do not cross-react with the helical polymer (Schechter et al., 1971). A not yet helical peptide, in which Tyr-Ala-Glu was repeated 11 times, was found to cross-react with antibodies to the helical polymer, and-when followed by circular dichroism-was shown to become helical on reacting with the Fab derived from antibodies to the helical polymer (Schechter et al., 1971). This may have been the first reported case where two biologically active macromolecules reacted with each other via their active sites and transconformation occurred in one of the molecules in order to permit the interaction. Antibodies to a polymer of Pro-Gly-Pro, which has the characteristic triple helix of collagen, cross-reacted with fish, rat, and guinea pig collagen (Borek et al., 1969). This was the first instance in which antibodies to a synthetic antigen reacted significantly with a natural protein, and this cross-reaction was clearly due to their higher-order structure. Similarly, a peptide analogous to a stretch of the hen egg white lysozyme sequence can be synthesized, closed into a ‘‘l00p” by a disulfide bridge, and attached to a synthetic branched polymer. The resulting macromolecule leads to production of antibodies that cross-react efficiently with a unique conformationdependent region of a native protein (Arnon et al., 1971). Antibodies to a peptide will cross-react with the parent protein either if they have a free-solution conformation similar to the one within the native protein or if they can easily transform into that conformation. Thus, on a priori grounds, if the protein segment is more flexible, the chance of crossreaction is higher, even though there are cases where a small peptide is already capable of having a relatively rigid conformation similar to the one it possesses within a native protein. It is obvious for these reasons that it is not realistic to expect that antibodies to any peptide corresponding to a sequence segment within a native protein will necessarily cross-react with that protein. In a study on the evaluation of surface areas on proteins that would be accessible to contacts with large ( 1 nm radius) spherical probes, Novotny et al. (1986) concluded that the primary reason why certain polypeptide chain segments are antigenic is their exceptional surface exposure, making them readily available for contact with antigen combining sites. Exposure of these segments frequently results in high mobility and, consequently, in the reported correlation between antigenicity and segmental flexibility. From the structures determined by X-ray diffraction of five complexes of a monoclonal antibody Fab fragment with its antigen, the epitopes all occupy large areas composed of 15-22 amino acid residues on several surface loops (Laver et al., 1990). The antigenicity of these epitopes is absolutely dependent on the conformation of the native proteins. Each epitope

302

MICHAEL SELA AND ISRAEL PECHl

has a buried surface area on the antigen of 650-900 square antigens. There are 75-120 bonds between the antibody and antigen, as well as salt links and hydrophobic interactions. Energetic calculations suggest that a smaller subset of 5-6 of the 15-22 residues contributes most of the binding energy, with the surrounding residues merely indulging in complementarity. When a native protein is used for immunization, it must be taken into consideration that, besides an immune response to the intact antigen, there will also be an immune reaction (antibodies and specific T cells) against a whole variety of partial degradation products. In other words, some of the cross-reactive antibodies may be a result of the immune response to such results of degradation. Illustrations of such a possibility have been described by Leder et al. (1994). Immunological cross-reactions between totally different antigens are sometimes reported, and may even lead to autoimmune phenomena (e.g., in rheumatic fever) because of the antigenic similarity between epitopes on cardiac tissue and those on streptococci (M protein andlor polysaccharides). A discussion of the molecular mimicry between microbial, viral, and host antigens is given by Shoenfeld and Isenberg (1989). Laine and Esser ( 1 989) have shown that polyclonal rabbit antibodies against melittin, the soluble hemolytic peptide present in bee venom, recognize human C protein C9, the terminal component of the membrane attack complex, and retard C9-mediated hemolysis. Human C9 contains a tetrameric and a pentameric sequence that together match a continuous segment in the melittin sequence. For thymus-dependent antigens it is logical to assume that even though the antibodies are made against conformation-dependent epitopes, T-cell help is triggered by sequential epitopes derived from the same antigen, and the same should be true for the triggering of cytotoxic T cells. Indeed, most of the T-cell clones described to date cannot discriminate between the native and the denatured form of the antigen (Benjamin et al., 1984). Lysozyme-specific T-cell clones have been described that discriminate between native and denatured antigen (Manca et al., 1994). While our current knowledge about the detailed interaction between peptides and the grooves of class I and class I1 MHC antigens is very extensive, nothing is known about the interactions of such grooves with epitopes of a nonpeptide nature, such as oligosaccharides, oligonucleotides, or small organic molecules acting as haptens. In a study on glycopeptides, Unanue and colleagues (Harding et al., 1993) proposed that recognition by T cells does not involve specific interaction between the carbohydrate moiety and the T-cell receptor. It seems, nevertheless, that oligosaccharides and other nonpeptide epitopes should be recognized by MHC class I and class I1 antigens. Otherwise, they would all have to be thymus-independent or to have help from minute amounts of peptides within the antigen.

THE NATURE OF THE ANTIGEN

303

V. ANTIBODY-ANTIGENIC EPITOPE INTERACTIONS

The pioneering kinetic studies on hapten binding to specific polyclonal antibodies (Froese et al., 1962; Day et al., 1963) suggested the operation of a single step binding mechanism:

where Ab, H, and Ab.H are the antibody, the hapten, and the complex, respectively. The specific rate of association is k,, and of dissociation, k,,E. This simple mechanism has been modified with the advent of the very first homogeneous antibody preparations secreted by induced myeloma cells. These allowed a more detailed and rigorous kinetic analysis of the association step. A systematic comparison of the kinetic behavior of a large family of related haptens interacting with an antigen binding site on the IgAMOPC315 indicated that the association process is even more complex (Haselkorn et al., 1974). These results fit a two-step association mechanism which is essentially applicable to all macromolecule-ligand association processes in solution (Eigen, 1974): Ab + H

[Ab.H] k-i

8

Ab.H

where [Ab.H] is an encounter complex in which the antibody and hapten form part of the solvation sphere of each other and Ab.H is the final specific complex. In the [Ab.H] some nonspecific interactions, e.g., electrostatic or hydrophobic, may be formed because of the mere process of the H becoming part of the Ab solvation sphere, in which case one should take Ab.H to be an outer sphere encounter complex. The preceding reaction scheme [Eq. (2)] was employed in a refined kinetic examination of a large number of haptens interacting with a given Ab site. It allowed the resolution of the encounter step and the following step, where establishment of the specific elementary interactions between the contact residues of the sites and the hapten occurs. Most of the reactions listed in Table I were discussed in detail earlier. [For the original detailed treatment, see Pecht and Lancet (1977).] The availability of monoclonal antibodies which allowed many new structures to be resolved led to a disappointingly small number of new kinetic studies on the interactions between specifically raised MAbs and their ligands. Hence current insights are still mainly based on earlier work employing chemical relaxation measurements. For the case of a diffusioncontrolled process, all the parameters of the overall forward reaction are expected to be similar to those of the encounter step formation. Identifica-

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MICHAEL SELA AND ISRAEL PECHT

tion of those binding steps that are diffusion-controlled reactions requires knowledge of several parameters: (1) AH,, in the range 4-5 kcal/mol; and (2) for hapten binding, k,, larger than about 3 x lo7 M’ sec-’.There may still be reactions where these two conditions hold, yet k2 >> k-1 does not. This happens when AH2 is in the range of 4 kcaVmo1 and -TA& is not very large (12.5 kcal/niol). In such cases it may be difficult to determine whether the particular reaction is diffusion-controlled. However, the previously mentioned study on a series of different haptens with the same binding site (Haselkorn et al., 1974) was helpful in this respect: A value of k , , practically independent of the chemical nature of the hapten would then imply diffusion control. The k,,, values determined for the reactions listed in Table I suggest that many may indeed be difbsion controlled. Still, the AH,,, value, together with the variation in k,, for different haptens, seem to indicate that the condition kz >> kl applies strictly for none of these, and that some of them may be at best “almost diffusion-controlled” (k2 k.1). Haptens that are simple aromatic compounds have relatively high rates of association with the antibody because of their rigidity and the hydrophobic nature of the interactions involved. The transition from diffusion control to difbsional preequilibrium is effected by a decrease in kn. This may be the result of a higher AHz, or a higher -TASz, or both. One possible reason for an increase in A H 2 is hydration of the reactants which has to be overcome before binding can occur. Other effects that may lower k2 are ( 1 ) nonspecific electrostatic interactions that have to be broken before binding; and (2) a conformational equilibrium between different forms of the hapten (this may be the case for oligopeptides or oligosaccharides that do not have a preferred conformation in solution). In such cases -TAS2 will be higher, yet no distinct conformational change will necessarily be resolved; and (3) conformational changes in the protein. A good illustration of this case has been reported (Maeda et al., 1977) for the reaction of homogeneous antipneumococcal polysaccharides with di- and tetrasaccharide haptens (Table I). As stated above, the number of more recent kinetic studies on antibodyepitope interactions is relatively small. Results of some representative ones are also presented in Table I. Unfortunately the very different experimental methods employed in these studies allow only a qualitative consideration and limited comparison among them. In the studies on fluorescein binding to specific MAbs, some of which have rather high affinity, a pattern similar to that of other hapten-binding MAb was observed (Kranz et al., 1982): k,, values close to lo7 M-’ sec-’, i.e., approaching diffusion control. Dissociation rates were thus the main cause for affinity variation. The induction of conformational transition in the MAb on hapten binding was assumed for a few cases, though not clearly resolved by the methods

-

TABLE I Kinetics $Antibody-Antzgen Interactionsa Immunoglobulin or antibody MOPC 3 15 Anti-NP MOPC 3 15 MOPC 460a MOPC 3 15 Antiflorescein HOPC 8 MOPC 3 15 Antidigitoxin Antidigitoxin Antipolyalanine Antilactose IgMc Antilactose IgMd Antidextran Anti-Pn. pdysaccharide MAb 4-4-20 MAb 20-4-4 MAb 2B5 MAb 2F8 MAb E225 (antiidiotype) MAb E5.2 (antiidiotype)

kon

Hapten or antigen

(M-I 8')

DNP-NH-CH3 DHNDS-NP a-N-DNP-glycine &-N-DNP-lysine &-N-DNP-lysine Fluorescein Phosphorylcholine DNP-(1ysine)g Digitoxin Ouabain Ala-NH-(CH)zNH-DNS Lactose-dye Lactose-dye IM4-NPFI Hexasaccharide

5.2 x 1.8 x 1.9 x 1.3 x 1.3 x 6.0 4.1 3.3 1.4 1.3 4.0 x 3.9 x 1.1 x 4.4 1.1 x

Fluorescein Fluorescein Cytochrome c Cytochrome c Antilysozyme idiotope Antilysozyme idiotope

6x 4.7-35 x 6.5 1.5 x 1x

lo8 108 108

10' lo8 107 107 107 107

107 lo6 106 106

105 106 lo6 106 105 lo6 103

2.3 x lo5

koff (s-9

540 760 1300 580 53 g X 10-5 110

32 2.4 lo4 1.4 x 10-2 2 29 5 3.9 12 3.7-3.4 x 9-12 x -8 1.0 3.6 x

lo4 10-2 10-5

lo4 lo4

5.2 x lo4

konboff

M-'

9.6 x lo5 2.4 x lo5 1.5 x 105 2.2 x 105 2.4 x lo6 6.6 x 1011 3.3 x 105 1.0 x 106 5.8 x 1010 9.3 x 108 2 x 106 1.3 x 105 2.2 105 1.1 105 g x lo4 1.7-1.8 x 5-27 -gX 1.5 x 1.5 x

AHon

-T&n

(kcaVmol)

(kcallmol)

6.4'

-0.86

7.1

-0.28

6.1 5.1

2.3 4.1

6.0

10" 107 109

lo1' 105

4.3 x 108

5.5 3.8

3.8 5.2

Temp. ("C)

Ref.

21 25 25 23 25 18.5 25 21 22 22 25 25 25 25 25

Haselkorn (1975) Froese and Sehon (1965) Pecht et al. (1972) Lancet and Pecht (1976) Pecht et al. (1972) Levison et al. (1975) Hartmann et al. (unpubl.) Haselkorn (1975) Smith and Skubitz (1975) Smith and Skubitz (1975) Licht (unpubl.) Blatt and Pecht (1976) Blatt and Pecht (1976) Lancet et al. (unpubl.) Maeda et al. (1977)

2 2 20 20 20.4

Kranz et al. (1982) Kranz et al. (1982) Raman et al. (1 992) Raman et al. (1992) Tello et al. (1994)

25

Tello et al. (1994)

a DNP, 2,4-Dinitrophenyl; NP, 4-nitrophenyl; AC, aminocaproate; DNS, 4-dimethylaminonaphthalene-1-sulfonyl-NH-; IMm-NPFI, (isomaltose)n-1-(m-nitropheny1)flavazole; lactose-dye,N-(a-N-acetyl-~-N-DNP-L-lysyl)~-aminophenyl-~-lactoside. Average value.

'

306

MICHAEL SELA AND ISRAEL PECHT

employed. Interesting insights will hopefully emerge from kinetic studies on MAbs binding to protein epitopes. This is illustrated by the study on MAbs raised to cytochrome c both with an affinity in excess of lo9M-' and specific rates of association of about lo6M-' sec-' which, for the two macromolecular reactants, is also at the diffusion control limit. Once more, the affinity is therefore reflected by rather slow dissociation rates (Raman et al., 1992; Kelley et al., 1992). Interestingly, differences in reactivity were resolved toward distinct conformers of the antigen, yet none in the MAbs themselves. The structural analysis of anti-idiotypic MAbs (Tello et al., 1994), notably those to antilysozyme MAbs opens up another exciting area for kinetic and thermodynamic studies (Bhat et al., 1994; Braden and Poljak, 1995). In addition, application of advanced forms of nuclear magnetic resonance (NMR) spectroscopy is also starting to provide information about the solution structure of Fv domains (Freund et al., 1994). Detailed analysis of the elementary steps of hapten binding to the IgA secreted by MOPC-315 is both of broader importance for other protein binding site-ligand recognition processes that take place in different parts of the immune system. Moreover, it may also provide a basis for deeper insight into the mechanisms that underlie the maturation of antibody response (Foote and Milstein, 1994). Thus, the original simplistic assumption that binding site-epitope binding could be represented essentially by the single-step equilibrium [Eq. (l)]resulted in the interpretation of dissociation rate constants as indicators of binding affinity. However, in the mid- 1970s kinetic studies had already resolved conformational transitions to be induced on epitope binding and hence to markedly affect Ab-epitope affinity (Lancet and Pecht, 1976). Significantly, an increasing number of homogeneous antibodies in which distinct conformational changes are induced on epitope binding have been resolved in recent years by X-ray crystallography studies (Rini et al., 1992; Padlan, 1994; Braden and Poljak, 1995). Thus, the view that an induced fit process characterizes antibodyepitope interactions, which first emerged from kinetic studies, is now being firmly substantiated and elaborated on by structural studies and will be briefly reviewed below.

VI. CONFOKM,~'I'IONAI. TRANSITIONS INDUCED BY

HAITEN

BINDING

The extent and significance of structural changes induced in an antibody molecule on binding of its specific hapten or antigen has been a problem addressed by a variety of physicochemical methods including the very early X-ray crystallographic studies (Davies et al., 1988; Padlan, 1994; Wilson and Stanfield, 1994). This was mainly because of interest in the

THE NA'I'UKE

O F THE ANTIGEN

307

mechanism by which immunoglobulin effector functions are initiated. However, it is only recently that direct evidence for the induction of such changes has emerged from structural studies. In fact, a surge in such reports, has taken place during the last few years and has yielded ample evidence for conformational transitions and underscored their relatively wide occurrence and unexpected large extent (Wilson and Stanfield, 1994). Establishing the functional significance of these transitions obviously depends, among other things, on resolving where, i.e., in which Ig domains, they take place. However, it is noteworthy that a range of different experimental methods had earlier shown that antigenic epitope binding induces conformational changes in antibodies of diverse specificities (Pecht, 1976). The time-resolved analysis of hapten-induced conformational transitions, though suffering at that stage from limited knowledge of their extent and functional significance, is becoming part of the clearest and better-established supporting evidence (Zidovetzki et al., 1980). Binding of a hapten (or an antigen) to the immunoglobulin may cause changes in the spatial arrangement of residues in the binding site. These changes may be limited to the contact residues or involve a larger part of the protein. In the latter case, other loci on the immunoglobulin may be affected; i.e., allosteric phenomena will arise (Monod et al., 1965).An allosteric mechanism for the induction of physiological activities of antibodies by antigen binding thus requires evidence for the involvement of longrange conformational changes. Such a model, proposed by Huber et al. ( 1976) based on X-ray crystallographic studies, raised the possibility that these changes include those in noncovalent interactions among the immunoglobulin domains, as well as in the hinge peptides and in the position of the Fab regions relative to the Fc. Spectroscopic and other static methods have also supported the induction of conformational changes, yet their nature and significance have not been unambiguously determined and are still a topic of current debate and experimentation (Schlessinger et al., 1975; Guddat et al., 1995). As in other physicochemical approaches to the study of immunoglobulins, the heterogeneity of normally induced antibodies was a major obstacle to achieving an unambiguous analysis of the kinetics of interaction with haptens. From the results reviewed here later, it is now quite clear that epitope binding-induced conformational transitions are a general characteristic of antibodies. Following the first kinetic study describing the hapten binding-induced conformational transition €or the nitroaromatic hapten-specific murine IgA MOPC460 (Lancet and Pecht, 1976), several other antibodies were studied in great detail and were all observed to conform to the same general pattern. The homogeneous myeloma immunoglobulin MOPC460 was found to display two distinct relaxation times in

308

MICHAEL SELA AND ISRAEL PECHT

its reaction with e-dinitrophenyl-L-lysine, the first in the range 0.25-1 .O msec and the slower in the range 10-18 msec (Lancet and Pecht, 1976). The well-resolved relaxation spectrum of protein MOPC460 with its haptens, as monitored via quenching of the protein tryptophan fluorescence, led to the proposal that this antibody exists in two conformational states and that the equilibrium between them is shifted by hapten binding. This systematic kinetic study of MOPC460 was later extended to a number of other monoclonal antibodies of different specificities and belonging to classes other than IgA. A common, most probably general, mechanism was consistently found to govern these reactions. The homogeneous murine IgM-MOPC 104E is specific for a(1+3)dextran (Schepers et al., 1978). The kinetics of interaction of a series of a-~-glucopyranosyl-(l~3) oligomers of different size and structure with this antibody were extensively investigated. In all cases the observed chemical relaxation spectrum exhibited two well-resolved relaxation times. Thus far data have been analyzed only partially (Schepers et al., 1978; Blatt et al., 1979): For the interaction with the tetrasaccharide both relaxation times and amplitudes fit the following mechanism: Ab+H

r:

Ab.H

R, kR

Ab*.H

ko k-o

Ab*+H

The kinetics of interactions between three galactan-binding homogeneous IgA molecules, XRPC24,5539, and TEPC601, and their oligogalactose haptens was another system studied extensively by the T-jump method. By monitoring the intrinsic fluorescence of the proteins, the chemical relaxation spectra of all three proteins reacting with (Gal)3were found to be composed of two relaxation processes: the faster related to the hapten binding, and the slower to a conformational transition of the proteins (Vuk-Pavlovicet al., 1978; Zidovetzki et al., 1980). A detailed analysis of the concentration dependence of the relaxation times and amplitudes has also shown that this system behaves according to the preceding general mechanism. Both the intact immunoglobulins and their Fab fragments exhibited identical kinetic behavior, indicating that conformational changes are not affected by the Fc and therefore probably do not extend beyond the Fab. To further examine the generality of this mechanism, the kinetics of hapten binding to a series of heterologous recombinants of heavy and light chains prepared from the latter galactan-specific antibodies (X24, 5539,

T H E NATURE OF T H E ANTICXN

309

and T601) was investigated (Zidovetzki et al., 1980). This group of hybrid molecules had earlier been shown to maintain an affinity for theP-D-(1-*6)oligogalactose haptens comparable to that of their parent molecules (Manjula et al., 1976). These antibody-hapten systems also exhibited two relaxation times. The kinetic and amplitude data for the hybrids were found to fit the same general mechanism as that followed by their parent proteins: They exist in two conformational states and the equilibrium shifts to the higher affinity state on hapten binding. Furthermore, some of the specific rates and the thermodynamic parameters of these different steps were found to have values very close to those of their parent molecules. The kinetic and thermodynamic parameters obtained for this group of related antibody molecules were compared in the context of the differences in their amino acid sequences. Particularly interesting is a comparison between a hybrid and its parent proteins. A significant correlation with the parent light chain donor is found only for the rates of conformational transition of the hapten-bound state (kl and k I )of the hybrids. This observation is instructive, as the light chains of T60 1 and X24 have identical sequences except for an alanine exchanged for a serine at position 100. 5539 differs from the former at five positions, and from the latter at six positions (Rao et al., 1979; Rudikoff et al., 1980). The VH regions of X24 and T601 differ at six positions, three of which are clustered in the J segment. VHof 5539 differs from that of the two previous ones in a larger number of positions, both in the D and J segments, as well as in the rest of this domain (Rao et al., 1979). Examinations of the positions that the substitutions in the chains constituting these hybrids occupy in the threedimensional structure of their domains (R. Feldman, personal communication, 1980) are rather informative: They clearly reveal that several of the more important exchanges (e.g., Ser to Ala at L-100) are in the VL-VH contact areas. This is in line with the J segment having a decisive role in the light chain folding and, most probably, also in the heavy-light chain association. Thus, the recombinational events joining Vr. with JI and VH with D and JH, apart from affecting the nature and morphology of the combining site directly, modulate it because of their presence at the VL-VH interface. The rates of structural transitions of the hapten-bound protein exhibit the widest variation, ranging over four orders of magnitude. The hapten association rates are similar to those found for other saccharide-binding proteins (Table I; Clegg et al., 1977; Pecht, 1976) and are two orders of magnitude slower than association rates observed for nitroaromatic-binding immunoglobulins (Pecht and Lancet, 1977). Even slower bimolecular rate constants were found for the binding of saccharides to lectins (Clegg et al., 1977; Loontiens et al., 1977). As suggested earlier (Pecht and Lancet, 1977; Vuk-Pavlovic et al., 1978), these slow rates

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MICHAEL SELA AND ISRAEL PECHI

of saccharide (and peptide) binding to proteins may be a result of the flexibility of these ligands and/or the need to disrupt and form several hydrogen bonds on association. The operation of a common reaction mechanism, shared by heterologous chain recombinants, constitutes strong evidence for the hapteninduced conformational transition being an inherent property of the tertiary domain structure of the immunoglobulin molecules. The variations found in the reaction rates constants most probably reflect modulation effected by the structural variance. For the few heterogeneous antibody preparations that were examined (e.g., equine antilactose antibodies, Blatt and Pecht, 1976), there is also evidence that the preceding general mechanism is operative. The well-characterized group of phosphorylcholinebinding homogeneous antibodies (S 107, T15, H8) has also been studied kinetically. Though only a single relaxation has been resolved, a detailed analysis of the concentration dependence indicates that a more complex mechanism is operative (Oratore et al., 1981). Two questions arise from these observations: (1) What are the structural corrollaries of these kinetically observed conformational transitions? (2) What is their functional significance? The increasing number of reports describing X-ray crystallographically determined antibody structures that undergo conformational transitions provides at least a partial answer to the first question (Rini et al., 1992; Wilson and Stanfield, 1994). It is gratifying that the earlier mechanistic conclusions are now supported by structural studies. Thus, from the activation parameters of the conformational transitions, as well as from the fact that these are monitored via changes in the intrinsic extinction and emission properties of the proteins, one is led to conclude that at least the whole variable module is involved in these transitions. An interesting model of the possible transmission of the structural transitions into the second (constant) domains of immunoglobulin has been suggested: namely, that the hapten binding induces longitudinal interaction spanning the whole length of the light chain dimer of protein 315 (Zidovetzki et al., 1979). Studies on Fd’ interactions with L1, CL1and VL (Alexandru et al., 1980) provided another illustration of the feasibility of longitudinal interactions within the Fab. These interactions could be attained through changes in the lateral contacts between the domains (Abola et al., 1980) and are illustrated in considerable detail by several structural studies (Lascombe et al., 1992; Guddat et al., 1995; Braden and Poljak, 1995; Stanfield et al., 1993). Though conformational transition induced by antigen binding is now becoming a common, generally accepted mechanism, the functional implications of this mechanism remain to be established. The specific rates and activation parameters observed for conformational transition of the range of different systems clearly support the

T H E NATURE OF T H E ANTIGEN

31 1

occurrence of substantial rearrangements. A minimal hypothesis accounting for the observed reaction patterns would be that it reflects readjustment of the proteins to a better binding conformation, i.e., an induced fit mechanism. Significantly, in their studies on humoral immune diversity and its maturation, Foote and Milstein (1991, 1994) have examined the kinetics of hapten (2-phenyl-5-oxazolone) binding to a family of (40) different specific MAbs, and several of these reactions were found to exhibit multistep binding equilibria. They concluded that maturation of the humoral immune response may in fact attain increased affinities of epitope binding via a given preferential conformer and that this may also be the basis for an increase in the diversity of the repertoire.

VII. T CELL-ANTIGENIC

EPITOPEINTERACTIONS

The recognition of antigens by the T-cell compartment of the immune system is a multistep process culminating in the formation of a ternary complex between the TCR for antigen and the binary complex of class I or class I1 MHC-encoded molecules, with short peptides derived from the antigen. Thus, the specificity of the TCR is for a neo-antigenic determinant composed of both the genetically restricting MHC molecule and the bound peptide (Bevan et al., 1994; Rammensee et al., 1993; Rothbard and Gefter, 1991). The recognition process may therefore be considered to consist of two distinct phases, the first in which peptides are produced and bound to the MHC-encoded proteins, and the second in which the TCR binds this binary complex. Since MHC-encoded molecules may bind peptides derived from both self and nonself proteins, the fundamental implication of this is the need for a selection process where cells with TCR that bind self peptides are eliminated during the development process in the thymus, yielding a repertoire of mature T cells that recognize MHC complexes with nonself peptides. Understanding the molecular basis of this selection and maturation process constitutes a major challenge to contemporary immunology. It has been proposed that this process is based on the affinity (and resultant cell surface avidity) between the TCR and a given MHC-peptide complex. Specifically, low avidity would lead to a positive selection, whereas high avidity would result in a negative one. Quantitative analyses of the binding interactions leading to this ternary complex are only beginning (e.g., Kageyama et al., 1995). High resolution three-dimensional structures of several human and murine class I molecules have been complemented by that of the human class I1 molecule (Bjorkman et al., 1987; Garrett et al., 1989; Brown et al., 1993). Both classes of molecules are heterodimeric proteins. Class I is

312

MICHAEL SELA AND I S M E L P E C H I

composed of a membrane-anchored heavy chain noncovalently associated with the P2-microglobulin.The peptide binding groove formed by the two membrane-distal heavy chain domains has been resolved: Two a helices form the walls of the groove, while its floor is provided by a @-pleated sheet. Class I1 molecules are membrane-anchored a and p glycoproteins forming a peptide binding groove, analogous to that in class I molecules. The polymorphism of both these proteins is primarily located in the grooves, producing allele-specific morphology. As a consequence of distinct intracellular processing pathways, class I molecules primarily present peptides derived from endogeneously synthesized (e.g., viral) proteins, whereas class I1 molecules present peptides of exogenous proteins that were taken up endocytotically by the antigen presenting cell (Rammensee et al., 1993; Rothbard and Gefter, 1991). The structure of complexes of defined antigenic peptides with human and murine class I molecules has also been resolved by X-ray crystallography (Madden et al., 1991; Fremont et al., 1992; Zhang et al., 1992). These structures have provided detailed insights into the way in which the groove accommodates amino acid residues of the fitting peptides and “locks” its C and N termini. Examination of the nature and position of the former so-called anchoring residues rationalized the formation of allelespecific peptide “motifs.” These structural insights were preceded and complemented by a large body of information derived from indirect, mainly immunological, studies. This work has yielded some general structural requirements for peptide binding and the resultant exposure of peptide residues to the recognizing TCR. The early demonstration that synthetic peptides representative of viral epitopes can be added to cells carrying appropriate class I molecules, and are therefore recognized efficiently by specific cytotoxic T lymphocytes (CTL), initiated a major effort employing this approach aimed at defining antigenic epitopes. Still, this approach was obviously fraught with uncertainties caused by possible intra- and extracellular proteolysis as well as by the binding mechanism of the added peptides competing with those already bound. It was the demanding challenge of isolating and characterizing the peptides naturally associated with the MHC molecules that provided the required chemical definitions of the different binding motifs (Rammensee et al., 1993). The limited number of different antigen presenting MHC molecules expressed by a given individual implies promiscuity; i.e., that a relatively large number of different molecules bind to each of the expressed MHC molecules in order to provide the required comprehensive response to a dynamically changing repertoire of pathogen-derived peptides. Indeed, estimates were made that more than lo4 different peptides can be bound

T H E NATURE OF T H E ANTIGEN

313

to a given MHC molecule. How this feature is accommodated with the binding affinity and the eventual specificity of the interactions with the TCR are problems that so far have only partial solutions. As stated earlier, X-ray crystallography has yielded high-resolution structures. Detailed analysis of both the structure of the groove formed by the a I and a pdomains of class I molecules and the analogous domains in class I1 together with those of the bound peptides have shown how these ligands interact by a combination of two or three van der Waals contacts between the peptide side chains residing in pockets or anchoring sites as well as by an array of hydrogen bonds. The shape and loci of the pockets were shown to be characteristic for a given MHC molecule and hence to determine the nature of the peptides that can bind to it. Moreover, specific sets of hydrogen bonding lock the C and N termini of peptides bound to class I molecules, thus setting constraints on their length. These binding patterns may in turn affect the conformation of the bound peptides, and vice versa. For example, the MHC structure may be influenced by the bound peptide. Thus, while a few class I molecules would bind octapeptides, most would prefer nonapeptides. In some cases, however, longer peptides would also bind, yet bulge out of the groove with different degrees of loss of binding energy. Still, peptides longer than 11 residues probably would not be bound because of the decline in binding energy. In addition, the question arises as to what extent there is interference in interactions between such bulging binary peptide-MHC complexes and the TCR or whether such structures are recognized at all. The more general issue of the extent to which binding interactions are formed between the TCR and the MHC itself as compared with those of antigenic peptides will be further discussed later. The conformation of bound peptides of equal length has been examined in complexes of the HLA-A2 molecule with four distinct epitopes (Madden et al., 1993). It was shown that as a result of “stapling” of the peptide at both ends via the anchor residues, as well as C and/or N termini, the central parts vary considerably in both chain and side-chain conformation. Thus, the conformation of bound peptides may be a function of both their sequence and their mode of interaction with the groove. Consequently, other residues and possible main-chain elements may be solvent- exposed and hence become TCR contact points. This may provide the rationale for the exquisite sensitivity to minor changes in peptide structure whereby a single residue change transforms a peptide into an antagonist in the T cell-induced response (Madrenas et al., 1995). Thus, while considerable constraints may operate in determining whether a peptide is bound because of its length and the nature of the anchor residues, great variability can exist in the exposed residues. The preceding considerations did not take into account the possible changes induced in

3 14

MICHAEL SELA AND ISRAEL PECHT

the conformation of the MHC molecule itself on peptide binding; since the TCR is assumed to recognize different composite structures constituted of contacts with both MHC and bound peptide elements, the induction of distinct MHC conformers on binding different peptides would provide an effective enlargement of the repertoire limited by the number of MHC alleles. While only side-chain conformation was observed to be peptide structure-dependent in the HLA-A2 molecule (Madden et al., 1993), the a - a helix of the H-2K" molecule was found to vary between two different peptide complexes (Fremont et al., 1992). This observation may perhaps indicate the wide range of potential structural cases to be expected. Pioneering studies aimed at quantitative understanding of peptideMHC interactions have already yielded insights into the thermodynamic and mechanistic aspects. Both soluble forms and cell surface-bound MHC molecules were employed in these studies, and it was assumed that the same complexes are formed with certain extraneously added peptides as with those produced by intracellular processing of antigen. Moreover, no knowledge of the actual state of the peptide binding sites was available in most cases, and another assumption was either that they are empty or that bound peptides are displaced. Still, monitoring in different ways the results of adding peptides is a widely accepted practice, and it has also been employed in efforts to quantitate affinity and the number of complexes required for CTL activation. Indeed, while earlier studies did not distinguish between intracellular and surface bound peptides, Kageyama et al. (1995) developed a more rigorous protocol for that purpose. Binding affinities were observed in a range similar to that reported by earlier studies (105-10xMI). The critical number of peptide MHC complexes required to become a CTL target ranged from several thousands to less than 10 per cell. This once more implies a relatively wide range of response and hence flexibility exhibited by this branch of the immune response. The marked similarity of the three-dimensional structure of class I1 MHC molecules implied on the basis of biochemical properties, domain organization, and genomic structure was clearly established by crystallographic analysis of the HLA-DR1 molecule. The similarity also extends to the overall architecture of the peptide binding site. However, striking differences are observed in the mode of peptide binding and hence in the nature of the peptides bound to the two classes. This is first noted in the length of the peptides bound; in contrast to the limited length of those bound to class I, apparently no such limit applies to those binding to class I1 (Chicz and Strominger, 1992; Hunt et al., 1992).The structural basis for these differences lies in the relatively small differences between the sites and the positioning of key residues forming H bonds with the peptide: In the structure of one defined peptide bound to the DR1 molecule (Stern et al., 1994) both ends of the 13-residue-long ligand extend outward and

THE NATURE OF T H E ANTIGEN

315

no hydrogen bonding is observed at the end of the groove. Probably because of the lack of clear relation between the end of the peptide and the anchor positions it is more difficult to characterize binding motifs for class I1 alleles. From random screening of libraries and binding measurements of systematically varied peptides, it became apparent that the motifs include more anchor residues than those of class I motifs and are less specific (Sette and Grey, 1993). The distinct modes of peptide binding to the groove of these two classes of MHC-encoded proteins also lead to marked differences in the pattern of peptide exposure. The class I-bound peptides are exposed mainly in the center of the groove, while those bound to class I1 present potential contact points distributed all along the groove (though approximately similar surfaces are produced in both cases). Results indicate that minor differences in the detailed structure of the composite peptide-MHC surface available for engagement with the TCR may provide distinct signaling (Madrenas et d., 1995). One of the parameters that may determine the distinct signals is the orientation of the engaged and clustered TCRs with respect to the above surface (Ortega et al., 1988). While the rigor of quantitative studies of MHC-peptide interactions on intact cells is somewhat limited experimentally, other problems have confronted investigations using soluble class I or I1 products. One is the relatively limited stability of these molecules in the “empty,” i.e., peptide-free, state and another involves the use of detergents. Still, the availability of recombinant-soluble class I molecules like the H2-Kd molecule, which exhibits considerable stability in the empty state, complemented studies done on intact cells and substantiated their validity (Fahnestock et al., 1994). Furthermore, extensive studies on peptide-class 11 binding kinetics have been carried out by McConnell and associates (Beeson and McConnell, 1994; Witt and McConnell, 1994; de Kroon and McConnell, 1994). This work showed that both peptide association to and dissociation from class I1 sites are slow (5 hr < t l / z < 100 hr). While the slow rate of binding is attributed to the required dissociation of the site-occupying peptide, the dissociation rate was found to be relatively constant and insensitive to the structure of the bound peptide (Witt and McConnell, 1992). The mechanism of binding is thus complex and involves both short- and long-lived peptide-protein complexes. The short-lived complex is probably an intermediate transformed into the long-lived species in a monomolecular step. Significantly it is the latter state of the complex that is assumed to be recognized immunologically. It was hrther proposed that formation of these intermediary species is a general feature of peptide-class I1 binding mechanism and that some of these species are due to two peptides being transiently associated with one protein molecule. Properties of the peptide-MHC class I complexes have also been probed by studying their intrinsic fluorescence as well as by monitoring

316

MICHAEL SELA A N D ISRAEL PECHT

fluorescence resonance energy transfer (Gakamsky et al., 1995; Catipovic et nl., 1994). While an expanded groove conformation was proposed for the empty state, it becomes more compact on peptide binding. An intriguing issue that emerges in considering the mode of peptide binding to class I and particularly class I1 MHC molecules is whether their grooves can accommodate molecules other than peptides. This question gathers considerably more significance in view of observations that T-cell response can be dramatically modulated even by minor changes in the sequence of bound peptides. The ability of class I1 sites to accommodate relatively long peptides has been shown to extend even to peptides with constrained conformations such as the loop peptide (residues 64-82 of hen egg white lysozyme), which is disulfide-bonded in addition to containing two prolyl residues (Visser et al., unpublished, 1990). Some evidence for the binding of ligands not derived from polypeptides emerged from studies on I-A extracts (Demotz et al., 1989; Rudensky et al., 1991). Moreover, helper T-cell reactivity toward streptococcal carbohydrates (Jackson et al., 1984) and evidence for direct binding of DNA to class I1 molecules (Mozes et al., 1996)clearly raise the interesting possibility of rather distinct molecular entities being bound and presented, at least on the latter MHC gene products. A different though important type of antigenic epitopes being presented by both class I and I1 molecules have structural elements that protrude from the bound peptide. Thus, chemically modified peptides bound to MHC molecules were shown to be the epitopes recognized by some specific T cells. In addition to the fundamental importance of this finding, there are obvious bearings on a wide range of drug and chemically induced allergic and autoimmune diseases. It also provides a rationale for T-cell reactivity toward transition metal ions coordinated to peptides (Von Bonin et nl., 1992; Martin et al., 1992). Moreover, the complexity of T-cell recognition of antigen has recently been illustrated by data showing that tails of MHC-bound peptides can also interact with the T-cell coreceptor CD4, increasing the affinity of these multipoint interactions (Vignolli and Strominger, 1994).

ANTIGENS VIII. THYMUS-INDEPENDENT

Most antigens are thymus-dependent; i.e., they require the cooperation of T and B cells for efficient antibody formation. Thus, soluble protein antigens are classified as T-dependent antigens because they do not elicit antibody responses in the absence of T-lymphocyte help, which may involve the presence of either T lymphocytes or T lymphocyte-derived factors (Mosier and Subbarao, 1982; Fitch et al., 1993).This is most probably

THE NATURE OF 'I'HE ANTIGEN

317

correct for cytotoxic T cells also, which may equally need helper T cells for an efficient, purely cellular response. On the other hand, T-independent antigens are those that can activate B lymphocytes in the absence of T lymphocytes (more precisely after depletion of T lymphocytes by the best methods available at the time of the experiment). There are two types of T-independent antigens. Bacterial lipopolysaccharides have intrinsic mitogenic activity and can cause polyclonal activation of murine B lymphocytes; they have been classified as type 1 T-independent antigens. Responses to this type of antigen probably require cytokines either provided by macrophages or produced by B lymphocytes in an autocrine fashion. T-independent antigens of type 2 are large polymeric molecules that contain multiple repeating antigenic epitopes (Feldmann and Basten, 1971) and are metabolized either not at all or only very slowly (Sela et al., 1972). This category includes many polysaccharides (pneumococcal polysaccharides, dextran, Ficoll, levan), polymerized flagellin, polymers of o-amino acids, and polyvinylpyrrolidone. Type 2 T-independent antigens may not be entirely independent of T-cell help since small numbers of T lymphocytes might greatly augment their response (Mond et al., 1980). The suggestion that repeating antigenic subunits are required for an immunogen to be T-independent (Feldman and Basten, 1971) may be a necessary but insufficient requirement for thymus independence since several multichain synthetic polypeptide immunogens, all possessing repeating antigenic determinants, need both thymus- and bone marrowderived cells to elicit efficient humoral immune responses (e.g., Shearer et al., 1972). The response to a multichain amino acid copolymer composed mostly of proline was T-dependent when the copolymer was composed exclusively of L-amino acids but totally T-independent when it was built entirely from D-amino acids. When a branched polymer was investigated in which peptides of L-phenylalanine and L-glutamic acid were attached to multichain poly-wproline, the response to the determinants with only Lamino acids on the outside was T-dependent, whereas the response to the inside region with only D-amino acids was T-independent (Sela et al., 1972). An important feature of T-independent antigens is a slow rate of metabolism, which results in the persistence of detectable amounts of antigens in macrophages of the spleen and lymph modes several weeks after immunization (Janeway and Humphrey, 1968; Medlin et al., 1970; Van den Eertwegh et al., 1992). The synthetic ordered polymer of the tripeptide L-prolylglycyl-L-proline, designated (Pro-Gly-Pro)", resembles collagen in its three-dimensional structure both in solution (Engel et al., 1966) and in the solid state (Traub and Yonath, 1966). Antibodies to this collagen-like polymer cross-react with several collagens (Maoz et al., 1973) but not with a random copolymer of proline and glycine similar to the

318

MICHAEL SELA AND ISR4EL PECHT

ordered polymer in its amino acid composition but not collagen-like. Fuchs et al. (1974) have found that the collagen-like (Pro-Gly-Pro) is T-independent, whereas the random polymer is T-dependent. Similarly, the native collagen was found to be T-independent, whereas in order to elicit a response to its denatured product, gelatin, thymus cells were required. Can one establish T-cell hybridomas specific to T-independent antigens? Zisman et al. (1993) described the establishment and characterization of T-cell hybridomas specific to the T-independent branched polymer composed exclusively of D-amino acids and compared them to T-cell hybridomas specific to the polymer of the same composition and structure built exclusively of L-amino acids and thus T-dependent. The T-independent wpolymer is presented to T cells by Ia molecules on antigen presenting cells, and the affinity of interaction with Ia molecules is similar to that of the T-dependent L polymer. Incubation with the D-polymer induces increased expression of membranal Ia molecules similar to the response reported for other T-independent antigens, namely, trinitrophenylated Brucella abortus (Vitetta et al., 1987) and antibody-conjugated dextran (Brunswick et al., 1989). The D-polymer has a faster kinetics of presentation than the L-polymer. This faster kinetics may explain the antigenic competition between stretches of D- and L-peptides within poly(DL-peptidyl) proteins, which elicited predominantly antibodies toward D isomers following immunization with poly(n1.-alanyl, tyrosyl, or phenylalanyl) proteins (Schechter and Sela, 1967). Rigorous T-cell depletion may completely abrogate the antibody response to T-independent antigens of type 2, indicating that T cells may be necessary for a bona fide response (Mond et al., 1980, 1983; Endres et al., 1983; Van den Eertwegh et al., 1993). The ligand for CD40 is gp39, and it is essential for T helper cell-dependent B-cell activation. Immunization with the T-independent trinitrophenyl-Ficoll led to a high frequency of gp39+ T cells (Van den Eertwegh et al., 1993). In the case of the Tindependent response of type 2 the process of T-cell activation could be explained by activated B cells being responsible for the activation of T cells. These results are similar to those described earlier from the work of Zisman et al. (1993) who showed that T-independent type 2 antigens were able to activate T cells. Snapper et al. (1994) recently suggested an in uitro model for T-independent induction of humoral immunity based on the requirement for NK cells. In this model in vitro-activated NK cells stimulated cells to secrete antibodies in the absence of any added cytokine. Polyvinylpyrrolidone is a typical T-independent type 2 antigen that is immunogenic in both enthymic and athymic nude mice (Anderson and Blomgren, 1971; Lake and Reed, 1976). Helper T cells activated by polyvinylpyrrolidone could be prepared, and they are similar in cell surface

T H E NATURE OF T H E ANTIGEN

319

phenotype to classic TH1 cells (Van Buskirk and Braley-Mullen, 1987). However, by several criteria they are not identical. Activation of polyvinylpyrrolidone-specific helper T cells requires that B cells be present during the first few weeks after the birth of the mice (Braley-Mullen et al., 1994). The examples of specific T cells against type 2 T-independent antigens just given lead to many questions which may be resolved only on additional experimentation.

Ix.

SUPERANTIGENS

No discussion of antigens would be complete without mentioning superantigens. The term superantigen was introduced to describe a group of microbial antigens that differ in several respects from conventional protein or peptide antigens (White et d.,1989). Most importantly, the recognition of superantigens by TCR appears to depend almost entirely on the variable domain of the TCR chain (Va),with little regard for the other diversity components (Kotzin et al., 1993). Because the relative number of Va genes is limited, a given superantigen is capable of interacting with a large fraction (5-30%) of the T-cell repertoire, whereas the corresponding response to a conventional antigen is usually much less than 1 in 1000. Like peptide antigens, superantigens are presented by class I1 MHC molecules, but they do not engage the peptide groove. Instead the intact, unprocessed superantigen interacts with conserved amino acid residues on the outside of the peptide-binding cleft. Polymorphic differences in MHC that affect peptide binding do not usually affect superantigen binding or presentation to TCR Va, and recognition of superantigens is not normally MHC-restricted (Kotzin et al., 1993). Two types of superantigens have been studied in detail. One type is the so-called minor lymphocyte-stimulating (Mls) antigens (to differentiate them from MHC antigens) first described by Festenstein (1973). These superantigens are encoded by endogenous retroviral genes [in the case of the MISfirst described, it was the product of mouse mammary tumor virus Uaneway, 1991)]. The other type of superantigen includes certain bacterial, mycoplasmal, and viral proteins, of which staphylococcal and streptococcal enterotoxins have been the most studied. Other members of this class include streptococcal M protein and mycoplasma arthritidis mitogen (Kotzin et al., 1993). T-cell receptor-MHC class I1 interaction is required for the T-cell response to bacterial superantigens (Labrecque et al., 1994). Both bacterial and retroviral superantigens share a common binding region on class I1 MHC antigens (Torres et al., 1993). Avery et al. (1994) have described a

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MICHAEL SELA AND ISRAEL PECH7

novel MHC-independent T-cell activation pathway for some bacterial superantigens, such as staphylococcal enterotoxins C and E, that leads to both clonal expansion and expression of CTL effector function, in class IInegative mice. Staphylococcal enterotoxin superantigens, as mentioned earlier, bind class I1 MHC molecules on antigen-presenting cells and on cell-to-cell contact stimulate proliferation of T cells expressing appropriate Vcl gene products. In addition, they can also deliver negative signals to antigen-specific T cells, resulting in a state of unresponsiveness or a loss of viability (Miethke et al., 1993). In some cases the staphylococcal enterotoxin superantigen induces programmed death (apoptosis) in a majority of antigen-specific CD4+ T cells accompanied by genomic DNA fragmentation (Damle et al., 1993). A better knowledge of superantigens has been obtained through elucidation of the crystal structure of staphylococcal enterotoxin B (Swaminathan et a,l., 1992). The unusual main-chain fold containing two domains may represent a general motif adopted by all staphylococcal enterotoxins. The TCR binding site encompasses a shallow cavity formed by both domains, and the MHC class I1 molecule binds to an adjacent site. The crystal structure of another superantigen, toxic-shock syndrome toxin- 1 (TSST-1), has also been reported (Acharya et al., 1994). Despite low sequence conservation, the TSST-1 topology is similar to the structure of the staphylococcal enterotoxin B mentioned earlier, but TSST- 1 lacks some structural features considered central to superantigen activity in the staphylococcal enterotoxin B. A more advanced study, on the three-dimensional structure of a human class I1 molecule complexed with staphylococcal enterotoxin B, has been reported (Jardetzky et al., 1994). The enterotoxin binds to t h e p l domain of class I1 molecules, positioning a TCR binding site above and to the side of the MHC peptide binding site. Antigenic peptides are not inhibitors of superantigen stimulation, and the structure demonstrates that the peptides and the enterotoxin occupy two distinct regions of the class I1 MHC molecule. Jardetzky and co-workers infer that the interaction of related superantigens with class I1 molecules may differ from that reported by them, as different superantigens do not all cross-compete in binding studies. Indeed, a subsequent study (Kim et al., 1994) showed the crystal structure of TSST-1 complexed with a human class I1 MHC molecule and found that the two binding modes differed. Superantigens play a crucial role in certain human diseases such as toxic shock syndrome, toxicity induced by bacterial toxins, and possibly even some autoimmune diseases such as Kawasaki syndrome, rheumatoid arthritis (Drake and Kotzin, 1992), and even insulin-dependent diabetis mellitus (Conrad et al., 1994). The role of superantigens in human diseases is not yet understood, and in many cases probably not even realized, but as

T H E NATURE OF T H E ANTIGEN

32 1

it is clear that superantigens have a dramatic effect on the immune system, it can be predicted that they may also have immunomodulatory effects that

might be beneficial for human health.

X. TUMOR ANTIGENS

A promising way to combat cancer-besides surgery, radiotherapy, and chemotherapy-is immunotherapy . This treatment includes efforts to increase immunity in a nonspecific way as well as specific immunotherapy, in which one uses either antibodies or T cells with a specificity toward antigens on tumor cells, or conjugates of such antibodies with drugs, toxins, or radioactive molecules for immunotargeting (Vogel, 1987; Pietersz et al., 1994), thus combining immunotherapy with radiotherapy or chemotherapy. The main problem in this approach is the search for truly tumorspecific antigens. One has to distinguish them from organ-specific antigens and histocompatibility antigens. In most cases studied, the antibodies used were against antigens present in much higher density on tumor cells as compared with normal cells, but they were never totally absent from the latter cells. Such antigens would therefore be more correctly defined as tumor-selective antigens. Tumor antigens are classified according to the origin of the tumor: experimentally induced (by chemical, physical, or viral carcinogens) or spontaneous. The category of oncodevelopmental antigens is of special interest. These antigens, exemplified by a-fetoprotein and by the carcinoembryonic antigen of the colon, are present in normal individuals before birth but disappear thereafter (or stay at an extremely low level) and reappear in the body fluids in the adult only concurrently with specific cancer diseases. Their quantification may therefore be of diagnostic value. Before discussing the few tumor antigens, described only in the last few years, that seem indeed to be tumor-specific, a few examples will be given from our own work on the successful use of antibodies against some tumorselective antigens in experimental in vivo studies. This may serve as an illustration of several similar studies reported in recent years. One example is the epidermal growth factor receptor, overexpressed in various types of human cancers such as epidermoid and squamous cell carcinomas and gliomas. A monoclonal antibody against the receptor was efficient against KB carcinoma in vitro and in nude mice (Aboud-Pirak et al., 1988). Another example is the Neu/ErbB-2 receptor tyrosine kinase (Stancovski et al., 1994). The monoclonal antibodies prepared against it induced either positive or negative growth effects on tumor growth in athymic mice (Stancovski et al., 199 1). A correlation between the growth-stimulating ef-

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fect of MAb N28 in viuo and activation of the tyrosine kinase function of the receptor was found. The MAbs that inhibited tumor growth had little effect on Neu phosphorylation but specifically induced phenotypic cellular differentiation that included markedly altered cytoplasm and nuclear morphology, synthesis and secretion of milk components (casein and lipids), and translocation of the Neu/ErbB-2 protein to cytoplasmic and perinuclear sites (Bacus et al., 1992). While these antibodies were demonstrated to have a tumor-inhibiting capacity, the inefficient accessibility of antibodies to solid tumors limits their clinical use. To redirect effector lymphocytes to tumor cells, we have constructed and functionally expressed in T cells chimeric single-chain receptor genes incorporating both the antigen binding domain of anti-NeuIErbB-2 antibodies and a transducing subunit of TClUCD3 complex. The resulting T cells, equipped with anti-NedErbB-2 specificity as the ligand binding domain of the chimeric receptor, respond specifically to NedErbB-2-bearing target cells (Stancovski et al., 1993). Several truly tumor-specific antigens have been described-proteins that seem to appear on tumor cells but not on healthy ones (Boon et al., 1994; Tsomides and Eisen, 1994).Attempts to identify the target antigens by biochemical fractionation of tumor cells have failed thus far, with the important exception of the identification of underglycosylated mucins present on breast and pancreatic carcinomas. Gene transfection approaches have proved more successful. A gene family named MAGE codes for antigens recognized by autologous CTL on a melanoma tumor (van der Bruggen et al., 1991; Traversari et al., 1992; Wolfel et al., 1993). These genes are not expressed in normal tissues except the testes. One gene, MAGE- 1, has been isolated (van der Bruggen et al., 199I), and the protein MAGE- 1 has been found to be located in the cytosol of human melanoma cells (Amar-Costesec et al., 1994). A peptide encoded by human gene MAGE-3 has been shown to induce CTLs that recognize tumor cells expressing MAGE-3 (van der Bruggen et al., 1994).When immunized with a melanoma cell vaccine, melanoma patients produced antibody responses to recombinant MAGE-1 antigen (Hoon et al., 1995). Using similar techniques, Kawakami et al. (1994) have reported on the gene (MART-1) for a shared melanoma antigen recognized by tumor-infiltrating lymphocytes (TILs) from patients with metastatic melanoma. MART-1 RNA was detected in melanocytes and melanomas, but not in other cell types, with the exception of retina cells. Identification of the gene for an antigen expressed by most melanomas and recognized by TILs in association with A2 represents another important advance in understanding and perhaps manipulating antitumor immune responses. Thus, hopes are raised again that we are close to the moment when the armamentarium of antigens for combating cancer will be sufficiently developed to undertake specific

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immunotherapy of this disease with vaccines (Bystryn et al., 1993). Roth etal. (1994) have prepared a review article on the immune response against tumors.

XI, CONCLUDING REMAKKS

The progress of immunology in the last few years has been enormous. This sentence could have been written anytime in the last 30 years and always be true. What is changing are the main subjects of this progressthey have moved from antigens to antibodies to immunocytes. The tremendous amount of knowledge acquired about T cells moves now to similar goals concerning B and NK cells. After achieving exciting results concerned with the nature of the signals triggering these cells, our sophistication aims at understanding in detail the actual steps taking place within the activated cells. Notwithstanding all this progress, within the context of this article it is worth stressing that antigenic stimulus is the key factor in any immune response and that the role and nature of the antigen will always play a central role in immunology.

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Progression” (R. Dickson and M. Lippman, eds.), pp. 161-191. Kluwer Academic, Boston. Stanfield, R. L., Takimoto-Kamimura, M., Rini, J. M., Profy, A. T., and Wilson, I. A. ( I 993). Structure 1, 83-93. Stern, L. J., Brown, J. H. Jardetzky, T. S. Gorga, J. C. Urban, R. G., Strominger, J. I.., and Wiley, D. C. (1994). Nature 368,215-221. Swaminathan, S., Furey, W., Pletcher, J., and Sax, M. (1992).Nature 359, 801-805. Swat, W., von Boehmer, H., and Kisielow, P. (1994). Eur.J. Immzmol. 24, 485487. Taussig, M. J., Mozes, E., Shearer, G. N., and Sela, M. (1973). Cd1. Immunol. 8, 299-3 10. _ . lello, D., Eisenstein, E., Schwarz, F. P., Goldbaum, F. A., Fields, B. A,, Mariuzza, R. A,, and Poljak, R. J. (1994).J. Mol. Recogn. 7, 57-62. Todd, P. E. E., East, I. J., and Leach, S. J. (1982). TIES 7, 212-216. Traub, W., and Yonath, A. (1966).J. Mol. Biol. 16, 404-414. Traversari, C., van der Bruggen, P., Van den Eynde, B., Hainaut, P., Lemoine, C., Ohta, N., Old, L., and Boon, T. (1992). Immunogenetics 35, 145-152. Tsomides, T. J., and Eisen, H. N. (1994). Proc. Natl. Acad. Sci. U.S.A. 91, 3487-3489. Van Buskirk, A. M., and Braley-Mullen, H. (1987).J. Immunol. 138, 1031-1037. Van den Eertwegh, A. J. M., Laman, J. D., Schellekens, M. M., Boersma, W. J. A,, and Claassen, E. (1992). Eur.J. Immunol. 22, 719-726. Van den Eertwegh, A. J. M., Noelle, R. J., Roy, M., Shepherd, D. M., Aruffo, A,, Ledbetter, J. A., Boersma, W.J. A., and Claasen, E. (1993).J. Exp. Med. 178, 1555-1565. van der Bruggen, P., Bastin, J., Gdjewski, T., Coulie, P., Boel, P., De Smet, C.,lraversari, C., Townsend, A,, and Boon, T. (1994). Eur.1. Immunol. 24, 3038-3043. van der Bnrggen, P., Traversari, C., Chomerz, P., Lurguin, C., De Plaen, E., Van den Eynde, B., Knuth, A,, and Boon, T. (1991). Science 254, 1643-1647. Vignolli, D. A. A., and Strominger, J. L. (1994).J. Exp. Med. 179, 1945-1956. Vitetta, E. S., Bossie, A., Fermandez-Botran, R., Myers, C. D., Oliver, K. G., Sanders, V. M., and Stevens, 7‘.L. (1987). Immunol. Rev. 99, 193-239. Vogel, C.-W. (ed.) (1987). “lmmunoconjugates.” Oxford University Press, Oxford. Von Bonin, A., Ortmann, B., Martin, S., and Weltzien, H. U. (1992) Int. Iirimunol. 4, 869. Vuk-Pavlovic, S., Blatt, Y., Glaudemans, C. P. J., Lancet, D., and Pecht, I. (1978). Riop/~ys.J. 24, 161-174. White, J., Herman, A., Pullen, A. M., Kubo, R., Kappler, J . W., and Marrack, P. (1989).Cell 56,27-35. Wilson, I. A,, and Stanfield, R. L. (1994). C u m Opin. Stmet. Riol. 4, 857-867. Witt, S. N., and McConnell, H. M. (1992)./. Am. Chem. Sac. 114, 3506-3511. Witt, S. N., and McConnell, H. M. (1994). Biochemzctry 33, 1861-1868. Wolfel, T., Hauer, M., Klehmann, E., Brichard, V., Ackermann, B., Knuth, A., Boon, ‘I.., and Meyer m m Buschenfelde, K.-H. (1993). Znt.J. Cancer 55, 237-244. Zhang, W., Young, A. C. M., Imaral, M., Nathenson, S. G., and Sacchetini, J. C. (1992). Proc. Natl. Acad. Sci. U.S.A. 89, 8403. Zidovetzki, R., Blatt, Y . , Glaudemans, C. P. .J., Manjula, B. N., and Pecht, 1. (1980). Biochemi.ytq 19, 2790-2795. Zisman, E., Dayan, M., Sela, M., and Mozes, E. (1993). Proc. Natl. Acad. Sci. U.S.A. 90, 994998.

ANTIBODY BINDING SITES By JAMES S. HUSTON,’ MICHAEL N. MARGOLIES,t and EDGAR HABER* ‘Creative BioMolecules, Inc. Hopkinton, Massachusetts01748 tDepartment of Surgery MassachusettsGeneral Hospital and Harvard Medical School Boston, Massachusetts02114 *Cardiovascular Biology Laboratory Harvard School of Public Health, and Department of Medicine, Harvard Medical School Boston, Massachusetts02115

I. Overview . . . . . 11. Protein Chemist A. Antibody Fragmentation and Chain Separation. . . . . . B. Refolding and Reassembly of Combining Site , . . . . . . . . . . . . . . . . . . . . . . . C. Antibody Paradigms and Analysis of Primary Structure . . . . . . . . . . . . . . . . . D. Immunoglobulin Shape and Domain Structure E. Immunogenetics of Antibody Formation 111. Engineered Antibody Binding Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Architecture of Fv and Design of sFv Analog . . . . . . . . . . . . . . . . . . . . . . . . . B. Studies of Fv and sFv Proteins ..... ..................... C. Targeting in Vivo by Antibody Sites. D. Binding Equilibria and Linkage in Antibody IV. Antibody Combining Site Structure: Antiarsonate and Antidigoxin A. Antiarsonate Response in Inbred Mice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Crystal Structure of Combining Site of Fab 36-71 ..... C. Site-Directed Mutagenesis Studies of Antiarsonat Contact Residues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Enhancement of Antiarsonate Antibody Affinity by Mutation of Noncontact Residues ... .................. E. Certain Mutations of Antiarsonate Antibodies Engineered ex Vho that Confer Increased Affinity Are Not Observed in Vivo. . . . F. Engineering Changes in Antiarsonate Antibody Specifici G. Structure of Digoxin Hapten and Analogs, and Utility as Model System. . . . H. Diversity among Antidigoxin Antibodie I. Variants of Antidigoxin Antibody 40 J. Structure and Mutagenesis of Antidi K. X-Ray Crystal Structure and Binding Specificity of Antidigoxin Antibody 40-50: Comparison of Structures and Binding Modes of Two Antidigoxin Antibodies, 40-50 and 26-10 V. Enhancing Enzyme Selectivity with Substrate-Selec A. Chemically Cross-linked Antibody-Enzyme Conjugates. . . . . . . . . . . . . B. Bispecific Antibodies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C . Antibody-Enzyme Fusion Proteins D. Targeted Prodrug Activation. . . . . E. Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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330 330 331 333 34 1 343 346 347 349 358 373 377 380 380 381 383 386 390 392 397 398 400 403

42 1 427 428 430 43 1 437 439 439

Copy)-ight0 1996 by Academic Press, Inc. All righta uf~eproductionin any form reserved.

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I. OVERVIEW Recombinant antibodies and their engineered fragments offer remarkable opportunities for theoretical study and practical development (Haber, 1992). Many facets of protein chemistry are integral to antibody engineering, as they have been to immunology (Porter, 1970; Nezlin, 1991). This chapter assesses advances in the understanding and manipulation of antibody binding sites and variable regions. In certain cases, current research is viewed in the context of early discoveries about antibodies to emphasize the continuity of protein chemistry in the field of immunology. This perspective can reveal important generalizations that transcend the limits of studies based solely on polyclonal, monoclonal, or engineered antibodies.

11. PROTEIN CHEMISTRY OF ANTIBODY FRAGMENTS AND ANHGEN BINDING REGIONS Our understanding of antibody structure has grown progressively more refined with advances in protein chemistry, molecular biology, and cellular immunology. The complexities of antibodies have been deciphered by applying a reductionist approach through which the immunoglobulin structure is simplified in stages to reveal its molecular organization. Antibody engineering has reached the vanguard of immunology by combining insights about the three-dimensional structure of antibody fragments with the ability to manipulate genes encoding subregions of antibodies and express them in forms that yield native protein. In 1940 Linus Pauling made one of the earliest efforts at developing a comprehensive theory of antibody structure and formation. It was based on a minimum of tenets, including the correct assumption that serum globulin of the 157,000 molecular weight class had a binding valency of 2 (Pauling, 1940). However, use of a simple model for antibody diversity led him to the incorrect proposition that “all antibody molecules contain the same polypeptide chains as normal globulin, and differ from normal globulin only in the configuration of the chain; that is, in the way that the chain is coiled in the molecule.” Subsequent experiments from his laboratory supported this hypothesis, apparently because specific and nonspecific interactions between antigen and immunoglobulin were indistinguishable (Pauling and Campbell, 1942). The mechanism of antibody diversity remained undetermined for several decades more as protein chemistry and molecular immunology developed the sophistication necessary to analyze antibody structure-fimction relationships. Dissection of the antibody molecule was central to solving

ANTIBODY BINDING SITES

33 1

the mystery of its capacity for binding diversity, as were concurrent breakthroughs in understanding the structure and renaturation properties of proteins. Key concepts that emerged included an appreciation for the hydrophobic effect in protein folding (Kauzmann, 1959) and an understanding of the procedures involved in refolding ribonuclease (Anfinsen et al., 1961; Anfinsen and Haber, 1961; Haber and Anfinsen, 1961, 1962).The antibody folding problem was framed by denaturation and renaturation studies of immunoglobulin proteins under conditions that kept disulfide bonds intact (Buckley et al., 1963; Noelken and Tanford, 1964).The more demanding but critical experiments were subsequently performed, demonstrating the recovery of antibody binding activity from fully reduced and denatured antibody fragments (Haber, 1964; Whitney and Tanford, 1965a,b). The latter work contributed to our understanding of the basis of antibody diversity (see Section 11,B).Polyclonal antibodies were used in these early investigations. The homogeneous immunoglobulin proteins that became available during this period, as accidents of human disease or as nonspecific products of experimentally induced mouse plasmacytomas, proved to be more uniform substrates for antibody binding experiments. These reagents predated, by decades, the tailored antibody binding sites now available from hybridomas, transfectomas, and combinatorial libraries. A. Antibody Fragmentation and Chain Separation The preferential susceptibility to proteolysis exhibited by the antibody heavy (H) chain hinge region is a fortuitous aspect of immunoglobulin structure that has had an enormous impact on our ability to study antibody structure. Work on chain separation dates back to the investigations of Petermann and Pappenheimer on the crude enzymatic digestion of native antibodies (Petermann and Pappenheimer, 1941; Petermann, 1942, 1946), which led to the first study by Rodney Porter on the papain hydrolysis of rabbit antibodies to ovalbumin (Porter, 1950). The enzyme preparations of that era were so impure and separation methods so cumbersome as to preclude accurate measurement of antibody digestion products. Nevertheless, Petermann showed that crude papain could digest the antibody into fragments of roughly one-quarter of its original size (Petermann, 1946), while Porter (1950) found that the products of antiovalbumin antibody fragmentation inhibited ovalbumin aggregation mediated by intact antiovalbumin antibody. In the years that followed Porter studied various aspects of antigen-antibody interactions (Porter, 1957), improved his techniques for fractionating rabbit y-globulin and antiovalbumin (Porter, 1955), and improved his enzyme cleavage experiments. Better separation methods and pure crystalline papain finally allowed him to carry his early

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JAMES S. H U S I O N ET AL.

study (Porter, 1950) to a decisive conclusion. In 1958 Porter published the first proof of the tripartite structure of immunoglobulin G (IgG), on the basis of his successful fractionation of its papain digestion products (Fig. l), which he described as follows (Porter, 1958): These results suggest that the gamma-globulin molecule may be made up of three parts: one of these (my crystallinefraction 111) is identical in all gamma-

globulin molecules and is responsible for the common antigenic specificity of gamma-globulins observed by Treffers and Heidelberger (see Treffers, 1944).The other two parts [fractions I and 111presumably contain the antibodycombining centres, and are also responsible for the physical heterogeneity of gamma-globulins; these parts may be expected to vary from molecule to molecule. This suggested structure of an identical section in all molecules of gamma-globulins and two variable sections which contain the antibodycombining sites is very similar to the picture drawn by Pauling in 1940.

The complete details of this investigation were published several months later (Porter, 1959). However, some critical aspects of antibody structure remained unclear, in part because N-terminal sequence data were consistent with only a single type of polypeptide chain. This confusion arose from a now well-recognized phenomenon that the light (L) chain N-terminus is typically amenable to end group analysis and sequencing but the H chain

0

160 320 480 640 800 960 1120 1280 Volume of eluate (ml)

FIG.I. Fractionation of a papain digest of rabbit y-globulin. Separation of Fab (fragments I and 11) and Fc (fragment 111) by gradient elution of digest adsorbed on a carboxymethylcellulose column. Sodium acetate, pH 5.5, gradient 0.01-0.9 M . (Reproduced with permission from Porter, 1958. Nature 182, 670-671. 0 1958 Macmillan Magazines Ltd.)

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ANTIBODY BINDING SITES

N-terminus is not, as it is usually blocked and unreactive in the Sanger or Edman sequencing procedure. At this time, Edelman discovered that the molecular weight of human IgG in denaturant was dramatically lowered on the addition of a reducing agent (Table I), suggesting “that human y-globulin contains subunits linked at least in part by disulfide bonds” (Edelman, 1959).Edelman and Poulik (1961) then isolated two distinct polypeptide chains from reduced and denatured protein after chromatography on carboxymethyl cellulose in 6 M urea, and the Porter group completed analysis of the polypeptide chain organization of rabbit IgG (Fleischman et al., 1963; reviewed by Porter, 1970). Pepsin was shown to attack the hinge region differently than did papain, cleaving residues C-terminal to the hinge region disulfide bonds to yield a bivalent fragment of 100,000 molecular weight (Nisonoff et al., 1960). Fragments I and I1 (described by Porter as fractions I and I1 in 1958) proved to be functionally similar mixtures of polyclonal antigen binding fragments. After 1965 fragments I and I1 were generally called Fab fragments. Fragment I11 (fraction I11 in Porter) became known as the Fc fragment, being crystallizable and complement binding. B. Refolding and Reassembly of Combining Site

Denaturants were used not only to separate immunoglobulin chains but were also applied in protein denaturation and renaturation studies to clarify the relation between the structure and antigen-binding properties of antibodies. In the early 1960s it was still debated whether binding sites T.4BLE I

Effect of Vurious Reagents on M,pp (1 - ii#) Vulues of Human y-Globulin‘ M a p p (1 - Vp) k standard deviation

Solventb

0.2 M KC1 6 M urea + 0.2 M KC1 0.1 M MEA + 0.2 M KC1 0.1 M M U + 6 M urea + 0.2 M KCI Reduced in 8 M urea 0.1 M M U , next dialyzed against 6 A4 urea + 0.02 M iodoacetamide, then 6 M urea 0.2 M KCI

+

(4.8 f 0.1) x (3.0 f 0.3) x (3.5 f 0.1) x (0.93 k 0.07) x (0.92 0.05) x

*

lo4 lo4 lo4 lo4 lo4

MaPP 192,000 158,000 140,000 48,000 48,000

+

‘ This sample of Cohn fraction I1 (Lederle) contained a small amount of heavy material sedimenting faster than the main 7s component. Reproduced with permission from Edelman, 1959.J. Am. Chem. Sac. 81, 3155-3156. 0 1959 American Chemical Society. b MEA, P-mercaptoethylamine hydrochloride.

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JAMES S . HUSTON E T AL.

differed strictly through variation in H and L chain sequences or through induction of antigen-specific conformations during folding. The proposition was resisted that every binding site to a distinct antigen differed in polypeptide sequence because it required the existence of an incredibly large number of proteins for a normal repertoire of antibodies to form in an individual. This proposition would have appeared more reasonable to immunochemists had they fully accepted the implications of the successful refolding of ribonuclease, which proved that primary sequence was sufficient for recovery of its unique native conformation and enzymatic activity. The fact that ribonuclease was a small, thermostable, globular protein of about 13 kDa, however, led many skeptics to postulate that its refolding did not reflect a general principle of protein chemistry but only a phenomenon peculiar to a subset of proteins. The wide acceptance of the Karush hypothesis (1958),which stated that antigen combining site diversity depended on permutations of disulfide bonding, indicated how little serious consideration was given to the proposition that each antibody refolded uniquely, with each distinct binding site the product of a different polypeptide sequence. In the 1960s the availability of monovalent antibody fragments was coupled with advances in physicochemical methods for monitoring protein structure and improved techniques for measuring antigen-antibody interactions. This climate produced a marked decline in the use of classical serological techniques for analyzing immunoglobulin structure and allowed rigorous studies of antibody renaturation that began from fully reduced and denatured monovalent antibody fragments (Haber, 1964; Whitney and Tanford, 1965a). This work is discussed in the following sections on refolding Fab fragments derived from antibodies to the small enzyme ribonuclease or to the dinitrophenyl (DNP) hapten. 1. Refolding of Antiribonuclease Fab

The insights from definitive research on ribonuclease structure and folding made it an attractive reagent for use in studies on antigen-antibody interaction. The association of fluorescein-labeled antigens with antibody could be monitored, and differences in fluorescence polarization could be used to distinguish aggregates from free antigen (Haber and Bennett, 1962). Spectrofluorimetry in conjunction with chromatography was also used to monitor the distribution of free and complexed antigen (Bennett and Haber, 1963). This research showed that antiribonuclease antibody could be purified from its precipitating ribonuclease antigen by size-exclusion chromatography under conditions that denatured the ribonuclease but left the antibody in its native state. This work also showed that any residual fluorescein-ribonuclease that might remain bound after immunoprecipitation could be detected with great sensitivity. For these studies, polyclonal y-globulin directed against ribonuclease was raised in rabbits. Papain

335

ANTIBODY BINDING SITES

cleavage of the antiribonuclease antibody and ion exchange separation of its digestion products yielded a monovalent Fab population (fragment I or F- 1) specific for ribonuclease. Procedures were established that allowed sensitive measurement of Fab binding activity for 'z51-labeledribonuclease. Experiments were conducted to decide whether the primary sequences of the polypeptides in the antiribonuclease Fab were intrinsically capable of refolding into their native conformations with recovery of their original antigen-binding properties. Denaturation of the antiribonuclease Fab (F-1) was studied under various conditions to find those that guaranteed complete unfolding of the reduced polypeptide chains. As shown in the optical rotatory dispersion analysis in Fig. 2, 6 M guanidine hydrochloride (GuHCl) abolished all evidence of residual structure. The existence of

'

** 3000

-

.

*2wo

-

+loo0

-

n

[II

0.

U

-1000

-ZOO0

-3000

-

I ' 2 10

I

1

230

I

1

250

I

1

270

FIG. 2. Ultraviolet optical rotatory dispersion (ORD) of refolded antiribonuclease Fab fragments. Progressive loss of ordered protein structure was monitored by ORD of' antibody Fab fragments (fragment I, F-I) in native solution or under denaturing conditions, before or after reduction and carboxymethylation of free sulfhydryls, A, Anti-RNase F-I in 0.1 M NaC1; A,anti-RNase F-I in 8 M urea; 0,anti-RNase F-I reduced and carboxymethylated in 8 M urea; 0, anti-RNase F-I reduced and carboxymethylated in 6 M guanidinium chloride. [From Haber (1 964).]

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IAMES S. HUSTON E T AL

residual structure would undermine any proof of the hypothesis in question, as would the presence of antigen. The extent of cysteine reduction under a variety of denaturant conditions was monitored by alkylation followed by S-carboxymethylcysteineanalysis. The values obtained were compared with the moles of cysteic acid per mole of F-1,as determined by amino acid analysis of performic acid-oxidized F- 1 protein. This analysis indicated that 6 M GuHC1, and probably 10 M urea, fully exposed the F-1 sulfhydryls to reduction and alkylation. Data from the refolding and reoxidation of antiribonuclease Fab (F-1) under various conditions of denaturation and reduction are summarized in Table 11. Reoxidation was performed at a low protein concentration of 10 pg/ml, which recovered levels of binding activity that were several times higher than those obtained at higher concentrations of 45-90 pglml. The aggregation state of the renatured protein was also monitored on a sucrose density gradient, which indicated the presence of native Fab with a sedimentation coefficient of 3.2s.Although 56% of the expected binding activity was recovered for the protein that had been denatured in 8 M urea, there was 20% recovery for the antiribonuclease Fab that had been fully denatured and reduced in 6 M GuHCl containing 0.1 M /3-mercaptoethanol,

TABLE I1

Antigen Binding ofAnti-RNme F-I Reduced and then Oxidized with AiP Protein remaining in solutiond

Binding activity after oxidation'

Conditions of reduction6

Conditions of oxidation'

(a)

(%I

8 M Urea, pH 7.5

1 mM Mercaptoethanol, pH 8.0 Carboxymethylated 0.1 M Acetic Acid 1 mM Mercaptoethanol, pH 8.0 Carboxymethylated 0.1 M Acetic Acid 1 mM Mercaptoethanol, pH 8.0 1 mM Mercaptoethanol, pH 8.0

30

56

45 52 62

0 0 22

65 46 53

0

0 27

58

20

8 M Urea, pH 7.5 8 M Urea, pH 7.5

10 M Urea, pH 7.5 10 M Urea, pH 7.5 10 M Urea, pH 7.5

6 M Guanidinium chloride, pH 8.0 6 M Guanidinium chloride, pH 8.5

'"Reproduced with permission from Haber (1964).

* All reductions were done in 0.1 M mercaptoethanol.

' All oxidations were done at a protein concentration of 10 pgiml. Determined by radioactive counting. Expressed as a percentage of activity of an equal concentration of [acetyl-I4C]anti-RNase F-I.

ANIIUODY BINDING SITES

337

conditions under which the antiribonuclease Fab appeared to have lost all residual secondary structure (Fig. 2). This yield of activity was at least 400-fold higher than what would be predicted from a random reformation of disulfide bonds in the protein, leading to the following conclusion (Haber, 1964): “These findings make it highly likely that the amino acid sequence alone determines the conformation of the binding site, and that the specificity of an antibody must be determined at some time prior to protein synthesis.” This recovery of binding activity not only demonstrated renaturation of the component chains but also demonstrated their reassociation into functional binding sites, thus indicating that both tertiary and quaternary structure are derived from primary sequence. 2. Refolding of Antidinitrophenyl Fab Fragments

Refolding studies on monovalent antibody fragments were also being pursued in Charles Tanford’s laboratory. This group had first shown that Fab fragments recovered their antigen-binding activity if their original disulfide bonds were kept intact (Buckley et al., 1963); Fab (against bovine serum albumin) renatured, in the absence of antigen, from concentrated GuHCl under oxidizing conditions. For their primary model system, Noelken and Tanford (1964) purified rabbit Fab (F-1) from rabbit antidinitrophenyl hapten antibodies and likewise recovered DNP-binding activity after refolding of denatured but unreduced anti-DNP Fab. These experiments disproved Pauling’s hypothesis that antibody specificity arose from noncovalent bonds formed within the antibody in the presence of antigen. Fully reduced and denatured anti-DNP Fab was refolded, and significant binding activity was recovered, but with a much lower refolding yield than for the unreduced protein (Whitney and Tanford, 1965a). The physical properties of similarly renatured Fab fragments from nonspecific IgG were also characterized (Whitney and Tanford, 1965b). Renatured anti-DNP Fab preparations were titrated with DNP-lysine to assess binding properties by fluorescence quenching titrations (Fig. 3) (Velick et al., 1960; Eisen and Siskind, 1964). Refolding experiments were carried out on anti-DNP fragment I1 that had been both reduced and denatured before refolding, either in the absence (Fig. 3A) or presence (Fig. 3B) of hapten. The renatured anti-DNP fragment I, refolded from protein with intact disulfide bonds, showed strong quenching of fluorescence (Fig. 3C), with a steep linear profile at low hapten concentrations indicating the presence of high-affinity binding sites (Noelken and Tanford, 1964). In contrast with the profile in Fig. 3C, the shallow curvature of the fluorescence quenching in Fig. 3A suggests a loss of high-affinity binding sites when the original chain pairing was lost, which may have also contributed to the lower magnitude of quenching. When the denatured and re-

JAMES

70 -

s. HUSI'ON

E-r AL

Reoxidized nonspecific fragment I n

n

n

n

Y

0

65

751

I

0

0.05

I

I

I

0.10 0.15 DNP-lysine (ml lop4 M)

0.25

0.20

~

0

0.05

DNP-lysine (ml

0.15

0.10

M)

FIG.3. Fluorescence quenching titrations of refolded polyclonal Fab fragments against dinitrophenyl (DNP) hapten with DNP-lysine. (A) Duplicate DNP-lysine titrations of refolded and reoxidized nonspecific or antibody Fab (fragment 11). The upper curve represents a control experiment using nonspecific rabbit Fab (fragment I) that had gone through the same cycle of unfolding and refolding reactions as the antibody Fab fragment. (B) Titration of nonspecific Fab (fragment I ) and antibody Fab (fragment 11) after reoxidation in the presence of a 100-fold excess of DNP-lysine. The hapten was removed from the reoxidized

339

ANTIBODY BINDING SITES

70 I I

11 Renatured Non-Specific 50 80

ff

I

I

I

I

I

I

F 70

E

d

1

60

Y

50 40

30

01

Renatured Anti-DNP

0.02 0.04 0.06 0.08 0.10 0.12 0.14 DNP-lysine (ml lop4 M)

protein before the titration was carried out. (C) DNP- lysine titration of y-globulin Fab (fragment I) refolded from the denatured state with disulfides kept intact. The top curve is for nonspecific Fab (fragment I) at a concentration of 0.017 g/lOO ml. The lower curve is for renatured anti-DNP Fab at a concentration of 0.018 g/lOO ml. [(A and B) from Whitney and Tanford (1965a); (C) from Noelken and Tanford (1964).]

duced chains of the anti-DNP fragment I1 were refolded in the presence of a 100-fold excess of DNP-lysine (Fig. 3B), the apparent affinity of the binding sites for hapten increased, presumably by enhancing productive chain pairing during refolding of the polyclonal mixture of anti-DNP L and Fd (the N-terminal half of the H chain). In related experiments, Cathou and Haber (1967) observed hapten stabilization of anti-DNP Fab exposed to 4 M GuHC1. They concluded that noncontiguous parts of the antibody molecule were involved in the binding of antigen, implying that discontinuous parts of each chain contribute to the combining site. 3. Refolding of Intact IgG

Although the renaturation of fully reduced and denatured IgG was a logical extension of Fab refolding studies, it represented a formidable tech-

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IAMES S. HUSTON E'I' AL.

nical problem because of the high molecular weight and heterogeneity of the H and L polypeptides in polyclonal IgG preparations. Renaturation of reduced and denatured whole antibody was first attempted by Freedman and Sela (1966a,b) in studies on IgG modified by the addition to lysine &-amino groups of poly-DL-alanyl side chains. Complete reduction and denaturation of polyalanylated IgG in 8 M GuHCl showed improved solubility of the denatured H and L chains. When these derivatized polypeptide chains were renatured, antigenic determinants characteristic of nonspecific IgG reappeared (Freedman and Sela, 1966a).Also, specific antigenbinding activity was recovered from renatured anti-bovine serum albumin IgG (Freedman and Sela, 196613). The isolation of H and L chains followed by their recombination to form IgG under native conditions represented another approach to the problem of chain association. Bjork and Tanford (1971a,b) examined rabbit IgG in which the interchain disulfide bonds had been reduced and alkylated but the intrachain disulfide bonds had been left intact. The unmodified H and L chains were isolated from nonspecific rabbit IgG and characterized in isolation, demonstrating that the H chain existed as a stable dimer, whereas the L chain comprised a stable population of monomers and dimers. The reassembly of these H and L chain preparations under native conditions resulted in full recovery of IgG physical properties (Bjork and Tanford, 1971~). The study of chain recombination was next applied to H and L chain populations isolated from rabbit anti-DNP IgG. The DNP binding sites were analyzed in the parent antibody and in its isolated chains (Painter et al., 1972a), as well as in reconstituted IgG (Painter et al., 1972b). As suggested by previous experiments on the binding properties of renatured anti-DNP Fab (Whitney and Tanford, 1965a), when chain pairing was randomized during reconstitution the average affinity for DNP hapten dropped by a factor of about 1000. Another closely related experiment with polyclonal chains involved comparing homologous and heterologous chain recombinants, where the pairing of the anti-DNP H chain population with nonspecific L chains resulted in lower affinity than when an anti-DNP L chain population had been paired (Haber and Richards, 1966; Painter et al., 1972a). Calculation of binding constants from molal concentrations of reaction components yielded the average unitary free energy change on binding, which simplified interpretation of the recombination experiments (Painter et al., 197213). On the basis of this analysis, chain recombination experiments indicated that the sum of the interactions between DNP and the separated H and L chains equaled that between DNP and the original anti-DNP IgG preparation. However, the mispairing of chains present in reconstituted anti-DNP IgG resulted in a drastic reduction in average

ANTIBODY BINDING SITES

34 1

binding affinity in comparison with that of unrandomized chain combinations.' These recombination studies further substantiated that both chains contributed directly to the antibody binding site and that recombination between different H and L chains could provide for a vastly increased binding site repertoire. These refolding studies first proved the hypothesis that antibody binding sites derive their specificity and affinity for antigen strictly from the sequences and pairing of their component polypeptide chains. This insight provided an important foundation for our understanding of antibody diversity at the protein level. Subsequent progress on the structurefunction relationships of antibodies showed the Fab to possess a highly conserved architecture capable of incorporating enormous diversity within its combining sites. The heterogeneity of antibodies was gradually proven to be directly associated with the regulated biosynthesis of a vast number of immunoglobulin proteins by the immune system. C. Antibody Paradigms and Analysis of Primary Structure

Sequence analysis provided the first indication of domain organization in immunoglobulins. Chemical studies of primary structure became practical with the availability of discrete H and L chain populations, in conjunction with antigen or complement binding fragments (Fab or Fc, respectively) and their component polypeptides. Initially, manual protein sequencing methods were applied to antibodies, and they spawned considerable interest in the comparative study of immunoglobulins. Advances in sequencing technology began with automated instruments (Edman and Begg, 1967; Waterfield et al., 1970) and continued with the development of DNA sequencing techniques (Sanger et al., 1977; Maxam and Gilbert, 1977) coupled with widespread application of the polymerase chain reaction (PCR) to gene cloning (Marks et al., 199 1 a). General features of the complex relation between antibody structure and immunogenetics began to emerge slowly. In 1965 Dreyer and Bennet suggested the daring theory that each H or L chain polypeptide was derived from a combination of two types of genes, variable (V) and constant (C). This hypothesis of antibody biosynthesis incorporated many contemporaneous concepts from protein chemistry. At the same time the studies of Hilschmann suggested the existence of a discrete pattern of variability in the N-terminal half of the L chain and, by implication, in the corresponding segment of the H chain (the Fd) (Hilschmann and Craig, 1965; Hilschmann, 1967). As a simplified model for natural antibodies, investiThis randomization effect has also been discussed in reference to the construction of combinatorial libraries, where original pairings tend to be lost (Gherardi and Milstein, 1992).

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gators made use of Bence Jones proteins, which consist of the homogeneous L chains secreted by patients with multiple myeloma. This malignancy is derived from proliferation of a single plasmacyte, resulting in massive production in the circulation of intact monoclonal immunoglobulin (myeloma protein) and, in the urine, hundreds of milligrams per day of homogeneous L chain (termed Bence Jones proteins). Myeloma protein can also be accumulated by plasmaphoresis in quantities as high as hundreds of grams from a single patient. These homogeneous immunoglobulins, contributed by many patients, became the cornerstones on which immunochemistry developed in the 1960s and 1970s. This development culminated in determination of the three-dimensional structure of an Fab by X-ray crystallography (Poljak et al., 1973). Before the structure was published, Wu and Kabat (1970, 1971) analyzed homologies between available L chain sequences from Bence Jones and myeloma proteins. They identified positions constituting three hypervariable segments in the light chain (V,) and, in conjunction with the corresponding segments of the heavy chain (VH),proposed that this region formed the antibody combining site. Homogeneous immunoglobulins directed against specific antigens or haptens-i.e., true antibodies of known specificity-were pursued by several routes. Highly repetitive antigens were sometimes found to elicit an antibody of highly restricted homogeneity, as in the case of rabbit antipneumococcal or antistreptococcal cell wall antisera, which represented an immune response so limited that it was possible to obtain the sequences of hypervariable segments (summarized by Haber, 1970, 1971; Krause, 1970). During this period Sela and co-workers began their long-term studies on antibodies raised against repetitive peptide antigens, which also produced very restricted responses in some cases. The induction of mouse plasmacytomas provided another source of homogeneous antibodies which were tested against panels of various haptens to find those that bound most tightly, i.e., those that were putative antigen analogs. In this manner McPC 603 was found to bind to phosphorylcholine, and the antigen-antibody complex was solved crystallographically (Segal et al., 1974), as was the complex of Fab’ NEW with the several vitamin K analogs to which it bound (Amzel et al., 1974). The MOPC 315 IgA mouse myeloma protein represented another important system, wherein the putative hapten was the 2,4-dinitrophenyl group (Eisen and Siskind, 1964). In 1966 the entire polyclonal rabbit Fc was sequenced by R. L. Hill and colleagues (1966a,b). The group found that the Fc was homogeneous, as Porter had surmised (1958, 1959), and the sequence data revealed that two homologous units constituted the rabbit Fc sequence. The Hill group proposed that the H and L chains evolved from a common ancestral gene that had undergone a series of gene duplications. While this work on the

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C-terminal half of the rabbit H chain did not directly address the nature of combining site diversity, it led to the sequence analysis of the N-terminal half of the rabbit polyclonal H chain by the Porter laboratory (Fruchter et al., 1970; Mole et al., 1971). This region, the Fd, represents the H chain component of the Fab. Porter’s group was able to obtain unique sequence throughout the Fd, except in the V H at allotypic sites showing a mixture of alternative residues and within each of the three hypervariable segments (now referred to as complementarity-determining regions or CDRs). Because the rabbit Fd was polyclonal, Edman degradation of Fd positions within hypervariable segments resulted in an indecipherable mixture of phenylthiohydantoin products. The final sequence of rabbit Fd thus showed blanks over the three hypervariable segments, in contrast to the sequence determined for the remaining three-fourths of V region framework and the entire first H chain constant region (CH1) structure. The immortalization of B lymphocytes secreting specific antibodies (Kohler and Milstein, 1975) finally provided access to true monoclonal antibodies raised by immunization with a specific antigen. This fostered increasingly sophisticated methods in molecular immunology, leading to analysis of the genetic basis for antibody diversity (Tonegawa, 1983) and maturation of the immune response (reviewed in this volume by Milstein and Neuberger).

D. Immunoglobulin Shape and Domain Structure Although it was clear from the work of Porter (1958, 1959) that the bivalency of IgG resided in a pair of antigen binding regions connected to a crystallizable complement binding region, it was not clear how the two Fab and the Fc were disposed spatially in solution. The Y-shape model of IgG was first supported experimentally by the analysis of hydrodynamic data collected on intact IgG and its papain fragments (Noelken et al., 1965) (Fig. 4A), and then substantiated by electron microscopic pictures of discrete antigen-antibody complexes (Valentine and Green, 1967) (Fig. 4B and C). The first three-dimensional structures of immunoglobulin fragments were solved for a human myeloma Fab (NEW; Poljak et al., 1973) and Bence Jones L chain (Schiffer et al., 1973), which ushered in a new era of atomic resolution in our appreciation of antibody structure. Poljak and colleagues recognized the immunoglobulin fold as the common structural element of domain folding in both the V and C regions. Increasingly refined interpretations of variable region fragment (Fv) structure evolved in the years that followed (see chapters in this volume by Padlan and by Novotny and Bajorath).

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A)

JAMES S. HUSTON ET AL.

B chain

I or II

Fragment Ill

FIG.4. The experimental demonstration of the Y shape of IgG. The gross conformation of IgG as predicted in (A) from hydrodynamic analysis of its fragments and intact structure. In (B) and (C) this shape was further substantiated by analysis of electron micrographs of intact anti-DNP IgG antibody complexes with bivalent DNP ligand (shown above). (A) Schematic representation of a possible model for immunoglobulin G . The short heavy line represents the single disulfide bond between the two A chains. Other disulfide bonds are not shown. [From Noelken et al. (1965).](B) Scale diagram of a hapten-linked trimer of IgG molecules, based on patterns visualized by electron microscopy [note (C)]. The distance between the extremes of the Fc fragments (C) was 225 rt 3 8, (mean and standard deviation of the mean). The length of two Fab fragments linked by the hapten was 120 f 3 A. The difference between these figures gave the estimate for the length of Fc (allowance being made for orientation). The widths of Fab and Fc measured on the electron micrographs varied between a maximum of f10 %, from the mean. (C) A high-magnification electron micrograph of anti-DNP IgG complexes with bivalent DNP ligand showing the projection at each corner of the polygonal shapes. The interpretation of the structure of these complexes is given in panel (B). Magnification: X 500,000. [From Valentine and Green (1967).]

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JAMES S. HUS'I'ON ET AL

E. Immunogenetics of Antibody Formation

The discovery of hybridoma technology by Kohler and Milstein (1975) provided a source of antigen-specific monoclonal antibodies, which were of pivotal importance in the development of immunology. This approach has given critical access to homogeneous antibodies of preselected specificity and provided sources of genes encoding their specific chains. This technology catalyzed advances in cellular and molecular immunology and permitted delineation of the major features of antibody biosynthesis. Late in the 1980s the advent of PCR technology allowed the large-scale generation of VHand VL gene repertoires, which have been assembled randomly into antibody combining regions that appear to function as well as those derived by immunization of mice, rabbits, or humans. This combinatorial approach had been anticipated in early efforts to partially explain the extraordinary diversity of the natural antibody repertoire by the random combination of H and L chains (Cathou and Haber, 1967; Tanford, 1968). Remarkable progress has been made in understanding antibody immunogenetics in relation to binding site structure (reviewed by Cook and Tomlinson, 1995; Milstein and Neuberger, this volume). It has been established that the VH gene is assembled in two stages from its component germline genes, with combination of the D andJHgene segments followed by joining to the VH gene segment to yield VH(D)JH.Likewise the final VL gene comprises a germline VL gene segment fused to a J L where both V and J segments are K or il.The assembly of these genes introduces numerous sources of sequence variation, and the resulting somatic mutations contribute to the diversity of the natural immune repertoire. Rigorous analysis of the human genome and compilation of all data on immunoglobulin loci have revealed the surprising insight that very limited polymorphism exists in human Ig germline genes. A complete map of the human V H locus on chromosome 14 has been constructed. It is 1100 kb in length and has 5 1 functional VH segments and 44 nonfunctional segments (pseudo genes). There are an additional 24 functional VH segments on chromosomes 15 and 16 (Cook and Tomlinson, 1995).Thus, a total of 119 VH germline gene segments have been identified, which can be divided among seven gene families in three clans. In addition, a restricted set of germline genes is involved in assembly of the C-terminal region of VH encoding the H3 loop (D segment) and adjacent FR4 framework region (JH segment), with approximately 30 D 6 J H segments. The human Vr. loci also comprise about 100 germline V gene segments, divided between K and ilfamilies. The presumably complete set of human germline genes for the VH,V,, and V,I segments, as well as the H chain diversity segment (DH) and joining regions (JH, J, JK, and J,I segments) have been identified and

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compiled for distribution through the World Wide Web (VBASE by I. M. Tomlinson, S. C. Williams, S. J. Corbett, J. P. I. Cox, and G. Winter; http://www.mrc-cpe.cam.ac.uk/; Cook and Tomlinson, 1995). Limited polymorphism of the VH loci is graphically analyzed in Fig. 5, which illustrates that, even prior to the V(D)J joining that adds H3 and FR4 to these sequences, the 51 functional VH segments show diversity over their whole length, including the FR1-3 and the first two CDRs. The H2 loop is clearly the region of greatest germline diversity, but several positions in FRs are comparable to H1 in their levels of diversity. Germline polymorphism or somatic mutations in these CDRs and FRs can be critical to the specificity and affinity of a particular combining site, as evidenced by the results of detailed structure-function studies on the binding sites discussed in Section IV. VBASE was used by Tomlinson and co-workers to decipher the general pattern of somatic mutation during maturation of the immune response: sequence diversity spreads outward from the center to the periphery of the binding site (Tomlinson et al., 1996). Molecular modeling of the complete set of germline H 1 and H2 loop conformations consisted of only 83 canonical structures (Chothia et al., 1992). The major sites of diversity in the H chain are in the H3 loop because of permutations and combinations of VH, D, and J H genes, as well as variable splicing of these genes. The 50 functional VH segments have been used to construct combinatorial libraries in which the H3 loop and FR4 were added synthetically to optimize the diversity of the resulting single-chain Fv (sFv) library (Nissim et al., 1994). These findings also provide a genetic basis for the observed success of molecular modeling in the prediction of CDR loop conformations. The experimental observation of a set of restricted canonical CDR loop structures (Chothia et al., 1989) is consistent with the combination of highly conserved framework architecture and a limited set of germline genes encoding the CDRl and CDR2 loops of each chain. This restricted polymorphism in germline antibody genes probably contributes significantly to making the modeling of antibody binding sites a tractable problem (Bruccoleri and Karplus, 1987; Bruccoleri et al., 1988). By comparison, the overall protein folding problem remains beyond our grasp. 111. ENGINEERED ANTIBODY BINDING SITES In 1972 the antigen binding region of an antibody was reduced to a 25-kDa minimum comprising a noncovalent heterodimer of VH and VL domains (Inbar et al., 1972). Discovery of this fragment, the Fv, marked the end of an era when protein chemistry was the principal source of structural

CDR1

10

20

30

CDR2

40

50

60

70

80

90

Amino acid position FIG.5. Germline variability of the 51 hnctional VH segments. Germline sequence variability was calculated for each residue in the VH domain using the formula of Kabat et al. (1991) (number of different amino acids at a particular position divided by frequency of the most common amino acid at that position). Numbering of amino acids and complementarity-determining regions (CDRs) are according to Kabat et al. (1991); designations of the H1 and H2 loops (lighter tint) are according to Chothia et al. (1992). [From Cook and Tomlinson (1995).]

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information about immunoglobulins, as the first high-resolution crystal structures were described in 1973 for an Fab (Poljak et al., 1973)and an L chain dimer (Schiffer et al., 1973).Since then, our understanding of antibody architecture has depended increasingly on X-ray crystallography, nuclear magnetic resonance spectroscopy, and molecular modeling. This activity has produced a profusion of antibody combining sites in novel forms, derived from biosynthetic sources ranging from Escherichia coli to plants. The development of engineered antibodies gained significant impetus from transfectoma expression methods, which allowed all or part of the L or H chain to be fused to an effector protein (Neuberger et al., 1984).For example, Fab fusion proteins were constructed to enhance the activity of recombinant thrombolytic agents through targeted delivery at sites of arterial occlusion (Schnee et al., 1987;see Section V,C). The first reports of recombinant antibodies synthesized in bacteria were published in 1984, involving expression in E. coli of an entire IgG antibody against carcinoembryonic antigen (Cabilly et al., 1984) and of an IgM antibody against 4-hydroxy-3-nitrophenylacetylhapten in E. coli (Boss et al., 1984)and in yeast (Wood et al., 1985). Although the yields in these systems were modest, proof of the synthetic principle was obtained in both cases. Concern about the antigenicity of murine monoclonal antibodies led to the engineering of humanized forms of V regions by the method of CDR grafting, in which murine CDRs are spliced between human FRs to form a chimeric Fv region (Jones et al., 1986).In their first report Jones et al. described the expression of a humanized VH region within an otherwise murine IgE, where it was fused to H chain C regions, placing the original murine VHCDRs of the binding site into a human framework.

A. Architecture of Fv and Design of sFv Analog The minimal antibody combining region, the Fv, was first isolated as a discrete entity in experiments on the MOPC 315 antibody (Inbar et al., 1972;reviewed in Givol, 1991).Because the MOPC 315 Fv heterodimer was intrinsically stable, it suggested that the antibody binding site was a discrete unit of structure, despite its two-chain composition, and that Fv integrity might be sufficient for targeting applications. However, efforts to prepare similar fragments by proteolysis from other homogeneous antibodies were met with the greatest difficulty. The following 15 years of research on Fv proved frustrating, as only a few additional papers appeared in the scientific literature. Finally, in 1988,general strategies for making the Fv were proven to be workable through recombinant DNA methods, suggesting new dimensions for future research in this field. Native Fv were expressed in myeloma cells (Riechmann et al., 1988)as well

350

~ A M E S s. HUSTON

Er

AL.

as in E. coli (Skerra and Pliickthun, 1988; Field et al., 1988), and the first sFv species were likewise produced by refolding of bacterially expressed protein (Huston et al., 1988a; Bird et al., 1988). A comparison of IgG and its proteolytic fragments with the sFv and model sFv fusion proteins is given in Fig. 6. Some of the engineered antibody binding regions of current interest are drawn schematically in Fig. 7, which emphasizes the central position of the Fv in these studies. I . Linker Considerationsfor Bridging V Domains

There are several reasons for covalently linking the V domains that associate to form a functional Fv region. The most significant is that the strength of the interaction between VHand VL domains can vary over many orders of magnitude, and dissociation of an Fv region reduces or eliminates its population of active binding sites. Linking V domains in a way that is conducive to normal binding site function is thus a very useful device. The most commonly utilized method for connecting V regions is to join them at the gene level, which allows a given sFv to be conveniently utilized as a targeting vehicle for any ancillary peptide or effector protein. Gene fusion also has the distinct advantage that genotype and phenotype may be linked in selection methods that rely on phage antibodies or other combinatorial methods (Winter et al., 1994). The choice of linker has FIG.6. Schematic comparison of immunoglobulin G and its Fab and Fv fragments, and single-chain Fv and its fusion proteins. (A) IgG antibody: four chains connected by disulfides, 150,000 molecular weight. Fab fragment: two chains connected by a disulfide, 50,000 molecular weight. Fv fragment: two chains, 25,000 molecular weight. sFv protein: one chain, about 26,000 molecular weight; the sFv is shown in its two possible permutations, VL-VH and VH-VL, with the dotted linker on the back face and the solid linker on the front, for the given orientation of V regions. (B) Single-chain Fv polypeptide chain. The typical sFv protein consists of about 250 amino acids and has a molecular weight of approximately 26,00027,000, with the specific value depending on the actual sequences of the V regions and linker segment. (C) Polypeptide of an sFv fusion protein with a protein effector fused to the C terminus of the sFv. (D) Polypeptide of an sFv fusion protein with a protein effector fused to the N terminus of the sFv. (E) Schematic drawing of an effector-sFv fusion protein in its native conformation [corresponding to the N-terminal fusion protein in (D)]. (F) Schematic drawing of an sFv-effector fusion protein in its native conformation [corresponding to the C-terminal fusion protein in (C)]. Numbers indicate parts of the proteins in (E) and (F) as follows: (1) first residue of the effector domain, which is the N terminus of the fusion protein; (2) N-terminal effector protein domain; (between 2 and 3) spacer sequence that facilitates dual function of effector and sFv; (3) first amino acid residue of VH; (4)last amino acid residue of VH; (between 4 and 5) sFv linker segment; (5) first amino acid residue of VL; (6) last amino acid residue ofV1.; (between 6 and 7) spacer sequence that facilitates dual function of effector and sFv; (7) C-terminal protein effector domain; (8) C terminus of the fusion protein. Light chain and VL, white; heavy chain and VH, gray; sFv linker, black; effector protein, such as a toxin or growth factor, hatched or black. Antigen binding site is part of the Fv region and is indicated by a V-shaped docking site. (Reproduced with permission from Huston et al., 1993b. Int. Rev. Immunol. 10, 195-217. 01993 by Gordon and Breach F’ubl.)

35 1

ANTIBODY BINDING SITES

@$J VH-linker-VL

V,-lin ker -V,

Linker

I

sFv

II

I

1 VH

Linker

VL

F) Antigen Binding Site

Antigen Binding Site

Amino Terminus Carboxyl Terminus Effector-sFv

sfv-effector

352

JAMES S . HUSTON ET AL.

DAbs

Fv

sFv'

sFv

Single-chain bispecific SFVI-SFV~!

Miniantibody (sFv-amph. helix);,

J .... ................... .... ......... .......... ......... )= ......... ......... ............... ........., ,... .... ..... .. ......... ........... ....... .... .... ....... . *

FIG.7. Schematic representations of minimal forms of monovalent and divalent combining site species. (A) VH domain binding site (12 kDa), also termed DAbs (Ward et al., 1989; Davies and Riechmann, 1995). (B) Fv heterodimer, comprising noncovalently associated VH and VL domains (Inbar et al., 1972). (C) Single-chain Fv (26-27 kDa) with linker peptide spanning the distance in the native conformation between the C terminus of the first domain and the N terminus of the second. (D) sFv', fusion of an sFv with a C-terminal cysteinyl peptide. (E) Fab fragment (50 kDa) comprising the L chain and Fd (amino-terminal half of H chain). (F) (sFv'):! dimer (54 kDa) consisting of two disulfide-linked sFv' binding regions (Adams et al., 1993; Kipriyanov et al., 1994; McCartney et al., 1995; Tai et al., 1995). (G) Single-chainbispecific (Huston et al., 1991), sFv2, also termed CRAbs (for chelating recombinant antibodies) (Neri et al., 1995). A 30 kDa dual binding site form of the sFv has been described (Keck and Huston, 1996), termed xBABS (for chimeric bispecific antibody binding site), in which the second binding site is grafted onto the bottom of the sFv to make a single-chain bispecific species. (H) Miniantibody form of sFv-amphiphilic helix fusion proteins (Pack and Pluckthun, 1992). (I) Bis Fv-Cys dimer (Cumber et al., 1992).u) Diabody form of tandem Fv dimers (Holliger et al., 1993; Whitlow et al., 1994). [Modified from Huston et al. (1994).]

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gradually become relatively routine because of the widely proven effectiveness of the original 15-residue linker (Gly4-Ser)3,used to make the 26-10 sFv (Huston et al., 1988a) and its fusion with the B domain of staphylococcal protein A (FB), FB-sFv (Tai et al., 1990). Other linkers have also proven useful, particularly the series designed by the Genex and Enzon group (Bird et al., 1988; Whitlow et al., 1993), but their properties are more complex than those of the 26-10 linker. Alternative methods for cross-linking the V domains of a given Fv were first described by Glockshuber et al. (1990), including genetic modification to introduce a pair of opposing cysteinyl residues that can form an interchain disulfide bond between the domains. In this approach no linker is used, and these disulfide-stabilized Fv (dsFv) species have enhanced resistance to denaturation, relative to the corresponding Fv or SFV.The disadvantages are that it requires considerable additional protein engineering and does not lend itself easily to phage library selection; furthermore, in those Fv regions that undergo conformational changes or domain translation on antigen binding, as is the case for D1.3, the interchain disulfide may preclude the normal fluctuations of structure with a corresponding impact on the ability to bind antigen. Nonetheless, this approach has proven to be of particular interest in constructing Fv-immunotoxins in cases where sFv fusion proteins have been difficult to prepare. Beyond the absolute requirement to be noninteracting and allow normal V domain refolding, the most important consideration in linker design is to choose a linker of sufficient length to bridge the distance between the C terminus of the first V domain and the N terminus of the second V domain. As noted in Table 111, compilation of these bridging distances has been calculated for a number of proteins with crystallographically determined structures. These numbers are given in terms of the linear or Euclidean distance between these points and thus are always less than the distance required operationally to produce a stable sFv. Thus, although the peptide unit length is 3.8 A, a 38-A linker of 10 residues is not sufficient to generate a stable sFv but rather leads to the formation of interchain Fv dimers termed diabodies (Fig. 7, panel J), as first described by Holliger et al. (1993). The effect of linker length is quite dramatic, as shown in Fig. 8 for a series of 26-10 sFv analogs with linkers comprising one to five units of (Gly4-Ser),such that 5- and 10-residue linkers result in 3.5s dimers, whereas 15- and 25-residue linkers yield stable sFv monomers with a 2.5s sedimentation coefficient. Longer linker lengths have been reported to result in less tendency to aggregate (Whitlow et al., 1993; Desplancq et al., 1994), which can possibly result from a variety of effects. In cases where a given linker is strained within the sFv structure, a longer linker always lessens or eliminates such strain in the native conformation; for example, Table I11 indicates that a VL-VH orientation of domains in an

354

JAMES S. H U S T O N ET AL

TABLE 111

Comparison of Interdomain Bridging Distances in Fu Regions of Known Structure" Euclidean distance between linker ends

(At

Structure

PDB

VH-VL

VL-VH

26-10' McPC 603 KOL 4-4-20 D1.3

ligi 2mcp 2fb4 4fab 1fdl 2hfl 3hfm 6fab 2tbj lfl9 1nca 3fab

35.92 34.55 33.06 34.27 35.44 35.28 3 1.93 36.09 34.72 34.74 36.66 29.30

-

-

39.10 39.18 39.50 43.27 42.97 36.55 41.34 4 1.44 43.04 37.20 39.80

4.55 6.12 5.23 7.83 7.69 4.62 5.25 6.72 8.30 0.54 10.50

Hy HEL-5 HyHEL-10 36-7 1 5539 R1Y.9 NC4 1 NEW

(VL-VH)-(VH-VI.)

' Reprinted with modifications from Huston et al. (1993a). With use of the Biosym Insight I1 program and the Protein Data Bank (PDB) coordinates noted, the Euclidean (linear) distance between linker ends was estimated by the following method. The algorithm was used to calculate the distance between the C-terminal a-carboxyl carbon of the first V region and the Nterminal a-amino nitrogen of the second V region; the linker was peptide bonded to each of these positions in their assumed sFv configurations. For the VH-linkerVL configurations, these end points are VH position 128 to VL position 1 according to the structural position numbers in Huston et nl. (1993a). For the VI_linkerVH orientation, these termini are VL position 117 and VH position 1. For all but the 26-10 structure, the differences in Euclidean bridging distances were determined for the VL-VH and the VH-VL constructs, yielding (VL-VH) - (VH-VI.); this distance was in all cases longer for the VL-VH isomer. The 26-10 crystal structure (Jeffrey et al., 1993) did not define the position of VH residue 1, and therefore the PDB data set for 26-10 Fab (ligi was used here) did not permit calculation of the bridging distance for a VL-VH isomer of the 26-10 SFV.

sFv always requires a longer bridging distance than a VH-VL. It has been shown by nuclear magnetic resonance (NMR) relaxation studies (Freund et al., 1993) that the (Gly4-Ser)slinker, within the context of the McPC 603 sFv, is fully hydrated, fluctuates rapidly in configuration, and is devoid of specific interactions with the V domain surfaces except at its ends. Therefore, another explanation for the impact of longer linkers depends on the volume excluded increasing with length of a highly mobile linker. Since self-association of sFv species appears to sometimes be mediated by con-

355

ANTIBODY BINDING SITES

1 .o h

P 0.8

a, Q

U

a,

$

0.6

v)

0,

.-P

g

0.4

0.0 0.0

1.0

2.0 s*

3.0 4.0 (Svedbergs)

5.0

6.0

FIG.8. Sedimentation profiles Ig(s*) versus s*] for 26-10 sFv species with different linker lengths. The (Gly4-Ser), linker was used, with n = 1, 2, 3, 5, resulting in linker lengths ranging from 5 to 25 residues; each 26-10 protein was refolded and affinity-purified as described previously (Tai et al., 1990; Huston et al., 1995). Consistent with the results of Huston et al. (1988a), the 2.5s monomer was formed spontaneously by sFv with 15 or 25 residue linkers, while abnormally short linkers of 5 or 10 residues resulted in noncovalent dimeric species of 3.5S, termed diabodies by Holliger et al. (1993). In this experiment, the diabodies consisted of tandem Fv dimers having the V F and ~ VL on one sFv polypeptide chain associated with the VI. and VH, respectively, on another sFv polypeptide chain (Fig. 75).The short 5 or 10 residue linkers resulted in an inability of the adjacent variable domains to form the intramolecular contacts of the normal unstrained sFv with 15 or 25 residues. These diabodies, or related multivalent Fv species described by Whitlow et al. (1993), thus offer alternative conformations that maintain variable domains in an Fv configuration. [From Tai et al. (1996).]

tacts with the bottom of the Fv, it is thus possible that longer linkers can act to inhibit self-association through steric hindrance of the contact surface on the bottom of the Fv region (McCartney et al., 1995; P. C. Keck and J. S. Huston, unpublished results). The (Gly4-Ser)Jlinker has probably been advantageous because it is devoid of charged or hydrophobic residues that might form strong interactions with V domain surfaces, which may occur with linkers such as the 212 version of the Genex linkers (Whitlow et al., 1993). This may explain why some groups have observed an improvement in antigen-binding affinity of as much as 10-fold on switching from a charged linker to the uncharged (Gly4-Ser)3(Newton et al., 1994; Rybak et al., 1995). During in vivo studies of sFv targeting, an alternative linker (Ser4-Gly), and its truncations also were tested (Adams et al., 1993; McCartney et al., 1995; Tai et al., 1995), but in fact this work has shown an increased tendency of sFv to dimerize in comparison with sFv species with

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JAMES S . HUSTON E T AL.

the standard linker. This may be due to the potential for additional hydrogen bond formation provided by the additional serines or may relate to the restriction of linker motion caused by adding bulkier side chains along the linker. 2. Combinatorial Libraries of Antibody Binding Sites Genetic selection methods have been critical to the emergence of antibody engineering. Whereas proteolysis of IgG and IgA offered no general route to the Fv, PCR cloning methods have provided ready access to murine and human V genes, so that Fv regions may in theory be reproduced from the paired V H and VL genes of any given hybridoma cell line. The extension of this strategy to the use of multiple primers for cloning mixtures of VH and VL genes in wholesale fashion has allowed the generation of V genes that can be assembled into Fab or sFv libraries. The antigen-driven selection of sFv binding sites from these combinatorial libraries of randomly paired VH and VL genes can be accomplished, for example, by expressing them as sFv fusions with a phage coat protein (Winter et al., 1994); methods in use also allow the screening of Fab libraries (Barbas et al., 1991; Burton et al., 1991). The preparation of phage libraries comprising human V region genes (Marks et al., 1991a) has allowed the selection of sFv binding sites composed of authentic human VH and VL domains (Marks et al., 1991b) and offers an efficient and elegant alternative to CDR grafting (Marks et al., 1992, 1993; Schier et al., 1995). Although individual recombinant antibody binding sites may also be derived from monoclonal antibodies and may be prepared either by secretion or by refolding of expressed protein, the combinatorial library is preferable, as its selection process yields sFv species that will necessarily be secreted by E. coli. Studies on the anti-carcinoembryonic antigen (CEA) MFE-23 sFv emphasize the advantages of an sFv carefully selected from a phage library. The sFv-phage library was derived from V genes of CEAimmunized mice, yielding MFE-23 sFv with a CEA affinity of 5 x 10' M-', secretion levels of 20 mg/l (Chester et al., 1994), and superb targeting of tumor metastases in the first sFv clinical trial (Begent et al., 1996).

3. Specificity and Afinity Measurements of Combining Sites Underlying advances in recombinant DNA and PCR methodology, carehl affinity and specificity measurements of antibodies continue to be critically important, as they have throughout the course of immunochemistry. These properties define the fimctional attributes of a combining site of interest, whether derived from a phage library, a monoclonal antibody, or a polyclonal antibody fragment. As this field moves increasingly toward the derivation of combining sites from phage display libraries, it is important to emphasize the

ANTIBODY BINDING SITES

357

cardinal rule of immunology, that the ultimate usehlness of a given combining site is generally governed by its antigen affinity and specificity. The properties of particular antibody binding sites can be defined only within the limits of available assays. Thus, even nearly ideal model systems are subject to experimental limitations. Under the best circumstances, one has the purified antigen and sensitive in vitro assays available, while in the most difficult situations one may have only an in vivo target antigen accessible in animal models. Given the former system, one might need only to compare several high-affinity combining sites selected against the same antigen from a phage library or hybridoma cell lines. Beyond obvious differences in affinity or specificity, such a comparative analysis may uncover subtle yet important differences, for example, in stability, solubility, self-aggregation, or production yield. In addition to equilibrium binding affinity the kinetic rate constants, for antigen association with an antibody binding site and their dissociation, are of particular interest. They are important to current discussions about what would be the most effective properties for targeted delivery of therapeutic agents (Schier et al., 1996) and what may be the natural limitations of the immune system (Foote and Eisen, 1995). This discussion has been fueled by a wealth of new data derived from widely used biosensor instrumentation that functions by surface plasmon resonance or resonant mirror techniques (Van Regenmortel, 1995). The use of stopped flow techniques may still be preferred for the physicochemical measurement of association and dissociation rate constants in the millisecond range. However, this classical approach is more technically demanding than the biosensor methods, which measure the increase or decrease in refractive index within a microscopic binding layer above the biosensor surface. By immobilizing an antigen of interest to the cross-linked dextran coating on the biosensor surface, both the binding and dissociation reactions with soluble antibody species may be monitored. These methods facilitate the comparative assessment of large numbers of analog molecules for binding site optimization or for quantitative assessment of species selected from combinatorial libraries (Schier et al., 1996). 4 . Structural Homology between Fv Regions

Despite the statistically enormous variation in binding properties of the Fv region, its architecture is conserved to a remarkable degree. A number of invariant structural features have been noted within each V domain (Novotny and Haber, 1985). These include the positions of the intradomain disulfide bridge and the adjacent buried tryptophan residue. In the process of expanding the database for this analysis, a scheme was devised for structural homology modeling that allows rapid alignment of a new sequence with a set of proteins having crystallographically determined

358

IAMES S. HUSTON ET AL.

three-dimensional structures. Thus, the conserved architecture of the Fv region is displayed with a schematic diagram of the D1.3 Fv peptide backbone (Fig. 9), wherein the beta strands have been numbered in consecutive order as outer strands (0s)if they are exposed to solvent, or as inner strands (IS) if buried at the interface between V regions. The corresponding structural alignment of this and other V region sequences is reviewed by Huston et al. (1993a). B . Studies of Fv and SFVProteins 1. Limited Proteolysis in Domain Isolation

Factors important in the application of limited proteolysis to immunoglobulins for the production of intact, compactly folded regions have included (1) the presence of specific protease recognition sequences at appropriate positions between the Fab and the Fc or in the switch regions that connect V and C domains; (2) the combination of accessible target sequence and backbone flexibility to promote reaction conditions that favor preferential cleavage at restricted positions; (3) the rigidity of the native domain structure, which helps to protect additional recognition sites from limited cleavage; and (4) the possibility of favoring cleavage between domains by appropriately chosen solvent conditions that enhance domain stability without protecting the hinge or switch regions. The resistance of native V and C domains to proteolysis contributed to the success of attempts to preferentially hydrolyze interdomain sequences. In IgG and IgA, this structural integrity typically served to restrict cleavage to the hinge region and spare the regions between the V and C domains. This protection of the switch region was enhanced by interactions between the Fd and L chains of polyclonal rabbit Fab, which proved resistant to the gentle conditions of papain hydrolysis that had cleaved the isolated Fd chains into 11.5-kDa globular regions (Huston et al., 1972). VI. and CI, domains were also cleaved from Bence Jones L chains (Solomon and McLaughlin, 1969) and served as the basis for characterizing their discrete refolding properties (Bjork et al., 1971). In the case of IgM, the acidic conditions required for peptic cleavage were able to dissociate L and Fd chains, which enhanced preferential cleavage of the interdomain switch regions. Preparation of Fv from IgM proteins by cold pepsin cleavage proved to be the only potentially general procedure for obtaining these fragments (Lin and Putnam, 1978), which involved reaction at pH 4 and 4°C for 24 hr. However, since the IgG and IgA classes of immunoglobulins have not typically yielded Fv under these conditions, and because of the low antigen-binding affinities of individual IgM binding sites, this approach has seen limited use.

VL

N IN-t

C-t FIG 9. Structural conservation of the immunoglobulin fold. (A) Tertiary folds of the Fv region drawn to emphasize conserved elements of Fv structure, based on the D1.3 VH and VL domains within the D1.3 Fab structure solved by Fischmann et nl. (1991) using the coordinates in PDB file lfdl from the Brookhaven National Laboratory (Bernstein et nl., 1977).Variable region amino termini (N-t) and carboxyl termini (C-t) are noted for VH and VI~,which were separated by horizontal translation from their heterodimeric state in the D1.3 Fab structure. Drawings are based on molecular graphics models constructed using the Biosym Insight I1 Program (Biosym Technologies, San Diego, CA). Conserved elements of V regions are designated by nomenclature related to that of Amzel and Poljak (1979). The 0-sheet contacts between the VH and VI- domains are formed by inner 0 strands (IS), indicated as shaded ribbons. The solvent-exposed outer0 sheets are made up of outer0 strands (OS), indicated as white ribbons. Loops in this figure are denoted as top loops (TL) and bottom loops (BL), which correspond to front and back loops, respectively, as defined by Amzel and Poljak (1 979). The CDRs are part of top loops that are drawn as ropelike connections between 0-strand ribbons; bottom loops are represented by linear connections between a carbons. The 0 strands drawn as ribbons in this diagram correspond to the definition of structurally conserved regions (Greer, 1991), being common to all aligned structures. [Reproduced with modification from Huston et nl. (1993a).]

360

JAMES S. HUSTON E T AL.

2. Derivation of MOPC 315 Fv by Limited Proteolysis and Recombinant

DNA Methods The antidinitrophenol MOPC 3 15 murine IgA myeloma protein was an early paradigm for homogeneous antibodies (Eisen et al., 1968), from which the first Fv was generated. Peptic cleavage of the 315 Fab’ (Inbar et al., 1972) or IgA (Hochman et al., 1973) resulted in cleavage of both the L chain and Fd region to yield the intact Fv heterodimer. Peptic digests of 315 Fab’, conducted at pH 3.7 and 37°C for 4 hr, were chromatographed on DNPlysine Sepharose to isolate 48% of the protein as hapten-binding species, 90% of which were Fv fragments. As it turned out, this was a particularly fortuitous example of Fv production (Sharon and Givol, 1976; Givol, 1991). The protein chemistry of 3 15 Fv was explored in a series of papers from the Givol group and later exploited by others as well. In their first two papers (Inbar et al., 1972; Hochman et al., 1973), the classic solution properties of the protein were defined and compared with data for intact 315 IgA derived by Eisen et al. (1968). The Fv was shown to be a heterodimer of VH and VL domains, which associated to form the complete antigen binding site which was indistinguishable from the original DNP binding site of 3 15 IgA or Fab’. These were the first experiments to unambiguously prove that the V domains of an antibody can associate strongly enough to maintain a competent antigen binding site in the absence of an interchain disulfide or C domain interactions. In addition to this characterization, the refolding properties of 3 15 Fv were characterized by Hochman et al. (1973, 1976). These results were consistent with previous studies on the recovery of L chain domain structure after refolding (Bjork et al., 1971; Rowe and Tanford, 1973) insofar as the VH and VL domains could be refolded alone and reassociated or could be refolded together provided that the intrachain disulfide bond was left intact or oxidized prior to renaturation. Formation of the intrachain disulfide bond was an obligatory step in the refolding of 3 15 protein whether it was an isolated V region or an equimolar mixture of both VH and VL. Recombinant forms of the 315 Fv and sFv have been investigated by two groups (McCartney et al., 1991; Cheadle et al., 1992). The simplicity of the classical protein chemistry used to generate 315 Fv contrasts with the highly technical process of engineering the 3 15 Fv and SFV.However, the conventional methods of protein chemistry that yielded 3 15 Fv have never proven general, whereas the recombinant approaches offer broadly applicable strategies for making Fv and sFv proteins. The natural 3 15 Fv refolding properties have been found to be characteristic of the recombinant 3 15 Fv and 3 15 sFv proteins. Furthermore, the disulfide-restricted refolding pathway required by 3 15 Fv is representative

ANTIBODY BINDING SITES

36 1

of other V domains and Fv regions, such as the RllDlO sFv (Nedelman et al., 1993) and 520C9 sFv (McCartney, Oppermann, and Huston, unpublished results, 1991). Refolding of isolated V regions by this approach is a high-yield process because only a single intrachain disulfide can form in vitro. However, in the sFv such oxidation results in one native disulfide cross-linked form and two nonnative fully oxidized forms (Fig. 10) or nine nonnative partially and fully oxidized forms (including the fully reduced form). These multiple oxidized states make such a refolding strategy an inherently low-yield process. McCartney et al. (1991) obtained only about a 4% yield of active 3 15 sFv for this reason. 3. Antidigoxin 26-1 0 sFv

The 26-10 antidigoxin monoclonal antibody has been the subject of comprehensive studies dating from its initial description (Mudgett-Hunter et al., 1982). These investigations continue with the detailed studies of its combining site and three-dimensional structure described in Section IV. The present discussion emphasizes its use as a paradigm in antibody engineering, particularly in the exploration of sFv (Table IV) and sFv fusion proteins. The 26-10 sFv has served as a valuable model system over many years (Huston et al., 1988a) and most recently aided in the development of genetically fined sFv-peptide chelates that provide for the facile coordinaT~ et al., 1995). tion of radiometals such as g g m (George a. sFv Species Based on Anti-Digoxin 26-10 IgG. The 26-10 monoclonal antibody was chosen for development of the sFv (Huston et al., 1988a) both for its potential clinical relevance and for its practical advantages: (1) The V region sequences of the 26-10 IgG had been determined by both protein and DNA sequencing (Novotny and Margolies, 1983; Huston et al., 1988a), giving confidence that, once expressed, synthetic VH and VL genes based on these known sequences would faithfully reproduce the authentic 26- 10 V region polypeptides; (2) the binding sites of the 26- 10 IgG and Fab were of high affinity (K, = 2.4 x log A 4 - l ) ; (3) assays of great sensitivity were available for monitoring the recovery of antigen-binding activity by recombinant 26- 10 species; (4)ouabain-amine-Sepharose affinity chromatography could be used for purification, with elution possible under native conditions on addition of 20 mM ouabain, a highly soluble analog of digoxin; (5) quantitative methods for affinity and specificity analysis allowed the detection of very small changes in the binding site contacts with antigen. b. Expression and Renaturation of 26-10 sFv Proteins. Early 26-10 antibody engineering predated common use of PCR methods, and consequently the 26- 10 V regions were constructed synthetically from overlapping synthetic oligonucleotides (Huston et al., 1988a). The sFv species were expressed as fusion proteins with leaders that enhanced the production of cytoplasmic

362

A)

JAMES S. HUSTON E T AL

Dilution refolding

-

-

Dilution refolding

Oxidation

B) Redox refolding

-

Redox-refolding __.__c

C) Disulfide restricted refolding

,(&, SH

N

formation Disulfide

SH

c

-€d

cl-

N

C - N

~

Nonnative

-

Renatur ation

FIG..10. Refolding schemes for sFv proteins. Structures on left-hand side represent the fully reduced and denatured sFv polypeptide, with the crenelated line indicating the linker segment. The intermediate state of the refolding process is indicated by the middle diagrams, and the right-hand schematics depict the native configuration of the sFv and its disulfide bonds. These disulfides bridge the innerp sheets (hatched walls) and outerp sheets (shaded walls) of each variable domain. (A) Dilution refolding involves a two-stage refolding process, with renaturation of the reduced protein followed by oxidation to form disulfides. (B) The redox-refolding process does not involve isolated intermediates since refolding and reoxidation occur concurrently in solution. (C) Disulfide-restricted refolding leads to multiple intermediates, of which only the correctly oxidized configuration (bottom intermediate) is capable of refolding to form native sFv. There are three possible intermediates if the sFv has been fully oxidized (indicated schematically by the intermediates) and seven other possibilities if the mixture also contains partially and fully reduced forms. [From Huston et al. (1991).]

363

ANTIBODY BINDING SITES

TABLE IV Single-Chain Fv Organization of 26-10 Constructions sFv or sFv’ 26- 10 (acid cleavage) 26-10 (direct expression) 26-loin (direct expression) 26- 1OiS 26- 10-1 26-10-2

Leader

VI

Linker

Vp

Tail

P A A A A A

VH VH VH

GGGGSGGGGSGGGGS GGGGSGGGGSGGGGS (GGGGS),, n = 1-5 SGSSSSGSSSSGS SGSSSSGSSSSGS SGSSSSGSSSSGS

VL VL

SGGGGC

VH VH VH

VL

VL VL VL

sc

inclusion bodies. The polypeptide leaders were removed by extended treatment of the fusion protein in denaturant at pH 2.5, which cleaved the protein at an acid-labile Asp-Pro peptide bond between the leader and sFv polypeptides. After removal of partial cleavage products by Whatman DE 52 anion-exchange chromatography in 6 M urea buffer, acid-cleaved sFv protein was renatured from a reduced, denatured state by dilution in 0.01 M sodium acetate, pH 5.5, followed by exhaustive dialysis to remove denaturant and foster reoxidation of intrachain disulfides. The renatured 26- 10 sFv was purified by ouabain-amine-Sepharose affinity chromatography, which eliminated inactive material and, on elution with 20 mM ouabain, concentrated the active sFv fractions in a relatively small volume. Characterization of the renatured 26- 10 sFv showed significant recovery of binding activity, with retention of most hallmarks of the 26- 10 specificity profile. However, the solubility properties of this early form of the 26-10 sFv were very poor in 0.15 M NaCl + 0.05 M potassium phosphate, pH 7.0, + 0.03% NaN3 (PBSA).Thus, all measurements of binding affinity were conducted in 0.01 M sodium acetate buffer, pH 5.5, containing 0.25 M urea to minimize aggregation. Furthermore, affinity measurements relied on immunoprecipitation with a polyclonal second antibody against V region framework determinants, resulting in perturbation of the Fv region under the conditions of this assay. The digoxin affinities (K,) measured in these experiments gave an association constant for the 26-10 sFv of (3.2 f 0.9) x 1O’M-l and for the 26-10 Fab control of (1.9 f 0.2) x lo8M-’, which were both lower than the normal value of 2 x lo9M-’ obtained for 26-10 IgG in PBSA at pH 7. Once immunoprecipitation was replaced with ultrafiltration, the need for direct binding by a second antibody was eliminated, and the free and bound 3H-labeled digoxin concentrations at equilibrium with each 26-10 species were used to define binding isotherms (Tai et al.,

364

JAMES S . HUSTON ET AL.

1990; Huston et al., 1991). Within experimental error, the 26-10 sFv, FBsFv, Fab, and IgG had identical binding affinities for digoxin of 2.4 x lo9M-l. Refolding of directly expressed 26-10 sFv protein by the glutathioneurea redox buffer procedure yielded 26-10 sFv with excellent solution properties and native 26-10 antigen-binding properties, as given in Table V (Tai et al., 1990; Huston et al., 1995). The inclusion bodies and refolded sFv proteins were prepared without recourse to acid treatment, which had been used in earlier studies to remove the leader (Huston et al., 1988a, 1991). These experiments proved unequivocally that 26-10 sFv can recover a native binding site that faithhlly reproduces the specificity and affinity properties of the natural 26-10 combining site. These results gave credence to the principle that these molecular designs are fundamentally sound and can result in sFv proteins that can recover competent antibody combining sites in general. This prompted our engineering of sFv proteins for immunotargeting to tumor antigens, which are often difficult to characterize in vitro. Direct expression of the 26-10 sFv and other sFv proteins has provided a routine source of inclusion bodies suitable for refolding (Huston et al., 1995; McCartney et al., 1995). With current procedures, at least 30%of the TABLE V

Relative Dissociation Constantsfor 26-10 Binding Sites and Cardiac Glycosidesa

Cardiac glycoside ~~~~~

sFv

FB-SFV

Fab

IgG

4.5 3.6 5.9 5 11.7 50 176

4.2 3.8 4.6 4.2 4.6 37 105

~

Digoxin Digoxigenin Digitoxin Digitoxigenin Acetylstrophanthidin Gitoxin Ouabain

4.2 5.5 10.1 7.6 11.8 50 143

4 4.8 4.4 4.4 6.8 52 160

a Kd,app values are given for 26-l0/digoxin complexes, measured by ultrafiltration to be 4.2 x lo-'' M, within experimental error. Results for other cardiac glycoside complexes were calculated from specificity assays, wherein affinity purified goat anti-mouse Fab was adsorbed to microtiter plates, followed by the 26-10 species of interest. values were derived from the product of the corresponding digoxin Kd,app value and the normalized concentration of glycoside that inhibited up to 50% of maximal 1251-digoxinbinding. For each type of 26-10 species, normalization involved dividing the concentration of each glycoside at 50% inhibition by the concentration of digoxin at 50%inhibition. Reproduced with permission from Tai et al., 1990.J. Biochemistry 29, 8024-8030. 0 1990 American Chemical Society.

ANTIBODY BINDING SITES

365

26-10 sFv protein renatures properly, with yields as high as 830 mg of product per liter of fermented cells when using controlled fermentation to obtain very high expression levels. However, renaturation is the most limiting step, as it typically must be conducted at protein concentrations of 0.1 mg/ml or lower, which in the case of 26-10 sFv yields about 30 mg of affinity-purified 26-10 sFv per liter, and thus demands rather large volumes for refolding gram quantities of protein. In this respect, the use of secretion methods can be competitive, as levels of 5-20 mg/liter can be obtained from the fermentation media or periplasm of cells using the standard secretion vectors for sFv produced from combinatorial libraries (Chester et al., 1994; Schier et al., 1995). Secretion can also be advantageous if an affinity purification step is unavailable, because it usually produces fully active protein. Refolding yields a mixture of active and inactive sFv that must be separated by chromatographic or affinity methods. If the secreted sFv has been engineered to have hexahistidine (His6) at its C terminus, it will complex with an immobilized metal affinity chromatography resin that is properly charged with a divalent cation; this step can both concentrate and purify the sFv that has been secreted. c. Folding Properties of sFv Proteins. The production of biosynthetic antigen binding regions has frequently relied on protein folding, in concert with secretion as an alternative that yields folded protein directly. The interpretation of protein folding reactions is of much current interest, and at the level of applied research, the producibility and stability of engineered antibody proteins is a critical factor in whether they can be clinically useful. The 26-10 sFv refolds spontaneously either by dilution refolding or redox refolding (Fig. 10).This contrasts with the refolding pathways followed by MOPC 3 15 sFv and other sFv molecules that utilize a disulfiderestricted refolding process. The transition curves for the antidigoxin 261O/S sFv in urea or guanidine hydrochloride (Fig. 11) substantiate that refolding is reversible as long as disulfide bonds remain intact during unfolding and refolding. d. N- Terminal Polypeptide Fusions to Form a Bafinctional FB-sFv Fusion Protein. The 26-10 sFv was also tested in the context of a bifunctional sFv fusion protein to investigate if an sFv was capable of refolding while in immediate proximity to an effector domain such as another globular protein. The B domain of staphylococcal protein A was a convenient hsion partner in this experiment, as it served in the dual capacity of enhancing FB-sFv expression while folding into a functional FB domain. In fact, measurements of digoxin and other cardiac glycoside affinities proved that the sFv binding site, with or without FB fusion, was the same as the parent 26-10 IgG combining site (Table V), and that the FB moiety was simultaneously capable of specific association with the Fc region of IgG (Huston and

366

JAMES S. HUSTON E T AL

0

2 4 6 8 Denaturant concentration (M)

FIG. 11. Transition curves for the 26-10/S sFv in guanidine hydrochloride (GuHCI) and urea. The coincidence of denaturation (X or +) and renaturation points (solid squares or triangles) indicates reversibility of the folding process when the disulfide bonds of the variable regions remain intact. The fraction denatured was based on the tryptophan fluorescence of the 26-10 V regions. The 3 hl urea conditions used for refolding 26-10 sFv are thus seen to correspond to mostly native species at equilibrium. Conditions of experiments were the following: a Perkin-Elmer LS-5 spectrofluorometer was used with excitation at 295 nm and emission at 350 nm; samples were incubated at a constant temperature in all experiments between 22.4" and 22.7"C; tryptophan fluorescence was enhanced by unfolding and quenched by refolding. All stock protein solutions were in PBSA and the 26-10 sFv concentration for measurements was 0.75 pA4. The linker used in this molecule was Ser-Gly-(Ser4-Gly)2-Ser.[From Huston et al. (1995).]

Oppermann, 1988; Huston et al., 198813, 1989; Tai et al., 1990). These experiments also proved that an effector domain could be fused to the N terminus of the sFv, which was an important facet of these novel molecular designs, since the N termini of V domains are always free in immunoglobulins and other members of the Ig superfamily. In fact, the sFv itself provided the first demonstration of fusion to the N terminus of a V region, but having a constrained linker fused at both ends to rigidV domains of an sFv is topologically quite different from having a mobile domain fused at the N or C terminus of the V domains (Huston et al., 1991). Access to the

367

ANTIBODY BINDING SITES

combining site of the FB-sFv may have been facilitated by the known flexibility of FB residues 48-58. The apparent advantage of keeping a flexible spacer between the effector and sFv regions has been important in the design of toxin fusions to the sFv N terminus (Nicholls et al., 1993). e. C-Terminal Peptade Fusions to Form Minimal Chelation Sites for y9mTc. During the development of sFv species for targeted immunotherapy, sFv’ proteins were designed with C-terminal cysteinyl peptides (Fig. 12). This C-terminal cysteine was incorporated to facilitate both site-specific labeling and the formation of disulfide-bonded (sFv’)~ dimers (Adams et al., 1993; McCartney et al., 1995). The specific biotinylation of sFv’ species has been demonstrated by Kipryanov et al. (1994), who likewise used cysteinyl peptides as a basis for covalent dimerization. An important medical application would be to design the SFV’for optimal chelation of radiometals. In

sFv Linker

sFv‘ Linker

Tail

Refolding wifh glutathione redox couple

sFv‘-GI

...... ......... ... .... ...... ...,.... ....

:v::

WC?:

:v -S-[Qiulalhi~nyl]

FIG. 12. The ( s F v ’ ) ~engineering scheme, showing the progressive stages of sFv’ condimers. struction and expression, sFv’ renaturation, and oxidation to disulfide-linked (sFv’)~ The sFv and sFv’ polypeptides are each depicted in the VH-VL domain orientation. The sFv‘ has been drawn schematically to emphasize the unpaired -SH at the C terminus. The sFv’ was constructed by fusing the sFv gene to an oligonucleotide encoding the appropriate cysteinyl peptide. The sFv‘ was refolded in a urea-glutathione redox buffer, resulting in a native sFv’ in a C-terminal mixed disulfide with the glutathionyl peptide (sFv’-GI). The protected sulfhydryl group was deblocked by gentle reduction and oxidation to yield disulfide-bonded (sFv‘)~. From McCartney et al., 1995. Protein Eng. 8, 301-314. Reproduced by permission of Oxford University Press.

368

JAMES S. HUSTON ET AL.

the past, antibody fragments were chemically conjugated with chelates for binding radiometals such as 99mTc,the preferred isotope for gamma camera imaging. Toward this goal, a chelation site was made by genetically incorporating Gly4-Cysat the sFv C terminus to form 26-10-1 sFv’ (George et al., 1995; McCartney et al., 1995). This 26-10-1 sFv‘ construction was based on 26-10/S sFv (Table IV), which has the same V regions as the original 26-10 sFv (Huston et al., 1988a),but direct expression resulted in N-terminal alanine, and a serinerich linker of 13 residues [S(G&)BGS]was utilized in place of the generally preferred 15-residue linker of - 10 sFv [(GGGGS)s]. These serine-rich linkers evolved to test the possibili of enhancing solubility with extra hydroxyl groups. The 26-10/S sFv and lated sFv‘ analogs were made as controls for studies with 741F8 sFv, whi targets the c-erbB-2 tumorassociated antigen (Adams et al., 1993; McCa ey et al., 1995). However, the additional serine in these linkers enhance the tendency for selfassociation in some forms of these sFv proteins (Tai, Stafford, and J. S. H., unpublished observations, 1992). Thus, (Ser4Gly)3or its variations should not be substituted for the (GlySer)~linker in routine sFv constructions (Huston et al., 1988a, 1995) but may be useful in enhancing dimerization, when desirable, or in improving the solubility of very marginally soluble Fv regions, as was the case for a T-cell receptor sFv (Hilyard et al., 1994). Ouabain binding by the uncomplexed 26-10-1 sFv’ was measured to determine if hsion of the peptide had an adverse impact on the combining site (George et al., 1995). When a resonant mirror biosensor was used to measure the rate constants for binding and dissociation, the 26-10-1 sFv‘ protein was shown to bind ouabain-labeled bovine serum albumin with a K d of (2.3 k 0.5) x lo-’ M , which was indistinguishable from the value of (2.1 k 0.3) x lO-’M for the 26-10/S sFv. These data confirmed that the presence of the C-terminal fusion peptide did not perturb the Fv in a way that compromised the combining site. The labeling studies presented in Fig. 13 defined optimal conditions for 99mTcchelation under which the 26-10-1 SFV’was able to coordinate 0.5-50 mCi of ggmTcin a high-affinity complex with its C-terminal cysteinyl peptide. Standard labeling conditions involved exposure of 5Opg of 26-10-1 sFv’ (0.5 mg/ml) to 18.5 MBq ggmTcO+in 0.22 mM SnFP at a final pH of about 9.5 for 60 min, which resulted in >97% incorporation of the radiometal. The control 26-10/S sFv was subjected to the same procedure with 6.4 f 2.7% incorporation, which verified that the C-terminal cysteinyl peptide was the principal coordination site in, 26- 10-1 sFv’. The coordination complex was also shown to be very stable when challenged with serum, saline solutions, or DTPA to attempt transchelation (Table VI). In addition, the ggmTc-sFv displayed much better retention of antigen-binding activity after 24 hr in vivo than protein radioiodinated by the chloramine-T method, showing

\

369

ANTIBODY BINDING SITES

2

-

-

20

1 m

-

A

TABLE VI Stability of 99mTc-[26-10-1sFv'j Complexa Sample Control (60 min) Control (24 hr) DTPA PBS Saline Serum

ITLC

TCA precipitation

97.6 f 0.7 98.2 k 2.1 97.0 f 3.6 96.4 +- 3.6 97.1 f 0.5 ND

92.2 f 2.0 ND ND ND ND 92.9 f 4.8

a 9gmTc-[26-10-1sFv'] was prepared and incubated for 24 hr either without dilution or following dilution in DTPA (diethylenetriamine entaacetic acid), PBS, saline, or serum. The radiopharmaceutical purity of the 'gmTc-sFv' was then determined, using instant thin-layer chromatography (ITLC) or trichloroacetic acid (TCA) precipitation, as indicated. In each case, the fraction of total counts that remain complexed by the sFv' is expressed as the mean percentage k standard deviation of three or more experiments. ND, Not done. Reproduced with permission from George et al. (1995).

that 74.2 f 3.9% (n = 8) of the g g m T ~ ~ -complex F~' was able to bind ouabain-Sepharose, whereas only 53.8 k 6.6% of the lz51-labeled26-10-1 SFV'bound to the immunoadsorbent. The 9 9 m T ~ - ~was F ~also ' more stable in vivo than '251-sFv' as measured by trichloroacetic acid precipitation.

370

JAMES S. HUSTON ET A1

4 . Anti-c-erbB-2 741F8 sFv and SFV' Proteins

To extend sFv studies to immunotargeting, the V regions were isolated by PCR cloning from the 741F8 monoclonal antibody directed against the c-erbB-2 tumor-associated antigen (also known as HER-2/neu or p 185H"K2). This oncogene protein has been shown to be abnormally amplified on the surfaces of tumor cells in approximately 25% of cases of breast cancer (Slamon et al., 1987) and in a significant percentage of other adenocarcinomas. The c-erbB-2 extracellular domain (ECD) had been previously cloned and expressed in mammalian cells (Hudziak et al., 1987; Hudziak and Ullrich, 1991), and subsequently a high-expressing Chinese hamster ovary (CHO) cell line was constructed to produce an ECD with a His6 C-terminal extension (McCartney et al., 1995) to facilitate purification by immobilized metal affinity chromatography (Porath, 1992). The purified 90-kDa ECD glycoprotein was used to characterize the 741F8 sFv' and 741F8 (sFv')e dimers (Adams et al., 1993; McCartney et al., 1995). The ECD was found to be a well-behaved monomer in solution, which simplified studies on its interactions with the self-associating 741F8 sFv species. Dimerization of the 26-10 and 741F8 sFv' proteins may be assumed to involve bottom surfaces diametrically opposite to their combining sites (note schematic diagrams in Fig. 14) (McCartney et al., 1995).The discussion here also includes studies on the 26-10 SFV'and (sFv')~proteins, which were used as reference proteins throughout these studies. a.Features of sFv and sFv' Constructions. The V region genes of the 741F8 IgG were cloned from the parent hybridoma cell line using general PCR primers that introduced some mutant residues into the N-terminal FR1 sequence of VH. Refolding of the sFv comprising this VH sequence (version I1 in Table VII) yielded no detectable antigen-binding activity. To correct these errors, refolding properties were compared for two other analogs of the V H in the context of 741F8 sFv. Refolding of the sFv incorporating the version I sequence gave five times the yield of the version I11 analog. Ultimately the anti-c-erbB-2 741F8 Fv region (Dorai et al., 1994) was found to be closely related to the antineuraminidase NC41 Fv (Colman et al., 1987). Excluding the CDR3 loops, their Fv sequences are about 94% identical, and the FRl sequences of the NC41 and version I-741F8 VH regions are identical apart from their N-terminal residues, being Glu in 741F8 and Gln in NC41. Such homologies can be expected to provide a basis for correcting PCR errors in other VH sequences, if necessary. These results suggest that, in isolated cases, primer-induced errors within the FR1 sequence may have a pronounced effect on refolding. In attempting to reproduce a given monoclonal antibody as a recombinant sFv protein, cloning details may thus require close attention in the event that folding

ANTIBODY BINDING SITES

37 1

+ X

X

FIG 14. Models for the reversible self-association of sFv’ subunits and conformational isomerization of (sFv‘):,dimers. (A) This reaction depicts the tendency of the blocked sFv’ species to self-associate through contact surfaces in the vicinity of the sFv C terminus. The true symmetry ofthe dimer cannot be predicted. The protecting group, X, is attached to the C-terminal tail peptide and has been sandwiched at the ( s F v ’ )interface ~ in the noncovalently associated form of the right-hand side. (B) This representation of (sFv‘)~ in solution emphasizes an equilibrium between two extreme conformations, each theoretically capable of bivalent antigen binding. In the compact species on the right-hand side, the sFv’ subunits interact noncovalently as well as through a disulfide bond. On the left-hand side of the reaction scheme, the sFv‘ subunits are linked by an interchain disulfide in an extended conformation, leaving contact surfaces exposed to solution. From McCartney et al., 1995. Protein Eng. 8, 301-314. Reproduced by permission of Oxford University Press.

yields are problematical. Combinatorial libraries are preferred for binding site isolation, as they incorporate selection methods and assays for sFv or Fab that detect only properly refolded molecules, as phage antibodies and as secreted sFv or Fab. 6. Preparation and Analysis of sFv’ and ( S F V ’ )Proteins. ~ The practicality of folding sFv’ proteins has been demonstrated (Adams et al., 1993; Kipriyanov et al., 1994; McCartney et al., 1995), as reasonable yields were obtained by redox-refolding procedures that should be applicable to any

372

JAMES S. HUSTON ET AL.

TABLE VII

VHAmino-Terminal Sequences Used for 741F8 sFvIa

Source

Sequence

Heavy chain’

E V Q L Q Q S G A E L V K P G A

Version I‘

E I * Q L V * Q S G P * E L K * K P G E * T V K

Version I I ~

E V Q L Q E * S G P * E L K * K P G E * T I K I

Version IIIe

E V Q L Q Q S G P*E L V K P G E*T I K I

I

a Residues in versions 1-111 that vary from the 741F8 heavy chain N-terminal sequence are indicated by an asterisk. The 741F8 sFv molecules were constructed with three different VH amino-terminal sequences. From McCartney et al., 1995. Protein Eng. 8, 301-314. Reproduced by permission of Oxford University Press. 741F8 VH sequence obtained by Edman sequencing of the 741F8 heavy chain. VH sequence of the 520C9 anti-c-erbB-2 IgG. VH sequence of 741F8 from cDNA sequence (variant residues introduced by FR1 PCR primer). VH sequence of the 26-10 antidigoxin IgG.

SFV’analogs that refold spontaneously from the reduced random coil (McCartney et al., 1995). The yields for 741F8 SFV’species vary, depending on their particular sequence, but are similar to those for unmodified 741F8 sFv (McCartney et al., 1995). The sFv’-G1proteins were stable at 4°C on extended storage, and their propensity for self-association was minimized substantially in the (sFv’)~ forms. The sFv’-G1 species were easily deblocked by mild reduction with 2 mM dithiothreitol at pH 8.5, and dialysis against the same buffer without dithiothreitol (0.05 M Tris-HC1, 0.15 M NaC1, pH 8.5) allowed oxidation to (~Fv’):! homodimers (McCartney et al., 1995; Tai et al., 1995), as indicated schematically in Fig. 12. The main 741F8 sFv’ constructions and variants used in these studies are listed in Table VIII. All proteins were generated by direct expression, typically using the PET-3d expression vector in the BL21-DE strain of E. coli (McCartney et al., 1995). The 26-10 antidigoxin sFv’ (Table IV)and the 741F8 anti-c-erbB-2sFv’ were refolded in urea-glutathione redox buffers (Tai et al., 1995; McCartney et al., 1995), which resulted in protection of the C-terminal cysteine, presumably as a mixed disulfide with the glutathionyl peptide (Gl). These species have been studied in animal tumor models (Adams et al., 1993; Weiner et al., 1995), and they can be targeted effectively by single or repetitive bolus injections. Continuous infusion maintains a high serum concentration but results in loss of targeting specificity (Weiner et al., 1995), which may nonetheless prove useful in certain sFv scavenging applications for the reversal of drug overdoses.

373

ANTIBODY BINDING SITES

TABLE VIII Single-Chain Fv Organization of 741F8 Constructions" sFv'

74 1F8 74 1F8- 1 741F8-2 74 1F8-3 74 1F8-4C

Leader

VI

Linker

Vph

Tail

A A ADNKFNKDP A A

vu

SSSSGSSSSGSSSS SSSSGSSSSGSSSS SSSSGSSSSGSSSS SSSSGSSSSGSSSS GSSGGGGSGGGGSMA

VL VL VL VL VH

GGGGC GGGGC SC GGGGC

VH VH VH

VL

-

" From McCartney et al., 1995. Protein Eng. 8, 301-314. Reproduced by permission of Oxford University Press. 11 The 741F8 VL domain terminated with the first three residues (RAD) of the switch region. Switch region residues represent part of the linker (Huston et al., 1991), and hence the 741F8-4 linker is formally 18 residues in length, consisting of RADGSSGGGGSGGGGSMA.

C. Targeting in Vivo bj Antibody Binding Sites

Radioimmunotargeting with engineered sFv antibody binding sites is attractive because the rapid sFv clearance yields high target-to-background ratios, both for radioiodinated species (Fig. 15) and specifically labeled Y Y m T ~ -species ~ F ~ ' (Fig. 16). After initial investigations of the 26-10 sFv and its fusion with the FB fragment, the 26-10 sFv became an important reference molecule in the development of other sFv proteins suitable for tumor targeting. This section on therapeutic applications focuses partly on an antitumor model, the anti-c-erbB-2 741F8 sFv, but controls involved various 26-10 sFv analogs studied in parallel experiments. The special merits of g g " l T ~ - ~complexes F~' in targeting tumors (George et al., 1995) suggest that they will be suitable for in vivo diagnostic imaging. Similar coordination chemistry applies to the incorporation of '"Re and '"Re for use in radioimmunotherapy. In virtually any practical application of engineered or natural antibodies, analysis of antigen binding to the combining site is of hndamental importance. The quality of binding in terms of specificity and afinity is very often a decisive factor in whether a given antibody binding site will prove clinically useful. In dealing with in vivo targeting, theoretical and practical issues can be very complex, particularly for multivalent antibody species binding to cells with multiple target epitopes. However, consideration of a simple model for such cellular targeting can avoid many of these complexities and be enlightening. The binding of monovalent antibody species to monomeric surface antigens on a cell represents a situation of

374

JAMES S. HUSI'ON E T AL

2

-s

1.5

v

P

E

l 0.5

0 Tumor

Blood Lungs Organ

Liver Kidneys

FIG. 15. Comparison of pooled 24-hr biodistribution data for 741F8 sFv, sFv'-CAM, Fab, and (sFv')z. The results of eight studies performed with radioiodinated 741F8-2 (sFv')~ (black), three studies performed with 741 F8-3 sFv'-CAM (hatched), and seven studies performed with 741F8 sFv (VH-VL; gray) are compared with 741F8 Fab (white) (Adams et al., 1993). Each separate study was performed with 20-100 pg of radiopharmaceutical administered intravenously in 100 pl to scid mice bearing 100- to 200-mg subcutaneous SK-OV-3 tumors known to express c-erbB-2. Groups of three to eight mice were sacrificed at each time point. Error bars were left out if the standard error of the mean was less than 0.02% IDlg. From McCartney et al., 1995. Protein Eng. 8, 301-314. Reproduced by permission of Oxford University Press.

considerable practical importance. The targeting of both monovalent and divalent species to antigenic sites on a cell surface were analyzed by Reynolds (1979) in terms of general thermodynamic equations and relevant cellular parameters, such as the diameter and curvature of the cell. The binding equilibrium between a monovalent protein and a monomeric ligand is governed by the law of mass action. The same equation applies when antibody binding site and antigen are in solution or when one is cell-bound and the other is in solution (Reynolds, 1979). For example, the targeting of an sFv monomer to the extracellular domain of a cell surface receptor is described as follows, where square brackets refer to the molar concentration of the given species in solution:

sFV

+ ECD

sFv~ECD

and the association constant is K=

[sFv~ECD] [sFv][ECD]

ANTIBODY BINDING SITES

375

FIG 16. Imaging of human ovarian tumor xenografts in scid mice by 9 9 m T741F8-1 ~ anti-c-erbB-2 sFv'. Gamma camera images were obtained at 1, 6, and 24 hr after the intravenous administration of 99mTc741F8-1 sFv' to scid mice bearing SK-0%'-3tumor xenografts. The 20,000-count anterior images from a representative mouse with a 478-mg tumor show radioactivity mainly in the tumor (t) and bladder (b). Kidneys are visible as two patches above the tumor. The moderate bladder and kidney activities detectable at 1 and 6 h r were aided by stimulation of urinary output, which would likewise be affected in a clinical setting. The 24-hr image also shows higher relative activity in the kidneys and bowel; in this imaging experiment the animal was not perfectly flat on the stage, as in the other images, resulting in the asymmetric tumor image. [Modified from George et nl. (1995).]

Including the equations for conservation of mass, one obtains several useful relationships. The solution concentration of the noncovalent sFv.ECD complex may be expressed by either of the following ratios, wherein SFVT and ECDT are the sum of the free and complexed sFv protein or ECD ligand, respectively: [sFv*ECD]- K[ECD] { 1 + K[ECD]} [SFVT] or with equal validity, the fractional saturation of ECD,

376

JAMES S. HUSTON ET AL.

The interaction of monovalent sFv and s sites of monovalent ECD on the cell surface can be treated by essentially the same equation, modified to give the average number of bound sFv molecules per cell, Nay(where N,, = sN): sK[sFv] Nav

= +-j

Graphical representation of the fractional saturation (N) of ECD on the cell offers some useful insights into immunotargeting. As shown in Fig. 17, the fractional saturation graphed as a function of the variables K[sFv] is a hyperbolic function. This function emphasizes that the fractional saturation may be raised by increasing the sFv binding afinity for ECD or by increasing the concentration of sFv in solution. There is a steep dependence of fractional saturation on the product of K and [sFv], which suggests that one can significantly improve target localization by increasing this product, especially in the early part of the curve, by increasing the target affinity of the sFv (Schier et al., 1996), its systemic concentration, or both. Data from Schlom’s group have shown in model radioimmunotherapy studies that a distinct therapeutic advantage was seen with only a 10-fold increase in binding affinity, from 2.5 x 10’ M-’ to 2.8 x 1O’O M-’ (Schlom et al., 1992).

c

0 ._ Y

F 3

a

Y

-

2 .Y

0

F

0.2

2O*4m0.0 O 0

10

20

30

40

50

K[sFv] FIG. 17. A simple model for sFv targeting. The effect of targeting a cell surface antigen (receptor) with soluble antireceptor sFv monomers is to associate with some portion of the available antigenic sites, interpreted as the fractional saturation, N . The value of N exhibits a hyperbolic dependence on the product of association constant, K, and free sFv concentration, [sFv], based on the equations of Reynolds (1979). For example, the quantity K[sFv] needs to reach only 9 for the fractional saturation of target sites to reach 90%. [From Huston et al., 1996.1

ANTIBODY BINDING SITES

377

Reynolds also solved equations for a divalent antibody species binding to a cell-bound ligand, envisioned as the combination of two steps: (1) collision between one binding site of the divalent antibody [or (SFV’)~] in solution and the cell-bound receptor, and (2) reaction between the remaining free combining site of the divalent antibody and additional cell-bound receptors, which takes place entirely on the surface of the cell where effective concentrations of antibody species differ from those in the bulk solution. In this case, the binding reaction depends not only on bulk concentrations and intrinsic binding constants but also on the cell radius or surface area. There are also other treatments of this targeting problem (Hogg et al., 1987) and related issues (Dower et al., 1981a,b). Theoretical studies on solid tumors have been proposed to present a complication described by Weinstein as a “barrier effect” that permits less penetration as higheraffinity antibody is used to target tumors or micrometastases (Weinstein et al., 1986, 1987; Saga et al., 1995). This is disputed for smaller species, the size of Fab and below, by immunotargeting studies on multicell spheroids (Langmuir et al., 1991) and tumor xenografts; Weinstein has also calculated that the dependence of the effect on molecular weight is IgG > F(ab’)2> Fab, and presumably sFv or Fv is still less susceptible to the effect. D. Binding Equilibria and Linkage in Antibody Binding Site Proteins 1. Linked Functions and Reciprocal Effects

For a rigorous appreciation of the antibody binding site, it is useful to apply a unifying viewpoint to the interactions, dynamic changes, and functional attributes of antibodies. The Wyman theory of linked hnctions (Wyman and Gill, 1990) provides such a theoretical framework for relating the disparate properties of antibodies. Within a coherent theory, the Wyman relations permit interpretation of all the thermodynamic equilibria for a given protein that are linked because it is a common reactant, even if it exists in different functional, conformational, or associated states. This theoretical approach has been used as the basis for a general thermodynamic interpretation of allosteric proteins, such as hemoglobin (Wyman, 1948, 1964). It has also been applied to diverse aspects of protein chemistry, from the interactions of tubulin in solution (Shearwin and Timasheff, 1992, 1994; Shearwin et al., 1994) to the role of water in protein folding (Tanford, 1969) and the effects of cosolvents on protein structure (Arakawa et al., 1990). The application of Wyman theory to antibodies can quantitatively relate changes in antibody structure and function. Thus, binding of antigen to an antibody Fv region may lead to meaningful changes at the bottom surface diametrically opposite the binding site. In the D 1.3 Fv this

378

JAMES S. HUSTON ET AL.

antigen-induced conformational change involved the relative translational movement of the VH and VL domains. Concomitant with these changes, distribution of the surface electrostatic potential may change, for example, and thereby alter pK, values of ionizable residues on the surface that could modulate other interactions. 2. Linked Functions in Antigen-Antibody Interactions

Until recently, the application of linked function theory to antibodies might have been premature, but current research has begun to measure the interactions that form the basis for such an analysis. Potentially, a wide range of experimental data may be quantitatively interpreted by these linked reactions and corresponding linkage hnctions. The details of these reactions are becoming available through efforts in X-ray crystallography, NMR spectroscopy, binding and dissociation kinetics, analytical ultracentrifugation (Stafford, 1994a,b), and other physicochemical methods. For the present discussion, a hypothetical case is described based on the Fv region of an antibody. Some of the equilibria that could take place are presented in the following hypothetical series of linked reactions. a. This model Fv contains a CDR loop which changes conformation from a relatively flexible state (F) to a rigid conformation that favors ligand binding (R), and thus even in the absence of antigen the following equilibrium takes place: K, c o d FvF

FvR

b. The differential binding affinity of antigen (Ag) in these states is thus described in the following reaction scheme, where KZaSSac << Kz

FvF

+ Ag

Fv'eAg

(2)

F&Ag

(3)

K3 aSSoC

+

F v ~ Ag

c. A conformational equilibrium also exists between the bound states:

d. In addition to a structural change involving CDR conformation, this hypothetical Fv also undergoes translational movement of its VH and VL domains, an equilibrium between the R and R* states, such that in the

379

ANTIBODY BINDING SITES

Fv-antigen complex, FvR*-Ag is the favored final state: K5 conf

FvR

FvR* K

~

FvR*+ Ag

A

~

~

~

~

~

FvR.Ag K&cunf

- FVR**Ag

A

FvR*Ag

(7)

e. Furthermore, the Fv fragment (VH-V, heterodimer) participates in a variety of association equilibria in the absence of antigen, which include the dissociation into V domains [Eq. (S)] and self-associationinto noncovalent dimers: &dissoc

FVF

VH + V L K~diiner

2FvR*

(FvR*)2

(9)

f. This dimerization reaction is favored if the Fv is in its rigid complex with antigen: K~dimer 2FvR*.Ag

- (FvR**Ag)2

A

(10)

g. The binding of antigen to preformed F V ~dimer ' ~ offers two further reactions: Kgassoc

FvR*2+ Ag

-

A

FvR*(FvK*.Ag)

Kioassoc FVR*.(FVR**Ag) + Ag (FvR**Ag)n

(1 1)

(12)

h. Finally, antigen equilibria can impact the ability to form complex. In this example the antigen may exist as both dimer and monomer, but only monomer is able to interact with the Fv (this reaction is not shown in the linkage scheme):

380

IAMES S . HUSTON ET AL.

The linkage between these reactions is apparent from the combination of these equilibria, as displayed here. The standard Wyman relationships apply to reaction scheme I and can be used to determine the dependence of any specific component on the concentration of any other, such as an analysis of how the formation of FvR*.Agcomplex changes with the addition of monomeric antigen. It is well known that the apparent equilibrium constant for the simple association of protein with ligand can be very dependent on ancillary protein self-association reactions. In examples of this situation, grossly incorrect values for the ligand binding constant may be calculated if the effects of linked reactions are not properly incorporated in the analysis (Wyman and Gill, 1990). It is likely that similar situations could arise in the binding of engineered antibody species to antigen, and proper determination of the actual binding constant would need to correct for ancillary linked reactions.

V,+V,

=FvF

Z

FvR

1

=

(FVR*)2

\ K3assoc

1 FvF*Ag

FvR*

Ag

KSAassoC FvR**(FvR**Ag)

\

FvR*Ag Z

FvR'*Ag

=

(FvR**Ag),

SCHEME I

IV. ANTIBODY COMBINING SITESTRUCTURE: ANTIARSONATE

AND

ANTIDIGOXIN ANTIBODIES

A. Antiarsonate Response in Inbred Mace Following immunization of NJ mice with p-azophenyl arsonate ( A r s ) coupled to proteins, the majority of antibodies produced express a shared crossreactive idiotype (CRI, or IdCR)(Kuettner et al., 1972) thought to represent shared antibody V region structures. Subsequently, analysis of a set of monoclonal idiotype-bearing Ars-binding antibodies indicated that they were "microheterogeneous," i.e., that their V regions were highly homolo-

ANTIBODY BINDING SITES

38 1

gous but differed from each other at one or more positions (MarshakRothstein et al., 1980). These antibodies are all encoded by a single, unique set of germline V gene segments in both the H and L chains, designatedVHIdCR, DFLK.~,, JH2,VKIO,and JK1(Siekevitzet al., 1982, 1983; Landolfi et al., 1986; Wysocki et al., 1986, 1987; Sanz and Capra, 1987), termed canonical. During immunization, canonical V region genes sustain mutations that often result in antibodies with higher affinity for hapten (Wysocki et al., 1986; Manser et al., 1985). The dominance of IdcRin the A strain anti-Ars response was explained by two factors: (1) The canonical gene segment combination exhibits a higher intrinsic affinity for Ars than other combinations, such as Id36-60 (Marshak-Rothstein et al., 1981; Near etal., 1984; Juszczak and Margolies, 1983). (2) The canonical gene segment combination has higher adaptability, i.e., the ability to sustain somatic mutations that enhance Ars affinity. Thus, affinity maturation was explained by increased binding affinity resulting from antigen-driven selection of favorable somatic mutations occurring during the course of immunization rather than through putative idiotype network regulation. The Ars system is a useful model for the study of antibody combining site structure-function relationships because of the existence of a large number of canonical hybridomas bearing somatic mutations, and engineered mutants, as well as the crystal structure of two anti-Ars antibodies: 36-71 (Strong et al., 1991a,b) and R19.9 (Lascombe et al., 1989, 1992).

B. Crystal Structure of Combining Site of Fab 36-71 Two different monoclonal anti-Ars antibodies, each using the same canonical V genes, were the object of studies undertaken to explain the structural basis of Ars binding and to determine the effects of somatic mutations: Antibody 36-65 expresses the canonical sequence in germline (unmutated) form, while antibody 36-71 contains 19 amino acid differences from 36-65, of which 17 are the result of somatic mutation (Fig. 18) and 2 are H chain D gene junctional differences. As a consequence, antibody 36-7 I binds Ars with an approximately 200-fold greater affinity than the germline antibody 36-65 (Rothstein and Gefter, 1983). The crystal structure of the 36-7 1 Fab was determined to 1.85 A resolution (Strong et al., 1991a,b). A model of the 36-71 Fab-phenyl arsonate complex was proposed based on a low-resolution electron density map of the complex. In this model, the side chains of the CDR residues LArg-96 (LCDR3), HAsn-35 (HCDRl), and HSer-99 (HCDR3) hydrogen-bond to the Ars moiety (Fig. 19), as does a tightly bound water molecule.*The side chains of HTyr-50 (HCDR2) and HTyr-106 (HCDR3) pack against the phenyl Consecutive numbering is used for the position of residues of anti-Ars antibodies.

36-65 36-71

I20 G T T L T V S S

- - ---- - -

FIG. 18. Amino acid sequences of the VH regions of the germline-encoded anti-ArsAb 36-65 and the somatically mutated 36-71 anti-ArsAb. Residues in 36-71 identical to those in 36-65 are indicated by dashes. Amino acids are denoted by the one-letter code in sequential numbering.

383

ANTIBODY BINDING SITES

/-

lo6

/-

lo6

FIG. 19. Stereo view of the modeled complex of 36-71 Fab with phenyl arsonate from the crystal structure (Strong et al., 1991a,b), including recent refinement (R. Strong, personal communication, 1995). Hydrogen bonds are indicated by shaded lines.

group of A r s . The side chain of HPhe-108 (HCDR3) forms the bottom of the combining cavity and may make van der Waals contact with the A r s oxygens (Wong et al., 1995).

C. Site-Directed Mutagenesis Studies of Antiarsonate Putative Hapten Contact Restdues Based on a comparison among the structures, sequences, and solventaccessible surfaces of Fab 36-71 and Fab R19.9, the germline-encoded antibody 36-65 was proposed to have the same general binding site features as 36-71 (Stronget al., 1991b). The sequence of R19.9 is identical to that of the germline-encoded 36-65 at 16 of the positions in the V regions where somatic mutations and junctional differences occurred to produce the 3671 sequence (Fig. 18). R19.9 binds A r s and is canonical except for the use of a different D gene. This structural comparison, which shows that the V regions are largely superimposable except for HCDR3, suggested that the unmutated antibody 36-65 used the same set of hapten contact residues to bind Ars as does the somatically mutated antibody 36-71. The available sequences (83) of monoclonal antibodies that bind A r s and use canonical genes were then tabulated (Strong et al., 1991a). The putative 36-71 contact residues listed previously are invariant among canonical Ars-binding

384

JAMES S. HUSTON ET AL

antibodies, also suggesting that the combining sites of these antibodies are similar in structure with respect to the geometric motif dictating binding to Ars. Among the hapten contact residues, HAsn-35 and HTyr-50 are encoded by the VH gene, while HTyr- 106 is encoded by the D gene and HPhe108 by the J H gene. HSer99 is not encoded in either the germline VH or D gene (Wysocki et al., 1986; Milner et al., 1986), yet is invariant in Ars-binding canonical antibodies (Strong et al., 1991a). It had been previously proposed, based on the results of chain recombination and sequence data, that the invariant LArg-96 was required for Ars binding (Jeske et al., 1984). LArg-96 arises as a result of V,), joining. This residue is also present in all anti-Ars antibodies which utilize different gene segments than IdCR (Juszczak and Margolies, 1983; Juszczak et al., 1984). In the Fab 36-71 model complex, LArg-96 contacts hapten via the E nitrogen (Fig. 19). LArg-96 was then mutated to Ala in the context of both the 36-65 L chain and the 36-71 L chain (Strong et al., 1991a); the mutant antibodies had no detectable Ars binding, consistent with the model. To further test the hypothesis that the overall binding site geometry was maintained among somatically mutated canonical anti-Ars antibodies, the germline-encoded antibody 36-65 was used to construct mutants, by oligonucleotide-directed mutagenesis, that differed at the putative H chain hapten-contacting residues as well as at the framework residue HTrp-47. All mutations made at H35 abolished Ars binding (Table IX). HAsn-35 plays a central role in the hydrogen bonding network with other residues in the combining site, acting as a hydrogen bonding acceptor for HTrp-47 and as a donor for HSer-99. Thus, substitutions at HAsn-35 not only removed a hydrogen bond to the hapten but also influenced the packing of HSer-99 and HTrp-47. The geometry of the packing of the HAsn-35 side chain is so restricted that conservative substitutions such as Gln, which can form hydrogen bonds, are not consistent with Ars binding. HTyr-50 and HTry-106 pack against the phenyl ring of Ars in an aromatic-aromatic interaction (Burley and Petsko, 1988). Mutagenesis at positions 50 and 106 indicated that replacement with Ala abolishes binding, while Phe can substitute for Tyr with a 3- to 6-fold reduction in a E n ity, presumably due to a change in side chain orientation owing to loss of the hydrophilic-OH group. At position H50, replacement of Tyr by Trp improved affinity 2.5-fold, indicating that at least in the germline structure, a larger planar aromatic group providing increased contact is tolerated. At position 106, Trp is not permitted. At Trp-47, all substitutions tested reduced Ars binding to a level unmeasurable using fluorescence quenching. Because replacement of Trp affects fluorescence, however, a solid-phase inhibition assay was used to assess binding; these results indicated that the Ala mutant was nonbinding,

385

ANTIBODY BINDING SITES

TABLE IX

Afinities of Wild-type and Mutant Antibodies" Antibody or mutant Wild-type 36-65 36-7 1 Light chain Arg96Ala Heavy chain Asn35Ala Asn35Asp Asn35Gln Asn35Ser Asn35Thr hn35Cys Trp47Ala Trp47Phe Trp47Tyr Trp47His Tyr50Ala Tyr50Phe Tyr 50Trp Tyr50Leu Ser99Ala Ser99Thr Tyr 106Ala Tyr 1O6Phe Tyr 106Trp Tyr 106Leu

K,l

(X

lo5K')

2.5 k 0.4 263 f 7.5 N M ~

NM NM NM NM NM NM NM NM NM NM NM 0.4 f 0.1 6.2 f 0.2 NM NM 3.5 k 0.6 NM 0.8 ? 0.4 NM NM

" K, was determined by fluorescence quenching using ArsN-acetyl-L-tyrosine. Mutants were constructed using the 36-65 (germline-encoded) Ab. Data are from Parhami-Seren et al. (1993) and Kussie et al. (1994), except for mutant Ser99Ala (Sharon et al., 1986). /I NM, Not measurable by fluorescence quenching or direct binding radioimmunoassay (RIA) on Ars-BGG-coated plates. while the other three mutants (Table IX) had a 13- to 53-fold reduction in binding, suggesting that they do not sufficiently restore the hydrogen bonding of Trp-47. The mutant HSer99Ala3was nonbinding, while HSer99Thr bound A r s as well as the wild-type antibody (Parhami-Seren et al., 1993; Sharon et al., Mutations are denoted by the position number, preceded by the wild-type residue in a one- or three-letter code, followed by the mutant residues.

386

JAMES S. HUSTON E T AL.

1986). HSer-99 is inaccessible to solvent; presumably the additional methyl group can be accommodated at the bottom of the site. As threonine is /?-branched, the distance from the backbone to the hydroxyl is the same as for serine. HThr-99 has never been observed in vivo, presumably for reasons related to the mechanism of generation of this residue. J. Sharon, in parallel with the work on antibody 36-65, mutated the proposed hapten contact residues in antibody 36-71 (Sompuram and Sharon, 1993). The results, in general, are similar to those enumerated for 36-65, showing a significant decrease in binding. However, for antibody 36-7 1 the mutant HSer99Thr decreases binding 90-fold, consistent with the idea that steric hindrance occurs in 36-71 owing to differences in binding site packing produced by somatic mutations of the noncontact residues in 36-71. The results of the mutagenesis studies on 36-65 and 36-71 support the contention that the general geometry of the combining site is preserved so as to present the same set of hapten-contacting residues. This conserved contact residue binding motif is consistent with the crystal structure and may represent the structure that confers maximum adaptability invoked in theories of antigen-driven selection used to explain the dominance of IdcRassociated with this canonical set of gene segments. Despite preservation of the contact residues in Ars-binding canonical antibodies, this geometry is modulated by somatic mutations and gene junctional differences to alter affinity.

D. Enhancement of Antiarsonate Antibody Afinity by Mutation of Noncontact Residues 1. Effect of H ChainJunctional Variation on Binding

Although the VK-JK junctional LArg-96 and the VH-D junctional HSer99 residues are entirely conserved, a variety of junctional residues are observed at HlOO and H107 in Ars-binding canonical antibodies. Arguments elaborated to explain idiotype dominance through antigen-driven selection of random somatic mutants (Manser et al., 1984, 1985) did not address the possible contribution of these D gene junctional residues. In order to examine the effect on affinity of junctional diversity independent of somatic mutations, antibodies were sought that bore identical unmutated gene segments but differed at the D gene junctions. Five anti-Ars canonical antibodies-obtained early (4-6 days) during a primary immune response, when somatic mutation is not yet operative-were sequenced. Sequence analyses confirmed that they were unmutated but contained three different H chain junctional pairs: His-lOO/Asp-107, His- 100Kyr107, and Asn-100Kyr-107 (Parhami-Seren et al., 1989). These structural

ANTIBODY BINDING SITES

387

differences were responsible for 6- to 10-fold differences in affinity compared to 36-65 (Val-100/Tyr-107). Thus, junctional variation arising from gene segment rearrangement potentially provides antigen-selective advantages for the expansion of certain clones prior to the occurrence of somatic mutation, and must be taken into account in hypotheses accounting for IdCRdominance based on the antigen-driven selection of somatic mutants. Many amino acids may be substituted at the D gene junctions, with retention of A r s binding, because at least 17 different junctional pairs were observed among canonical Ars-binding antibodies for which sufficient sequence data are available [see Strong et al. (1991a) for references; the number of junctional pairs now exceeds 301. The direct effect of these junctional differences on affinity cannot be estimated because of additional somatic mutations in these hybridoma proteins. Different amino acids were introduced, therefore, into positions HlOO and H107 in antibody 36-65 (Parhami-Seren and Margolies, 1996). Table X shows the results of binding analysis for 20 different junctional pairs involving five different residues at position 100 and six at position 107. Sixteen of the 20 mutants have affinities greater than or equal to one-half of that for antibody 36-65. The range of relative affinities due to junctional differences varies over 150-fold (Asn-1OO/Tyr- 107 vs Val-1OO/Lys-107); compare the affinities due to only the single amino acid replacement Val- 100Frp-107 vs Val-1OO/Lys107. The range of affinities due to single amino acid differences in the set is greater than that found for any single VHregion somatic mutant thus far characterized. Of the 20 junctional pairs produced in vitro (Table X), 9 have been observed thus far in vivo. Four of the five mutant antibodies with the highest affinity for A r s contain junctional amino acids identical to those observed in secondary immune response anti-Ars antibodies. In contrast, five of six junctional pairs with the lowest affinity for Ars were not observed in vivo. The data support the thesis that gene rearrangement results in affinity enhancement that can be acted on preferentially during subsequent antigen-driven selection of V region somatic mutants. However, the sample size of the population of hybridoma antibodies adequately characterized is relatively small, and a comparison among affinities of junctional pairs not seen in vivo and those observed in vivo may not be significantly different statistically. Further, such an analysis assumes that the mechanism resulting in the appearance of a particular junctional residue is random; Manser (1990) has provided evidence that this may not be the case. Examination of the crystal structures indicates that the VHjunctional residue HGlu-100 in 36-71 lies in a cleft behind the binding site, between HCDR3 and HCDRl. The side chain of HlOO may influence A r s binding by affecting the packing of the side chain of HTyr-50, which contacts the hapten phenyl group. For example, in 36-71, which has HGlu-100 rather

388

JAMES S. HUSTON E T AL

TABLE X

Effect of Heavy Chain Junctional Diversity on Anti-Ars Antibody A@nitya Amino acid residues Source

VH-D 100

V H E

N v E N H

s

v E N

v

s

E

N H V

E

Y

_ _ _ _

Y

_ _ _ _

G

_ _ _

_

G

_ _ _

_

S

_ _ _

_

Y

_ _ _

_

_ - _ _ _ _ _ _ _ _ _

_ _ _ _ _ _

_ _ _ _ _ _ _ _ _ _ _ _ _

_ _ _ _ _ _ _

_

_ _ _ _ _ _ _ _

_

_ _ _ _ _ _ _ _

V a

Relative affinity’

D-J H 107

_

_ _ _ _ _ _

_

_ _ _ _ _ _

_

_ _ _ _ _ _

- _ _ _ _ _

Y Y Y Y K K

s s s s s

F -

-

N N N N

-

D D D D

-

w

-

1.o 0.9 0.3 0.1 12.YC 3.0

6.3 5.4 2.1 1.4 1.2 4.4 1.3 1.0 0.7 2.5 1.5 0.5 0.4

20.1

Affinity was determined by fluorescence quenching using Ars-N-acetyl-1.-tyrosine.

’ The ratio of affinity of each mutant Ab to the affinity of 36-65. ‘ Reported previously by Sharon (1990).

than Val as in 36-65, the E oxygen atom of Glu hydrogen-bonds to the carbonyl oxygens of H 131 and H 101. The negative charge of Glu likely repels the phenolic hydroxyl group of HTyr-50, thus forcing this contact residue closer to the hapten and causing a steric clash. Sharon (1990) has shown that the mutation HVallOOGlu reduces affinity four-fold. Affinity differences due to the identity of the H 107 side chain are mediated by its effect on the position of the contact residue HTyr-106 (Fig. 20). In 36-71, HLys-107 forms a salt bridge to HAsp-109 on the other side of HCDR3 from the Ars binding pocket. The substitution Tyr 107Lys (Sharon, 1990) results in a shift in the position of the Ca of H106 so that the Tyr-106 side chain is “pulled” away from A r s , allowing optimal packing against the A r s phenyl ring. This mutation results in a 12.9-fold increase in affinity in the context of 36-65 (Sharon, 1990).

389

ANTIBODY BINDING SITES

One possible explanation for failure to find certain junctional residue pairs at positions HlOO and H107 in viuo may be that when they are combined with V gene somatic mutations that occur subsequently, the affinity is thereby reduced, rather than the effect being additive. This hypothesis was tested by combining five different sets of junctional residue pairs with mutations at positions 58 and 59 in HCDR2 that have been documented to occur frequently in vivo and are associated with increased affinity (discussed below) (Sharon et al., 1989) (Table XI). In all cases, when these different pairs were combined with Thr58Ile or Lys59Thr, the effects were additive, with affinities increased 2.6- to 6.5-fold. Thus, at least in these cases, antibodies with different D gene junctions are capable of sustaining recurrent somatic mutations typical of the in viuo anti-Ars response, with additive effects on affinity.

TABLE XI

Effect of Combined H Chain CDRP Mutations and Junctional Amino Acid Replacements on Afini9f.r An" 35-65: Amino acid residues at heavy chain positions" VH 58

VH 59

VH-D 100

D-JH 107

Relative affinity"

T I T T I T T I T T I T

K K T K K

V V V S

K K T K K T K K T

N N N N N N

Y Y Y N N N N N N D D D D D D

1.O 2.9 6.5 1.2 4.6 3.6 4.1 11.7 8.3

1' I T

rr

s s

H H H

2.7 7.0 10.2 1.5 5.8 6.4

" Affinity was determined by fluorescence quenching using Ars-N-acetyl1.-tyrosine. b The wild-type residues at 58 and 59 are Thr (T) and Lys (K), respectively. The mutations T58I and K58T are found frequently in anti-Ars canonical Abs and contribute to increased affinity (Sharon et al., 1989). The ratio of affinity of each mutant Ab to the affinity of'36-65.

390

JAMES S. HUSTON E T AL.

2. Recurrent Somatic Mutations in Vivo Conferring Increased Ars Afinity The mutations Thr58Ile and Lys59Thr have been observed among 4050% of somatically mutated canonical anti-Ars antibodies associated with increased affinity relative to the germline 36-65. The contribution to affinity of these mutations was tested by introducing each singly and in combination into antibody 36-65 (Sharon et al., 1989) (see Fig. 18).The affinities of mutant antibodies were three- and fourfold higher for the single mutants and eightfold higher for the double mutant. These results supported the contention that the repeated appearance of common somatic mutations in independently derived canonical V regions was due to selection on the basis of affinity for antigen possessed by these V regions. Single recurrent somatic mutations in antiphenyloxazolone and antihydroxynitrophenyl antibodies (Berek and Milstein, 1987; Allen et al., 1987) were also shown to be associated with affinity enhancement. These results support the notion that antigen-driven selection of somatic mutants accounts for affinity maturation without the necessity of invoking other selective pressures, such as loss of autoreactivity or network effects. Subsequently, in a more extensive mutagenesis study, Sharon showed that the affinity of antibody 36-71 could be recapitulated in the 36-65 context by introducing the two recurrent HCDR2 mutations plus the junctional difference Tyr 107Lys (Sharon, 1990).

E. Certain Mutations of Antiarsonate Antibodies Enganeered ex Vivo that Confer Increased Afinity Are Not Observed in Vivo One goal of antibody combining site engineering is to increase antibody affinity by an instructive approach, i.e., to predict changes in binding on the basis of three-dimensional structures. Inspection of the model of the crystal complex of 36-71 Fab with phenylarsonate suggested that HPhe108, which forms the base of the binding cavity, affects Ars binding (Figs. 19 and 20). Wong et al. (1995) proposed that replacing Phe with Trp would increase binding. HPhe-108 was mutated to Trp and other amino acids in both 36-65 and 36-71 (Table XII). The data indicate that Phe-108 is essential for binding in both antibodies and that an aromatic side chain is preferred, while charged residues are incompatible with binding. In 36-65, substitution of the larger aromatic side chain Trp increases affinity 10-fold. In 36-71, however, the same mutation reduces binding more than 1000-fold. This result suggests that the packing of the 36-71 combining site is “tighter” than that of 36-65 and cannot accommodate the larger Trp residue without disruption of binding. Other data supporting this conclusion were adduced previously (Parhami-Seren et al., 1993; Sompuram and Sharon, 1993). Mutations at position 108 have never been identified

ANTIBODY BINDING SITES

39 1

FIG.20. Stereo view of the region of HCDRS of Fab 36-71 in relation to phenyl arsonate (Strong et al., 1991a,b).

among somatically mutated canonical anti-Ars antibodies in which Phe108 is encoded by the JH2 germline gene, despite the increased affinity of the Trp-108 mutant. One explanation for the lack of appearance of the mutant Phel08Trp in vivo is that this mutation requires two base changes from the germline. Thus, antibody engineering ex vivo is not limited by codon usage of germline V region sequences or by the possibility that somatic hypermutation is not completely random, resulting in V region mutational hot spots (Berek and Milstein, 1987; Levy et al., 1988). Another possible explanation for the failure to observe this mutation in uivo is that when HPhe108Trp is combined with commonly observed mutations, binding is reduced. Therefore, the mutant Phe 108Trp was combined with the recurrent mutations at positions 58 and 59 and with the favorable junctional residue H 107Lys (Table XII). The data indicate that H108Trp can combine with some mutations (Thr58Ile and Thr5811e/ Lys59Thr), resulting in antibodies that bind Ars with affinities significantly greater than that of the wild type. Thus, HlO8Trp is not structurally forbidden in the context of other somatic mutations, but it does not contribute to additivity. Although the mutations HTyr 107Lys and HPhe 108Trp each increase A r s binding significantly in 36-65 (Table XII), the combined mutant Tyrl07Lys/ Phel08Trp is nonbinding. To determine whether Phel08Trp in antibody 36-71 ablates binding because of steric hindrance with 107Lys or because of the effect of a charged residue at 107, Lys-107 was converted to Tyr-107

392

JAMES S. HUSTON E T AL.

TABLE XI1

Binding Constant (K,) of Antibodies and Mutants for Ars-N-Acetyl-L-tyrosine

Antibody or mutant Wild-type 36-65 F 108W F108A F 108Y F 108Q

Affinity" K, ( x 1 0 ' K ' )

Antibody or mutant

2.91 29.2 0.35 1.49 0.45

F108E, F108H, F108K

NM

T58I K59T T58IiK59T T58IIF108W K59TIF108W T58IIK59TIF1 08W Y107K Y 107WFIO8W

5.63 6.55 12.5 16.6 NM 10.9 35.1 NM

Wild-type 36-7 1 F108W F 108A F108Y F 108L F108V F 108T F108E, F108H

Affinity K, (xlo" M-I) 248.3 N M ~ NM 41.4 16.1 13.8 10.6 NM

K107Y K107YiF108W ~

2.97 NM

~~~

'' Binding affinity (K,) was determined by fluorescence quenching.

*

NM, Not measurable by fluorescence quenching or direct binding RIA on Ars-BGGcoated plates.

(36-65-like) in 36-71. This mutant bound A r s with an affinity similar to that ofwild-type 36-65, but when it was combined with Phel08Trp, the resultant antibody was nonbinding. The results indicate that Trp-108 cannot fit in the 36-7 1 binding site with retention of hapten binding. The side chains of residues 107 and 108 are oriented in opposite directions (Fig. 20), making it unlikely that steric hindrance results from their direct interaction. Although crystal structures of antibody-antigen complexes can be used effectively to pinpoint sites of mutations for engineering changes in affinity or specificity, precise predictions resulting in the desired effect are not the rule. Although position H108 was found to be important in binding, substitution of Trp increased affinity in the germline antibody but did not increase affinity in antibody 36-7 1. F. Engineering Changes in Antiarsonate Antibody Specificity

1. Single Mutation Effecting Switch in Fine Spec$city Wysocki and co-workers (Ellenberger et al., 1993) obtained hybridomas that bind sulfonate (Sulf) from mice immunized first with Ars-protein con-

393

ANTIBODY BINDING SITES

jugates and boosted subsequently with Sulf-protein conjugates. Among these were three monoclonal antibodies that bound Sulf but not Ars, yet used the canonical V genes associated with the anti-Ars response. They contained unique somatic mutations in both V H and VL, but also shared the identical mutations HAsn35Ser, HLys59Asn, and the H chain junctional residues His-100 and Ser-107. To determine which H chain residues confer specificity for Ars versus Sulf, the relevant mutations were introduced into antibody 36-65 (Kussie et al., 1994). All these substitutions have been identified in Ars-binding antibodies, with the exception of the conserved Asn-35, a putative contact residue to Ars (Fig. 19) in the 36-71 crystal structure. When Asn-35 was replaced by Ser (as in the Sulf-binding hybridoma protein described by Wysocki, HPSulfl-Table XIII) or Thr, Ala, or Cys, the single mutations converted an Ars-binding antibody (K, = 3.6 x lo5M-I) to antibodies that bind Sulf (1.O-1.9 x 10' M-l) but no longer bind Ars (Table XIII, Fig. 21). Combinations of three of these mutations at H35 with the junctional changes Val 1OOHisEyr 1O7Ser observed in the hybridoma protein HPSulfl resulted in antibodies with even higher affinities for Sulf (2.6-5.4 x 10' M-I), while antibody 36-65 containing the VallOOHis/

TABLE XI11 Binding Constants and Relative Ajinities of Antibody/Mutantsf r N-Acetyl-L-tyroszne Conjugates of Sulf and Ars

Antibody or mutant HPSulf-1 36-65 (N35) wild type N35S N35T N35A N35C N35Q N35D N35SN1OOHE 107s N35TNI 00HE107S N35ANlOOHEl07S V100HE107S 36-71 (N35) wild type N35A

Sulf-N-acetyl-Tyr K~ ( ~ 1 ~04 ~ - l ) ~ 25 k5.1 NM~ 10 f 0.6 15 f 1.9 19 k 3.3 15 f 1.6 NM NM 26 f 0.8 34 f 7.0 54 f 3.0 NM 1.4f0.3 343 k 97

Ars-N-acetyl-Tyr K, ( ~ 1 0 ' N M ~ 3.6 f 1.4 NM NM NM NM NM NM

NM NM NM 19 k 1.3 283 k 76 NM

Minities were determined by fluorescence quenching. NM, Binding constant could not be determined, as in this assay system the 5 x lo4 M-'. lower limit is K,' a

-

36-71

3

36-71 N35A 36-65 wt 36-65 N35A 36-65 N35T

2

36-65 N35S

A

U

36-65 N35C

'0 Y v

w .b a

36-65 N35Q

E

8

36-65 N35D 1

36-65 V1OOW107S 36-65 N35AN1OOWl07S 36-65 N35SNlOOHN107S 36-65 N35TN1OOHNlO7S HP Sulfl

0 10 Antibody (ng)

36-71

3

36-71 N35A 36-65 wt 36-65 N35A

-

36-65 N35T

2

36-65 N35S

U

36-65 N35C

'0 v T

36-65 N35Q

E

8

36-65 N35D 1

36-65 V1 OOHNl07S 36-65 N35NV1OOHNlO7S 36-65 N35SNlOOHN107S 36-65 N35TN1OOHNlO7S HP Sulfl

0 1

Antibody (ng) FIG. 2 1 . Direct binding analysis of Abimutants to Sulf-BSA (top) and Ars-BSA (bottum). Increasing concentrations of Ab were tested for their ability to bind directly to a hapten-BSA-coated plate. (Reproducedwith permission from Kussie et al., 1994.J. Zmmunol. 152, 146-152. 0 1994 The American Association of Immunologists.)

396

JAMES S. HUSTON ET AL.

Tyr107Serjunctions does not bind Sulf. When the mutation Asn35Ala was introduced into the higher-affinity antibody 36-7 1, the resulting antibody also recognized Sulf ( K , = 3.43 x lo7MI) but no longer bound Ars. Taken together, the results indicate that a single mutation at H35 is responsible for the switch of fine specificity from Ars to Sulf. In addition, in both Arsand Sulf-binding antibodies, the identity of the D gene junctions can modulate (enhance) binding. The switching of antibody specificity to a structurally unrelated antigen has been reported: A single mutation in a phosphorylcholine-binding myeloma VH region resulted in a loss of binding to phosphorylcholine, with acquisition of binding to DNA (Diamond and Scharff, 1984).An antitetanus toxoid antibody was converted to an antifluorescein antibody by extensive mutation of HCDR3 using phage display selection (Barbas et al., 1992). However, reported alterations in fine specificity, i.e., specificity for hapten structural analogs, by engineered mutations are quantitatively small and in no case render the mutants heteroclitic. Several possibilities could explain the specificity shift from Ars to Sulf. As all mutants demonstrating the specificity change appeared initially to have side chains smaller than those of the wild-type Asn, a change in shape complementarity could account for the specificity change; however, phenyl sulfonate is smaller than phenyl arsonate, and the S-0 bond lengths are shorter than the Ars-0 bond lengths (0.29 A difference). Moreover, the dimensions of p-azophenyl phosphonate (Phos) are more similar to those of Sulf, as measured by solvent-accessible surface area and bond lengths, yet Phos binding parallels A r s binding in all monoclonal antibodies and mutants, indicating that hapten size is not a critical factor in antibody discrimination. The three haptens differ also in net charge and in X-0 bond length (where X = sulfur, phosphorus, or arsenic), which potentially impacts hydrogen bonding geometry. In the 36-7 l-Ars complex, HAsn-35 not only hydrogen-bonds to an A r s oxygen but also forms a hydrogen bond network with HSer-99 and HTrp-47. Thus, mutations such as HAsn35Ala potentially disrupt this network. Previous analyses of a large number of crystallographic protein structures lend support to proposed different hydrogen bonding geometries for Sulf relative to Ars or Phos (Kanyo and Christianson, 1991). In sulfonyl-hydrogen bond interactions, most donor hydrogen atoms are found in eclipsed positions, in contrast to phosphonyl donor H atoms which are found more broadly in staggered positions. Thus, sulfonyl and phosphonyl groups are not functionally interchangeable. The distinction between Ars and Phos on the one hand and Sulf on the other is conserved among elicited antibodies and is also remarkably preserved in nonantibody proteins. Bacterial phosphate-binding proteins also bind arsenate, but not sulfate (Pflugrath and Quiocho, 1988; Luecke

ANTIBODY BINDING SITES

397

and Quiocho, 1990). Perhaps the mutation at position 35 interrupts the hydrogen bond network, resulting in a decrease in the size of the binding cavity. In this new binding pocket, the hydrogen bonding geometry is optimal for Sulf but not for A r s or Phos. It is remarkable that the subtle structural differences between these haptens can be distinctly discriminated by antibodies that differ only in a single amino acid. 2. Changing Specijicity Using Phage Display and Random Mutagenesis The degree of constraint in sequence and structure that conferred a specificity switch was investigated further by introducing sequences representing the 36-65 Fab into the pComb3 phage display expression vector (Barbas et al., 1991). After it had been confirmed that the phage-displayed Fab and the soluble Fab expressed in bacteria after excision of gene 3 had binding properties identical to those of Fab enzymatically prepared from the hybridoma protein, random mutations were introduced at H chain positions 30-36 inclusive, using synthetic oligonucleotides containing NNS codons at these positions, where N is any base and S is C or G. Following several rounds of biopanning against Sulf-bovine gamma globulin, Wong et al. (in preparation, 1996) isolated 55 Sulf-binding mutant clones containing seven different HCDRl amino acid sequences. All seven mutants bound Sulf with affinities from 1 x lo5 MP to 1.5 x lo6 M-' but had no detectable A r s binding. At position 35, Val and Ile were observed in addition to Ala. There was marked sequence variation at the other positions, with as many as six different amino acid residues among seven sequences. A remarkable finding was that at position 33 all the clones contained glycine, a residue also conserved among all anti-Ars canonical antibodies. In the 36-71 structure, substitution of residues with side chains at HGly-33 would produce a steric clash with the hapten contact residue, H50Tyr, thus possibly accounting for the invariance of HGly-33 in Ars- and in Sulfbinding antibodies. Indeed, mutation of Gly-33 to Ala in the unmutated anti-Ars antibody 36-65 abolishes A r s binding; the same mutation in an anti-Sulf mutant reduced binding to Sulf 50-fold. The diversity of amino acid replacements in the segment encompassing H chain residues 30-36 among Sulf-binding mutants indicates greater than expected plasticity of structure, each of which can result in the specificity switch from ArsIPhos to Sulf. G. Structure of Digoxin Hapten and Analogs, and Utility as Model System

Antibodies raised against the cardiac glycoside digoxin conjugated to protein (Smith et al., 1970) demonstrate high affinity and specificity relative to other antihapten antibodies. These properties were used in clinical assays to determine the level of digoxin in sera of patients treated with the

398

JAMES

s. HUSTON Er

AL.

drug (Smith et al., 1969), and to demonstrate that administration of Fab can reverse otherwise fatal digoxin toxicity in humans (Smith et al., 1976). For purposes of antibody combining site structure-function studies, antidigoxin antibodies have proven a useful model system. The cardiac glycosides consist of a C23 steroid body, a conserved C-14 B-OH, an a& unsaturated five-membered lactone ring linked to position 17, and a?!, O-linked carbohydrate at position 3 (Fig. 22). Cardiac glycosides differ from each other by defined substitutions on the conserved steroid moiety of the cardenolide, particularly at the 12 and 16 positions and the A and B rings, at the 3 position, and at the lactone ring. Digoxin is a relatively rigid hydrophobic hapten, free of charge groups, with rotation possible at the C-17-lactone bond and at the C-3-sugar and sugar-sugar bonds. Many (17) cardiac glycoside and aglycone structures were determined by X-ray crystallography (summarized in Schildbach et al., 1993a). Hundreds of natural and synthetic analogs of digoxin have been described that serve as fine specificity probes of antidigoxin antibody structures. H. Diversity among Antidigoxin Antibodies A library of murine monoclonal antidigoxin antibodies of high affinity, as well as spontaneous and engineered mutants, have proved useful in the correlation of sequence and binding afinity and specificity with threedimensional structures determined by X-ray crystallography.

1. Structure-Function Relationships among Set of Homologous Antibodies Using Same V Region Genes Immunization of A/J mice with digoxin-human serum albumin results in the expression of high-affinity antibodies ( 109-10" M-' ) which utilize diverse V region genes and demonstrate a wide range of specificity for digoxin analogs (Mudgett-Hunter et al., 1982, 1985). This immune response differs from that toward Ars in that the digoxin-specific antibody repertoire is not dominated by any single V region gene combination. Nevertheless, among this diverse set, five antibodies (four of them clonally related) were identified that share highly homologous VH and VL region sequences (Panka and Margolies, 1987). They differ from each other in affinity (1.1-1 2 x lo9M-') and display three distinct fine specificity patterns. The corresponding rearranged V, and VL genes were cloned and characterized; the five hybridomas each use the same H and L chain V region gene segments (Near and Haber, 1989). Chain recombination using gene FIG.22. Cardenolide numbering system and structures of digoxin (digoxigenin tridigitoxoside) and ouabain (ouabagenin rhamnoside).

Lactone

Cardenolide 11

Oii

A

B

4

6

610

OH

L

-

Digitoxose3

610

QoH

i)H

310

OH

OH

Rhamnose

OH

400

JAMES S. HUSTON ET AL.

transfection into L-chain-producing variants, combined with site-directed mutagenesis, indicated that the fine specificity differences resulted from H chain somatic mutations, particularly in HCDR2 (Near et al., 1991). 2. Chain Combinatorial Diversity Four clonally related antidigoxin hybridoma proteins, designated 40-20, 40-60, 40-90, and 40-100, utilize the same VH and VL regions and differ from each other by only zero to two somatic mutations in the V regions (Hudson et al., 1987, 1990). The independently derived antibody 26-10 (Mudgett-Hunter et al., 1982) uses the same L chain genes as the 40-series, but associated with an entirely different VH region. Both antibody 26-10 and the 40-series antibodies bind digoxin with high affinity but quite distinct specificity. Antibody 26- 10 is indifferent to hydroxyl substitutions at C - 12 and to the C-3 sugars, while the 40-series antibodies are sensitive to these structural features. Hudson et al. (1987, 1990) used somatic cell fusion to effect chain recombination using drug-marked L-chain-producing variants between the 26-10 H chain and each of the 40-series L chains. Three recombinants bound digoxin with reduced affinity, but the recombinant between 26- 10 H and 40- I00 L chain was nonbinding. The single L chain sequence difference Pro/Leu at the VK-JK junction (position 96) was responsible for the binding loss in the context of one H chain (26-10) but causes little change in binding associated with the parental H chains. It was shown subsequently that LPro-96 is an important hapten contact residue in the 26-10-digoxin crystal complex (see Section J, 2; Jeffrey et al., 1993).4 I. Variants of Antidigoxin Antibody 40-150

The hybridoma antibody 40- 150 binds digoxin with an affinity of 5.4 x 1O9 M-' but has an 890-fold-reduced affinity for digitoxin. Digitoxin differs from digoxin only by the absence of a C - 12 hydroxyl in digitoxin (Fig. 22). Thus, 40- 150 variants were sought that demonstrated altered binding. Panka et al. (1988) isolated a spontaneous variant in vitro using two-color fluorescence-activated cell sorting. This first-order variant, 40- 150 A2.4, had reduced affinity for digoxin (9.2 x lo6M-') due to the single mutation Ser94Arg at the framework position H94. A second-order variant, designated 40-150 A2.4P.10, was isolated from 40-150 A2.4 and demonstrated a partial regain of binding to digoxin (4.4 x lo8 W ) .Protein sequence analysis demonstrated that the 40-150 A2.4P.10 H chains were secreted as a mixture of full-length chains and chains with deletion of the N-terminal two amino acids (in addition to the mutation Ser94Arg). The purified Numbering for antidigoxin antibodies is according to Kabat et al., 1991

ANTIBODY BINDING SITES

40 1

truncated species proved responsible for the regain in affinity of 40-150 A2.4P.10. Thus, an unusual framework change results in increased affinity despite the fact that the H chain N terminus is distant from the antigen combining site. Computer models of 40-150 and the two variants suggested that the substitution Ser94Arg found in 40-150 A2.4 results in formation of a hydrogen bond network with HAsp-101, LArg-46, and LAsp55, which modifies the combining site so as to decrease digoxin binding (Novotny et al., 1990). Deletion of the first two H chain N-terminal amino acids would increase the solvent accessibility of HArg-94, thus disrupting the putative hydrogen bonding network, restoring the structure to one similar to that of 40-150, and thus accounting for the regain in binding of the second-order variant. The variant 40-150 A2.4P. 10 was subsequently found to contain a signal peptide mutation, Gly+Pro, at the -2 position (Shaw and Margolies, 1992). The presence of a proline at the -2 position partially shifts the cleavage site of the signal peptidase to the +2 position, resulting in production of full-length and truncated H chains (Fig. 23). To further address the relation of H chain truncation or other Nterminal modifications to cardiac glycoside binding, the relevant mutations were introduced into the cloned and expressed 40-150 rearranged H chain V region gene and transfected into a 40- 150 L-chain-expressing cell line (Ping et al., 1993). First, the spontaneous variants 40-150 A2.4 and 40-150 A2.4P.10 were reproduced to confirm that the mutations were indeed responsible for the observed phenotype. An assessment of the combined effect on binding of two mutations seemingly distant from the binding site required construction.of signal peptide mutations and N-terminal deletions in the presence of both HSer-94 and HArg-94 (Fig. 23). Deletions of one to three amino acids had little effect on binding for mutants containing the parental Ser-94, whereas two residue truncations produced directly, or by signal peptide mutation, increased affinity approximately 40-fold for mutants containing HArg-94 (as in 40-150 A2.4). These observations are consistent with the computer model. Introduction of Pro at the signal peptide -3 position in 40-150 resulted in cleavage at alternative sites. The signal peptide of antibody 26-10 H chain was also mutated to Pro at the -2 position, which resulted, unexpectedly, in the expression of H chains elongated by three residues at the N terminus. This mutant antibody had a 100-fold decrease in affinity. Thus, both extensions and deletions of H chain N termini can result in enhanced or reduced antigen binding, depending on the structural context of specific antibody combining sites. Although the conformation of a tripeptide tail in solution, as in 26-10, may differ from that in which the H chain N terminus is attached to another polypeptide domain, the fact that N-terminal length or sequence identity can modulate binding must be borne in mind when engineering

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J . Structure and Mutagenesis of Antidigoxin Antibody 26-1 0 1. Spontaneous Variants and Site-Directed Mutants

a. Spontaneous Variants. Because antibody 26- 10 had been crystallized (Rose et al., 1983), it was studied intensively. Spontaneous variants displaying altered binding were isolated using two-color, fluorescence-activated cell sorting, which permitted the selection of variants with subtle binding differences. Eleven variants were isolated, cloned, and sequenced, and their binding characterized. Among these, 10 different, unique V region amino acid sequence mutations were identified, all of which were in CDRs-9 in V H and 1 in VL. Eight variants had single amino acid replacements, while three contained multiple clustered VH region mutations, suggesting that they were due to gene conversion or recombination. Among nine VH mutants, two contained single mutations at position 35, and the three variants with multiple mutations all included position-35 mutations. Other mutations occurred at VH 50, 52, 58, 100B, and VL 92 (see Fig. 24). b. Mutations in Antibody HCDRB: Mutagenesis Studies on Contact and Noncontact Residues. The spontaneous variant 26-1OLL2 contains a single mutation, HTyr50His, which results in a 40-fold reduction in affinity for digoxin (Schildbach et al., 1991). To define the pattern of hapten recognition, the binding of 33 digoxin analogs was compared to that of digoxin in competition assays. As shown in Table XIV, antibody 26-10 does not recognize the C-3-attached sugar moieties, although there is a slight decrease in binding if the 3-hydroxyl is a rather than p. Antibody 26-10 is also indifferent to the presence (digoxin) or absence (digitoxin) of the 12hydroxyl. However, the mutation HTyr50His results in a combining site with altered specificity. This mutant is sensitive to the absence of the 12hydroxyl, as the relative affinities for digitoxin, digitoxigenin, evomonoside, and neriifolin are lower than for digoxin. Specificity changes for a second HCDR2 mutant, 26- 10LB4 (HSer52Phe), are less marked (Schildbach et al., 1993b). Both antibody 26-10 and in particular the mutant Tyr50His FIG. 23. Engineered 40-150 mutant antibodies and cleavage sites of signal peptidase and corresponding affinities for digoxin. Amino acid sequences are shown in the one-letter code for the 40-150 H chain signal peptide C-region, N-terminal region of the mature H chain, and residues 92-100 in antibody 40-150 and engineered mutants. Mutations resulting in amino acid replacements are in boldface. A deleted (delta) amino acid is indicated by a box. The vertical arrows indicate cleavage sites by signal peptidase, based on the results of amino acid sequences of expressed H chains (Ping et nl., 1993). Dashes indicate identity with the topmost sequence. FW,Framework. [Modified from Ping et al. (1993).]

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FIG.24. Amino acid sequences of the VH and VL regions of antidigoxin antibodies 2 S 1 0 and 40-150. Identities with the topmost sequences are indicated by dashes. <, Pyrrolidone carboxylic acid. Asterisks are introduced at positions H52a, HlOOc, d, e, and L27e to align sequences of unequal length in CDRs. Asterisks above or below certain residues indicate hapten contact residues, as shown in the crystal structures of the respective complexes (Jeffrey et al., 1993, 1995).Amino acids are given in the one-letter code; numbering is according to Kabat et al. (1991).

~

TABLE XIV Specificity of Binding of Digoxin and Gitoxin Analogs

Substitutions at steroid positionsa Analog

Digoxin analogsb Digoxin (digoxigenin tridigitoxoside) Digoxigenin bisdigitoxoside Digoxigenin monodigitoxoside Digoxigenin 3-Epidigoxigenin Digitoxin Digitoxigenin Evomonoside (digitoxigenin r-rhamnoside) Neriifolin (digitoxigenin thevetoside) Gitoxin Diginatin (16-hydroxydigoxin) 12-Acetyldigoxin Digoxigenin 3,12-diacetate Dihydrodigoxigenin (C-20C-22 bond saturated Gitoxin analogs' Digoxin Gitoxin Gitoxigenin monodigitoxoside Strospeside (gitoxigenin monodigitaloside) Gitoxigenin Gitoxigenin 3-acetate Gitaloxin (16-formylgitoxin) Gitaloxigenin 16-Acetylgitoxin Oleandrin Oleandrigenin monodigitoxoside Oleandrigenin Gitoxigenin 3,12-diacetate

Ratio of inhibitory concentrations

128

16B

Tridigitoxose

-OH

-

1

1

1

Bisdigitoxose Monodigitoxose

-OH -OH

-

1 1

2 2

1 1

-OH a-OH Tridigitoxose -OH L-Rhamnose

2 4 1 2 3

4 3 8 13 14

1 2 4 5 5

Thevetose

2

12

4

5 2

46 4

15 2

3

26-10

LL2

LB4

Tridigitoxose Tridigi toxose

-OH

Tridigitoxose -0COCH3 -OH

-0cocr-1~-OCOCH3 -OH -

160 750 1700

150 930 1100

130 480 590

Tridigitoxose Tridigitoxose Monodigitoxose

-OH -

-

-

-OH -OH

1 5 4

1 46 40

1 15 14

Monodigitalose

-

-OH

5

40

12

-OH -0COCH3 Tridigitoxose -0 H Tridigitoxose Oleandrose Monodigitoxose

-

-OH -OH -0CHO -0CHO -0COCH3 -0COCH3 -0COCH3

13 12 30 150 150 740 770

66 74 160 540 430 3900 3300

22 29 76 170 220 580 630

-OH -0COCH3

-

-OH -OH

-0COCH3 17,000 >16,000 2100 -0COCH3 36,000 > 13,000 2200

' Refer to Fig. 22 for steroid numbering system. Orientation of substitutions at the 3 position is /3, except as noted. Digoxin analogs were used to compare with 1251-labeleddigoxin for binding to antibody 26-10 and its mutants. The results are presented as the ratio of concentrations of analog to digoxin that inhibits 50% of binding of 'z51-labeled digoxin to antibody. ' Gitoxin analogs were used to compete with '"I-labeled digoxin for binding to antibody 26-10 and its mutants. The results are presented as the ratio of concentrations of analog to digoxin that inhibit 50% of binding of '"I-labeled digoxin to antibody. 405

406

JAMES S. HUSTON ET AL.

have reduced binding to gitoxin, which contains a 16-hydroxyl. The importance of the 12-hydroxyl group in the mutant is indicated by the “correction” of binding when a 12-hydroxyl is added to a 16-hydroxyl, as in diginatin (Table XIV). The presence of a 12-acetyl group reduces affinity for 26-10 and the variants. In addition, replacement of the sugar with an acetyl group (digoxigenin 3,12-diacetate) hrther impairs binding. Antibody 26-1 0 and both mutants bind gitoxin congeners containing a 16-hydroxyl (but lacking a 12-hydroxyl)with slightly higher affinity when there is a sugar at the 3 position. Affinity progressively decreases as a 16-formyl group is substituted (gitaloxin), and is lowest for the larger 16acetyl group. The deleterious effect on binding due to the absence of the

a

b

C

d e FIG.25. Orthogonal views (left and right) of space-filling representations of (A) digoxigenin monodigitoxoside, (B) ouabain, (C) 12-acetyldigoxigenin, (D) oleandrin, and (E) oleandrigenin monodigitoxose. Carbon atoms are dark and oxygen atoms are light. The lactone is at the left for each structure, and the sugar (if present) at the right. See Table XXI and Fig. 22 for chemical denotation of structures. The different orientations observed for the lactone in digoxin congeners are shown with digoxigenin monodigitoxoside (A) and 12-acetyldigoxigenin (C) in one orientation and ouabain (B), oleandrin (D), and oleandrigenin monodigitoxose (E) in the other. Note the different orientations of oleandrose in oleandrin (D) and digitoxose in oleandrigenin monodigitoxose (E). Produced using MOLSCRIFT (Kraulis, 1991).

407

ANTIBODY BINDING SITES

sugar groups is greatest for congeners with the largest 16 substituents (compare with congeners in Fig. 25). The mutants LL2 and LB4 demonstrate altered specificity in that they bind less well to the 16-substituted analogs than to digoxin, as compared to 26-10 (Table XIV). The observation that a 3-position substitution affects binding only in the context of 12- and 16-position substitutions may be explained by a change in orientation of the hapten in the site in the presence of bulky 12- or 16-position substituents, causing steric hindrance and resulting in new contacts with the 3-position substitution (see later discussion). Additional specificity studies (not shown) involving ouabain and eight ouabain congeners implicated the presence of the 1la-OH group as responsible for the lower binding of 26-10 and the two mutants to ouabain as compared to digoxin. The role of HTyr-50 in the antibody 26-10 combining site was further investigated by site-directed mutagenesis (Schildbach et al., 1993a). The 26-10 rearranged VHregion gene was cloned and inserted into an expression vector (Near et al., 1990, 1991). Following oligonucleotide-directed mutagenesis, the vector containing the mutated 26-10 V H was transfected into a 26-10 L-chain-expressing cell line. The affinities of eight mutant antibodies containing H50 amino acid replacements are shown in Table XV. Replacement of HTyr-50 with other aromatic residues causes little change in affinity, whereas replacement with other amino acids results in up to a 4000-fold decrease in affinity. The affinity of mutant antibodies roughly correlates with the size of the H50 side chain. Mutants were subjected to a TABLE XV

Ajinity of Antibodiesfir Digoxin' Affinity Antibody or mutant

(x~o-'M - ~ )

26-10 wild type (HTyr5O) HTyr50Phe HTyr50Trp HTyr50Asn HTyr50His (LL2) HTyr50Leu HTyr50Ala HTyr50Gly HTyr50Asp

910 k 100 1200f200 670 k 90 29k6 25 f 4 9.2 k 0.9 3.8 k 0.4 0.29k 0.10 0.23 f 0.07

' K, for digoxin as measured in a saturation equilibrium assay. Affinity values given are results from representative assays with estimated standard error as given by the LIGAND program.

408

JAMES S. HUSTON E?’ AL

LPro-96

LPro-96

c FIG.26. Stereo view of digoxigenin and its orientation to HTyr-47, HTyr-50, and LPro96 from the X-ray crystal structure of the 26-10 Fab-digoxin complex (Jeffrey et al., 1993). The atoms of HTyr-50 and hapten that are in contact are shown as solid circles. Hydrogens are shown only for the Tyr phenolic and the digoxigenin hydroxyl groups. [From Schildbach et al. (1993a).]

modeling procedure that combined a side-chain conformational search with energy minimization (Schildbach et al., 1993 a,b), based on the crystal structure of the 26-10 Fab-digoxin complex (Jeffrey et al., 1993). Mutants Tyr50Phe and Tyr50Trp exhibit no change in specificity for 26-10, and in the models contain all the wild-type contacts with digoxin except that involving the Tyr 0 (Fig. 26). The side chains of HTyr50His, HTyr50Asn, and HTyr50Asp cannot provide many of the other contacts, but their C/3 and C y atoms are in the same position as those of HTyr-50. The Asp and Asn side chains in the models are stabilized by hydrogen bonds to the -OH of HTyr-47. Mutants HTyr5OLeu and HTyr5OAla also mimic some of the wild-type hapten contacts. These mutants demonstrate higher affinity for 12-acetylated analogs relative to digoxin than does 26- 10. When 12-acetyldigoxigeninwas docked into the wild-type structure and into the HTyr50Ala binding site model (Fig. 27), the acetyl group caused unfavorably close contacts with both LPro-96 and HTyr-50. In the HTyr50Ala binding site, however, the hapten has shifted in position, relieving these unfavorable contacts. The modeling results explain the observed 50- to 100-fold relative increase in binding to 12-acetylated congeners observed in HTyr50Ala compared to wild-type 26-10. This altered fine specificity, however, occurs at the cost of significantly reduced affinity. The contribution of 26-10 HTyr-50 to digoxin binding derives from shape complementarity rather than hydrogen bonding. The binding of

ANTIBODY BINDING SITES

409

FIG. 27. Stereo view of the orientation of 12-acetyldigoxigenin in the binding sites of (upper) 26-10 and (lower) HTyr50Ala. In both, 12-acetyldigoxigenin is in the center with the 12-acetyl group extending downward. The residue on the left is LPro-96, and the amino acid on the right is the H50 residue. Also included is the main chain of the amino acids N-terminal and C-terminal to LPro-96 and H50. [From Schildbach et al. (1993a).]

the H50 mutants is consistent with the conclusion that shape complementarity alone can contribute to specificity and affinity. The spontaneous variant 26- 1OLB4 (HSer52Phe) has 150-fold-reduced affinity for digoxin yet does not contact hapten in the 26-10 Fab-digoxin complex (Jeffrey et al., 1993). To examine the basis of decreased affinity, mutant antibodies with nine different H52 substitutions were constructed and compared to the wild type and the LB4 variant (Schildbach et al., 199313) (Table XVI). The mutagenesis data indicate that the Ser hydroxyl makes no contribution to binding, as confirmed in the crystal structure. To test the correlation between the volume of each H52 residue and affinity for digoxin, energies of complexation were calculated and plotted against H52 residue volume (Fig. 28). The results, which did not take into account side chain shape, indicate that antibody affinity decreased concomitantly with increased side chain size. The modeling studies indicated that each substituted side chain may be accommodated without substantial rearrangement of the binding site structure, and that the substituted residues do not contact hapten. The effect on affinity is likely mediated through the adjacent HTyr-33, which contacts the C-3, C-4, C-7, and C-15 atoms of digoxin (Figs. 22 and 29) (Jeffrey et al., 1993). Thus, mutations at noncontact residues can alter affinity indirectly, an observation made pre-

410

JAMES S. HUSTON ET AL.

TABLE XVI

Afinilies for Digoxin Amino acid residue volume Antibody or mutant

Ka (x 10" ivf-l)a

(A3)

26-10 wild type (HSer-52) HSer52Gly HSer52Ala HSer52Thr HSer52Leu HSer52Cys HSer52Val HSer52Ile LB4 (HSer52Phe) HSer52Trp HSer52Tyr

9100 f 1000 10,000 f 1000 8000 f 1400 950 f 160 760 f 120 500 f 40 370 f 40 330 f 90 61 f l 0 59f7 36f3

88.6 59.9 88.3 115.7 166.2 108.1 139.3 166.2 189.1 226.9 192.9

a Affinities were measured by an equilibrium saturation assay using filtration through glass fiber to separate bound from free [3H]digoxin (Schildbach et al., 1991). A representative affinity measurement is given with standard error estimates calculated by LIGAND.

-10.0

-1 1.o -12.0 -13.0 -14.0 II 50

I I

I

I

I

100

150

200

250

Amino acid residue volume (A3) FIG 28. Plot of the energy of complexation of digoxin with each antibody versus the volume of the amino acid residue at H52. The points are identified by the one-letter code for the amino acid at H52. The energies were calculated from the experimentally determined KO for digoxin according to Ec = RT In KO, where R is the gas constant and T is 293OK.

41 1

ANTIBODY BINDING SITES

a

K

a

K

FIG.29. (Top)Stereo view of the Fab 26-lO-digoxin complex (Jeffrey et al., 1993) as seen from VL. The hapten digoxigenin monodigitoxoside is at the upper center and is darkened. HTyr-33, HTyr-50, and LPro-96 are labeled. HTyr-47 is immediately to the left of LPro-96. (Bottom)Stereo view of the complex as seen from HCDR3. HTyr-33, HTyr-50, and HTrp-100 are labeled.

viously for antilysozyme antibodies (Lavoie et al., 1992), antiphosphocholine antibodies (Chien et al., 1989), and the antidigoxin antibody 40-150 (Panka et al., 1988). c. Recurrent Mutations at H Chain Position 35: Site-Directed Mutagenesis Studies. The 26- 10 spontaneous variant LIB 1 isolated by cell sorting contains two VH mutations, Asn35Tyr and Arg38Met (Schildbach et al., 1994). When introduced into 26-10, the mutation Asn35Tyr ablates binding, while Arg38Met has no effect on affinity, indicating that the defect occurs with substitution of the bulky tyrosine at position 35. Another variant, 26-10R3, contains a single mutation, HAsn35Lys, and also fails to bind

412

JAMES S . HUSTON ET AL.

digoxin. Because there were additional variants identified containing mutations at H35, mutagenesis experiments were undertaken to define the contribution of this position to antibody 26-10 digoxin binding. The affinities of mutant antibodies are shown in Table XVII. As the reductions in affinity of position 35 mutants for digoxin are greater than those expected based on the small hapten contact area of the wild-type Asn, molecular modeling experiments were performed. The X-ray crystal structure of Fab 26-10 complexed with digoxin was obtained subsequent to completion of the mutagenesis experiments and was used as a basis for the modeling. The mutant Asn35Gln, which has 10-fold-reduced affinity but unchanged specificity, appears to maintain a hydrogen bond to HTyr-47, as in the wildtype structure. HAsn35Asp could also maintain hydrogen bonds, but this mutant demonstrates significantly decreased affinity, likely due to charge effects. The specificity of each of the position-35 mutants for six digoxin analogs was measured. The specificity of wild-type 26-10 was compared to that of the mutant Asn35Ala (Table XVIII). This mutant showed significantly increased relative affinity for gitaloxin and the 16-acetylated haptens. The affinity of Asn35Ala for oleandrigenin is actually greater than that of wild-type 26-10, despite the more than 200-fold decrease in affinity of Asn35Ala in comparison with that of the wild type. To seek an explanation for the altered fine specificity for HAla-35, models of 26-10 and HAsn35Ala were docked with oleandrin. The reduced side chain volume TABLE XVII

Afinitj of H35 Mutantsfor Digoxin' Antibody or mutant 26-10 wild type HAsn35Gln HAsn35Val HAsn35Thr HAsn35Leu HAsn35Ala HAsn35Asp HAsn35Lys HAsn35Tyr

Affinity (x10-S M-1) 91,000 k 10,000 8400 k 1000 970 k 120 440 f 70 390 f 50 380 k 60 6 6 k 16 < loh
a Affinities were measured by an equilibrium saturation assay using filtration through glass fiber to separate bound from free [3H]digoxin (Schildbach et al., 1991). Affinity below lower limit of this assay (106M-').

413

ANTIBODY BINDING SITES

TABLE XVIII

Relative K, Valuesfor Digoxin Analogsa Analog Digoxin Gitoxin Gitaloxin 16-Acetylgitoxin Oleandrin Oleandrigenin Dihydrodigoxin

26-10 wild type 1

6 32 250 920 9900 1300

HAsn35Ala 1 14 3 8 19 14 190

a Ki values for antibodies for digoxin analogs were determined in a solution-phase competition assay. Kt is Kd as determined by competition assay. Values were normalized to the K, for digoxin for each antibody.

of the Ala mutant provides space for the oleandrin 16-acetyl group, thus explaining the specificity shift (Fig. 30). Similar arguments account for improved relative binding of HAsn35Ala to dihydrodigoxin (Table XVIII). HAsn-35 contacts the D ring and lactone atoms C-16, C-17, C-20, C-21, and C-22 (Figs. 22 and 29) and forms hydrogen bonds with the hydroxyls of HTyr-47 and HSer-95, both of which are hapten contact residues. The results of modeling in the context of the crystal structure, taken together with the binding measurements, support the contention that the hydrogen bonding of HAsn-35 is essential to maintain local binding site structure and specificity. The importance of the identity of H35 in hapten recognition has been demonstrated for many other antibodies (summarized in Schildbach et al., 1994). The relatively conserved structure of HCDRl among Fabs (Chothia et al., 1989) often positions H35 at a pivotal site at the bottom of the binding site. 2. X-Ray Crystal Structure of 26-10 Fab and 26-10 Fab in Complex with Digoxin The three-dimensional structure of the 26-10 Fab in complex with digoxin was deterrrined at 2.5 8, resolution (Briinger, 1991; Jeffrey et al., 1993). In addition, the uncomplexed Fab structure was determined to 2.7 A resolution. Digoxin is bound in the center of the site, between the VH and VL domains, with the long axis of digoxin (0-3 atom to C- 17 atom) approximately parallel to the pseudo twofold axis relating VH and VL (Fig. 29). The lactone ring is bound deepest in the site, with the first digitoxose moiety exposed to solvent. This orientation is consistent with the fact that the digoxin is coupled to protein through the terminal digitoxose moiety

414

JAMES S. HUSTON ET AL.

)

HTyr-47

lHT

B

B FIG.30. Stereo views of modeled complexes of 26-10 (top) and 26-10 HAsn35Ala (bottom) with oleandrin. Oleandrin, HTyr-33, HTyr-47, HSer-95, and the H35 residue are shown (thick lines) with the corresponding side chains and hapten molecules from modeled complexes of the antibodies with digoxigenin (thin lines). The main-chain atoms of amino acids are displayed through the C, of adjacent residues. Hydrogens are shown explicitly only on potential hydrogen bond donors. Reproduced with permission from Schildbach et al., 1994. Protein Sci. 3, 737-749. 0 1994 by Cambridge University Press.

to produce the immunogen. Surface complementarity between antibody and hapten is closest at the lactone and the steroid D ring and decreases toward the periphery of the binding site. The atomic B factors are correspondingly lower at the lactone. The close complementarity around the lactone ring renders the complex specific for only one of the two possible lactone conformations of digoxin. There is no significant difference between the structure of digoxin in the complex and the small-molecule crystal structure (Go et al., 1980). Digoxin is packed between the aromatic rings of HTyr-33, HTyr-50, and HTrp-100 (Fig. 29). However, there are gaps in the complementary surfaces in the region of the 12- and 14-

415

ANTIBODY BINDING SITES

hydroxyl groups of digoxin. There are no significant conformational changes that occur between the complexed and uncomplexed Fab. The second and third (most peripheral) digitoxose groups are not observed as electron density. A list of contacts between hapten and Fab is shown in Table XIX. All the contacts between Fab 26- 10 and digoxin are nonpolar; there are neither hydrogen bonds nor charge group interactions. Sixty-one painvise contacts involve 10 amino acid residues from four CDRs, including all three H chain CDRs and LCDRS, as well as VH framework 2, and 19 digoxin atoms on all four steroid rings and the lactone. The majority of TABLE XIX

Contacts between Fab 26-1 0 and Haptena

Region LCDRl LCDR3 HCDRl FR2 VH HCDR2 HCDR3

Contacting residues

Digitoxose Ring A Ring B Ring C RingD Lactone Total

(Az)

LThr-9 1, LPro-96 HTyr-33, HAsn-35 HTyr-47 HTyr-50 HSer-95, HTrp-100, HA1a- 100a, HMet- lOOb

Total

Region

Fab to hapten Buried Pairwise area contacts

Contacting atoms

C-2, C-3, C-4 C-6, C-7, C-19 C-12,O-12 0-14, C-15, C-16, C-17, C-18 C-20, C-21,O-21, C-22, C-23, 0-23

0 9 13 6 6 26

5 92 55 19 74 126

59

383

Hapten to Fab Buried Pairwise area contacts (A21

0 4 3 17

26 36 36 37 75

27

78

59

274

8

Digoxin region

Ring D; lactone Rings A, C, D; lactone Ring D; lactone RingsA, C, D Rings B, D; lactone

Fab region

HCDR1, HCDRP HCDRl, HCDR3 LCDR3, HCDRP LCDR3, HCDR1, HCDR2, HCDR3, FR2 VH LCDR3, HCDR1, HCDR3, FR2 VH

a Noncontacting 26-10 residues contribute 79 A' of the total buried surface area. Noncontacting digoxin atoms contribute 39 A' of the total buried surface area. FR2, Framework region 2. HCDRs 1-3 refer to CDRs 1-3 in the immunoglobulin heavy chain; LCDRs 1 and 3 refer to CDRs 1 and 3 in the light chain.

416

JAMES S. HUSTON ET AL.

pairwise contacts involve four aromatic Fab side chains: HTyr-33, HTyr47, HTyr-50, and HTrp-100, and the lactone and D rings of digoxin. The monodigitoxose makes no contact with the Fab. The crystal structure of the 26- 10-digoxin complex provides explanations for the observed fine specificity of 26- 10 (Table X N ) . Antibody 26- 10 does not recognize attached sugars, corresponding to the limited interactions between digitoxose and Fab in the complex and the disorder of the second and third digitoxose groups. The 12P-hydroxyl is not a major determinant of specificity, as 26-10 binds digitoxin and digoxin equally, despite two contacts made between the 12P-hydroxyl and LPro-96. It is possible that the energy gained from antibody-antigen interaction is offset by the necessity for partially desolvating the 12P-hydroxyl and forming the complex. The reduction in affinity occurring with large C- 16 substituents is accounted for by the close complementarity between the digoxin D ring 16 position and antibody. The specificity and affinity of antibody 26-10 is based solely on shape complementarity, in contrast to the situation in other crystal structures of Fab in complex with antigen. The complementarity between the solventaccessible surfaces of digoxin and 26-10 is imperfect, yet it is sufficient to exclude water from the interface between antibody and antigen. Thus, the displacement of water ordered at the surface of digoxin, rather than dispersion forces, is the dominant term in the high affinity of 26-10 for digoxin. This hydrophobic effect (Kauzmann, 1959) may be enhanced by the rigidity of the hapten and the combining site aromatic rings because fewer degrees of freedom are lost on immobilizing the hapten than would be the case for a more flexible hapten. 3. Structural Constraints in H Chain CDRl Revealed by Random Mutagenesis

of Phage-Displayed 26-10 Fab A phage display system was used to accelerate analyses of the complementarity between antibody 26-10 and digoxin. DNA sequences encoding the 26-10 Fab were introduced into the vector pComb3 (Barbaset al., 1991), which had been modified to reproduce the 26-10 H and L N-terminal amino acids. The Fab is expressed on the surface of bacteriophage M 13 as a gene-3 fusion protein and is secreted following excision of gene 3. The affinity-purified bacterially expressed Fab was indistinguishable from enzymatically prepared Fab in size, sequence, immunoreactivity, and binding affinity. Short et al. (1995) constructed a library of mutants randomized at H chain positions 30-35 and selected by panning against conjugates of digoxin and certain analogs. By enriching and selecting mutants by panning, it was possible to determine to what degree structural constraints on digoxin binding limit sequence diversity in the HCDRl loop: Is there

417

ANTIBODY BINDING SITES

more than one sequence in this segment consistent with high-affinity binding? Mutants with increased affinity relative to wild-type 26-10 were also sought. Among 73 antigen-positive clones, 26 different nucleotide sequences were observed. The majority of Fab had a high affinity for digoxin (K, 2 3.4 x lo9M-’). A sample of the sequences obtained and corresponding affinities is shown in Table XX. The statistical distribution of amino TABLE xx AfJinity for Dzgoxin of 26-10 H Chain Mutants Heavy chain amino acid sequence Fab or mutant

Affinitya *) ( X ~ OM-- ~

30

26- 1OEb 26-10B A4- 19 A4-20 D4- 1 D4-2 D4-3 D4-4 D4-5 D4-6 D4-8 D4-9 D4- 10 D4-11 D4- 12 D4-15 D4-17 D4- 18 G6- 1 G6-2 F6- 1 F6-2

5.4 k 0.6 5.3 1.9 21.7 k 8.1 9.7 k 3.8 3.4 0.2 5.7 k 1.1 0.006 0.9 k 0.1 3.5 k 0.2 1.8 f 0.5 4.5 k 0.1 2.0 k 0.6 6 . 6 + 1.6 6.6 k 1.0 4.0 k 0.2 1.8 f 0.2 5.1 k 0 . 3 5.6 k 0.1 4.3 k 0.6 0.3 +_ 0.03 3.9 k 0.6 5.6 k 1.7

T T P R W P N G W P P W R N A D H R G S T S

* *

35 D D S D D G N S P P D P G N R D D G E K R H

F F F F L R Y G S A L Q F Y W T F L R R Y S

Y Y Y Y W Y F S Y Y Y Y Y P Y Y F Y F Y W Y

M W Y Y V I F I I F I V Y F I N F Y F I F I

N N N N N N V N N N N N N N N S N N N N N N

‘”Affinities (&) for digoxin of Fah 26-10 and mutants (randomly mutated at positions H30-H35 inclusive) selected from a bacteriophage library by digoxin (D), gitoxin (G), 16-acetylgitoxin (A) and 16formylgitoxin (F). Minities were measured using an equilibrium saturation method with filtration through glass fiber filters for separation of hound and free ligand (Schildbach et al., 1993a), except that Fab was immobilized on the filter using goal anti-mouse Fab. 26-10E refers to Fab enzymatically prepared from hybridoma protein while 26-10B was prepared from bacterial supernatants in a manner identical to that for the mutant samples.

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JAMES S. HUSTON E T AL

acids at positions H30-H35 was determined by the method of Wells (Matthews et al., 1994) where the data are given as the standard deviation (0) of the difference between the observed frequency of each amino acid and the expected frequency (Fig. 3 1).

3

2 1 I

0

I -1

a Amino acid

Amino acid

4

.I

Amino acid

419

ANTIBODY BINDING SITES D

33

n

I

m

2

15

10

J D

J

1

ACDEFGHIKLMNPQRSTVWY

I

Amino acid

8

ti ., I

ACDEFGHIKLMNPQRSTVWY

I

Amino acid

3

3

Amino acid FIG. 31. Statistical distribution of amino acids at H chain positions 30-35 among a set of unique clones recovered after panning, using four different cardiac glycosides, of a 26-10 Fab library randomized at H30-H35. Position numbers are at the upper right in each case. Au is the standard deviation of the difference between the observed frequency and the expected frequency (Matthews et al., 1994). Note that the maximum scale (upper)is Au= 6, and (lower) Au = 30. [From Short et al. (1995).]

420

JAMES S . HUSTON ET AL.

A distinct consensus pattern of amino acid usage was observed (compare wild-type sequence in Fig. 24). Most dramatic was the conservation of Asn at position H35 (24 of 26 sequences), consistent with previous results of site-directed mutagenesis (Schildbach et al., 1994) and the crystal structure, which shows tight complementarity between HAsn-35 and digoxin, as well as the participation of HAsn-35 in a hydrogen bonding network. The structure of 26-10 HCDRl is shown in Fig. 32. At position H34 the wild-type Met was not observed. The predominant residues were Ile, Phe, and Tyr. The H34 side chain packs into the interior. Substitution of Tyr would cause a steric clash with HPro-52 and HTyr-32, resulting in local structural rearrangement. The four mutants containing HTyr-34 had affinities greater than or equal to that of wild-type 26- 10, indicating that such rearrangement can increase complementarity. Two Fabs (A4-19 and A4-20, Table XX) had affinities 4.1- and 1.8-fold greater than 26-10, indicating that although antibody 26- 10 is relatively optimized through affinity maturation in vivo to bind digoxin, the affinity can be further increased in vitro. HTyr-33 is also a contact residue in the crystal structure but can be replaced with Phe or Trp, consistent with the requirement for a planar, hydrophobic residue at this position. At H30-H32, great sequence variability was observed, as compared to positions H33-H35 (Table XX, Fig. 31). Ten to 14 different amino acids were observed at positions H30-H32 in digoxin-binding clones. This promiscuity in amino acid usage is paralleled by the observed disorder in the crystal structure at residues H30-H32,

Thr-30

9-

-

) Met-34

k Asn-35

\

Asn-35

FIG. 32. Stereo views of HCDRl and digoxin from the X-ray crystal structure of the 26-10 Fab-digoxin complex (Jeffrey et al., 1993). Digoxigenin monodigitoxoside is on the left with the lactone at the bottom. At the top is shown a single attached sugar (digoxigenin monodigitoxoside). HTyr-33 and HAsn-35 of CDRl make van der Waals contacts with the hapten. [From Short et al. (1995).]

ANTIBODY BINDING SITES

42 1

where most side chains are solvent-exposed. The crystallographic disorder indicates either that several conformations occur here or that this region is highly mobile. Although the diversity in HCDRl is thus great, it is remarkable that so many amino acid combinations result in Fabs with a similar affinity for digoxin. The variability at positions H30-H32 does not prevent digoxin binding but must permit a stable framework for the contacting region H33-H35. K. X-Ray Crystal Structure and Binding S$ec$city of Antidigoxin Antibody 40-50: Comparison of Structures and Binding Modes of Two Antidigoxin Antibodies, 40-50 and 26-10 As the antidigoxin antibody 40-50 produced suitable crystals, Jeffrey et al. (1995) determined its sequence, affinity for digoxin, and fine specificity. The crystal structure determination provided a unique opportunity to compare the combining sites of two different high-affinity antibodies elicited by the same hapten. Antibody 40-50 binds digoxin with an affinity of 1.7 x loyM P . The amino acid sequence of 40-50 differs markedly from that of antibody 26-10 (Fig. 24); each antibody uses entirely different V region gene segments. The antibodies differ in length in HCDR3 and LCDRl and exhibit little homology in the CDR regions. The specificity of antibody 40-50 for 28 digoxin analogs is shown in Table XXI, where it is compared to that of antibody 26- 10. The structure of the complex between 40-50 and ouabain was determined to 2.7 A resolution (Jeffrey et al., 1995). Ouabain is bound in a groove involving mainly the L chain (17 x 7 x 6 A) that contains a pocket at the center of the combining site (Fig. 33). The lactone ring and D ring reside in a pocket formed by VLand VH (6 A deep, 7 A in diameter). There is close surface complementarity between ouabain and antibody 40-50 except in the region of HTyr-100 (Fig. 34). The lactone and steroid D rings are completely buried, but rings A through C and rhamnose are partly solvent-accessible as a single patch. Aromatic side chains contribute 60% of the total buried surface area. All CDR loops save LCDR2 contain residues that make painvise contacts with ouabain (Table XXII). HCDR3 contributes the majority of contacts and buried surface area. Two hydrogen bonds are formed involving 0-14 and 0-21 of the hapten; 0-14 and 0-21 are conserved in all cardenolides. As cocrystallization of antibody 40-50 in complex with digoxin did not yield suitable crystals, a model of 40-50-digoxin was constructed by superimposing digoxin from the 26- 10digoxin crystal complex onto the 40-50-ouabain crystal structure. Digoxin occupies the 40-50 Fab binding site without major structural rearrangement in either the antibody or the hapten, suggesting that the position of

T ~ LXXI L Specaficaty of Binding ofAntzbody 40-50

to Digoxzn, Gatoxzn, and

Ouabain Analogs

Substitutions at steroid positions" Analog

p.

t s rci

Digoxin analogs Digoxin (digoxigenin tridigitoxoside) Digoxigenin monodigitoxoside Digoxigenin 3-Epidigoxigenin Digitoxin Digitoxigenin Evomonoside (digitoxigenin rhamnoside) Neriifolin (digoxigenin thevetoside) Gitoxin ( 16-hydroxydigitoxin) Diginatin (16-hydroxydigoxin) 12-Acetyldigoxin Digoxigenin 3,12-diacetate Dihydrodigoxin (saturated lactone) Dihydrodigoxigenin (saturated lactone) Gitoxin analogs Digoxin Gitoxin Strospeside (gitoxigenin monodigitaloside) Gitoxigenin

K, (+S.E.) (M)'

Tridigitoxose Monodigitoxose j3-OH a-OH Tridigitoxose B-OH L-Rhamnose

-OH -OH -OH -OH

Thevetose Tridigitoxose Tridigitoxose Tridigitoxose -OCOCHs Tridigitoxose j3-OH

-

-

-

-

-

-

-

-

-

-OH

4 H -OCOCH3 -0COCHj -OH -OH

4 H -

-

Tridigitoxose Tridigitoxose Monodigitalose

-

-OH

-

-OH

-

-OH

(4.3k 1. l ) x 10-'0 (2.5 f 0.3) x 10-l' ( 1 . 0 f 0 . 6 ) ~lo-' (5.1 f 0.3) (5.6 f 1.7) x lo-'' (7.7 f 1.5) x 10-1" (2.5 f 0.2) x 10-1" (5.4 f 0.3) x lo-'" (7.0 f 1.5) x (1.4 f 0.4) x (2.1 f 0.4) x 10-I" (2.8 f 0.3) x lo-'" (1.2 f 0.2) x (1.3f0.2)~10-'

40-50 relative K, '

1

0.6 2 12 1

2 0.6

1 16

33 0.5 0.7 280 300

26-10 relative inhibiting concentrationd

1 1

2 4 1 2 3

2 5 2 160 750 1300 1700

-OH

(4.3 f 1.1) x 10-1" (7.0 f 1.5) x lo-' (1.5 f 0.3) x

35

1 5 5

-OH

(4.0 f 0.4) x

93

13

1 16

Gitoxigenin 3-acetate Gitaloxin (16-formylgitoxin) 16-Acetylgitoxin Oleandrin Oleandrigenin monodigitoxoside Oleandrigenin

-OCOCHj Tridigitoxose Tridigitoxose Oleandrose Monodigitoxose -OH

-OH 4CHO -OCOCHj -OCOCHs -OCOCHs -OCOCH3

-

-

-

-

(3.2 f 0.4) x (1.5 f.0.2) x (2.5 k 0.2) x (8.6 f 2.2) x (1.7 f 0.5) x (3.7 f 2.4) x

lo-' lo-' lo-' 10-' 10"

Substitutions at steroid positionsa Analog

18

38

58

lla

19

-OH -OH 4 H -OH -OH -OH

-OH -OH

-OH -OH -OH =O =O =O

Kt (kS.E.) (M)'

74 35 58 200 4 8600

12 30 150 740 770 17,000

40-50 relative Ki '

26- 10 relative inhibiting concentrationd

~

+ N

Ouabain analogs Ouabain Ouabagenin Acovenoside A Strophanthidol Strophanthidin Acetylstrophanthidin Erysimoside (strophanthidin digilanobioside)

-OH -OH -OH

L-Rhamnose -OH 6-Deoxy-3-O-Methyl-I~-talose 9 H -OH -0COCH3 Digilanobiose

-

-

(2.8 f 0.2) x lo-' (4.0 f 1.2) x lo-' (2.1 f 0.4) x lo-'' (1.8+0.2)~10-~ ( 1 . 8 f 0 . 4 ) lo-' ~ (4.4 f 0.9) x lo-' (1.3 f 0.2) x lo-'

7 9 0.5 4 4 10 3

35 50 2 2 2 2 1

Refer to Fig. 22 for steroid numbering system.

' K, of Abs for digoxin analogs were determined in a solution-phase assay. S.E., Standard error of mean. Values for each analog tested were normalized to the K, for digoxin. Ratio of concentrations of analog to digoxin which inhibit 50% of binding of iodinated digoxin to antibody in a plate assay (Schildbach et nl., 1991). The results are identical within experimental error to the K, using a solution-phase assay (Schildbach et al., 1993b).

424

JAMES S. HUSTON E T AL.

FIG.33. Stereo views of 40-50 and 26-10 antibody combining sites with VL on the left and VH on the right and shaded to display concave (light gray) and convex (dark gray) molecular surfaces. (A) The 40-50 binding site is a groove mostly on the surface of the light chain. (B) The 26-10 binding site is a deep pocket involving principally the heavy chain. Produced using GRASP (Nicholls et nl., 1991). [From Jeffrey et nl. (1995).]

digoxin in a 40-50-digoxin complex is similar to that of ouabain. The interactions in the vicinity of the lactone ring are highly conserved, while the interactions at the carbohydrate groups are likely to differ. The details of the crystal structure are entirely consistent with the antibody 40-50 specificity pattern (Table XXI). Antibody 40-50, like 26-10, does not distinguish the glycoside moiety of digoxin or digitoxin. The rhamnose of ouabain binds to the antibody in a broad region at the end of the binding groove, and contacts HCDRl and LCDR3 (Figs. 33 and 34). The lack of specific surface complementarity with rhamnose is consistent with the permissiveness of the antibody toward different carbohydrate groups (Table XXI): The 40-50 combining site is not long enough to allow interaction with the more distal carbohydrate groups (i.e., the second and

ANTIBODY B I N D I N G SITES

425

FIG. 34. Stereo views of ouabain (darkened) in the 40-50 antibody combining site (Jeffrey et al., 1995). (A) View looking into the “narrow” side of ouabain. The rhamnose is at the top. (B) View looking into the “broad” side of ouabain, approximately orthogonal to the view in (A).

third digitoxose groups of digoxigenin), accounting for similar affinities of 40-50 for digoxigenin monodigitoxoside and digoxigenin tridigitoxoside. The similar affinities of 40-50 for digoxin, digitoxin (lacks 12-hydroxyl), and 12-acetylated haptens suggests that there are no critical contacts between antibody 40-50 and the hapten 12 position. Particularly striking are the high affinities of 40-50 for 12-acetylated haptens (Table XXI) in light of the bulk of this substitution relative to the size of the cardenolide (Fig. 25). The 40-50 Fab-digoxin model complex indicates that there is adequate access to bulk solvent to accommodate large position 12 substituents. In contrast, although the 12/3-hydroxyl in 26-10 is partially solvent-accessible, the limited volume of the pocket in 26-10 precludes ready access of large 12-acetylated substituents, causing a 160- to 750-fold decrease in affinity (Table XXI). Saturation of the lactone (dihydrodigoxin and dihydrodigox-

426

JAMES S. HUSTON ET AL.

TABLE XXII

Contacts between Ouabain and 40-50" 40-50 Region LCDRl LCDR3

HCDRl HCDR2 HCDR3

a

Residue

Contact2

Hydrogen bonds'

LThr-27d LHis-32 LSer-91 LArg-92 LTyr-94 LLeu-96 HHis-35 HLeu-50 HTrp-52 HPhe-95

4 8 8 2 4 3 5 1 2 14

HPhe-97 HTyr-100

1 14

-

HTyr-lOOa HTyr-100c HVal-100e

1 10 1

-

-

Ouabain Atomsd 0-5, C-6 C-6, C-7 C-7, C-8, C-14, 0-14* c-19 C-18, C-21 C-23, 0-21, 0-23 0-21*, C-23,0-23 c-21 C-12, C-17 C-16, C-17, C-204-23, 0 - 2 1, 0-23 C-16 C-2, C-3, C-15, C-510, 0-510, C-610 0 - 2 10 0-14, C-15, C-16, C-22 0-23

Rings A A, B B, D D D, lactone Lactone Lactone Lactone D D, lactone

D A, D, rhamnose Rhamnose D, lactone Lactone

There are 78 painvise contacts and 2 hydrogen bonds between ouabain and 40-50.

* Painvise contacts determined by the method of Sheriff et al. (1987a), but using extended atom radii (Gelin and Karplus, 1979). Hydrogen-bond contacts are not included in the contact counts. Hydrogen bonds assigned where distance between a pair of polar atoms was less than 3.5 %, and the interaction had the expected geometry and chemistry. Refer to Fig. 22 for numbering. Atoms involved in hydrogen bonds are marked with an asterisk.

igenin) causes a marked decrease in affinity (1300- to 1700-fold) in both 40-50 and 26-10. The lactone ring becomes puckered, and the steroid ring moves with respect to the lactone ring when saturated (Schildbach et al., 1991). The complementarity around the lactone ring in both antibodies is quite good, and only one specific steroid and lactone ring orientation is permitted. Thus, lactone saturation significantly disturbs complementarity. Antibody 40-50, like 26-10, is sensitive to substitution at the hapten C-16 position (Table XXI), which reduces affinity concomitant with increasing size of that substituent (Fig. 25). In 40-50, 16-position substituents would collide with the HCDR3 residues HPhe-95, HPhe-97, and HTyr-102. Antibody 40-50 binding to 16-acetylated congeners is greatly influenced by the position 3 substituent. Antibody 40-50, unlike antibody 26- 10, binds oleandrigenin monodigitoxoside with 50-fold higher affinity than oleandrin. The two congeners differ only in the nature of the at-

ANTIBODY BINDING SITES

427

tached monosaccharide (see Fig. 25). The 16-substituted haptens must be bound in an orientation different from that of ouabain or digoxin, resulting in significantly different carbohydrate interactions than are seen in 40-50. Analogous behavior occurs for 26- 10 (see previous discussion). The affinity of 40-50 for 3-epidigoxigenin is reduced 12-fold relative to that for digoxigenin, suggesting that the 3a-hydroxyl of 3-epidigoxigenin interferes with binding. Inspection of the crystal structure indicates that a 3a-hydroxyl would collide with HTyr- 100, accounting for the reduced affinity for 3-epidigoxigenin. With respect to the binding of ouabain and ouabain analogs by 40-50, correlation of specificity data (Table XXI) and three-dimensional structure (Jeffrey et al., 1995) indicate that the 5phydroxyl and perhaps the 19p-hydroxyl of ouabain contribute to the reduction in the affinity of 40-50 for ouabain compared to that for digoxin. In both Fab 26-10-digoxin and Fab 40-50-ouabain, the hapten is bound with the lactone completely buried and carbohydrate exposed to the solvent; however, the orientation of the hapten to the antibody backbone differs. Further, the lactone of digoxin is deeper in the combining site of 26-10 than that of ouabain in 40-50. (The combining sites of 40-50 and 26-10 are compared in Fig. 33.) The lactone ring orientation with respect to the D rings differs by 180". Both antibodies contain a preponderance of aromatic side chains as contact residues, although 40-50 also contains two hydrogen bonds while 26-10 does not. Although the surfaces of 26-10 and 40-50 both exhibit great surface complementarity to their respective haptens, the positions of atoms making up these surfaces differ. The aromatic rings in each complex do not interact with equivalent surfaces of the hapten in the two complexes. Comparison of the two sequences (Fig. 24) shows that in the two antibodies, none of the contact residues are identical, and their CDR loops exhibit low homology. Although both antibodies 40-50 and 26-10 bind digoxin with high affinity, with the dominant force in binding for both being burial of a hydrophobic surface, each antibody uses entirely different amino acid side chains in different orientations to achieve specific high-affinity binding. ENZYME SELECTIVITY WITH SUBSTRATE-SELECTIVE ANTIBODIES V. ENHANCING

Enzymes are selective for their substrates to varying degrees, and it is often possible in this era of facile protein engineering to alter the selectivity of a given enzyme through judicious point mutations in its cDNA (Higgins and Bennett, 1990; Smith et al., 1992; Pro5 and Schimmel, 1988).An alternative approach is to create an enzyme of unique specificity de novo, by using an antigen binding site specific for a potential transition state analog (Wolfenden, 1969) as a starting point and then modifying the

428

JAMES S . HUSTON ET AL

structure of that binding site so that it possesses substrate-binding as well as catalytic functions (Schultz and Lerner, 1995). This approach has great potential, especially with the development of new screening methods for finding catalytic antibodies efficiently (Tawfik et al., 1993). To date, however, it has been difficult to create catalytic enzymes that have specific proteolytic properties de novo. A third approach-by which a targeted enzyme is readily obtainable-is to produce a fusion protein containing both a desired antigen binding site and an appropriate enzyme catalytic site. This approach works because the antibody molecule (150 kDa for IgG) is highly modular (see Section II,A),which allows excision of the DNA coding for an antigen binding domain and subsequent expression of that domain as a small (26-kDa) sFv or as part of an sFv fusion protein that can contain another functional unit such as an enzyme or a toxin (Vitetta et al., 1987; Chaudhary et al., 1989; Batra et al., 1990; Brinkmann et al., 1992; Siegall et al., 1993, 1994; Wolff et al., 1993). I n vivo, this fusion protein would bind to the antigen complementary to its antigen binding site and thereby concentrate enzymatic activity or a toxic effect in a desired region. Two potential therapeutic applications of antibody-enzyme fusion proteins are discussed in this section, in the treatment of occlusive vascular thrombosis and in the treatment of cancer.

A. Chemically Cross-linked Antibody-Enzyme Conjugates Chemically cross-linking an antibody to another protein is the most rapid and straightforward method for determining whether the production of a fusion product by recombinant DNA technology would be worthwhile. The cross-linking procedure can be carried out quickly and with little difficulty if both proteins are available, and, in contrast with the production of fusion proteins, the cross-linking method does not require cloned genes for each of the two proteins or the working out of effective bacterial or eukaryotic expression systems. Although this is not always the case, the chemically cross-linked model conjugate also often predicts attributes of the fusion protein. Significant disadvantages of chemically cross-linked proteins include heterogeneity, low yield, lack of stability, and immunogenicity associated with the presence of the cross-linking agent in the product. Also, chemical cross-linking reagents are often indiscriminate about the amino acid side chains with which they interact. For example, any of the &-aminogroups on the protein surface can participate. Should a reactive group be near an active site (on the antibody or the enzyme), the functional properties of either molecule may be altered. The commonly used two-stage cross-linking reactions, which are designed to produce heterodimeric complexes, are often subject to side reac-

ANTIBODY BINDING SITES

429

tions that result in multimers. These multimers make necessary sizefractionation steps that often reduce the ultimate yield of the conjugate. For example, it has been difficult to obtain active heterodimers in yields in excess of 10% (by methods summarized later). Disulfide conjugates also lack stability on storage and in vivo, although there has been progress in refining cross-linking reactions to produce more stable conjugates. Finally, even though there has been no clear demonstration that cross-linking reagents increase immunogenicity, one would expect these protein-linked organic groups to behave like classical haptenic antigenic determinants. These disadvantages notwithstanding, fibrin-targeted plasminogen activators provide an example of the utility of cross-linked conjugates as models for antibody-enzyme fusion proteins. As it was essential that the antigen binding site be specific for a component of the clot and not crossreact with soluble serum proteins or antigens present on endothelial cells, fibrin was selected as the target because it has antigenic epitopes that differentiate it from fibrinogen, its precursor in circulating plasma. Monoclonal antibody 59D8 (Hui et al., 1983), which is specific for an epitope exposed when thrombin catalyzes the conversion of fibrinogen to fibrin, is the cornerstone of this work. Another monoclonal antibody of similar specificity, 64C5, was used in some of the initial studies (Hui et al., 1983; Bode et al., 1985; 1987). Antibody 59D8 (as well as 64C5) was raised in response to immunization with a peptide of the sequence GHRPLDK(C), which represents the seven N-terminal residues of the /3 chain of fibrin combined with a Cterminal cysteine for cross-linking to keyhole limpet hemocyanin. The N terminus of the /3 chain appears to be conformationally protected in fibrinogen, as evidenced by the fact that there is essentially no cross-reactivity between fibrin and fibrinogen when tested with this antibody. Another important consideration in selecting a target on the thrombus is whether the epitope recognized by the antibody persists during clot dissolution. Chen et al. (1992) showed that, contrary to some reservations, the epitope recognized by 59D8 is lost from the clot (during in vitro fibrinolysis) at a rate identical to the rate of clot dissolution. Thus, epitope availability is sufficient for antigen binding throughout the course of fibrinolysis. Holvoet et al. (1989) have confirmed the utility of targeting fibrin in their experiments with monoclonal antibodies that have little reactivity with fibrinogen but react with fragment D of non-cross-linked fibrin or fragment D-dimer of cross-linked fibrin. Bode et al. (1985) first showed that a conjugate of two-chain urokinase plasminogen activator (tcuPA) and antifibrin antibody 64C5 substantially enhanced in vitro fibrinolysis in comparison with tcuPA. Bode et al. (1987) then demonstrated that tcuPA conjugated to the 64C5 Fab’ was equally active and that single-chain urokinase plasminogen activator (scuPA)

430

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could be used in a 59D8 Fab’-plasminogen activator conjugate (Bode et al., 1990). Because the antigen for 59D8 and 64C5 is a hapten, it was possible to demonstrate unequivocally that the enhancement of fibrinolytic potency was solely due to the antigen-antibody reaction: A sufficient concentration of peptide GHRPLDK reduced the fibrinolytic activity of the conjugate to that of its urokinase plasminogen activator (uPA) parent (Bode et al., 1985). Even the activity of tissue plasminogen activator (tPA), by itself fibrinselective, could be enhanced by coupling it to a fibrin-specific antibody (Runge et al., 1988). In vivo results for a 59D8-tPA conjugate in a rabbit venous thrombosis model were very encouraging (Runge et al., 1987).

B. Bispec$c Antibodies Instead of chemically cross-linking an antibody to a plasminogen activator, another approach would be to create a bispecific antibody able to bind both fibrin and a plasminogen activator without diminishing its enzymatic activity. Such a bifunctional antibody would serve to bring the plasminogen activator into proximity with fibrin, without the need to chemically manipulate the enzyme. Bode et al. (1989) and Charpie et al. (1990) first tested the feasibility of this approach with antibodies to tPA or uPA chemically cross-linked to 59D8, the fibrin-specific antibody discussed previously. A significant enhancement in fibrinolytic activity was demonstrated both in vitro and in vivo with the 59D8-anti-tPA conjugate (Bode et al., 1989) and in vitro with the 59D8-anti-uPA conjugate (Charpie et al., 1990). A conjugate of the anti-tPA Fab‘ and the Fab’ of 59D8 was also as effective as the intact antibody conjugate (Runge et al., 1990). Sakharov et al. (1988) have demonstrated a 10-fold enhancement in plasma clot lysis in vitro with cross-linked antibodies specific for fibrin and uPA. 1. Bispec$c Antibodies Produced by Cell Fusion A more elegant method for producing bispecific antibodies, which avoids the disadvantages of chemical cross-linking, is to use somatic cell fusion to produce bivalent antibodies that possess two different antigen binding sites. This method was first elaborated by Milstein and Cuello in 1983 and has been applied more recently in the design of bifimctional antibodies that bind both tPA and fibrin (Branscomb et al., 1990). IgG is a symmetric molecule possessing two antigen binding domains of the same specificity. Since the component chains of the molecule are assembled after their individual biosynthesis, it is possible to obtain molecules of mixed specificity from cells that synthesize two different antibodies (Suresh et al., 1986). Somatic cell fusion between the hybridoma line se-

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creting antifibrin antibody 59D8 and another hybridoma line secreting anti-tPA antibody TCL8 resulted in a cell line that produced a mixture of antibodies. In addition to the antibodies characteristic of the parental lines and inactive immunoglobulins, an antibody was secreted that was able to bind both tPA and fibrin. This antibody was isolated from mixtures in culture medium or ascites by two steps of affinity chromatography, using tPA as immobilized antigen in the first and a peptide at the N terminus of the fibrin /Ichain [GHRPLDK(C)]in the second. This bispecific antibody bound simultaneously to tPA and fibrin in a solid-phase immunoassay. 2. Functional Properties of Bispecijc Antibodies In addition to binding to the fibrin matrix of a thrombus, an antibody specific for both fibrin and tPA would be expected to bind to tPA in plasma, thereby increasing the concentration of tPA at the surface of the thrombus. This expectation was confirmed by in vitro clot lysis experiments showing that the 59D8-TCL8 bispecific antibody enhanced the potency of tPA 14-fold when added to the assay system before tPA and 22fold when mixed with tPA to form an immunoconjugate before addition to the assay system. When the 59D8-TCL8 bispecific antibody was tested in vivo in the rabbit jugular vein model, a 1.6-fold enhancement in fibrinolytic activity was observed (Branscomb et al., 1990). Kurokawa et al. (1990) have extended this work and produced by cell fusion bispecific antibodies that bind uPA and fibrin and tPA and fibrin. Imura et al. (1992) tested an immunoconjugate of recombinant (r) scuPA and a bifunctional antibody with both scuPA and fibrin specificities in a baboon venous thrombosis model. The immunoconjugate had a fivefold higher thrombolytic potency than unconjugated rscuPA, as a result both of fibrin targeting by the specific idiotype of the antibody and of a slower clearance from the plasma. The production of bihnctional antibodies by somatic cell fusion is severely limited by product yield. Because the method depends on a random assortment of immunoglobulin chains within the fused cell, none of the products are secreted in large amounts. In the future it is likely that bispecific antibodies will be produced as hsion proteins by recombinant DNA methods. C . Antibody-Enzyme Fusion Proteins

The most practical approach to antibody targeting is the creation of a single molecule by recombinant DNA methods that contains both an antigen binding site and a plasminogen activator. In addition to avoiding the difficulties and complexities of chemical cross-linking, it is possible to produce the protein simply and in large quantity by fermentation techniques.

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1. Antijbrin Antibody-tPA Fusion Protein

Building on the pioneering work of Neuberger and co-workers (Neuberger et al., 1984; Williams and Neuberger, 1986) and on experience with cross-linked antibody-enzyme model proteins, Schnee et al. (1987) and Love et al. (1989) used recombinant technology to create a fusion protein with the activities of antifibrin antibody 59D8 and tPA. This fusion protein was assembled by joining the gene coding for the 59D8 immunoglobulin H chain to the gene coding for tPA and transfecting this chimeric construct into a hybridoma cell capable of producing only immunoglobulin L chain. The resulting cell line produced a bifunctional protein with domains for activating plasminogen and for attaching to cross-linked fibrin. a. Cloning Rearranged Immunoglobulin Gene. During somatic development of the B cell, germline V and joining (J) regions are juxtaposed to produce a unique rearranged VJ sequence that codes for the antigen binding site of the H or L chain of the immunoglobulin. Also during this process the H chain incorporates a diversity (D) segment at the J region (Tonegawa, 1983). These rearrangements result in a unique VDJ or VJ exon sequence that codes for the antigen the antibody recognizes. Unfortunately, expression of a particular immunoglobulin chain can occur only after the unique rearrangement has been cloned. For the expression plasmid coding for the 59D8-tPA fusion protein, the VDJ segment of the rearranged H chain of 59D8 was cloned and incorporated. It was unnecessary to clone or otherwise manipulate the L chain gene because the H chain constructs were transfected into cell lines that had lost the ability to express normal H chains but retained the ability to produce L chains. It is possible to obtain H chain VDJ sequences either by cloning complementary DNAs (cDNAs) constructed from the mRNA of the hybridoma or by cloning genomic sequences from high molecular weight DNA derived from the hybridoma; although genomic sequences were used initially, it became apparent later that expression plasmids could be constructed with equal facility by using cDNAs. b. Constructing 59D8-tPA Expression Vector. A previously described immunoglobulin expression vector (pSV2gpt) (Near et al., 1990) was adapted to a cassette format to facilitate expression of recombinant immunoglobulin. The pUC12 polylinker was inserted into the EcoRI-PstI site of pSVPgpt, and an XbaI fragment containing the mouse y2b H chain C region (Tucker et al., 1979) was inserted into the polylinker. The cloned 59D8 rearrangement was inserted with a unique EcoRI site 5’ of the C region, which produced sequence coding for a complete 59D8 H chain. tPA is secreted as a single-chain, 70-kDa protein that is subsequently cleaved by plasmin to form A and B chains attached by a single disulfide

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bond (Harris, 1987; Gething et al., 1988). Each chain contains multiple intrachain disulfide bridges. Because only the catalytic function of the protein was of interest, only the sequence coding for the B chain was used. To construct the 59D8 H chain-tPA fusion protein, the y2b C region 3' of the XhoI site in the hinge region of pSV2gpt was removed and replaced with a tPA B chain cDNA sequence. An SfaNI site in the tPA cDNA was converted to an XhoI site by the addition of a synthetic oligonucleotide adapter (which also added a glycine residue to the fusion product). The cDNA fragment was thus inserted in-frame into the XhoI site in the H chain hinge region, creating a new hybrid exon. No attempt was made to modify the 3' portion of the tPA cDNA, which contained a polyadenylation signal. c. Selecting Loss Variant Cell Lines. To select for H chain loss variant hybridomas, the cells were first grown in soft agarose containing goat antimouse H chain antiserum. Clusters secreting H chain developed halos. Cells without halos were picked and subcloned. d. Transfecting Expression Plasmid. The hybrid H chain construct was transfected by electroporation into the H chain loss variant hybridoma line described in the preceding paragraph. Selection occurred in medium containing xanthine, hypoxanthine, and micophenolic acid. e. Purzj'jing and Analyzing 59D8-tPA Fusion Protein. Protein was purified from the cell supernatants and from ascites by sequential double-affinity chromatography (Bode et al., 1992). One column consisted of the GHRPLDK(C) peptide (used to generate 59D8) linked to Sepharose, and the other of an anti-human tPA monoclonal antibody (TCLS) linked to Sepharose. $ Recombinant Protein Expression Levels. Although the structure and function of the 59D8-tPA recombinant protein were as anticipated, the amount of protein secreted into the cell culture supernatant was only 1% of the amount secreted by the original hybridoma cell line. It became apparent later that protein production could be enhanced greatly by modifying the 3' untranslated region of the mRNA. Love et al. (1993) found that cell lines transfected with constructs in which the 3' untranslated region was coded by plasminogen activator genes produced very low levels of both mRNA and protein (0.008-0.06 pglml) in comparison with the parental 59D8 myeloma cell line (7.6-1 0 pglml). In vitro nuclear runoff analysis indicated that these low steady-state levels of mRNA did not result from a lower rate of transcription of the transfected gene (relative to the rate of transcription of the endogenous H chain gene in the 59D8 parent cells). In contrast, cell lines transfected with expression plasmids in which the 3' untranslated region of the mouse y2b H chain or human P-globin gene had been substituted for the 3' untranslated region of the plasminogen activator gene showed an increase in recombinant protein secretion of 68- to 100-fold.

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2. Antijbrzn Antibody-scuPA Fusion Protein Although the 59D8-tPA fusion protein (Schnee et al., 1987) described previously retained both the fibrin antigen-binding and plasminogenactivating activities of its parents, its inability to lyse plasma clots was disappointing. It eventually became apparent that the tPA catalytic site had been an inappropriate choice-the loss in the construct of the N-terminal portion of the protein prevented the requisite enhancement of catalytic activity on fibrin binding (Love et al., 1994). It was thought that the catalytic site of uPA might function better in a fusion protein because its activity is independent of fibrin binding. The single-chain form, scuPA, was chosen for use because it has the additional advantage of being resistant to inactivation by plasminogen activator inhibitor-1 and a,-antiplasmin. As it travels through plasma, a fusion protein containing scuPA might resist circulating inhibitors and remain incapable of activating circulating plasniinogen until it reaches the plasmin-rich environment of the thrombus, where it would become active through cleavage of the plasmin-susceptible Lys-158-Ile-159 peptide bond (Declerck et al., 1990). Only the Fab part of the antifibrin antibody was included to reduce the mass of the chimeric protein to its essential components. In a similar vein the uPA kringle and growth factor regions were omitted, and the sequence of low molecular weight (32-kDa) scuPA-reported to be as active in fibrinolysis as the intact molecule (Stump et al., 1986)-was used. Although the CH3domain of the antibody H chain had also been included initially as a spacer between the antibody and the plasminogen activator, later experience (S.-Y. Shaw, 1991, unpublished observations) indicated that this was not necessary. The fusion protein contained antibody 59D8 H chain from residues 1 to 351 and, in contiguous peptide sequence, residues 144-41 1 of low molecular weight scuPA (Runge et al., 1991). The 3' untranslated region from P-globin was included for reasons described in Section V,C, 1,f. To assemble a heterodimer that included this fusion protein and an immunoglobulin L chain, the fusion protein expression plasmid was transfected into H chain loss variants. Sodium dodecyl sulfate (SDS) gel electrophoresis, immunoblot analysis, and DNA sequencing showed that the product, 59D8-scuPA(32kDa),was a disulfide-linked 103-kDa heterodimer consisting of an immunoglobulin L chain linked to the fusion protein H chain. The K,,, of 59D8-scuPA(32kDa) was 16.6 p M and that of tcuPA, 9.1 p M . Fibrin binding was also similar in the recombinant protein and its parent. In an in vitro plasma clot assay, 59D8-scuPA(32kDa) was 6 times more potent than scuPA, with considerably diminished fibrinogen degradation and a?-antiplasmin inactivation in the supernatant. In vivo, in the rabbit

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jugular vein model, 59D8-scuPA(32kDa) was 20 times more potent than SCUPA(Fig. 35). It should be noted that some of this enhancement in activity in vivo must in part have been related to a fivefold increase in the half-life of 59D8-scuPA( 32kDa) (in comparison with scuPA) in the rabbit. Runge et al. (1996) have since studied the in viuo activities of 59D8scuPA(32kDa),scuPA, and tPA in a baboon model that allows critical comparison of thrombolytic potency and inhibition of thrombus deposition in relation to both the dose and the plasma concentration of each plasminogen activator. In the lysis of thrombi, 59DS-scuPA(32kDa) was 8-10 times as potent as rtPA and 15-20 times as potent as rscuPA by dose administered and 2.8 times as potent as rtPA and 6.3 times as potent as rscuPA by plasma concentration. This difference in potency (as calculated by the dose administered in comparison with the plasma concentration) can be explained by the observation that in the baboon the plasma half-life was 12 times longer for 59D8-scuPA(32kDa) than for rscuPA. And 59D8-scuPA(32kDa) was 11 times more potent than scuPA in the inhibition of thrombin deposition in an experiment in which pharmacokinetics did not play a role. Of equally great interest is the observation that, at equipotent thrombolytic doses, template bleeding times €or 59D8-scuPA(32kDa) in the baboon were unchanged, whereas those for tPA and scuPA were significantly pro-

40

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scuPA (mg/kg) FIG. 35. Thrombolysis in vivo with scuPA (broken line) and 59D8-scuPA(32kDa) (solid line). Data represent the means of values from between three and eight animals at each point. The 20-fold increase in potency derived for 59D8-scuPA(32kDA) was calculated by comparing the percent lysis curves in plasma clot and rabbitjugular vein assays, which were fit using a two-parameter exponential function (Runge et nl., 1988). [From Runge et al. (1991).]

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longed. Since bleeding time prolongation seems to reflect the risk of clinical hemorrhage (Gimple et al., 1989), it would be of interest to determine whether 59D8-scuPA(32kDa), in addition to being more potent, might also be safer. Holvoet et al. (1991) have further refined this concept by constructing an M,. 57,000 single-chain chimeric plasminogen activator consisting of a 33-kDa fragment of scuPA and an Fv derived from a fibrin-specific antibody directed at a cross-linked epitope of the D dimer. This single-chain molecule was expressed by baculovirus-infected cells of the insect Spodoptera frugiperda. The recombinant molecule showed high affinity for binding the fibrin D dimer fragment (essentially identical to that of the parent antibody molecule) and a very similar Michaelis-Menten constant for activating plasminogen. When tested in the lysis of a plasma clot in v i m , the recombinant single-chain molecule was 13 times more potent than low molecular weight scuPA. In the hamster pulmonary embolism model, the thrombolytic potency of the fusion protein was 23-fold greater than that of rscuPA. In rabbits with a jugular vein clot prepared from human plasma, the thrombolytic potency of the antibody-targeted fusion protein was 11fold higher than that of rscuPA. And in baboons with an autologous wholeblood clot in the femoral vein the chimera showed a fivefold higher thrombolytic potency than scuPA (Dewerchin et al., 1992). Vandamme et al. (1992) subsequently constructed a humanized version of the sFv contained in this fusion protein. Its properties were very similar to those of the molecule containing the murine Fv. Holvoet et al. (1992) then showed that the increased fibrinolytic potency of this fusion protein was due both to targeting of the plasminogen activator to the clot via the sFv segment (a sixfold increase) and to a more efficient conversion of the single-chain urokinase segment to its two-chain derivative (an eightfold increase). In a further examination of the relation of clearance rates to thrombolytic potency, Holvoet et al. (1993a,b) examined the recombinant single-chain molecule in a glycosylated and in a nonglycosylated form by substituting a Glu residue for Asn-88 to abolish the glycosylation signal. The nonglycosylated form showed a fourfold slower clearance in the hamster but less efficient targeting. Overall potency of the two forms was similar, however, in that prolonged clearance compensated for lower specific activity. Thus, the thrombolytic potency of a chimeric antibody-targeted plasminogen activator can be increased by increasing its specific thrombolytic activity, reducing its rate of clearance, or both. Yang et al. (1994) described a fusion protein that contained a fibrinspecific antigen combining site and a modified scuPA catalytic domain. The design of this molecule was based on the observation that a high concentration of thrombin is present in the vicinity of an intravascular thrombus. Although thrombin is capable of cleaving and inactivating native

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scuPA, the urokinase-derived catalytic segment contained in this fusion protein was modified by site-directed mutagenesis so that the peptide bond normally cleaved by plasmin to activate urokinase would then be cleaved by thrombin. Thus, selective thrombin cleavage in a molecule targeted to fibrin would initiate clot lysis following thrombin activation. The specific change made to the urokinase domain was the deletion of Phe-157 and Lys-158. According to its design, then, the modified 59D8scuPA (59D8-scuPA-T) was activated by thrombin but not by plasmin, whereas the fusion protein just discussed, 59D8-scuPA(32kDa), was activated by plasmin but not by thrombin. When activated by thrombin, 59D8-scuPA-T converted plasminogen to plasmin. In vitro plasma clot lysis assays showed that 59D8-scuPA-T lysed clots that resulted from the action of thrombin and that heparin and hirudin could prevent clot lysis. When incorporated as part of a thrombin-induced clot, 59D8-scuPA-T was able to lyse the clot; 59D8-scuPA(32kDa) and high molecular weight scuPA were ineffective. These results suggested that this thrombin-activatable form of 59D8-scuPA has the potential to selectively lyse fresh clots (which are thrombin-rich) more effectively than old clots (which generally do not contain so much thrombin). A clinical event (such as a coronary or cerebral artery occlusion) requiring thrombolysis usually presents acutely and is the consequence of a very recent thrombus. The therapeutic aim is to dissolve that thrombus but not disturb older thrombi that might be beneficially preventing undesirable hemorrhage (at the site of a peptic ulcer, for example). Targetability engendered by a high local thrombin concentration in recent thrombi may well be the key to an important increase in specificity. Fibrin is but one of the epitopes contained within a thrombus that may be a potential target for the development of antibody-plasminogen activator fusion proteins. Other candidates include epitopes on platelets (Bode et al., 1991; Dewerchin et al., 1991) and fibrin-linked az antiplasmin (Reed et al., 1990). Bode et al. (1994) synthesized a bifunctional molecule that incorporates an antifibrin antibody and the thrombin inhibitor hirudin. The intent was to inhibit further fibrin deposition at sites of thrombosis while avoiding systemic anticoagulation. In vitro observations demonstrated a sixfold reduction of fibrin deposition on a clot suspended in plasma in the presence of the antibody-hirudin conjugate in comparison with equimolar concentrations of hirudin. The construction of a fusion protein based on this principle is in progress. D. Targeted Prodrug Activation

Often a drug that might be useful in therapy is too toxic to be administered systemically. A means of targeting such a toxin to a lesion would

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accrue two advantages: the localized concentration of the drug would be sufficient to render it effective, and its systemic concentration would be below toxic limits. Particularly cogent applications of targeted toxins or chemotherapeutic drugs are found in cancer chemotherapy, where agents potent in killing tumor cells are also highly toxic to normal cells-especially in tissues characterized by high proliferative rates such as the bone marrow or gastrointestinal epithelium. Antibodies selective for epitopes on tumor cell membranes have been used to target toxins directly to tumor cells, but an application more consistent with the thrust of this article is the targeting of enzymes that cleave inactive (and thereby nontoxic) prodrugs into active cytotoxic agents. Since the antibody concentrates the enzyme at the site of the tumor, the conversion of prodrug to active drug occurs preferentially at this site, thereby sparing normal tissue from a high concentration of the cytotoxic agent. A general strategy envisions the administration of an antibodyenzyme conjugate systemically.After enough time has elapsed for the conjugate to bind to antigens on the tumor cell and, most importantly, to clear from nontarget tissues and thereby avoid systemic toxicity, a prodrug is administered that is catalytically converted to an active antitumor agent by the antibody-targeted enzyme bound only to the tumor cells (Hellstrom and Senter, 1991). A singular advantage of this method not shared by the use of toxins directly targeted to tumor cells is that if not all tumor cells in a mass possess the antigen for which the monoclonal antibody is selective, it should still be possible to attain a cytotoxic concentration of active drug in the vicinity of these cells. One of its disadvantages is that substances of high molecular weight, such as antibodies, do not diffuse readily into the relatively avascular interior of a tumor. However, because the active antitumor agent released from the prodrug is of low molecular weight, it should diffuse readily from the vascular region (where it would be catalyzed by the antibody-enzyme fusion protein) to the avascular interior of the tumor. Choosing the appropriate enzyme is critical to the success of antibodytargeted prodrug activation. While it would be desirable to use human enzymes because of their lack of immunogenicity, poor selectivity may rule against their use. For example, Senter et al. (1988, 1989) used human alkaline phosphatase linked to a cancer-selective antibody to activate etoposide phosphate at the tumor surface. However, endogenous alkaline phosphatase-in addition to the antibody-linked enzyme-also activated the etoposide phosphate, thereby significantly reducing the specificity of the method. Although nonmammalian enzymes are likely to be immunogenic, they possess the potential of interacting with substrates that are resistant to all mammalian enzymes, thus affording a very high degree of

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selectivity to the enzyme-substrate interaction (Kerr et al., 1990; Senter et al., 1991; Springer et al., 1991; Bignami et al., 1992; Svensson et al., 1992). Antibody-enzyme fusion proteins for prodrug targeting have been produced by recombinant methods analogous to those described previously for antibody-targeted plasminogen activators. In general, it is possible to preserve the activity of both the enzyme and the antigen binding site, as well as to humanize the nonmammalian enzyme to diminish problems with immunogenicity (Bosslet et al., 1992). The success of antibody-targeted prodrug activation will ultimately depend on the stability of the drug in vivo, the difference in cytotoxicity between the prodrug and the drug, the pharmacokinetics of the prodrug, the tumor selectivity of the antibody, the turnover rate of the enzyme, the retention of the conjugate at the tumor site in contrast with that at normal tissues, the presence of an endogenous enzyme that can activate the prodrug, and the potential immunogenicity of the antibody-enzyme complex (Hellstrom and Senter, 1991). E. Outlook

Advances in the production of fully human antibodies in mice (Lonberg ei al., 1994; Green et al., 1994) coupled with significant advances in our ability to reengineer the specificity of enzymes will now permit the construction of antibody-enzyme fusion proteins that are likely to be minimally, if at all, immunogenic. Although only two important therapeutic applications for these antibody-targeted drugs have been described, some reflection will suggest that the ability to deliver a specific enzymatic activity to a particular site in vivo should have a very broad application in medicine.

ACKNOWLEDGMENTS J. S. Huston’s work was supported by a National Cancer Institute SBIR grant (CA39870) and a National Cooperative Drug Discovery Group award ( U 0 1 CA51880). M. N. Margolies was supported by National Institutes of Health grants RO1 CA24432 and R 0 1 HL47415. E. Haber was supported by a grant from Bristol-Myers Squibb.

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. . . . . . . . . . . . . . 451

B. TargetArea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

.............. F. Cis-Acting DNA Elements for Recruiting Mutat

A. Selection of Mutate

ences . . . . . . .

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VI. Structural and Evolutionary Implications . . . .

B. Complementarity between Ger References . . . . . . . . . . . . . . . . . . .

I. INTRODUCTION

Specific biological interactions generally arise over evolutionary time as a result of optimization of the molecular recognition by a protein or a nucleic acid of a small or large molecular species. Enzymes recognizing one substrate and receptors recognizing one ligand are examples of such one-to-one relationships. Antigen-antibody interactions are prime examples of molecular recognition, but the evolutionary processes involved are fundamentally different. This is because animals have evolved a strategy such that all individuals learn to recognize the unknown. Learning molecular recognition is much more than recognition by chance; however, it starts that way. Indeed, the word learning is meant to imply a process of improvement of affinity (affinity maturation). Initial recognition by chance is achieved by the presence of a large number of alternative potential ADVANCL5 IN PROTEIN CHEMISTRY, Vol. 49

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antibodies. This initial recognition need not be highly specific or of high affinity. Indeed, affinity of interaction and specificity of antibodies are in the vast majority of cases two sides of the same coin.’ The concept that such a learning process is one of the fundamental properties of the immune system has been controversial over the years. The first theoretical model of the origin of antibodies, proposed by Ehrlich at the beginning of this century, did not even consider antibodies as molecules intended to recognize foreign invaders. “That [antitoxins] are in function specially designed to seize on toxins cannot be for one moment entertained. It would not be reasonable to suppose that there were present in the organism many hundred of atom groups destined to unite with toxins , . .” (Ehrlich, 1900). For him, these “toxophile protoplasmic groups in reality serve normal functions reproduced in excess during regeneration and therefore pushed off from the protoplasm thus coming to exist in the free state.” The fact that animals could learn chemical recognition was too far-fetched for Ehrlich and indeed beyond the comprehension of most biologists of the first half of the twentieth century. Even the chemical nature of antibodies was for a long time controversial. Marrack (1954) reminded us that “as late as in the 1929 edition of Wells’ book The Chemical Aspects of Immunity we find ‘We do not know whether (antibodies) are specific molecular aggregates or merely physical forces dependent on altered surface energy of the same substances present in the blood before the process of immunization was begun.”’ It was only after the role of proteins was understood that the reality of the antibody puzzle started to emerge. That the quality of the antibody response improved over multiple immunizations and that this improvement was not merely a matter of quantity of antibody but also of its “avidity” was strongly supported by Jerne (1951). The attraction of the learning process is clearly manifested in the early (instructive) theories of the origin of antibodies whereby the antigen was proposed to function as a template directing the final shape of the combining site of the specific antibody (e.g., Pauling, 1940). Perhaps that is why instructive theories remained popular for a long time, although they were based on misguided assumptions and inaccurate predictions (Haber, 1964).*That the real meaning of the learning process is basically

*

High and low affinities are relative terms. A typical primary response antihapten antior lo-’ moliliter is low relative to the body with dissociation constants in the order of commonly obtained following hyperimmunization. However, such values may not be considered sufliciently high for classical radioimmunoassays or for some therapeutic uses. The hypothesis, however, seems to contain a grain of truth. The analysis of complex antibody-hapten binding kinetics supports the view that the antibody is not a single threedimensional structure in solution hut exists as two or more forms in dynamic equilibrium. Only one of the forms recognizes the hapten in a burst reaction, while a second, slower,

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Darwinian became apparent when the clonal selection theory was formulated by Burnet (1959) and when antibodies were recognized as proteins with diverse amino acid sequences. It used to be said that if one could explain the genetic origin of the diversity of, say, 1 million antibody structures, the mystery of antibodies would be solved. So perhaps the whole antibody repertoire was encoded in the germline, and the problem to be solved was only one of different expression of specific proteins [the discovery of constant and variable regions (Hilschmann and Craig, 1965) was a separate, though related issue]. Such hypotheses did not imply learning but simply selection of what was imprinted in the genome (Szilard, 1960). After all, “lo5 [light chain] genes would occupy less than 1% of the human genome . . . ,” according to Dreyer et al. (1967). For these authors, “the maturation of the immune system is considered to be aprecisely controlled process [our emphasis] which results in a large number of highly differentiated cells, each committed to the production of a single [antibody]. During prolonged exposure to an antigen there should be progressive shift toward a cell population which produces more tightly binding antibodies.” On the other hand, theories based on somatic diversification implicitly contained as a corollary a glimpse of the learning process: “The diversity of the precursors of antibody forming cells arises from a high rate of spontaneous mutation during their long life proliferation” (Lederberg, 1959). “The result of the specific contact of antigenic determinant and immunocyte may be either destructive or stimulating . . . .” Its fate would be determined by “its degree of maturity, the local internal environment and the presence of drugs or somatic mutations” (Burnet, 1967). While the concept of a Darwinian improvement of antibody affinity was attractive, it was not easy to accept because it was felt (correctly as it turned out) that such a process could not explain the efficiency of the response of young animals. Surely there was not enough time for a newborn to accumulate enough mutations and immunological experience to select the suitable mutants.3 The controversy generated by the genetic origin of antibody diversity dominated the minds of scientists for two decades. The innumerable arguments and counterarguments were a great incentive for what otherwise would have been a rather boring but necessarily extensive protein sequencing exercise. In the event, precise understanding of the genetic origin of reaction reflects conversion of the antibody structure to the more reactive form. It is conceivable that the alternative antibody structures could interact with alternative antigens (Foote and Milstein, 1994). However, the possibility that somatic hypermutation is involved in the generation of the primary repertoire in sheep has been proposed by Reynaud et al., 1991. They observed that ileal Peyer’s patches have histological properties resembling those of the bursa of Fabricius of chickens but that diversity is not created by gene conversion but by somatic hypermutation.

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AND MICHAEL

s. NEUBERGER

antibody diversity was spearheaded by the dramatic advances in DNA technology in the 1970s. Somatic events were indeed dominant generators of diversity, and somatic rearrangements alone were capable of generating innumerable numbers of variants. The question of whether there was indeed a learning process remained open. The actors in the antibody diversity story were cast (a restricted number of germline gene segments, combinatorially rearranged with junctional diversity plus somatic mutations of unknown significance) and it was time to return to the plot. “In other words, how, in real life in the animal, do all those genetic events capable of producing antibody diversity actually operate in response to an antigenic stimulus” (Milstein, 1985). The hybridoma technology, permitting dissection of the immune response, and the development of fast methods of mRNA analysis were the tools that spearheaded analysis of the problem (Hamlyn et al., 1981; Kaartinen et al., 1983). The basic rules of the learning process became established: The primary diversity (which in mice and humans was derived by combinatorial assortment of gene fragments) provided the virgin, nonantigen-induced source of variants. The motor of the affinity maturation was hypermutation and Darwinian selection of improved variants. 11. GENETIC AND STRUCTURAL DIVERSITY OF PRIMARY REPERTOIRE

A. Organization of Antibody Genes The naive antibody repertoire is derived by combinatorial assortment of light and heavy chains. This is, however, not universal since antibodies made only of heavy chains have been found in camels (Hamers et al., 1993).The variable regions of light ( K and A) and heavy chains are formed by the assembly ofV and J and V, D, and J gene fragments, respectively. V, D, and J fragments occur in multiple nonidentical copies. The number and organization of the gene fragments in each locus varies considerably, not only among different species but also within a species. Such diversity reflects the dynamic nature of the evolution of immunoglobulin genes, fueled by a process of genomic expansion and contraction of their components (Milstein and Pink, 1970). The complex and variable nature of the organization of the antibody gene loci in different species has been rationalized into three basic scenarios (Litman et al., 1993). In many instances, there is combinatorial joining between a substantial number of V genes which occur in tandem, followed by a cluster of D segments (in the heavy but not in the light chain loci) and then a cluster of J segments joined to the C region segment(s). This “extended” configuration is exemplified by the heavy and kappa (K) chains of mice and humans (Ichihara et al., 1989; Zachau, 1989a). On the

MATURATION OF T H E IMMUNE RESPONSE

455

other hand, the mouse lambda chain locus contains only three V segments which occur in two recombination units: VA~-VAX-JA~-CZ~-YJA~-YCZ~ and VAl -JA3-c23-JA l-CZ 1. In such a clustered configuration, joining is largely restricted to fragments within the same recombination unit (Eisen and Redly, 1985; Boudinot et al., 1994). The single-gene configuration is radically different and is exemplified by the heavy and light chains of chickens. Although there is a multiplicity of V genes, the rearrangement involves exclusively or almost exclusively only one of them. The diversity of the naive repertoire is derived by gene conversion utilizing the other V genes (Reynaud et al., 1987). A similar situation is found in rabbit heavy chains, where gene conversion again seems to play a major role in diversification of the antibody repertoire (reviewed by Knight and Crane, 1994). In the case of rabbits, the preferentially rearranged gene is called VH1, and there is a mutant rabbit, Alicia, in which the VH1 gene is missing (Kelus and Weiss, 1986). In this case, predominant expression is switched to other genes called VH4-and VHl-like (Chen et al., 1993). The difference between the single-gene and the extended gene configuration is therefore not in the genetic arrangement per se but in the extensive use of gene conversion as a process of diversification. The very extensive studies in mice and humans have not revealed positive evidence for somatic gene conversion events. On the contrary, in some cases there is convincing evidence that somatic gene conversion does not contribute significantly (if at all) to the diversity of the naive or of the memory repertoire (Wysocki and Gefter, 1989;Wysocki et al., 1990; Milstein et al., 1992; Gonzilez-Fernindez and Milstein, 1993; Ford et al., 1994). It is relevant that birds have a special organ, the bursa of Fabricius where gene conversion takes place. Mammals do not have such organs but have a gut-associated lymphoid tissue (GALT) which shows histological similarities to the bursa. The suggestion has been made that in the rabbit gene conversion occurs in the appendix (Knight and Crane, 1994; Pospisil et al., 1995). For all these reasons, and because investigations of the events leading to maturation of the antibody response have been so far mainly concerned with mouse and more recently with human responses, we will concentrate on these two species. B. Somatic Diversijkation of Germline

V(D)J joining gives rise to the antigen receptor and constitutes the primary source of the diversity of the naive repertoire of mice and humans. In birds, the joining diversity is highly restricted and gene conversion during embryogenesis is the main source of the complexity of the naive repertoire. Whether somatic point mutations play a major role in development of the naive repertoire in chickens is not so clear. In mice and humans, this

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CESAR MILSTEIN AND MICHAEL S. NEUBERGEK

does not seem to be the case since the vast majority of the rearranged V segments found in circulating B cells and in peripheral naive B cells (more precisely IgM+ IgD+) are unmutated germline sequences (Milstein et al., 1992; Schittek and Rajewsky, 1992). Furthermore, at very early stages after immunization, the stimulated B cells largely express unmutated sequences (Griffiths et al., 1984; Manser et al., 1987; Levy et al., 1989; Weiss et al., 1992). It has been suggested that in sheep, the extensive somatic point mutations that accumulate after birth in ileal Peyer’s patches B cells are major contributors to the naive primary repertoire (Reynaudet al., 1991). In the rabbit, the appendix has properties resembling those of both the bursa of chickens and the ileal Peyer’s patches of sheep. Both gene conversion and hypermutation operate in that organ, which does not involute (as is the case for the bursa) in older animals (Weinstein et al., 1994). It remains to be seen to what extent this process is antigen-independent and contributes to peripheral or local responses. In the mouse, Peyer’s patches B cells largely express unmutated sequences at birth, which slowly accumulate point mutations to reach a plateau in adult life, and this is thought to be due to stimulation by environmental antigens (Gonziilez-Ferniindezet al., 1994a). The genetic bases of the diversity of the naive repertoire have important implications for the nature of the chemical diversity of the antibody combining sites. Both light and heavy chains contain three complementaritydetermining regions (CDRs)which are anchored to a common rigid framework (FW) and determine antibody specificity (Fig. 1). This is demon-

Antibody

L1 32

32

2

26

1

26

29 Ile

Leu

3

2

L3 95 Pro 95 Pro 97

1

97

3

2 VH

H2

1

2

3

4

FIG. 1. Canonical configurations of CDRs. The antigen binding site of antibodies consists of six polypeptide loops of variable shapes and sizes. (A). The loops occur in a small number of canonical configurations for CDRl and CDR2 in both heavy and light chains, and most of them are illustrated in (B). (Reproduced with permission from Chothia et al., 1989. Nature 342, 877-883. 0 1989 Macmillan Magazines Ltd.) Differences between amino acids that are not critical to the definition of canonical structures may play a major role in affinity maturation either by altering the exposed surface or by introducing minor shifts in the orientation of the loops. In the case of CDR3, the number of configurations is too large to fit all of them into a simplified picture. However, in the case of human K light chains, five canonical configurations have been defined that account for 70% of the available information (Tomlinson et al., 1995).

458

CESAR MILSTEIN AND MICHAEL S. NEUBERGER

strated by the success of CDR grafting, which involves the exchange of CDR coding fragments between one antibody gene (e.g., of mouse origin) and the framework of another (e.g., of human origin) Uones et al., 1986). Such exchanges often involve some loss of binding energy, which is generally recovered by judicious changes in well-chosen F W residues. Thus, even though the basic rigid frames are to a considerable extent interchangeable, the affinity for antigen can be quantitatively affected by amino acid substitutions well removed from the combining site. In spite of the multiplicity of V genes, there is a large degree of structural similarity between them. With the exception of the CDR3 of the heavy chains, the folding patterns of the CDRs adopt a restricted number of canonical structures, many of them defined by crystallographic analysis (e.g., Fig. 1) (Chothia et al., 1992). Canonical forms do not occur in all combinations. For instance, in human heavy chains there are three CDRl and six CDR2 canonical structures. Of the 18 potential combinatorial forms, only 8 are found in the germline. Identical canonical backbones differ among V genes in the nature and orientation of the side chains of critical amino acid residues and such differences ultimately define the final molecular shape of the combining site. V genes that do not necessarily share canonical structures but which display a higher degree of sequence identity than the average, are grouped into families. The members of the largest V gene families that share the same canonical structure seem to diverge in the coding sequences more markedly in the CDR2 than in the CDR1, a point to which we will return in Section VI. The high diversity of CDR3 is due not only to recombination of multiple V(D)J fragments but also to the flexibility of the recombination event. The mechanism of V(D)J recombination has been the subject of intensive research (reviewed by Lewis, 1994), but we need to be concerned only with the sequence variability generated. The first level of such variability is the imprecision of the point at which the germline fragments are joined. This can give rise to two or three (sometimes more) amino acids in the same coding residue. During joining, a variable number of bases from a point defined by the joining (heptamer) motif are deleted. While this gives rise to longer or shorter amino acid sequences, it also implies a high probability of frame shift. Consequently many of the joining events are “nonproductive” but are retained in the chromosome if the other chromosome (or the other locus in the case of light chains) is “productively”rearranged. Such distinctions between productive and nonproductive rearrangements are valuable to differentiate between genes that are subjected to antigen selection and those that are not.4 Another level of diversity is provided by the Out-of-frame rearrangements produce a peptide with an altered amino acid sequence in the C region and premature chain termination. Such truncated chains containing intact V segments are potential competitors of normal chains. However, it seems that there is a

459

MATURATION OF THE IMMUNE RESPONSE

Antigen + accessory cells

0-0 Progenitor cell

Pre-B cell Memory cells

Combinatorial and junctional diversity

Hypermutation

FIG. 2. B-cell differentiation.

addition of P (for palindromic) residues, which although not so common are important in describing the mechanism ofjoining (Lafaille et al., 1989). P residues are short, inverted repeats of the untrimmed ends to be joined. Other levels of diversification are almost exclusively applicable to the heavy chain locus. The most important is the addition of extra bases (N) to V(D)Jjoining boundaries. N regions are usually G/C-rich and can be quite long (up to about 15 residues). Their creation is associated with the enzyme terminal deoxynucleotide transferase which is expressed at the pre-B-cell stage when heavy chain gene fragments are joined but no longer found at later stages when the joining of light chain genes takes place (Fig. 2). Hence there is an infrequent occurrence of N residues in light chains (Victor et al., 1994). In addition, D genes can be recombined in an inverted form (Tuaillon et al., 1994). Furthermore, there are D-gene segments containing signal sequences designed to produce nonstandard V(D)J joints (Ichihara et al., 1988). Not all the potential variants are expressed since, for example, certain heavy and light chain combinations or the structures arising as a consequence of joining diversity are incompatible with final folding. However, this is only a fraction of the total and it is likely that in mice and humans, 10" molecular species represent an underestimate of the potential diversity of nuclear mechanism that regulates RNA metabolism and downregulates the level of the prematurely terminated mRNA species and hence of the truncated chains (Lozano et d.,1994; Carter et al., 1995).

460

CESAR MILSTEIN AND MICHAEL S. NEUBERGER

the naive repertoire. Furthermore, a single primary sequence does not necessarily imply a single three-dimensional structure. On the contrary, it has been suggested that antibodies exist in two or more forms which are in equilibrium, each with potentially different binding properties (Foote and Milstein, 1994). However, such huge numbers disguise a simpler picture (Table I). The largest contribution to the diversity of the naive repertoire is restricted to the CDRS segment. When this segment is excluded, the repertoire is restricted to the combinatorial number of functional V genes in light and heavy chains. This number is about 5 x lo3in humans [about 50 each for K a n d l light chains (Zachau, 1993; Williams and Winter, 1993) and about 50 for heavy chains (Matsuda et al., 1990; Cook et al., 1994)] and a similar order of magnitude in mice. Thus, a more realistic picture of the potential naive diversity revolves around a basic repertoire of part of the combining site defined by the four CDR loops included in the V segments (CDR1 and CDR2 of heavy and light chains) which is hrther diversified by a huge variety of shapes and sizes in the other two CDR3 loops. The basic repertoire, although large, is considerably smaller than the lymphocyte population expressing it (in the order of lo7 clonotypes in mice) while the super-

TABLE I

Potential Diversity

of Human Naive Repertoirea Diversity of CDRS

Parameter

Diversity of CDRl and CDR2

V germline genes

- 100 (V, + VA)x 5 0 ( V ~ )=

Light chain -

5 x lo3 (restricted to < 8 x 15 = 120 canonical combinations)

Combinatorial Boundary diversity Total Grand total

Heavy chain

SOV, x 45, 4J2 x3

-

+ 50Vn x

5 0 V ~X ~ J XH20D

x6VDx6DJ=2x105 x > 50 (N segments) 1 x 103 -1 x lo7 Light x heavy 1Olo

-

a Diversity in CDR3 and the other CDRs differs greatly. In reality the expressed repertoire is much smaller than the potential repertoire because the calculations do not take into consideration forbidden combinations and the restricted repertoire expression. On the other hand, there is an unknown contribution of other sources of diversity like unconventional rearrangements and conformational isomerism.

MATURATION OF THE IMMUNE RESPONSE

46 1

imposed diversity of CDR3 loops is orders of magnitude larger. The potential repertoire as calculated takes no account of the frequency distribution of the components. This is not random for a variety of reasons. For instance, there is evidence that V and D genes most proximal to J segments are preferentially expressed (Yancopoulos et al., 1984; Schroeder and Wang, 1990) and that such preferences are at least in part antigen-independent (Tuaillon et al., 1994). Furthermore, the joining of some V gene fragments may be biased toward certain J segments (Milstein et al., 1992). More generally speaking, it is possible that the combinatorial joining efficiency of the fragments is sequence-dependent and that not all V regions are equally efficiently recombined. In addition, there is a bias in the number of residues removed duringjoining; e.g., large deletions or no deletions with or without P residues are less likely. The addition of N residues is biased by the specificity of terminal transferase. In summary, while unusual joining events can occur, their frequency could be quite low. Even so, if present in the naive repertoire at the right time, they could become dominant components of specific immune responses of individual animals.

111. AVAILABLE REPERTOIRE AND ONSET OF IMMUNE RESPONSE In response to a primary antigenic stimulus, B cells proliferate and differentiate. Some interact with stimulated T cells to give rise to T celldependent responses, to affinity maturation, and to memory. Minity maturation is primarily dependent on mutations in the antibody genes and selection of those that express improved antigen binding properties. Selected cells give rise to terminally differentiated plasma cells, actively secreting antibody, and to memory cells. B cells originate in the bone marrow where they are continuously generated to express the primary repertoire. It is estimated that a mouse produces up to 2 x lo7 B cells per day (Freitas and Rocha, 1993; Osmond, 1993). However, unless rescued by antigen or other factors, these B cells are short-lived and within a few days (average life span of 3-4 days) the large majority die, although some are recruited into a circulating population with a much longer life span (weeks rather than days). The population of recirculating follicular B cells represents a considerable fraction of the splenic “virgin” B cells even though it is possible that it has been selected by tolerance and by environmental factors (MacLennan and Chan, 1993). These cells (which express surface IgM and IgD, Fig. 2) constitute the main components of the available repertoire that give rise to the primary response to a newly injected antigen. It is true that memory B cells (which do not express IgD) are also components of the available repertoire. How-

462

CkSAR MILSTEIN AND MICHAEL S. NEUBERCER

ever, such cells, if somatically mutated, do not seem to participate in primary responses, probably because they have been selected to recognize a single antigen with high affinity. The primary response relies on chance recognition of the antigen by elements of the available repertoire. This simple statement, however, has complex implications. The mechanism of B-cell activation is not fully understood, but it is generally thought to involve internalization of the antigen recognized by the B-cell receptor, followed by intracellular degradation and presentation to T cells of derived peptides attached to class I1 MHC molecules. The receptor-antigen complex must quickly become stabilized or initiate an irreversible cascade since off-rates in those cases are mostly >1 sec-'. Recognition implies a minimum affinity of binding of ligand and receptor. Affinities on the order of 1O5 mol-' seem adequate for triggering since hybridomas of such affinity have been isolated (Makela and Kaartinen, 1988). However, it is possible that even lower values could be sufficient to initiate a response. The lower the affinity required, the smaller the need for a highly diverse repertoire. That very low affinity is indeed sufficient is strongly supported by the ability of mice carrying transgenic miniloci containing a very limited number of VH human genes to produce hybridomas expressing human antibody. Such transgenic animals are very restricted in generation of the diversity of the primary repertoire, and very few of the canonical structures can be represented (Wagner et al., 1994; Taylor et al., 1994). Once the process starts, increases in affinity are achieved by affinity maturation. On the other hand, the higher the complexity of the available repertoire, the higher the diversity and affinity of the initial humoral response. This initial response is critical to an animal confronted with a new infection. Antigen is presumably partitioned between clones depending on the affinity of recognition. When free antigen is in excess, a range of affinities are likely to be involved and, to some extent, the frequency at which identical hybridomas are derived from the primary response correlates with the affinity of their antibodies (Makela and Kaartinen, 1988). However, other factors must be taken into consideration. An important one seems to be the frequency with which the individual genetic rearrangements recognizing antigen occur in the naive repertoire (Berek and Milstein, 1988). Furthermore, affinity may not be the only consideration since kinetic parameters may also play an important role (Foote and Milstein, 1991).The dominance of certain immune responses (idiotypic responses) to a variety of antigens, particularly simple antigens like the hapten 2-phenyloxazolone, has been explained by a combination of factors like affinity and frequency (Milstein et al., 1992).

MATURATION OF T H E IMMUNE RESPONSE

463

Broadly speaking, there are two types of primary responses, T celldependent and T cell-independent responses. Only the former can give rise to maturation and memory. These events are closely linked to the development of germinal centers, which follows initiation of the primary T cell-dependent responses. In rodents, the proliferation of B cells is first detectable in certain areas of lymphoid organs rich in T cells called periarteriolar lymphoid sheaths (PALS), where they further differentiate into plasma cells (Jacob et al., 1991a). These secrete the IgM antibodies characteristic of the primary response. In parallel to these events, germinal centers become organized, and it is there that B cells further proliferate and differentiate eventually to emerge as memory cells. It is likely that the two proliferating B-cell populations derive from the same precursor (Jacob and Kelsoe, 1992), but this may be an oversimplification of a more complex pattern (Berek and Ziegner, 1993; Berek, 1993). The development of B cells following antigenic stimulation is characterized by two critical structural changes, class switch and somatic mutation, and both seem to take place in the environment of the germinal center. The heavy chain V(D)J segment is initially expressed in two forms, IgM and IgD, and during development of the primary response they switch off the expression of IgD (Fig. 2). Germinal center cells are therefore IgD-, and while some retain the IgM phenotype, the majority switch by a process of DNA rearrangement to express IgG or other classes. The precise timing and the compartment(s) in which the switch takes place are uncertain, and while switching and mutation could somehow overlap, they are independent events. Indeed, IgG unmutated sequences are commonly observed in the early stages of antigen-induced B-cell proliferation (Kaartinen et al., 1983; Cumano and Rajewsky, 1985; Wysocki et al., 1986) and, conversely, mutated IgM antibodies are detectable in late primary or secondary responses (Griffiths et al., 1984). There is now good evidence that hypermutation takes place during the development of B cells in the environment of the germinal center (Berek et al., 1991;Jacob et al., 1991b;Jacob and Kelsoe, 1992; GonzBlez-FernBndez and Milstein, 1993). In the dark zone of germinal centers, primary blast B cells proliferate to become centroblasts. This has been proposed to be the stage when hypermutation takes place (MacLennan et al., 1992). Centroblasts then migrate to the light zone where they become centrocytes which come into intimate contact with antigen attached to follicular dendritic cells (Klaus et al., 1980). It is thought that centrocytes are destined to die by apoptosis unless rescued by antigen (Liu et al., 1989; Pulendran et al., 1995; Shokat and Goodnow, 1995). This is therefore the stage when selection for improved binding properties takes place.

464

CESAR MILSTEIN AND MICHAEL

s. NEUBERGER

n/.. HYPERMUTATION

A . General Characteristics The nature of the mutations occurring in the immunoglobulin V genes during affinity maturation have been analyzed for various antigen-specific responses. Typically, mutated V genes contain up to 24 amino acid substitutions within the coding part of the V, with the extent of mutation broadly increasing as the response matures. Information about the nature and distribution of mutations has also come from the analysis of immunoglobulin genes of unknown antigen specificity where the V gene sequences have been obtained from hybridomas or primary tissue (e.g., germinal centers) by use of the polymerase chain reaction (PCR). The identification of somatic mutations is achieved by comparing the sequence of the expressed V gene with that of its identified (or presumed) germline progenitor. Two developments have greatly assisted the task of identifying V region somatic mutants: One is the improved characterization of mouse and human immunoglobulin V gene loci; the other is the development of immunoglobulin transgenic mice. Here we summarize many of the features of hypermutation that have been deduced from the sequence analysis of mutated V genes.

B. Target Area Hypermutation is targeted to the region near the rearranged immunoglobulin V gene itself, with the constant regions and unrearranged V genes usually being left untouched (Fig. 3). However, in the case of the mouse I locus, occasional mutations have been described in the constant region (Motoyamaet al., 199l), although this may simply reflect that in the mouse I locus the C region is closer to the J cluster than is the case with the other immunoglobulin loci. The region encompassing the bulk of the mutations (the hypermutation domain) has been examined in mouse heavy chain (Gearhart and Bogenhagen, 1983; Both et al., 1990; Rogerson, 1994); K light (Weber et al., 1991a,b; Rothenfluh et al., 1993; Steele et al., 1992; Rada et al., 1994; Rogerson, 1994); and I chain loci (Motoyama et al., 1991; Gonzdez-Fernhndez et al., 1994b). Although occasional mutations have been described upstream of the promoter, they are rare and the mutation domain essentially starts downstream of the promoter of the rearranged V gene. The domain extends well into the JC intron ending, at least in the case of the mouse K locus, around the intron enhancer-matrix attachment region (EVMAR) (Both et al., 1990; Weber et al., 1991a,b; Motoyama, 1991, 1994; Gearhart and Bogenhagen, 1983; Steele et al.,

465

MATURATION OF T H E IMMUNE RESPONSE

Where somatic hypermutation occurs r)

L VJ

C

Cis controlling elements

r,

L VJ

C

Required

Can be delered =Can

be substituted

0Untested FIG 3. The hypermutation boundaries and the cis elements controlling the process.

1992; Rothenfluh, 1993; Rogerson, 1994). Thus, the mutation domain extends over about 2 kb. It should not be thought that mutation simply peaks within the V with a tailing off to either side. First, the border at the 5'-end is relatively sharp (Rada et al., 1994; Rogerson, 1994), and second, some sequences located in the JC intron well 3' of the V gene are often more heavily mutated than parts of the V gene itself (GonzGlez-Fernhdez et al., 199413). It is tempting to speculate that it is the site of the transcription promoter that determines the 5' border of the mutation domain (see later discussion);the 3' border could be determined by the location of other regulatory elements (e.g., the intron enhancer or matrix attachment region) or mutation may simply ultimately fall off at some distance 3' of the promoter as a consequence of an inherent limit to the processivity of the mechanism.

C. Nature of DNA Target Immunoglobulin V genes are the targets of hypermutation. Do they contain DNA sequences that uniquely confer their ability to act as targets? Several experiments have been carried out to answer this question (Umar et al., 1991; Hackett et al., 1992; Azuma et al., 1993). Recent experiments with transgenic mice (Yklamos et al., 1995) have revealed that when the protein-coding segment of the V gene is replaced by a heterologous se-

466

CESAR MILSTEIN AND MICHAEL S. NEUBERGER

quence (human P-globin or Escherichia coli gpt or neo DNA), this heterologous DNA is an effective target for hypermutation. Thus, not only can heterologous sequences by efficiently targeted for mutation, but the V gene itself is not necessary for mutation recruitment. Clearly, other sequences near the protein-coding part of the V segment must be responsible for recruiting hypermutation, and the identity of some of these sequences is discussed later.

D. Types of Mutations Created Nearly all the mutations created by the hypermutation are single nucleotide substitutions, with nucleotide insertions or deletions being only more rarely obtained. The substitutions can be fairly widely distributed within the mutation domain although a slight bias in favor of clustered substitutions has been observed (Klein et al., 1993).The nuceotide substitution preferences (Table 11) reveal a bias in favor of transitions (accounting for about 50% of the mutations as opposed to the randomly expected 33%) with some transversions being preferred over others. The substitution preferences also reveal a nonrandomness in the targeting of the individual bases for mutation. Thus, on the coding strand, A residues are more likely to be targeted for mutation than T residues, and G residues more likely than C. Given, of course, that a T residue on the coding strand is partnered by an A residue on the opposite strand, this differential targeting for mutation of A's and T's on the coding strand means that the mutation mechanism exhibits an ability to distinguish between the two DNA strands-a phenomenon termed strand polarity. TABLE 11 Nucleotide Substitution Preferences' To From

T

c

A

G

Total

T C A G

0.155 0.084 0.033

0.068 0.055 0.118

0.040 0.019

0.022 0.036 0.151

0.13 0.2 1 0.29 0.37

0.219

-

' The frequency of each base substitution is given as a proportion of the total with the overall proportion of mutations targeted to each of the four bases being shown in the righthand column. The results are given with respect to the coding strand and have been calculated from a database of 1075 mutations in immunoglobulin VH and V, genes, removing the major antigen-selected hot spots and correcting for base composition. The data are taken from Betz et al. (1993b) and the compilation is from Neuberger and Milstein (1995).

MATURATION OF T H E IMMUNE RESPONSE

467

E. Mutations Unevenly Distributed

As discussed earlier, when the pattern of mutations in antigen-specific responses is analyzed, mutational hot spots are often observed. Typically, these hot spots reflect amino acid substitutions that give improved antigenbinding characteristics and indeed the residues involved are often directly implicated in antigen contact. However, quite apart from the dramatic skewing resulting from specific antigen selection, the mutations themselves are in fact targeted in a markedly nonrandom fashion. This was revealed by looking at the distribution of silent mutations in antigen-selected V genes (Berek and Milstein, 1988; Weiss et al., 1992) and has been analyzed in far more detail by use of immunoglobulin transgenes. Thus, mutational hot spots have been identified in transgenes that have not themselves contributed to the antigen-specific antibody expressed by the B cell and have therefore acted as silent “passenger” targets for mutation (Sharpe et al., 1991; Betz et al., 1993a, 1994).The same hot spots identified in the mouse V,Ox-1 gene when present as a passenger are also revealed when a V,Ox- 1 transgene has mutated to yield antibodies binding to a diverse array of foreign antigens with consequent avoidance of the skewing provided by singleantigen selection (Betz et d., 1993a; Gonzhlez-Fernhndez et al., 1993). Furthermore, a similar nonrandom distribution of mutations is found when comparing in-frame or out-of-frame (therefore not subjected to antigen selection) V-J rearrangements of 1 chains (Gonzfilez-Fernfindezet al., 1994). Mutated VH sequences in human peripheral blood lymphocytes also reveal a highly skewed distribution of mutations (Fig. 4; Wagner et al., 1996). Intrinsic hot spots have now been analyzed in several immunoglobulin V genes. Many are found to be in serine codons encoded by AGC or AGT (grouped as AGY) triplets (Sharpe et al., 1991; Betz et al., 1993a,b; GonzhlezFernhndez et al., 1994b; Wagner et al., 1995), although the same DNA sequence can constitute a hot spot when found in a different reading frame (Fig. 4). However, hot spots are also located at other positions and certainly not all AGY triplets are hot spots; other features apart from immediate local sequence context must be of importance. Nevertheless, a good proportion of hot spots do conform to a Pu-G-Py-(NT) consensus that has been deduced as a favorite site for mutation (Rogozin and Kolchanov, 1992). This applies not only to the hot spots in immunoglobulin V genes but also to those obtained when nonimmunoglobulin gene DNA is used to replace the V-modified transgenes (YClamos et al., 1995). F. Cis-Acting DNA Elements for Recruiting Mutation

Transgenic mouse experiments have revealed most of what we know about the cis-acting DNA elements required to recruit hypermutation. The

CDR2

A82a lAACl

A23 [GCAGC

Amino acid position FIG.4. Pattern of mutation in V ~ 2 6sequences in human peripheral blood IgM- IgD-B cells. Variability is plotted against amino acid position in V ~ 2 and 6 the data are from Wagner et al. (1996).

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5‘ border of the K hypermutation domain is about 150 bp downstream of the promoter (Rada t t al., 1994). The V, promoter itself is not required for hypermutation in that the rate of hypermutation is hardly affected on replacing it with the promoter of the p-globin gene (Betz et al., 1994; Meyer et al., 1996). On the other hand, removal of either the K 3 ’ enhancer (E,3’) or the K-intron enhancer-matrix attachment region (Eki/MAR) causes a drastic reduction in hypermutation which is particularly marked in the latter case (Betz et al., 1994). Is the effect of the enhancers on hypermutation secondary to their activity as transcription activators or do they stimulate hypermutation by an independent but parallel process? Interestingly, whereas the removal of E3’ causes a dramatic fall in transgene expression as monitored by RNA levels in hybridomas, no such drop is seen with the Ei/MAR deletion (Betz et al., 1994); indeed, K transgenes carrying this deletion are also expressed well at the B stage of development as reflected by flow cytometry analysis. One can easily build models based on such data. For example, sequences in the Ei/MAR region might be directly implicated in recruiting factors that initiate hypermutation but with effective hypermutation still requiring either active transcription or an open chromatin structure. Clearly, these ideas are speculative, but the data certainly direct one’s thinking toward models that link transcription with hypermutation. Although high-level hypermutation of K transgenes has been readily obtained, this has not clearly been the case with 1 and IgH transgenes. Although the mouse L locus is a good target for hypermutation (GonzfilezFernfindez et al., 1994b; Motoyama et al., 1991, 1994), no mutation has been obtained of a 1 transgene whose expression was driven by the IgH intron enhancer (Hengstschlager et al., 1994). In analogy with the K locus, it may be that regulatory elements distal to C i and not included on the 1 transgene are necessary for recruiting hypermutation. With regard to IgH transgenes, a low level of hypermutation of rearranged IgH transgenes has been observed although mutation is greatly enhanced on trans-switching between the transgene and endogenous IgH loci (Giusti and Manser, 1993; Sohn et al., 1993), supporting the view that full hypermutation depends on sequences at the 3’ end of the locus that are not included on the transgene. Hypermutation has also been studied in mice transgenic for human IgH miniloci in which the V, D, and J segments of the minilocus need to undergo productive rearrangement to yield functional antibody (Taylor et al., 1994; Wagner et al., 1994). Although hypermutation was observed whether or not the minilocus included the IgH 3’ enhancer, it appears to have been at a modest rate (Wagner et al., 1994). Thus, all the elements in the IgH locus necessary to achieve mutation at its h l l rate may not yet have been identified. It will clearly be interesting to test the im-

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portance for hypermutation of other regulatory elements 3’ of Ca recently identified (Madisen and Groudine, 1994; Michaelson et al., 1995). G. Possible Models of Hypermutation Mechanism

The dependence of hypermutation on the presence of EilMAR with its associated cluster of binding sites for topoisomerase I1 suggests EiIMAR might play a role in the initiation of hypermutation by, for example, encouraging the formation of single-strand nicks. The presence of these nicks or other DNA modifications would be sensed by RNA polymerase I1 which, on being caused to halt, could recruit error-prone DNA repair to the coding strand. Such a mechanism obviously shows some parallels to nucleotide excision repair. It could explain the facts that mutation largely starts downstream of the promoter, that it depends on both E3’ and Ei/MAR, and that it exhibits strand discrimination. If the DNA polymerase involved in the repair lacks proofreading activity, then a significant level of nucleotide substitutions could be expected. One would still, however, need to explain how the misincorporations are not themselves corrected by mismatch repair. Finally, it is interesting to note that although humans and mice use hypermutation to diversify their immunoglobulin V genes, chickens make substantial use of gene conversion. It has been reported that immunoglobulin transgenes may undergo gene conversion-like events when a donor V gene fragment is included next to a rearranged IgH gene (Xu and Selsing, 1994). Since in the case of human and mouse there is strong evidence that gene conversion does not play a role in hypermutation (Wysocki and Gefter, 1989; Wysocki et al., 1990; Milstein et al., 1992; Gonzhlez-Fernhdez and Milstein, 1993; Ford et al., 1994), the result could reflect the different distance between genomic V genes and transgenes in tandems. Even so, it suggests that important components are shared by both processes. It is possible that hypermutation and gene conversion represent distinct outcomes resulting from different ways of resolving a common local insult to the immunoglobulin gene DNA (Maizels, 1995; Weill, J.-C., and Reynaud, C.-A., 1996).

V. ANTIGENIC SELECTION A . Selection of Mutated Sequences Affinity maturation is basically a Darwinian selection process within the microenvironment of the individual since it is a result of the generation of large number of somatic variants transmitted through the B-cell lineage,

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which are selected by virtue of competitive advantage in being able to recognize a gradually decreasing concentration of antigen. There are two stages where antigen selection operates, one is selective proliferation of cells from the available repertoire, and the second is selective survival following exposure to the hypermutation process. Selective proliferation from the primary repertoire, hypermutation, and selective survival in the environment of the germinal centers are characteristic stages of maturation of the primary response. The events following secondary and subsequent responses are probably similar. In some cases it has been possible to correlate antigen binding improvement with mutations repeatedly found in the V gene segments during maturation. For instance, in the response to 2-phenyloxazolone (phOx), the repeatedly found substitution His-34-Asn or Gin of the VKOxlgene improves binding affinity by a factor of 10 or 8, respectively (Berek and Milstein, 1987). A similar improvement in the NP response results from the substitution Trp-33-Leu in the heavy chain (Allen et al., 1988). In the response top-azophenyl arsonate, the heavy chain substitutions Thr-57+Ile and Lys-58-Thr increase affinity by a factor of 3 and 4, respectively, and 8 if both occur together (Sharon, 1990). Indeed, it is not unusual to find key mutations not individually but in pairs or even in groups of three or four, which although they are sometimes clustered are not the result of gene conversion events (Wysocki et al., 1990). For instance, in the case of the phOx response it is very common in mature responses to find that the mutation to Asn-34 is associated with Tyr-36+Phe and in several instances also with Ser-31hArg which has also been shown to improve binding (Dreher et al., 1991). However, mutations known to improve antigen binding are accompanied by neutral mutations. Typical neutral mutations (i.e., not selected by antigen) are silent mutations. The mere fact that they are commonly observed (e.g., the third base coding for Val-30 in the VKOxl)suggests that some of the expressed mutations are also likely to be neutral. An attempt to measure the number of neutral mutations that arise during the immune response to phOx has been made by estimating the difference in the mutation rates of silent and total mutants. The difference (taking into consideration that on a random basis, approximately one-third of total random mutations are silent) was very small (3 and 4 x lo4, respectively), suggesting that on average three-fourths of the mutants are neutral (Berek and Milstein, 1988). It is also interesting to note that hypermutation hot spots often give rise to a variety of amino acids, each one at a frequency predictable by the intrinsic bias of the hypermutation event. When the mutation is antigen-selected, it often has a directionality and frequency that depart from the average (Betz et al., 1993b). This can allow antigen-selected sub-

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stitutions to be identified in databases of somatically mutated sequences. It is not surprising that relatively few, relative to neutral, point mutations give rise to improvements in binding. Deleterious mutations, or mutations impairing affinity, although intrinsically also very frequent, are eliminated during antigen selection. This imbalance in the frequency of “good” vs “bad” mutations, has important implications in the interplay between hypermutation and selection. It means that while the probability of selecting a beneficial mutation increases with the mutation rate, the likelihood of introducing a deleterious mutation is much higher. A mutation rate approaching lO-’/bp per generation implies that on average almost one point mutation is introduced with every cell divsion in the coding segments of antibodies. This seems to be optimum for generating maximum diversity with a tolerable level of degeneracy (Allen et al., 1987; Weigert, 1986). Indeed, the problem is not creating diversity but efficiency in selection of improvement against a high background of degeneracy. How is this efficiency achieved? Two selection stages are involved, and while both are driven by antigen, it is quite possible that they operate in different ways. The first stage operates soon after stimulation and is responsible for the initial proliferation of either virgin or memory cells. In a primary response when no antibody is present in the circulation, antigen is likely to be in excess and the competition for antigen is negligible. However, as antibody begins to be produced, antigen is quickly eliminated and the competition for free antigen is soon established. The second and possibly stronger selection stage is antigen-driven rescue from apoptosis of mutant clones in germinal centers. This stage is also probably the most complex since it seems to depend on antigen trapped in the follicular dendritic network. The eKiciency of selection is exemplified by the already mentioned examples of late primary immune responses where multiple (at least two) identical mutations are commonly found in independent animals and in multiple clones. If each mutation arises at the average rate of 4 x 10“ per cell generation, two selected mutations would on average occur in populations above loycellswell above the size of a mouse spleen. On the other hand, each mutation can easily occur in populations on the order of 10,000 cells. If such a cell is rescued from apoptosis and allowed to proliferate and mutate, the double mutant has an excellent chance of arising and being selected in two stages, each mutation involving fewer than 10,000 cells. Theoretical calculations have shown that the most efficient strategy for improvements in recognition is not by continuous selection of a hypermutating population but by separating the stages of proliferation, mutation, and selective survival (Agur et al., 1991; Kepler and Perelson, 1993). Therefore, following primary stimulation, memory cells arise through multiple cycles of hypermutation and selective survival followed by pro-

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liferation (antigen-driven?)and back to hypermutation, selection, etc. Presumably, the process comes to a halt when antigen is exhausted. Indeed no more hypermutating cells are found in the spleen 3 4 weeks after primary stimulation (Rada et al., 1991; Weiss et al., 1992). However, antigen remains trapped in the follicular dendritic cells for months if not years, and therefore the reason for the acute response phase on repeated immunizations must be connected to another physical form of the antigen (e.g., free antigen). Kinetic on-rates seem also to be important in the process of antigen selection, suggesting a role for the involvement of free antigen (Foote and Milstein, 1991). The role that kinetic on-rates could play is unclear. Kinetic parameters are measured using free haptens in solution, and the limiting factor for maximum k,,, when not constrained by an energy barrier (e.g., imposed by the antibody structure) is presumed to be the diffusion rate. However, the membrane Ig of the B-cell antigen receptor is attached to the B-cell membrane. If B-cell activation and/or rescue from apoptosis requires antigen (in this case attached to a carrier protein) presented in the form of complexes or attached to cell surfaces (dendritic cells?), on-rates would be much lower. It is tempting thus to conclude that this implicates free antigen in either proliferation or rescue from apoptosis or both. An interesting observation has been that injection of soluble antigen at the peak of a normal response induces antigen-specific apoptosis (Pulendran et al., 1995; Shokat and Goodnow, 1995). The meaning of this observation remains unclear, but the suggestion has been put forward that this is due to elimination of self-reactive clones arising during affinity maturation. Whatever the interpretation of such findings, they suggest that selection is likely to be a compromise between conflicting signals leading either to apoptosis or to further differentiation into plasmablasts, etc., or memory cells. Another type of result also points to a quantitative aspect of selection. This refers to the differential expression of multiple transgene copies when one of the copies has acquired key mutations increasing antigen binding. It appears that antigen is able to distinguish the disadvantage derived by expression of the other copies and selects mutants (e.g., nonsense mutations) of these other copies to remove them as competitors (Lozano et al., 1993). The development of the secondary response may follow a pattern analogous to that of the primary, namely, selective proliferation of memory cells that migrate to germinal centers where they hypermutate and are further selected by antigen to generate new plasma cells and improved memory cells. In mature responses the whole process may be shorter and more synchronized (Fig. 5). The accumulation of mutations in secondary and tertiary responses (Berek and Milstein, 1988; Rada et al., 1991), as well as in chronic stimulated cells in Peyer’s patches, support this view (GonzdezFernhndez et al., 1994a). However, memory cells expanded into irradiated

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Antigen

Selective proliferation

1 Mutation

Selective survival

1

Time (days) FIG.5 . Mutation and selection in secondary responses.

mice do not show evidence of further mutation (Siekevitz et al., 1987). It is, however, uncertain whether under the conditions of an adoptive transfer experiment, there are suitable germinal centers for hypermutation to take place. It has also been proposed that hypermutation may not operate when the affinity for antigen reaches high values. In other words antigenic competition also selects high-affinity variants to spare them from deleterious mutations. The finding of identical mutated sequences in a single germinal center is quoted as supporting evidence (Berek and Ziegner, 1993; Ziegner et al., 1994). B. Repertoire Sh$

The bone marrow continuously generates primary B cells which express the potential repertoire. Since the potential repertoire of antibodies is considerably larger than the number of B-cell clones in an animal (particularly in a small animal like a mouse), the available B-cell repertoire at any single moment can be only a fraction of the total potential. It follows that at the time of antigenic challenge, a large fraction of the potential sequences are not available. Indeed, some sequences may arise so rarely that their participation in an immune response may be a chance event for

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individual animals. The idiotypic response to certain immunogens is explained as a result of the frequent presence, in the repertoire of certain mouse strains, of suitable binding components. Their dominance at later stages of the response is continuously eroded particularly (but not exclusively) by competition with other elements of the potential repertoire that are initially poorly represented or rarely present. These alternative structures, utilizing different genetic elements of the potential repertoire, introduce a distinct and fundamental factor in the process of affinity maturation. In the primary response, when antigen is present in large excess over antibody binding sites, even low-affinity receptors are likely to be triggered and a very heterogeneous initial response may occur (Makela et al., 1978; Kaartinen et al., 1986). As the primary response develops, lower-affinity combining sites are quickly displaced by newly formed antibody so that among the more frequent components of the available repertoire only those with better binding properties will become dominant. This is the simplest explanation of idiotypic responses like that of 4-hydroxy-3nitrophenacetyl (NP, Makela and Karjalainen, 1977; Bothwell et al., 1981), 2-phenyloxazolone (Kaartinen et al., 1983), phosphorylcholine (PC, Malipiero et al., 1987), p-azophenyl arsonate (Manser et al., 1987), GAT (Schiff et al., 1986),B( 1,6)-galactan (Rudikoff, 1988), etc. For example, the V,Ox 1-J~5light chain gene combination dominates the primary response to phOx and is the most abundant among the combinatorial forms expressed by the corresponding family containing about 30 V, germline genes (Milstein et al., 1992). Furthermore, in mice expressing the V,OxlJK5as a transgene, the response to the antigen phycoerythrin is dominated by this light chain, even though in wild-type mice, other members of the family are used more often (Rada and Milstein, 1994, unpublished). However, as the response proceeds, and in particular following further rounds of immunization, the early combination of genes for heavy and light chains is slowly replaced by new elements. The balance of the repertoire shifts from its initial dominance to new gene combinations. Repertoire shift and hypermutation are clearly complementary, interdependent strategies. The clones that emerge during the repertoire shift also undergo selective proliferation, hypermutation, and antigen selection. Those underrepresented in the available repertoire may take much longer to become important components of the response, and some observations support this view. The VHOxl gene is dominant in the primary response of BALB/c mice to phOx. Their presence must originate from a number of independent B cells of the naive repertoire since the D segments do not usually share identical nucleotide sequences in different hybridomas from the same mouse. A recurring component of the repertoire shift during early maturation belongs to the VH-M~1 family. Unlike VHOx1, D segments show repeats in hybridomas derived from the same

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mouse, indicative of a common precursor B cell. Since different mice produce different repeats, the number of precursor cells expressing the M21type antibody in the naive repertoire must be small. This is likely to be why M21 appears in later responses. Other gene combinations may arise even less frequently in mature responses. The importance of such clones is exemplified by the anti-phOx antibody NQ11.7.12 which displays the highest affinity of a large panel of mature antibodies and which expresses a J558like VH gene rarely found in such responses (Berek and Milstein, 1988). The response to the hapten PC is another well-analyzed example of the repertoire shift during maturation (Stenzel-Poore et al., 1988). The primary response is dominated by group I antibodies expressing S107 V H genes. In mature responses (secondary and tertiary), antibodies with different fine specificities, group 11, become codominant. This second group, however, represents a collection of quite diverse germline gene combinations. The initial idiotypic dominance has been attributed to precursor frequency, the codominance of group I1 antibodies to the difference in epitope recognition giving improved binding properties. So far we have given emphasis to affinity considerations. However, kinetic factors may also be involved in antigenic selection and in the repertoire shift. vH1 1-V,45 anti-phOx antibodies are the dominant idiotype in some strains of mice like C57BW10 (Kaartinen et al., 1988) while they are only a minor but consistent component of BAL,B/c primary responses. They represent, however, a major participant in the repertoire shift. Their affinity for antigen is not on average higher than that of the others at the same stage of the response. A very significant difference, however, is in the kinetic parameters. All of the VHll-VK45 type have a consistently high on-rate, which seems to be limited by the diffusion rate, while that of the V,Oxl-related antibodies is lower. The reason for the different in kinetics between the two types of antibodies is probably connected with the stereochemical nature of the hapten-antibody interaction: a deep narrow cleft in the latter (Alzari et al., 1990) vs an interaction more restricted to surface residues in the former (McManus and Riechmann, 1991). This difference in kinetic behavior may explain their emergence in the early secondary response in spite of a possible lower clonal frequency in the naive repertoire of BALB/c mice. Once maturation is under way, a different type of competition takes place. As discussed previously, key single-point mutations improve antigen binding, and this is likely to again be a chance event. This gives immediate advantage to certain gene combinations. For instance, in the example just given, the VH11-VK45 antibodies, key mutations with drastic affinity improvements similar to those of V,Ox 1 have not been identified, which may explain why they tend to disappear in more mature responses. A similar situation may occur in the anti-NP response where after an initial improve-

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ment following a key mutation, the I-type antibodies are replaced by others during the maturation stages. In other words, the success of a particular combination of germline genes in persisting or in replacing other combinations depends in the long run on their relative ability to acquire suitable mutations to compete for an increasingly limiting amount of antigen (Berek et al., 1985; Manser et al., 1987). While this process of selection explains the gradual shift of the repertoire of (suitably mutated) V genes during maturation, the picture is likely to be more complex. We have discussed that only a fraction of the potential repertoire is expressed at any given time. If potentially excellent combinations are not in the repertoire at the time of immunization but arise at a later stage, they will face stiffer competition with other antibodies that have already undergone affinity maturation. In fact, both high- and lowaffinity antibodies seem to coexist in secondary and tertiary responses. An extreme example is the isolation of unmutated V,Oxl antibodies in tertiary responses, together with highly mutated high-affinity versions (Berek et al., 1987). An important clue to this apparent anomaly may be that the low-afinity forms are found in hybridomas prepared 7 days after an intraperitoneal rather than 3 days after an intravenous injection of antigen. It has been suggested that to give “late arrivals” a chance to develop the available pool is compartmentalized. Compartmentalization could be achieved by cell kinetics, by antigenic presentation, by anatomical features, by cell markers, etc., and could provide a way to by-pass competitive stimulation of the naive and memory repertoires (Berek and Milstein, 1988). The subpopulations of B cells giving rise to either primary or memory responses (Linton et al., 1989)may provide a handle for analysis of this process. Jacob et al. (1991a) and Jacob and Kelsoe (1992) found that as proposed by MacLennan et al. (1990), two distinct B-cell subpopulations, one from foci present in PALs and the other from germinal centers, develop after antigenic stimulation. The GC cells appear to derive from PAL focus cells. These two subpopulations are probably subjected to independent processes of antigen selection. Furthermore, the authors suggest that interclonal competition primarily focuses in the PALs while intraclonal competition takes place in germinal centers. VI. STRUCTURAL AND EVOLUTIONARY IMPLICATIONS

A. Germline V Gene Sequences Evolved to Bias Targeting of Somatic Mutation Antibodies derive from the initial recognition of elements of a large repertoire of naive structures intended to recognize the world of antigens. Following antigen stimulation, individual structures are selected and fur-

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ther diversified by point mutations leading to affinity maturation driven by competition for antigen. Evolutionary considerations have made this process much less random than it appears to be in such simple statements of general strategy. We will address those that refer to structural features of the naive repertoire diversity and to the nonrandom nature of somatic hypermutation. There is good reason to believe that the sequences of germline V genes have evolved to exploit the nonrandomness of the somatic hypermutation mechanism in such a way that somatic mutations are more likely to be targeted to those parts of the V gene where they have a good chance of yielding changes leading to improved antigen binding (complementaritydetermining regions) and away from places where they are likely to compromise the structure of the antibody scaffold (frameworks).This has been revealed by looking at the distribution of the two types of serine codonsAGY (=AGC and AGT) and TCN (=TCA, TCC, TCG, and TCT). Whereas many serine AGY triplets fall within the Pu-G-Py-(A/T)hot spot consensus, TCN triplets do not. Analysis of the sequences of human immunoglobulin V genes has revealed a dramatic favoring of the use of AGY triplets for serine residues located within the CDRs (particularly CDRl) and of TCN for framework serines (Wagner et al., 1995). In the sequences of T-cell receptor V genes, where there is no evidence for functional diversification by somatic hypermutation, TCN is used more than AGY not only in the framework but even more so in CDRl and in CDR2. Thus, it appears that V gene sequences have evolved such that somatic mutation is more usefully targeted within the V region, perhaps one of the more subtle pressures exerted on genome evolution. However, it is tempting to speculate that the selection for biased codon usage occurred prior to the evolution of higher mammals and that the codon bias that evolved earlier was simply maintained. Thus, whereas in human and mouse, somatic hypermutation appears to contribute only to generation of the secondary antibody repertoire and is followed (or accompanied) by a period of extremely fierce antigenic selection, the situation may be different in other animals. For example, in sheep somatic hypermutation appears to play an important part in generation of the primary repertoire (Reynaud et al., 1991) and in some lower organisms such as frogs (HindsFrey et al., 1993; Greenberg et al., 1995), although hypermutation takes place, the system of antigen selection may not be so well-developed, there being a lack of obvious germinal centers (Wilson et al., 1992). Thus, the biased codon usage may have been selected in a situation where the directed targeting of mutation was particularly beneficial either because selection was less powerful or because the mutation contributed to diversification of the primary repertoire.

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B. Complementarity between Germline and Somatic Diversijcation As discussed in Section 1I.C and illustrated in Table I, the diversity of the naive repertoire is largely directed toward CDR3. Since in that region, diversity of size and folding as well as primary sequence is huge, there is a high probability that it will provide the initial elements of random recognition of repertoire components. At this stage, the canonical structures of the other CDRs and critical residues in the vicinity of CDR3 are also likely to play a fundamental role. Limited variability in these positions gives extra diversity to the canonical structures. In human heavy chains, three out of four of the most variable positions in the germline of the same canonical structure are concentrated in the CDRP (Fig. 6). As shown in Table I, the total potential diversity so generated is sufficiently low to be within the expected number of naive clones. However, a considerable degree of tolerance in other positions is to be expected and germline diversity is restricted at this stage. Residues there must not hinder antigen binding but need not provide for optimal interactions.

FIG 6. The relative positions of the most variable sites within a set (canonical structures 1-3) of human germline VH genes. A similar picture is given by the other large canonical structure sets. [From Chothia et al. (1992).]

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Twenty-four members of the mouse VKOxgene family are 90% identical (Milstein et al., 1992). As in the human VH, the most variable residues are in the CDR2 segment with little diversity in the CDR1. This is in sharp contrast with the somatic mutation pattern where the variability is maximally concentrated in the CDRl (GonzBlez-FernBndezand Milstein, 1993). It is important to keep in mind that (as discussed in Section N . E ) the high concentration of somatic mutants in the VKOx-1CDRl is mostly due to intrinsic features of the mutation process. However, in apparent contrast, in mouse 3, chains the intrinsic mutational hot spots are found equally distributed in all three CDR segments (GonzBlez-FernBndezet al., 1994b). There is, however, an important difference in the primary repertoire generated by the two gene families. In the case of VKOx,the large family of closely related genes generates a large CDR3 diversity during recombination to any of the four J K segments, but in the case of mouse 3, chains almost no diversity is found in terms of gene families or during VJ recombination. Thus, it appears that during evolution of the germline genes, the position of hot spots has been biased toward segments that not only shape the binding site but also where they complement the germline diversity (GonzBlez-FernBndez et al., 1994b). This proposal is reinforced by other observations. An analysis of the somatic mutants of human heavy and K light chains also shows that they are more abundant in CDR residues showing lower germline diversity (Tomlinson et al., 1996). While antigen selection plays a part in shaping this pattern, as discussed in Section IV, the majority of the somatic mutants are intrinsic. The effect of somatic mutations is thus to extend the area of diversity from a tight, small surface centered in CDR3 to a much larger one including the whole of CDRl and CDR2. Although only a few of these mutations are important in the maturation process, these few are the critical events. The biased distribution of mutation frequency favors the generation of maximal diversity in those segments most likely to provide better contact residues or minor topological changes in the binding region. The possibility that other hot spots (e.g., Ser-77 of VkOxl), while not in the vicinity of the binding site, could affect the geometry of the site by small changes in the P-sheet angles remains a tentative speculation. To summarize then, the structural repertoire for naive recognition (selected during evolution and in that sense optimal) depends on a very high structural and sequence diversity in CDRS, with orders of magnitude smaller structural diversity in CDR2 and CDRl . The amino acid diversity within each canonical structure tends to be larger in CDRS than in CDR1. The affinity maturation is the result of complementary diversification which is not generated by the primary repertoire but which is required to increase the number of contact residues or the fine geometry of a binding

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site selected to bind defined antigens. We propose that evolution has favored high-mutation-rate DNA configurations (intrinsic hot spots) in CDR segments designed to complement the diversity generated by germline and combinatorial diversity.

ACKNOWLEDGMENTS We wish to thank C. Rada, S. D. Wagner, and K. Spillard for help in the preparation of the manuscript. C. Milstein is grateful for the generous support of the National Foundation for Cancer Research, and M. S. Neuberger is the recipient of an International Research Scholars award from Howard Hughes Medical Institute.

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AUTHOR INDEX Numbers in italics refer to the pages on which the complete references are listed.

A

Allen, D., 390,439,471472,481 Allen, E., 435, 447 Allen, I. E., 361, 445 Allen, M. J., 305-306,327 Allen, P. M., 7, 21, 4 0 4 2 , 48,50,54-55, 234,237 Alliger, N. L., 156,236 Allison, J. P., 4,4 8 , 5 1 3 2 Almassy, R. J., 214,237 Al-Ramadi, B. K., 25, 26, 27, 29,49 Alt, F. W., 55, 234,238, 460, 484 Altman, A,, 41,50 Altschuh, D., 62, I??, 170,210, 214,253, 258 Alzari, P. M., 61-63, 86, 106-107, 111, 128-131, 146,148, 181-182,219,230231, 235, 240,246,248, 310, 326, 381,413,441,444,457458,476,481 Amar-Costesec, A,, 322,323 Amemiya, C. T., 454,483 Amit, A. G., 46, 48, 170, 196, 201, 210, 213,231,233,237,240 Amzel, L. M., 59, 61, 64, 70, 75, 81, 119120,128,130-131, 199-200,206,250, 342-343,349,359,439,446 Amzel, M., 186,237,256 Anchin, J. M., 63, I30 Andersen, K. N., 307, 310,325 Anderson, A. O., 456, 484 Anderson, K., 20, 30, 48-49 Anderson, W., 398,445 Anderson, W. F., 63-64, 129, 131 Andersson, B., 318,323 Andrew, S. M., 225,248,367,445 Andrews, P. R., 285 Anfinsen, C. B., 162, 213,237, 301, 323, 33 1,43 9 4 4 0 , 4 4 2 Anglister, J., 139, 143-144, 148, 178,237, 249,259 Anquez, V., 455,484 Anthony, J., 227,237 Antoniw, P., 438, 448

Abagyan, R., 199,208,236,257 Abastado, J.-P., 19,53 Abderrahim, H., 439,442 Abergel, C., 127,128,131 Abola, E. E., 60, 66, 68, 70, 125,128-129, 132, 168,242,310,323 Aboud-Pirak, E., 321,323 Abragam, A., 136, 148 Abuchowski, A,, 298, 325 Acharya, K. R., 320,323 Ackermann, B., 322,328 Ackermann, F., 302,326 Acuto, O., 4 , 5 2 Adair. J. R., 60, 128 Adams, G. P., 224,231,236,352,355-357, 361, 364-365,367-376,439,442-443, 445,447-449 Adams, K. M., 430-43 1,440 Adamson, A. W., 196,236 Adema, G.J., 21,48,51 Adler, B., 433, 442 Agard, D. A., 165, 199,238,259 Agur, Z., 472, 481 Ahmad, K., 79,130 Ainsworth, C., 60,130,132 Air, G., 86,129, 181-182, 230-231,240, 4 13,441,458,481 Air,G. M., 126,129,203,210-211,218, 220-221,248,251,258, 300-301,326, 370,441 Aisaka, K., 190,249 Alam, S. M., 43,48 Alber, T., 170,236 Aldovini, A,, 17, 18, 21, 30,55 Aleksander, I., 4,55. 233, 259 Alexander, C. B., 455,481 Alexander, H., 214,218,244,257 Alexander, J., 30,41,48-50 Alexandru, I., 310,323 Alfthdn, K., 224,257 487

488

AUTHOR INDEX

Apell, G., 352, 356-357, 365, 376, 443, 447 Appel, G., 372, 449 Appel, J. R., 63, 64 Appella, E., 16, 17, 20-21,50-51, 67, 128, 314,316,324-325

Arai, K. I., 233,252 Arakawa, T., 377, 440 Arata, Y., 222,246 Arden, B., 233,237 h e n s , M., 437,440 Arevalo,J. H., 62, 128, 133, 147, 148, 197, 23 7

Bacus, S. S., 322,323 Bagshawe, K. D., 438,448 Bahadur, G., 7 54 Bahraoui, E., 214415,237, 244 Bahraoui, E. M., 214,242 Baier, M., 203, 210,245 Bain, J. D., 396,440 Baird, B., 74, 133 Bajorath, J., 60,64,130, 149, 179, 184, 192193,231,235-236,237,243,245-246 Baker,A. T., 126,129,203,220-221,258, 370,441

ArgoS, P., 161-162, 183,224,237,254-255 Arnold, E., 62, 128 Arnon, R., 213,237, 294, 301, 323 Arrhenius, T., 41, 48 Arthos, J., 41,53 . h f f o , A . , 179,237, 318,328 Arulanandam, A. R. N., 166,259 Ashe, S. A., 438,447 Ashley, J. A., 263-265, 280, 283,285-287 Ashton-Rickardt, P. G., 20,30,36,48,54 Ashwell, J. D., 39, 48 Askonas, B. A., 17,32,48 Assulin, O., 178,249 Astier, J. P., 216,246 Atarhouch, T., 454, 482 Atassi, M. Z., 2 13,23 7 Athay, R. J., 68, 132 .4therton, E., 22, 29, 50 Auditor, M.-T. M., 267-268, 270-271,285286

Auphan, N., 223,244 Aust, R. M., 63, 131 Austen, K. F., 177,210,245 Avbelj, F., 198,247 Avdalovic, N. M., 229,253 Avery, A. C., 319,323 Avey, H. P., 70, 81,131, 342-343,349,446 Avila, D., 478,482 Avnur, Z., 391, 444 Avogadro, L., 163,257 Axel, R., 41.52-53, 233,248 Azuma, T., 465,469,481,483

B Babbitt, B. P., 7 , 21, 48, 234, 237 Bacik, I., 20, 55 Bacon, D., 243

Baker, D., 165,238 Baker, E. N., 144,148 Baker, T. S., 63,131 Bakker, A. B. H., 21,48 Balderas, R. S., 63, 64 Baldwin, E., 267,285 Baldwin, E. P., 267,285 Baldwin, J. E., 278,286 Ballard, D. W., 61, 122, 130 Baltimore, D., 6 , 8 , 4 9 , 5 5 , 221, 253, 460, 475,481,484

Ban, N., 63, 118,128 Bandeira, A., 30, 36,48 Bank, I., 234, 2?8 Bannwarth, W., 4 1 , 49 Barbas, C. F., 261, 283,284 Barbas, C. F. 111, 281,286, 356, 396-397, 416,440

Barber, B. H., 19, 20, 30,49 Barclay, A. N., 166-167, 259 Barlow,A., 17, 18,53, 316,327 Barlow, D. J., 214,257 Barlow, D. W., 213, 238 Baron, J. L., 11,50 Barrett, R. W., 261, 283,284 Barterls, K., 198, 246 Bartlett, P. A., 267-268, 285 Barton, G. J., 160,254 Bashford, D., 165,238 Bass, S. H., 249 Bassohno-Klimas, D., 188-189,238 Basten, A., 317,324 Bastin,J., 16, 19, 29, 30, 49,52,54, 322, 328 Batni, S., 291,327 Batorsky, R., 360-361,445 Batra, J. K., 428,440 Bauer, S., 437, 440 Baumann, H., 62,128 Beaufay, H., 322,323

AUTHOR INDEX

Bechis, G., 214, 242 Becka, L. N., 131 Becker, D. M., 4, 8,49 Becker, M. L. B., 223,238 Beckers, W., 298,323 Bednarek, M. A,, 19,53 Beeson, C., 315, 323 Begent, R. H., 365,441 Begg, G., 341,441 Behboo, R., 320,324 Bell, B. A., 224,258, 353, 355,449 Bell, J. I., 224,245, 368,442 Bellot, F., 32 1,323 Benacerraf, B., 5,51 Bendahman, N., 454,482 Bendig, M. M., 229,247 Benedetto, J . D., 381, 445 Bengoechea, T., 439,444 Benjamin, D. C., 163,213-214,218,238, 256,302,323

Benjamini, E., 301,327 Benkovic, S. J., 123, 128, 182, 222,254, 261,263-265,271,282-283,284-285, 287,356, 397,416,440

Bennett, J. C., 334, 340-341,440442 Bennett, W. F., 427, 442 Bennett, W. S., 12, 15-16, 48, 31 1, 324 Bennick, J. R., 7, 20, 55 Benoist, C., 40, 49 Bentley, G. A., 15, 46, 48, 61, 63, 94, 96, 100-101, 107, 1 1 1 , 117, 125-126,128130, 185, 196, 203, 211, 234,238, 243,359,441 Berek, C., 381,390-391,440,444,456, 463,471,474,477,481482,485 Berendsen, H. J. C., 15 1, 156,258-259 Berg, L. J., 43,52 Berg, P., 221,251 Berger, A,, 3 17, 324 Berger, J.J., 361,445 Berggard, I., 358, 360,440 Berke, G., 21,52 Berliner, L. J., 136, 148 Bernar, H., 436,448 Bernard, 0.V., 169,238 Bernstein, F. C., 66,128, 153,238, 359, 440 Berry, J., 465,484 Bertoletti, A,, 43, 48 Berzofsky, J. A., 32,49, 213-214,238, 302, 323 Betley, G. A., 63, 106, 131, 306,324

489

Better, M., 231,256 Betz, A. G., 466-467, 469, 471, 481 Bevan, M. J., 5, 17-18, 36, 41, 42, 44, 48, 51,53, 311,324

Bhat, N., 185,243 Bhat, R., 377, 440 Bhat, T. N., 46, 48, 61,63, 64, 94, 96, 100101, 107, 111, 126,128-130,133, 196, 203, 21 1,238,257,259, 306, 324, 359,441 Biddison, W. E., 20,56 Bignami, G. S., 438, 440 Billetta, R., 222, 256 Bird, R. E., 223,238, 350, 353, 440 Birshtein, B. K., 469, 483 Birsner, U., 3 16, 326 Bizebard, T., 62-63, 64, 124, 130 Bjork, I., 340, 358, 360, 440, 443 Bjorkman, P. J., 12, 15-1 7, 19, 48-50, 64, 75, 78-79,128,235,241,311, 315, 324-325 Blackwell, T. K., 55 Blatt, Y . , 305, 307-310,318, 324, 327-328 Blattner, F. R., 432, 448 Blier, P. R., 61, 122, 130 Bloch, D., 4, 48 Blomgren, H., 318,323 Bloomer, A. C., 214,258 Blow, D. M., 197,200,243 Bluestone, J. A., 42-43,51 Bluethmann, H., 10,55 Blumberg, R. S., 39, 48 Blundell, T. L., 58, 128 Bode, C., 429-430,433435,437,440, 44644 7 Bode, W., 198,246 Boden, J. A., 365,438,441,448 Bodenhausen, G., 136,148 Bodmer, H., 15, 21,54 Bodmer, H. C., 17, 32,48 Boel, P., 322,328 Boersma, W. J. A., 317-318,328 Bogenhagen, D. F., 465,482 Bohm, D., 152,238 Bollinger, R. C., 20,50 Bolton, E. M., 296, 324 Bona, C. A., 296,325 Bond, M. W., 144,148, 178,237 Boniface, J. J., 23-25, 27-28, 34-35, 41, 43,52 Bonnert, T. P., 356, 445

490

AUTHOR INDEX

Bonneville, M., 459, 483 Boodhoo, A., 129 Bookman, M. A., 12,50, 224, 231,236, 352,355-356,364-365,367-368,370374,376,439,443,445,447449

Boon, T., 21, 48-49,52, 322,324,328 BOOS^, J.-A., 433,442 Boot, T., 21,52 Borek, F., 292, 301,324,327 Bork, P., 166-167,238 Born, M., 151,238 Bornhauser, S., 302,326 Boss, M. A., 220, 222,238,259, 349, 440, 449

Bossart, P. J., 203, 210-211, 220-221,251 Bosshard, H. R., 302,326 Bossie, A., 318, 328 Bosslet, K., 439, 440 Boswell, D. R., 11-12,49, 234,240 Both, G. W., 465,481,484 Bothwell, A. L. M., 25-27, 29,4Y, 54, 61, 122, 130, 465,475,481,484

Bottger, V., 219,238 Bottomly, K., 43,55 Boudinot, P., 455, 481 Bougueleret, L., 12, 15, 49, 234, 240 Boulianne, G . L., 222,238 Boulot, G., 15,46,48, 61-62,94, 96, 117, 125-126,128,130, 185,234,238,243, 306,324,359,381,441,444,476,481 Bourell, J. H., 230,247, 306,325 Bouthjillier, F., 63, 131 Boutin, R., 361,445 Bovey, F. A., 144,148 Bowdish, K., 210, 222,245,250 Bowie, J. U., 165,238,249 Boxer, G., 365,441 Boyd, D., 43,51 Boyd, J., 173,239 Boyd, L. F., 16, 19, 25-27, 29,49 Braciale, T. J., 17, 30,52 Braciale, V. L., 17, 30,52 Braden, B. C., 58,63, 100-101,129,306, 3 10,324 Bradley, J. A., 296,324 Brady, J., 186,256 Brady, R. L., 60, 128 Brady, W., 222,249 Brady, W. A., 23 1,245 Braisted, A. C., 271-272,286 Braley-Mullen, H., 318-319,324,328

Brampton, A. D., 173,239 Branchaud, B. P., 273-274,286 Branscomb, E. E., 430431,440 Bray, A. M., 261, 283,284 Bray, R. C., 427,448 Brehm, R. D., 320,323 Breitling, F., 231,247, 352, 367, 371, 444 Brenner, D. G., 439, 442 Brenner, M. B., 234,238 Breyer, R. M., 210,239 Brggemann, M., 462,468469,484 Briboulet, A., 282,287 Brice, M. D., 66, 128, 153,238, 359, 440 Brichard, V., 21,49, 322,328 Brick, P., 197, 200,243 Brinkmann, U., 227,239,253,258, 428, 440

Brisson, J.-R., 62, 128 Brocker, T., 40,55 Brockhaus, M., 10, 11,53 Brocklehurst, K., 283,287 Broder, S., 222,239 Brodeur, P., 381,448 Bromberg, S., 160,239 Brooks, B., 156, 181, 188,218,239,256 Brouwers, E., 436,443 Brower, R. C., 32,4Y Brown, J. H., 12, 17,49,54, 314, 320,325, 328

Brown, J. K., 3 1 1, 324 Brown, J. P., 438,447 Brown, R. K., 300,324 Bruccoleri, R. E., 155-157, 159, 163, 172, 186-191, 193, 195-197, 199-201,203205,210-211,213-214,216,219,223224,233,238-240,246,250-252,255, 298,300-301,326,347,398,400-401, 403,407414,417,420,423,426, 440,443,445-447 Bruderer, U., 466,484 Bruenger, A. T., 60-62,128,130 Brune, D., 171,239 Brunger, A. T., 137, 144,148 Briinger, A. T., 413,440 Brunmark, A., 23-29,35-37,41,44,46,54 Brunswick, M., 318,324 Brunt, E., 361,445 Bryant, S., 165, 183,239 Bryant, S. H., 64, 66, 75,128 Buchegger, F., 377,444 Buchner, J., 428, 440

AUTHOR INDEX

Buckley, C. E., 163-164,250, 343-344,446 Buckley, C. E. 111, 33 1, 337, 440 Bugg, C. E., 214,237 Bulens, F., 436,448 Buluwela, L., 460, 482 Bundle, D. R., 62, 64, 119, 128-129,132133, 171, 181, 185,241,259

Bunin, B. A., 261, 283,285 Burke, J. F., 427,448 Burke, P. J., 438, 448 Burley, S. K., 384, 440 Burmeister, W. P., 64, 75, 78-79,128 Burnet, F. M., 453,481 Burnett, W. V., 438, 444 Burton, D. R., 72, 128, 173-174, 176,239, 242,259,356,440

Busch, R., 21,51 Butler, V. P., 398, 448 Butler, V. P., Jr., 397, 448 Butler, W. F., 63, 131 Buus, S., 16, 19, 21, 29, 32,49,53 Bye, J. M., 356-357,376, 445,447 Byrn, R. A., 222,239 Bystryn, J. C., 323,324

C Caban, R., 435,447 Cabilly, S., 221,239, 349, 441 Cabral-Denison, N., 360-361,445 Cado, D., 8,50 Cafferkey, R., 222,245 Caldwell, J. B., 61, 130, 203, 225,244,247 Calvert, J. E., 222,259, 349, 449 Cammarota, G., 4 1,49 Campbell, D. A., 283,287 Campbell, D. H., 330,446 Campbell, R., 61, 132, 381, 383-384, 387, 39 1,448

Campbell, R. L., 62, 130, 189, 197,246, 354,400,404,408409,411,413, 420,443 Cannon, L. E., 177,245 Cantor, H., 319,323 Capon, D. J., 222,239,439,442 Capra, J. D., 381, 384,444445,447,459, 46 1,484 Caputo, A., 67, 128 Carbone, F. R., 36, 41, 42, 44,51 Carlsen, W., 31 7

49 1

Carlson, W. B., 214,251, 301,316 Carlson, W. D., 183,257 Carmack, C. E., 439,444,462,469,484 Carpenter, S. H., 267-268,285 Carperos, W., 60,132 Carter, D. C., 59, 130 Carter, M. S., 458,481 Carter, N. P., 460, 482 Carter, P., 60, 129, 182, 197, 200, 230, 239,242-243,247

Cartner, P., 306,325 Carver, M. E., 230,239 Casale, E., 59, 130 Casanova, J.-L., 19,53 Case, D. A., 156,258 Casorati, G., 10-11,53 Cassaza, A. M., 229,257 Cassimeris, J., 234, 238 Castagnoli, L., 298,323 Castelli, C., 21, 49 Cathou, R. E., 339, 346, 441 Catipovic, B., 222,241, 315-316,324 Cazenave, P.-A., 10,52,455, 481 Celis, E., 19, 29, 49 Cella, M., 35,55 Cerottini, J.-C., 48, 322,324 Cerundolo, V., 16, 19, 29-30,49 Cesareni, G., 298,323 Chace, D. F., 428,448-449 Chacko, S., 58-59,61,64, 127,128-129 Chamow, S. M., 222,239 Chan, A. C., 40,49 Chan, E., 461,483 Chan, H. S., 165,206,239 Chan, S. H., 40, 49 Chancock, R. M., 356,440 Chandler, D., 157,240 Chang, C.-H., 60,81,128,130,132 Chang, C. Y . , 60, 62, 64, 130, 189, 193, 197,246,354,400,404,408-409, 411,413,420,443 Chang, C.-Y. Y., 404,421,424-425,427,443 Chang, N., 229,257 Chang, T. W., 29,49 Changeux, J. P., 307,326 Chao, H. G., 232,243 Chap, R., 282,287,428,448 Chappel, M. S., 176,240 Charpie, J. R., 430, 441 Chaudhary, V. K., 225,240,428,440441 Chauhan, V. S., 291,327

492

AUTHOR INDEX

Cheadle, C., 360, 441 Cheetham, J. C., 181, 188, 192,249,253 Chen, B. L., 70, 81,131, 342-343, 349, 446 Chen, B. P., 19,49 Chen, F., 429,441 Chen, H. T., 455,481 Chen, J. P., 414,442 Chen, Y., 21,49 Chen, Y.-T., 322,323 Cheng, R. H., 63,131 Cherfils, J., 159-160, 209,240 Chesnut, R. W., 19,49 Cheson, B. D., 125, I29 Chess, L., 234,238 Chester, K. A., 365, 441 Chi, Y.-I., 320, 325 Chicz, R. M., 17, 18, 49, 314,324 Chien, N. C., 41 1,441 Chien, Y., 4, 8, 49 Chien, Y.-H., 43,52, 191, 233,240,252 Chin, D., 322,323 Chinitz, A,, 300,316 Chisari, F. V., 43, 48 Chitarra, V., 63, 106-107, 11 1, 129, I31 Chomerz, P., 322,328 Choppin, J., 225,250 Chothia, C., 11, 12, 46, 49,51, 86, 129, 155, 158, 160-161, 163, 165-170, 176, 181-182, 196, 198-199,230-231, 233-234,238,240,244-245,248-249, 257-258,347-348,413,441,457-458, 479480,481,484 Chou, C.-C., 433435,444,446 Christianson, D. W., 396, 444 Christinck, E. R., 19, 20, 30, 49 Chui, Y . L., 465, 467, 485 Chung, S., 224,245, 368, 442 Churchill, M. E. A,, 63, 64 Claassen, E., 317-318,328 Clark, A. D., Jr., 62, 128 Clark, G. M., 370, 448 Clark, M., 222,229,244,253 Clark, P., 62, 128 Clark, S. P., 4,55, 233,259 Clarke, J., 302,326 Claverie, J.-M., 12, 15,49, 234,240 Clayton, L. K., 166,240 Clegg, R. M., 309,324,326 Cobbold, S. P., 229,244 Cochet, O., 365, 441 Cochran, A., 273,286

Cochran, A. G., 262-263,285 Coelho-Sampaio, T., 231, 249 Coggeshall, M., 41,50 Cohen, D. I., 4, 8, 39,49, 51, 233,245 Cohen, F. E., 159, 181,244,253 Cohen, G. H., 60-61,88,98, 104, 125, 127,128,131-132, 170, 189,196,219, 252,254-255,257,342,447 Cohen, R. J., 7, 24, 25-29, 33-35, 36, 37, 4 1, 46, 49,54, 356 Cohn, M., 5,49 Colcher, D., 377,447 Cole, M. S., 232,248 Coligan, J. E., 19,53, 223,242 Collen, D., 429,431, 434, 436437, 441443,448 Coller, B. S., 436, 442 Collura, V., 187, 190, 244-245 Colman, P. M., 58, 60-61, 68, 70, 75, 8586, 117, 126,129-132, 161, 181-182, 197,203,213,219-221,225,230231,240,247-249,258,307,325, 370, 413,441,457458,481 Cob, S. M., 16, 21, 29, 32, 41, 48-49 Connell, G. E., 70, 129 Connolly, M. L., 66, 129, 158-159, 207,241 Conrad, B., 320,324 Constantine, K. L., 153, 241 Conway-Jacobs, A,, 301,327 Cook, G. P., 346348,441,460,482 Cook, W. D., 170,241,254 Copley, S. D., 267-268, 270,285 Corbella, P., 6, 49 Corbett, C., 341, 449 Corey, R. B., 168,252 Corr, M., 16, 25-27, 29, 49, 225,249 Cosand, W. L., 438,447 Cosgrove, D., 40,49 Coulie, P., 21, 49, 322,328 Coulson, A. R., 341,447 Courtet, M., 478, 484 Covarrubias, M., 230,247, 306,325 COX,A.L., 16-17, 21,49,51, 314,325 Cox, J. P. L., 199,259,457, 480, 484 Craig, L. C., 163,245, 341, 442, 453, 482 Crainic, R., 64, 133 Cram, D. J., 171,241 Crane, M. A., 455,483 Crea, R., 223-224,246, 350, 353, 355, 361,363-364,368,443 Creadon, G., 392,441

AUTHOR INDEX

Cresswell, P., 16, 20-21, 30, 48-49,53,55 Crimi, C., 19, 49 Crippen, G. M., 159,248 Crooks, M. E. C., 40, 49 Crumpton, M. J., 300,324 Cuello, A. C., 430, 448 Cumano, A., 390,439,463,471472,481482 Cumber, A. J., 352, 441 Cunningham, B. A,, 75,129 Cunningham, B. C., 210-211,241 Cun-xin, W., 151,259 Curtis, P., 229, 257 Cusack, S., 200,241 Cwirla, S. E., 261, 283, 284 Cygler, M., 62-63, 64, 64, 128-129, 131, 133, 171, 181, 185,241,259 Czech, J., 439,440

Daenke, S., 43,51 Dahlberg, C., 19,54 Dai, X., 41, 53 Dailey, H. A., 262-263, 285 Dall’Acqua, W., 46, 48, 61, 96, 126, 128, 133, 196,203,211,238,259,306,324 Dal Porto, J., 222,241 Damle, N. J., 222,249, 320,324 Dandliker, W. B., 305,326 Daniels, R., 62, 64 Daniels, R. G., 270,286 Dao-pin, S., 170,236 Darrow, T. L., 21, 49 Darsley, M. J., 171, 181, 219, 241 Darwin, C., 151,241 Dasgupta, J. D., 4 0 , 5 3 Dauter, Z.,61, 111, 131, 218-219,253 David, N. E., 439, 442 Davies, D., 61, 64, 86, 127, 128-129, 413, 441,457458,481 Davies, D. R., 9, 46, 49, 58, 60-61, 64, 6768,87-88,98, 104, 124-125,129,l31132, 138,148, 170, 176, 179, 181-182, 189, 196,219,230-231,240,252,254255,257,306,324,342,447 Davies, J., 352, 441 Davies, R. D., 170,254 Davies, S. L., 462, 468-469, 484 Davis, C. B., 40, 49

493

Davis, G. L., 229,254 Davis, M. M., 4, 8, 10, 12, 15, 23-25, 27-28, 34-35,39,41,43,49-52, 199,204205,223,233,235,239-241,244-245, 252,465,482 Davis, S. J., 166,246 Day, E. D., 19,50 Day, J., 60, 63,68, 118, 128, 130, 164,245 Day, L. A., 303,324 Dayan, M., 3 18,328 Dear, P. H., 226, 229,246, 349, 444, 458, 482 d e Boer, A. J., 21,48 De Bruin, M. L. H., 20,54 De Carli, M., 43, 48 Decker, D. J., 477,483 Declerck, P. J., 434,441 DeCloux, A,, 459,483 De Cock, F., 436-437,441,443 Deisenhofer, J., 59-60, 68, 72, 74-76, 7879,129,131, 174, 198,241,307,325 de Jongh, B. M., 19,50 d e Kroon, A. I. P., 315,324 d e la Cmz, X., 197,241 Delaney, J. R., 30, 36, 48 Delaney, R., 163,245, 300,324, 342,442 de la Paz, P., 171, 181, 241 Delbaere, L. T. J., 61, 111, 131, 218-219, 253 Delgado, C. H., 21,51, 322,325 del Guercio, M.-F., 19,54 DeLisi, C., 32, 49, 199,258, 377, 441 Dellabona, P., 10, 1 1 , 5 3 Delori, P., 2 14,242 Delpeyroux, F., 64, 133 DeMagistris, M. T., 41, 5 0 DeMars, R., 19, 49,54 Demarsin, E., 436, 443 Dembic, Z., 4 , 5 0 Demotz, S., 17, 20, 30,50, 316,324 Deng, S.-J., 62, 133, 171,259 Denishefsky, S. J., 263,285 Denzin, L. K., 202, 225,241, 256 DePinho, R. A., 234,238 DePlaen, E., 21, 49,52, 322,328 Deres, K., 16, 17, 18, 21, 3 2 , 5 0 , 5 3 Derrick, J. P., 63, 129 Desiderio, S. V., 61, 119-120, 128, 130, 460,484 De Smet, C., 322,328 Desplancq, D., 224-225,241, 353,441

494

AUTHOR INDEX

Dessi, V., 302,326 De Sutter, K., 222,241 Deutsch, H. F., 60,67-68, 125,129-130 Devlin, J. J., 261, 283,284 Devlin, P. E., 261, 283,284 Devos, P., 429,442 Dewerchin, M., 436437,441,443,448 Dialynas, D. P., 234,238 Diamond, B., 396, 441 Diamond, R., 161-162,241 Dianzani, U., 43,55 Diaz, P., 8,50 DiBrino, M., 19,53 Dickinson, T. A,, 17,51 Dildrop, R., 390,439,472473,481,484 Dill, K. A,, 160, 165, 206,239, 241 Ding, J., 62, 128 Dintzis, H. M., 75, 131, 318,324 Dittmar, M. T., 40,50 Doering, W. v. E., 272,286 Doherty, P. C . , 5,56, 234,260 Doig, A. J., 199,259 Domogatsky, S. P., 430, 447 Dongworth, D. W., 463,482 Doniach, S., 209,252 Doolittle, R. F., 163, 256 Dorai, H., 229,254, 370,441 Doran, D. M., 41,49 Dorf, M. E., 5,51 Dorrington, K. J., 170, 176,240,246, 3 10, 323

Doscow, J., 458,481 Dower,S. K., 135,148, 177, 179-180,241242,258,377,441

Dower, W. J., 261,283,284 Drake, C. G., 320,324 Drapier, A. M., 455, 481 Dreher, M. L., 471,482 Drenth, J., 58, 129 Dreyer, W. J., 341,441,453,482 Drier, E., 360-361, 445 Drijifhout, J. W., 19.50 Driscoll, P. C., 166,242 Drohan, W. N., 181, 210,218,248,256, 411,444

Dubel, S., 231,247, 352, 367, 371, 444 Dudzik, K. I., 223,244 Duncan, A. R., 174, 176,242 Duncan, J. F., 229,253 Dunitz, J. D., 212,242 du Pasquier, L., 478,484

Duquerroy, S., 159-160, 209,240 Durfor, C . N., 283,287 Dutz, J. P., 17, 30, 36, 37, 46,50 Dwek, R., 136, 139,148, 173,239 Dwek, R.A., 135, 144,148, 177, 179-180, 241-242,248,257-259

Dwight, R. A. H., 63,64

E Early, 169-170,242 East, I. J., 213-214,238, 300, 302,323,328 Easterbrook-Smith, S. B., 173,239 Eberle, T., 430, 440 Edelman, G. M., 75,129, 163,242,333,441 Edidin, M., 31 5-31 6,324 Edman, P., 341,441 Edmundson, A. B., 59-61,63,68, 70, 122, 125,129-130,132, 168, 185, 197,202, 236,242,245, 307, 310,323,325, 343,349,447 Edwards, A,, 43,51 Edwards, D. J., 60,128 Edwards, J., 43,51 Edwards, M. S., 213-214,238,257 Eggensperger, D., 377,447 Ehrlich, P., 452,482 Eigen, M., 303,324-325 Eigenbrot, C . , 60,129, 182, 230,242,247, 306,325 Eilat, D., 223,242 Eisele, J.-L., 63, 100-101, 107, 111,128-129 Eisen, H. N., 4, 7 , 10-1 1, 15-39, 41, 44,

46,49-55,233-234,251,254,311, 314,322,325,328, 337,342,356-

357,360,441-442,449,455,482 Eisenbach, L., 21,52 Eisenberg, 249 Eisenberg, D., 157, 165, 208, 212,238,242 Eisenhaber, F., 183,255 Eisenstein, E., 305-306, 328 Eisenstein, M., 2 1,52 El Ayeb, M., 214-215,237,242,244 Eliyahu, S., 21,51, 322, 325 Ellenberger, J., 392,441 Ellington, A. D., 261, 283,284 Elliott, T. J., 16, 19, 29, 46, 49-50 Ellman, J. A., 261, 283,285 Elofsson, M., 302,325 Elvin, J., 16, 19, 29,49

AUTHOR INDEX

495

Elvin, J. G., 467,484 Ely, K. R., 59-60, 68, 70, 125, 129,132,

Fazekas d e St. Groth, B., 15, 24-25, 34,41,

168,242,310,323, 343,349,447 Emanuel, E. J., 173,239 Emtage, J. S., 60, 128, 222,259, 349, 449 Endres, R., 3 18,324 Engel, J., 304, 315, 317, 324,326 Engelhard, V. H., 16, 20, 21,49,51, 314, 325 England, R., 32, 49 Englander, S. W., 213, 218,252 Ennen, J., 40,50 Entage, J. S., 220,238, 349,440 Epp, O., 60, 75, 129 Epstein, C. J., 162,242 Epstein, R., 5, 49 Erard, F., 44,50 Eren, D., 267-268, 270,285 Erickson, H. P., 29,53 Ernst, E., 227,237 Ernst, M., 40,50 Ernst, R. R., 136,148 Escobar, C., 63, 118,128 Eshhar, Z., 63, 124, 130, 223, 225, 228, 242,244,282,287,322,327,428,448 Essen, L.-O., 63, 129, 182, 243 Esser, A. F., 302,326 Esser, U., 15,51 Eulitz, M., 60, 130 Evans, S. V., 62, 119,129 Evavold, B. D., 41, 42,50,54 Even, J., 455,461462,470,475,480,483 Everett, M., 176,240 Ewald, P., 198,243

Fearon, D. T., 222,241 Feeney, A. J., 459,484 Fehlhammer, H., 60, 129 Feigelson, D., 144, 148 Feldman, M., 2 1,52, 3 17,324 Feldman, R., 309,325 Feldman, R. M. R., 19,50 Feldmann, R. J., 181, 218,243,256 Fell, H. P., 222, 231,244-245 Fellows, R. E., 163,245 Fellows, R. E., Jr., 342, 442 Feltkamp, M. C . W., 19,50 Fendly, B. M., 204, 210-211, 216, 219,

Faath, S., 16, 32, 44, 46,53 Fahnestock, M. L., 19,50, 315,324 Fairchild, P. J., 22, 29,50 Fairman, R., 232, 243 Falk, K., 16-18, 20-21, 32, 44, 46,50,53, 296,311-312,327

Fan, Z.-C., 59, 129, 307, 310,325 Fand, I., 224, 231,236, 352, 355, 364, 367368,370-374,439,443,445,448

Fanning, D. W., 214,243,251, 301,326 Farrar, J., 3 18,326 Fausch, M. D., 125,129

51-52

230,246,253

Feng, S.-L., 224,258,352-353,355,449 Fermandez-Botran, R., 318,328 Ferrari, C., 43, 48 Ferreira, S. T., 231,249 Ferris, A. L., 62, 128 Ferrone, S., 323,324 Fersht, A. R., 197,200,243 Festenstein, H., 319,324 Fett, J. W., 68, 130 Feynman, R. P., 151-152,243 Fiaccadori, F., 43, 48 Fidelis, K., 243 Field, H., 350, 441 Fields, B. A., 61,133, 21 1,259, 305-306, 328

Fields, L. E., 465, 481 Fiers, W., 222,241 Fieser, G. G., 63, 64 Fieser, T. M., 61, 132, 197,256 Figdor, C. G., 21, 48 Filman, D. J., 64, 133 Filpula, D., 224,258, 352-353, 355, 449 Findeklee, H., 40,50 Fine, R. M., 66, 132, 171, 186-187, 190, 237,243,247,249

Finegold, D., 320,324 Fink, P. J., 12,50 Finkelman, F. D., 318,324 Finkelstein, A. V., 200,243 Finkelstein, D., 436, 442 Finnern, R., 356,445 Finney, J. L., 159, 200,241,243 Finzel, B. C., 61, 98, 132, 2 19,255 Firestone, R. A., 229,257 Fischer, E., 196,243

496

AUTHOK INDEX

Fischer, K. J., 438, 440 Fischer Lindahl, K., 44,50 Fischmann, T. O., 61, 94, 96, 128, 130, 185,243,359,441 Fishwild, D. M., 439, 444 Fita, I., 197,241 Fitch, F. W., 4,52, 316,324 FitzGerald, D. J., 225, 227,239-240, 428, 440-441 Fitzgerald, K. A,, 4,52 Flajnik, M. F., 478, 482 Flanagan, J. G., 222,250 Fleischman, J. B., 333,442 Fleming, J. E., 262-263,285 Fletterick, R. J., 63, 124, 133, 261, 266, 284-285 Flory, P. J., 165,243 Flynn, G., 347,446 Fodor, S. P. A,, 261, 283,284 Foeller, C., 67, 130, 348, 400, 404, 444 Folks, T. M., 316,325 Fontecilla-Camps,J. C., 214-216,237,243244,246 Foote, J., 10, 26, 28-29, 46,50, 182, 226, 229,243,246, 31 1,325, 349, 357, 442,446,452,458,460,462,473,482 Foote, P. H., 349,444 Ford, J. E., 455,470,482 Forres, B. A,, 325 Foster, L., 30,54 Fougereau, M., 475,484 Fourquet, P., 215,244 Fox, J., 129,230,242 Fox, R. O., 128, 137, 144,148,222,250, 349,432,445 Frankel, S. R., 16, 49 Freedman, M. H., 300,325,340,442 Freeman, G. J., 291,325 Freire, E., 199-200, 204, 206,250 Freitag, M., 434-435, 437, 440, 446 Freitas, A. A,, 461, 482 Fremont, D. H., 17, 46,50,52, 62, 133, 312,314,325 Freund, C., 225,243, 306,325 Frey, T., 139, 143-144,148, 178,237 Fridkin, M., 21,52 Friedman, A. R., 209,243 Friedman, M. L., 243 Friedman, R., 171, 196, 206,255 Friedman, S., 148, 303-304,325

Friedrichs, M. S., 153,241 Froese, A,, 303, 305,325 Frolow, F., 21 1-212,255 Fruchter, R. G., 343,442 Fruh, K., 20,54 Fuchs, S., 317,325-326 Fuertges, F., 298,325 Fuhua, H., 151,259 Fujii, I., 283, 287 Fujio, H., 300,326 Fukusen, N., 18, 24, 25,44,55 Fuller, K. A., 291,325 Fuller-Farrar, J., 318,326 Fulton, R. J., 428, 449 Furey, W., 320,328 Furey, W., Jr., 60,128, 130

Gaeta, F. C. A,, 41,48,50 Gaffney, P. J., 436, 443 Gagne, S. M., 62, I28 Gait, M. J., 454, 482 Gajewski, T., 316, 322,324,328 Gakamsky, D. M., 315,325 Gall, W. E., 75, 129 Gallacher, G., 283,287 Gallo, J., 372,449 Gammon, M., 20,48 Gammon, M. C., 20,56 Ganju, R. K., 188,203, 225,235-236,243, 251 Gansemans, Y., 436,443 Garboczi, D. N., 17,46,52,3 13-3 14,326 Garcia, C., 199, 206,250 Garcia, K. C., 61, 119-120, 130 Garcia, K. S., 119, 128 Garcia, R., 63, 118, I28 Gardner, M., 199,259 Garlick, R. L., 41,55 Garnier, J., 187, 190, 244-245 Garrett, T. P.J., 17,41,50,55,31 1,325 Garrigues, U., 428, 448449 Garza, D., 439, 442 Gascoigne, N. R. J., 223, 233,240,244 Gascoigne, R. J., 43,48 Gately, M., 428, 440 Gavish, M., 360,442 Gawlak, S., 428, 449

AUTHOR INDEX

Gayle, M. A,, 23 1 , 245 Gearhart, J. D., 465,484 Gearhart, P. J., 456, 465, 475, 482-484 Gefter, M., 31 1-312, 327, 381, 385,445, 44 7 Gefter, M. L., 21,53, 222,255, 381, 384, 386,389-390,444449,455456,463, 465,470471,475,477,483484 Gelatt, C. D., Jr., 188, 247 Gelin, B. R., 67, 130, 426,442 George, A. J. T., 225,248, 355,361,364,

366, 368-369,373,375-376,442-443 Georgiadis, T. M., 283,287 Gerard, R. D., 433,442 Gerhard, U., 199,259 Gerhard, W., 24, 25,55 Germain, R. N., 4, 20, 22, 42,50,52-53, 313,315,326

Gernstein, M., 160, 166,245 Gerstein, M., 160,244 Gerstein, R. M., 469, 484 Gether, U., 222,241 Gething, M.-J.,433,442 Getsoff, E. D., 41 1, 441 Gettins, P., 136, 139, 148, 177, 179-180, 241-242,257-258

Getzoff,E.D., 182, 191,210-211, 213214, 218, 222,240,244,250,254,257, 300,327 Geuze, H. J., 21,52 Geysen, H. M., 59,129, 211, 213-214, 218, 244,261,283,284 Gherardi, E., 170, 181,240, 341, 347-348, 441442,455,457,461462,470473, 475,479430,481484 Ghiara, J. B., 63, 130 Ghiara, P., 298,323 Ghrayeb, J., 229,257 Giangrande, P., 43,51 Giannini, S. L., 469, 483 Gibrat, J. F., 187, 190,244 Gigant, B., 63, 124,130 Gilbert, W., 341, 445 Gill, D. S., 397, 449 Gill, S. J., 377, 380, 449 Gilliland, L. K., 231,245 Gilmore, D., 473,482 Gimmi, C. D., 291,325 Gimple, L. W., 436, 442 Ginsberg, M. H., 437,441

497

Girling, R. L., 70, 125, 129, 132, 343, 349, 447

Giusti, A. M., 170, 191,240-241,254, 41 1, 441,469,482

Givol, D., 148, 163, 177, 179-181,241-242, 246,252,257-259,303-305,307,325, 327,347,349,352,360,441443,447 Glas, R., 20,56 Glaudemanns, C . P. J., 181,243 Glaudemans, C. P. J., 307-310,326-328 Glenney, J. R., Jr., 191,254 Glickman, M., 283,287 Glimcher, L. H., 319,323 Glockshuber, R., 227,244,353,442 Go, K., 414,442 Go, N., 187,244 Godeau, F., 19,52-53,225,250 Godel, K., 151, 244 Godelaine, D., 322,323 Gold, H. K., 436,442 Gold, L., 261, 283,284 Goldbaum, F. A., 61,133,211,259,305306,328 Goldberg, A. L., 20,50 Goldstein, D. J., 75,130-131 Goldstein, J., 436,449 Golinelli-Pimpaneau, B., 6243.64, 124, 130 Gololobov, G. V., 270,286 Gomez, S. M., 223,244 Gomi, H., 230,250 Gonfloni, S., 298,323 Gong, B., 280,282,286-287 Gonzalez, T., 129, 230,242 Gonzhlez-Fernhndez, A,, 455,46 1 4 6 3 , 465,467,469470,473,475,480,481483,485 Gonzhlez-Gernndez, A,, 465, 467, 480, 482 Goodall, M., 78, 131 Goodfellows,J. M., 212,259 Goodman, J. W., 262,285 Goodman, L. J., 418419,445 Goodnow, C. C., 223,244,463,473,484 Goodsell, D. S., 209,244 Gordon, J., 463,483 Gordon, R. D., 5,50 Gorga, J. C., 17, 18, 21,49,51,54, 311312,314, 320,324-326,328 Gorick, B. D., 356, 445 Gorka, J., 17, 30,52 Gorman, C. M., 230,239,253,418419,445

49 8

AUTHOR INDEX

Gorman, S. D., 229,244 Goshorn, S. C., 222,244 Gotch, F., 30, 49 Gotch, F. M., 7, 54 Gottesman, K. S., 67, 130, 181, 229,247, 348,400,404,444 Gottlieb, P. D., 75, 129 Gould, H. J., 176,257 Gouth, N. M., 169,238 Gouverneur, V. E., 276-277,286 Goverman, J., 12,55, 223,244 Goyenechea, B., 465,467,485 Grandea, A. G., 381,449 Granier, C . , 214-215,237,242,244 Gray, G., 291,325 Gray, J. V., 267-268,270,285 Gray, W. R., 59, 129, 453,482 Green, A., 365, 441 Green, B. S., 63, 124, 130, 282,287,428, 448 Green, L. L., 439,442 Green, N. M., 163,258,343-344,448 Greenberg, A. S., 478,482 Greene, M. I., 46, 48, 61, 96, 126, 128, 196,203, 21 1, 219,238,248,306,324 Greenspan, N. S., 218,244,296,325 Greenstein, J. L., 39, 48 Greenwood, A,, 60, 63, 68, 118, 128, 130, 164,245 Greer, J., 179,244, 359, 442 Gregoire, C., 223,244 Gregoret, L. M., 159,244 Gregory, T., 222,239 Greschik, H., 427, 448 Grey, H. M., 16-17, 19-21, 29-30, 32,41, 48-51,54,3 15-3 16,324,327 Gribben, J. G., 291,325 Gridley, T., 381, 386, 445,449 Griffin, J. A,, 64, 64 Grifiths, A. D., 232, 249, 350, 352, 356, 445,449 Griffiths, G. M., 454, 456, 463, 475, 482 Griggs, N. D., 325 Grimal, H., 455, 484 Groopman, J. E., 222,239 Grosmaire, L., 222,249 Gross, G., 223, 225, 228,242,244 Grossberg, A,, 262,285 Grossberg, A. L., 177, 201,253 Groth, H., 67, 133 Grothaus, P. G., 438,440

Groudine, M., 469,483 Gruen, L. C., 61,130, 203, 225,244,247 Grusby, M. J., 319,323 Guardiola, J., 41, 49 Guddat, L. W., 59, 63, 68, 129-130, 307, 310,325 Guild, B. C., 218, 231,252 Guilford, W. J., 267-268, 270,285 Guillot, S., 64, I33 Guindon, C . A., 229,254 Gulliver, G. A,, 202,241 GUO,H.-C., 17,50 Guo, J., 63, 124,133,261,266,284 Gupta, S. K., 465,467, 472-473, 480, 482483 Gurd, F. R. N., 213-214,238,302,323 Guss, J. M., 60, 129 Gussow, D., 352,449 Guth, B., 225,243 Guzikevich-Guerstein, G., 21 1-212,255

Haas, E., 315,325 Haas, W., 4 , 5 0 Haba, S., 381, 444 Haber, E., 7, 21,48, 62, 130, 162-163, 168-169, 176-177, 188-191, 193, 197, 203-204,210-211,214-216, 219,223225,227,231,233-234,237,239,245246,251,255,257,301,326,329-331, 334-337,339-342,346-347,349-350, 352-355,357-359, 361-364,366,368, 373,397-398,400-401,403-404,407409,411,413-414,417,420,423,432,

434,439443,445449,452,482,403, 407,410-412,423,426,428-434,444, 435, 4 3 7 , 4 4 0 4 4 1 , 4 4 3 4 4 7 Habersetzer-Rochat, C., 216,243,246 Habu, S., 262,285 Hackett, J., Jr., 465, 482 Hadzi, D., 198,247 Hagler, A. T., 156, 198,245,247 Hagstrom, R., 171,247 Hainaut, P., 322,328 Haire, R. N., 454,483 Haldane, J. B. S., 262, 265,285 Hales, J. F., 439, 442 Hama, K., 222,257 Hamaoka, T., 5 , 5 1

AUTHOR INDEX

Hamers, C. C., 454,482 Hamers, R., 454,482 Hamilton, J. A,, 400,443 Hamlyn, P. H., 454, 482 Hammerling, G. J., 20,52 Hammond, S. A., 20,50 Hampl, J.,43,52 Handschumacher, M., 159, 176, 195,213214, 216,219,231,251,298,300301,326 Hannum, C., 4,51,213-214,238,302,323 Hamburg, D., 12,55 Hansen, A. S., 16, 19, 29,53 Hansen, P. R., 16, 19, 29,53 Hanson, B. L., 59,129 Hanson, S. R., 435,447 Hardardottir, F., 11,50 Harding, C. V., 20, 30,50, 302,325 Harding, F. A., 439,444 Hardman, K. D., 223-225,238,256,258, 350, 353,355,440,449 Hardman, N., 229,247 Hardy, M. C., 439,442 Harker, L. A,, 435,447 Harker, M., 59, 129 Harley,V. R., 61, 85, 117, 131, 170, 196197,201,203,210-21 1,219-221,249, 258 Harlos, K., 166,246, 320,323 Harpaz, Y., 160, 166-167,245 Harrer, T., 20,56 Harris, D. L., 59, 129 Harris, L. J., 60, 68,130, 164, 231,245-246 Harris, T. J., 433, 442 Harrison, S. C., 41,55 Harrris, L., 162, 182, 184,237 Harty, J. T., 17, 18,53 Hasel, K., 63, 118, 128 Hasel, K. W., 60,68,130, 164,245 Haselkorn, D., 148, 303-305,325 Hashimoto, Y., 429,442 Haskins, K., 4 , 5 1 Hassig, C. A,, 197,237 Hauer, M., 322,328 Haupt, H., 75,129 Hawkins, J. C., 20,56 Hawkins, R. E., 203, 210,245, 350,356, 365,441,449 Hawley, R. G., 22 1,251 Hayashida, H., 454,482 Hayashida, M., 322,325

499

Hayday, A. C., 4, 39,53 Hayday, A. D., 233,254 Hayden, M. S., 231,245 Haynes, M. R., 63, 123,130, 261, 266, 268, 284 He, X.-M., 59, 61, 122,129-130, 185, 197, 202,236,245 Heath, W. R., 10, 36, 44,51 Hedrick, S. M., 4, 12, 39,50-51, 223, 233, 238,245 Heeg, K., 320,326 Heelan, B. T., 361,368-369,373,375-376, 442443 Heemels, M.-T., 20, 30,51-52,54 Heisenberg, W., 151,245 Hellstrom, I., 60, 64, 130, 193, 229,246, 257,428,438,444,447-449 Hellstrom, K. E., 60, 64, 130, 193, 229, 246, 257,428,438439,442,444,447-449 Helm, B. A., 79,130 Henderson, A. J., 229,257 Henderson, R. A., 16, 20-21, 49,51, 314, 325 Hendrickson, W. A., 41,52-53, 214, 233, 248,257,426,448 Hengstschlger, M., 469, 482 Henner, D., 230,239 Henry,A. H., 153, 192,211,218,231,252, 258 Hensley, P., 153,241 Hercend, T., 4,52 Herman, A., 319,328 Hermans, J., 156,245 Hermes, J., 20,48 Hermes, J. D., 20,56 Herron, J. N., 59,61,68, 122, 125,129130, 185,197,202,236,245,304305,325 Hershey, C. W., 218,256 Hershey, E. D., 218,256 Herzenberg, L. A., 191,221-222,250-251, 255,?27,411,413-414,420,446447

Hess, A. C., 70, I29 Heya, T., 377,447 Heyneker, H. L., 221,239,349,442 Hiatt, A., 222,245 Hibbits, K., 61, 64 Hibbs, A. R., 151,243 Hicks, A. N., 305,326 Hicks, J. B., 282,286 Higginbottom, A., 79, 130

500

AUTHOR INDEX

Higgins, D. L., 427, 442 Higgins, K. M., 439, 444,462,469,484 Higo, J., 187, 190,244-245 Hill, K. W., 271,286 Hill, R. L., 163,245, 342,442 Hiller, R., 144, 148 Hilschmann, N., 163,245, 341, 442,453, 482

Hilvert, D., 63, 123, 130, 186, 261, 266268,270-271,282,284-285

Hilyard, K. L., 224, 245, 368, 442 Himmelspach, K., 308,327 Hinds-Frey, K. R., 454,478,482483 Hinkle, G., 377,447 Hirabayashi, Y., 460,483 Hiroto, M., 298,327 Hirs, C . H. W., 58, 133 Hirschberg, D. L., 438, 444, 447 Hirschmann, R., 265,285 Hizi, A., 62, 128 Hochman, J., 163,246, 307,327, 347, 349, 352,360,442-443

Hodgdon, J. C., 4,52 Hodsdon, J. M., 60, 129 Hoekstra, D. M., 396,440 Hoeveler, A,, 40,55 Hoffmann, R., 270,286 Hoffren, A. M., 246 Hofstead, S., 229,257 Hogg, P. J., 377,442 Hogle, J., 64, 133 Hoglund, P., 30,52 Hogquist, K. A., 36,51, 3 11,324 Holak, T. A,, 225,243, 306,325 Holliger, P., 64, 131, 197, 224,246,252, 352-353,355,442

Holm, A., 16, 19, 29,53 Holm, L., 166-167, 183,238,246 Holmes, W. E., 221,239, 349, 441 Holowka, D., 74, 133 Holvoet, P., 429, 436, 441443 Hong, S.-C., 17, 18,53, 316,327 Honig, B., 66, 126,130, 132, 171, 188, 196, 199,206,247,250,255-256,424,445

Honjo, T., 222,257, 262,285, 460, 483 Hood, L., 12,55, 223, 233,237,244,453, 482

Hoogenboom, H. R., 232,249,347, 350, 356,367,445-446,449

Hook, L. E., 360, 441 Hoon, D. S. B., 322,325

Hopper, J., 262,285 Horne, C., 170,246 Horton, N., 199,246 Horwitz, A. H., 231, 256 Hotaling, T., 129, 230,242 Houchens, D., 377,447 Houdusse, A., 63, 107, 11 1, 129 Houghten, R. A,, 214,257 Housset, D., 216,246 Houston, J. S., 224, 231,236 Houston, L. L., 224, 231,236, 352, 355356,361,364-365, 367-376,439,441443,445,447-449 Howard, J. L., 36,51 Howard, M., 318,326 Howlett, G.J., 61, 130, 225,247 Hozumi, N., 221-222,238,251 Hsiao, K. C., 231,246 Hsieh, C. L., 469, 484 Hsieh, L. C., 273, 275, 278,286 Hsu, E., 478, 484 Hsuin, P., 263,285 Huang, D.-B., 60,130 Huang, E. C., 21,49 Huang, P. L., 433435,444,446 Huang, S., 381,449 Huang, S.-Y., 381,386,444445,448 Huang, W., 63, 124,133,261,266,284 Hubbard, R. E., 60,128, 144, 148 Huber, A. H., 64,75,78-79,128

Huber, R., 59-60,68,72,74-75,129,131132, 198,246,307,325

Huberman, E., 322, 323 Hubert, S. L., 224,258, 353, 355, 449 Hudelmayer, M., 437,440 Hudson, N. W., 349,400,407,432,434, 443,445,447

Hudson, P. J., 61, 130, 225,247 Hudziak, R. M., 352,355,364,367-368, 370-374,441,443,445,448

Hue, I., 475, 484 Hughes, A., 478,482 Hughes, M., 478,482 Hughes, S. H., 62, 128 Hughes-Jones, N. C., 356,445 Hui, K. Y., 429430,440,443 Huler, E., 156,245 Hull, L., 19,53 Hulst, M., 454, 483 Humphrey, J. H., 317,325-326,463,482 Humphrey, R. L., 75.130-131

AUTHOR INDEX

Humphreys, T., 438,440 Hunkapiller, T., 223,244 Hunt, D. F., 16-17, 20-21,49,51, 314,325 Hurd, M. E., 44,51 Hurwitz, E., 321-322, 323, 327 Husain, Y., 41,55 Hussey, R. E., 4,52, 188, 203, 225, 235,251 Huston, J. S., 223-225,246,257, 329, 350, 352-356, 358-376,439,441443,445, 447-449 Huszar, D., 439,444, 462, 469,484 Hynes,T. R., 128, 137, 144,148

I Ichihara, Y., 454,459, 482 Igarashi, T., 222,246 Iglesias, A., 10,55 Iida, E., 227,237 Ikeda, S., 263,285 Imaeda, S., 20,54 Imanishi-Kari, T., 475, 481 Irnarai, M., 17,46,55, 312,328 Irnmonen, T., 224,257 Imura, Y . , 431,443 Inada, Y . , 298,327 Inbar, D., 163,246, 347, 349, 352, 360, 442-443

Inman, J. J., 318,324 Ip, S., 234,239 Irving, B. A., 39,51 Isakov, N., 42,52, 313, 315,326 Isenberg, D., 302, 327 Isenman, D. E., 176,240 Itano, A,, 6, 49 Itzhaky, H., 279,286 Ivancic, N., 61, 130, 225,247 Iverson, B. L., 222,254, 263, 283,285,287 Iverson, S. A., 222,254 Iwabuchi, Y., 186, 279 Iwasa, S., 431, 443-444 Iwashima, M., 40, 49 Izadyar, L., 282,287

J Jackson, Jackson, Jackson, Jackson,

C. S., 283,287 D. Y . , 267-268,285 M., 23-29, 35-37,41,44,46,54 M. R., 19,52

50 1

Jackson, R. C . , 177,241 Jackson, R. M., 194, 199,246 Jackson, S., 316,325 Jackson, S. A., 343,442,445 Jackson, W. R. C., 144,148,248 Jacob, J., 462463,477,482 Jacobo-Molina, A., 62, 128 Jacobs, J.W., 124,132, 261-262,271,284 Jacobsen, J. R., 263-265,285 Jacobson, J. W., 223,238, 350, 353,440 Jacobson, M. A., 407,432,445 Jacobus, C. M., 231,248 Jaenichen, R., 466,482 Jager,G. C., 191,255,411,413-414,420, 44 7

Jakobovits, A,, 439, 442 Jamar, F., 361,368-369,373, 375-376, 442-443

James, M. N. G., 186,250 Jameson, S. C., 36, 4 1 4 3 , 4 8 , 51, 31 1, 324 Janda, K. D., 263,277-278,280-281,283, 285-28 7 Janeway, C., 319,325 Janeway, C. A., Jr., 11, 17, 18, 20, 42-43, 50,53-55,3 17,3 19,325

Janeway, C. J., 316,327 Janin, J., 46,51, 159-160, 169, 194, 196, 199-200,209,240,243,246

Janssens, C., 2 1,52 Jardetzky, O., 136, 148, 154,259 Jardetzky, T. S., 12, 16-17, 21, 49-51,54, 311,314,320, 324-325,328

Jardieu, P. M., 230,253 Jarvis, J., 384, 444 Jarvis, J. M., 11,52, 62,128, 455, 461-462, 465,467,470,473,475476,480, 481,483-484 Jaton, J. C., 304, 315,326 Jaulin, C., 225,250 Jedrzejas, M. J., 64, 64 Jefferis, R., 78,131, 174,259 Jeffrey, P. D., 60, 62, 64, 130, 189, 191, 193, 197, 246,255, 354, 398, 400, 404,407-409,411,413414,416-417, 4 1 9 4 2 1 , 4 2 3 4 2 5 , 4 2 7 , 4 4 3 , 447-448 Jelesarov, I., 302,326 Jelonek, M. T., 25, 26, 27, 29,49 Jemmerson, R., 305-306,327 Jencks, W. P., 123, 126,130, 263,285 Jenis, D. M., 21, 29,49 Jenkins, M. K., 42,51-52

502

AUTHOR INDEX

Jensen, L. H., 58,132 Jerne, N. K., 117,130,452,482 Jernigan, R. L., 250 Jeske, D. J., 384,444 Jiang, F., 159, 209, 246 Jiang, J.-S., 60, 128 Jin, D., 350,352,356355,358-359, 364, 366-368,370-374,443,445,448

Jin, L., 204, 210-211,216,219,246 Joachimiak, A., 2 11-2 12,255 Johansen,T. E., 222,241,315-316,324 Johns, J. A., 436,442 Johnson, C. A., 144,148 Johnson, G. D., 463,483 Johnson, H. M., 325 Johnson, J. L., 19,50, 315,324 Johnson, L. N., 58, 128 Johnson, M. J., 222,250 Johnson, R. P., 17-18,20-21, 30,55-56 Johnson, S., 223,238, 350,353,440 Johnson, V. G., 367,445 Jondal, M., 20,56 Jones, E. Y., 166,246, 320, ?2? Jones, P. T., 226, 229,246, 349, 352, 444, 449,458,482 Jones, R., 177,242 Jones, T.A., 60,75,78-79,129,132, 170, 179-180, 183, 231,246 Joo, M., 3 1,54 Jordan, P., 151,238 Jores, R., 235,246 Jorgensen, J. L., 15,51 Jorgensen, W. L., 156,209,246 Joshua, D. E., 463,483 Jost, C. R., 225,23 1,248 Jouhal, S. S., 222,250 Jouvin-Marche, E., 10,52 Jovin, T. M., 309,324,326 Ju, A., 361, 398,400,445 Jue, R. A., 63,131 June, C. H., 42,51,318,324 Jung, G., 16-18,20-21,32,50,53 Jung, S. H., 227-228,247,253 Junghans, R. P., 225,229,240,253,428, 441 Jureziz, R., 67, 131 Jurs, P. C., 159,256 Juszczak, E. C., 381, 384,444-445 Juszczak, E. J., 384,444

Kaartinen, M., 224,257, 454,456,463, 475,482 Kabat, E. A., 67, 90, 125,130,133, 168, 177, 181, 186, 210, 229,247,259, 342,348,400,404,444,449 Kabsh, W., 161, 190,247 Kadow, J. F., 438,448 Kageyama, S., 17,20,23-32,35-37,44, 46,50-51,54,311,314,325 Kahn, R., 62,64 Kaiser, K., 210,250 Kakinuma, A., 431,444 Kalbacher, H., 17, 30,54 Kam-Morgan, L., 61, 127,128,203,247 Kanagawa, O., 291,325 Kanaoka, M., 230,250 Kane, K. P., 44,51 Kang, A., 261,283,284 Kang, A. S., 356, 397,416,440 Kannourakis, G., 463,473,483 Kantesaria, D. V., 20,54 Kanyo, 2. F., 396, 444 Kanzy, E. J., 223,254 Kao, C. Y. Y., 229,247 Kaplan, M., 302,326 Kappler, J. W., 4-5,51,297,318-319,324326,328 Karaki, Y., 283,287 Karjalainen, K., 15, 24-25,48,55, 234, 238,462,475,483 Karlsson, F. A., 358,360,440 Karpas, A., 341, 356,445 Karplus, M., 66-67,130, 155-157, 163, 183, 186-188, 197,200,233,239-241, 251,256-237,347,426,440,442 Karre, K., 30,52,54 Kartha, G., 414, 442 Karush, F., 19,51, 177,247, 396,444 Kassir, R., 462463,477,482 Kast, W. M., 19-20, 30,50,54 Katchalski, E., 317,324 Katsube, Y., 222,246 Katsuragi, T., 438,447 Katz, D. H., 5,51 Kaufman, B. M., 223,238,350,353,440 Kauzmann, W., 195,206,212,242,247, 331,416,444

AUTHOR INDEX

Kavaler,J., 233,240,245 Kawakami, Y., 21,48,51, 322,325 Kay, R. M., 439,444,462,469,484 Kayden, C . S., 62,132 Kaye, J., 223,238 Kaye, P. T., 199,259 Kearney, J. F., 460,484 Kearse, K. P., 39,53 Keck, P., 350,354-355,358-359,443 Keep, P., 365,441 Keinan, E., 279,283,286-287 Keisenhofer, J., 198,246 Kelley, R. F., 21 I, 230,247, 306,325 Kells, D. I. C., 310, 323 Kelly, A. B., 435, 447 Kelsoe, G., 10,56, 462-463, 477, 482 Kelus, A. S., 455,482 Kennard, O., 66,128, 153,238,359,440 Kenten, J. H., 220, 222,238,259, 349, 440,449 Kepler, T. B., 472,482 Kerner, J. D., 43,53 Kerr, D. E., 222,244,438,444 Kessler,J., 129, 230,242 Kestin, A. S., 433, 444 Khilko, S., 25-27, 29, 49 Kiefer, H., 4,50 Kihlberg, J., 302,325 Kikuchi, G. E., 223,242 Kikuchi, M., 283,287 Killeen, N., 40, 49 Kim, J., 320,325 Kim, S., 171,239 Kim, S. H., 159,209,246 Kim, Y. S., 25-27,29,49 Kindred, B., 5,51 Kindt, T. J., 316,325 King, D. J., 60,128,224-225,241,353,441 Kinoshita, T., 300,326 Kinsky, S. C., 318,324 Kinuya, S., 377,447 Kioussis, D., 6, 49 Kipriyanov, S. M., 231,247, 352, 367, 371, 444 Kirkpatrick, S., 188,247 Kirkwood,J. G., 208,247 Kirsch, J., 204-205 Kisielow, P., 290,328 Kitazume, T., 279,286

503

Kitson, D. H., 198,247 Klapholz, S., 439,442 Klapper, I., 171,247 Klaus, G. G., 463,482 Klausner, R. D., 39-40,43,48,51-53 Klehmann, E., 322,328 Klein, J., 296,325 Klein, M., 170,246, 310,323 Klein, M. H., 176,240 Klein, R., 466,482 Klenerman, P. S., 43,51 Kleywegt, G. J., 60, 75, 78-79, 132 Klinman, N. R., 477,483 Klix, N., 465, 467,485 Klotz, J. L., 233,237 Klug, A., 214,258 Klussman, K., 320,324 Kneller, D. G., 181,253 Knight, K. L., 455, 483 Knill-Jones, J., 197, 200,243 Knorr, R., 41,49 K~OSSOW, M., 62-63,64, 124,130 Knott, J. C. A,, 177,242 Knowles, J. R., 267-268, 270,285 Knowles, J. K. C., 224,257 Kniipfer, U., 232,251 Knuth, A., 322,328 Koch, A., 275,286 Kochersperger, L., 263-265,275,278,285286 Kocks, C., 390,439,472-473,481,484 Kodera, Y., 298,327 Koetzle, T. F., 66, 128, 153,238, 359, 440 Kohler, G., 221,254, 352, 367, 371,444 Kolbinger, F., 229,247 Kolchanov, N. A., 467,484 Kollman, P. A., 156,258 Kon, S., 391, 444 Kondo, K., 300,326 Kono, H., 63,64 Kontermann, R. E., 231,247, 352, 367, 371,444 Koppe, B., 43,51 Koprowski, H., 229,257 Kortt, A. A., 61, 130, 225,247 Kossiakoff, A. A., 60, 129, 182, 230,242 Kostelny, S . A., 232,248 Koszinowski, U. H., 32,53 Kotts, C., 230, 239

504

AUTHOR INDEX

Kotzin, B. L., 319-320,324-325 Kourilsky, P., 19,53, 225,250,317, 322 Kozack, R. E., 171,248 Kozlowski, S., 16, 19, 32,49, 222, 225,241, 249 Krangel, M. S., 234,239 Kranz, D. M., 4, 10-11,36,39,44,51,5354,225,233-234,251,254-256,304305,325 Kratasjuk, G. A,, 430, 447 Kratochvil, C. H., 67, 130 Kraulis, P. J., 167, 174, 178,248 Krause, R. M., 342,444 Kreitman, 227,253 Kreitman, R., 227,258 Krutzch, H., 309,327 Krystek, S., 160, 172, 210, 220,248 Kubler, W., 430,437,440 Kubo, R.,4, 19,51,54, 223,238, 319, 328 Kucsman, A., 273,286 Kuderova, A., 63,131 Kuettner, M. G., 380,444 Kufer, P., 249 Kuhn, T. S., 151,248 Kujau, M., 232,251 Kukla, D., 198,246 Kumar, A., 291,327 Kunkel, A., 463,482 Kuntz, I. D., 159, 248 Kuo, C. C., 439,444,462,469,484 Kurokawa, T., 431,443444 Kurosawa, Y., 454,459,482 Kurrle, R., 223,254 Kurth, R., 40,50 Kurtz, J., 301, 317,324 Kurucz, I., 225, 231, 248 Kushmir, E., 318,324 Kussie, P., 404, 421, 424-425, 427, 443 Kussie, P. H., 130, 383, 385, 390, 393, 395, 444,446,449 Kuznetsov, D., 208,236 Kwong, P. D., 41,53 Kwong, R.-F., 416,419420,448 Kyun Shin, E., 460, 483

L Laaksonen, L., 246 Labrecque, N., 319,325 Lacy, E., 39,48

Lacy, M. J., 225,256 Ladd, M. F. C., 154,248 Lafaille, J. J., 459,483 Lahr, S. J., 230,253 Laine, R. O., 302,316 Lake, J. P., 318, 326 Lal, A. R., 199,259 Lalloo, D., 43,51 Laman, J. D., 317,328 Lamb, C., 30,49 Laminet, A. A., 352, 355, 364, 367-368, 370-374,441,443,445,448 Lamoyi, E., 126, 131 Lan, N. C., 12,55 Lancet, D., 303, 305-309,326-328 Lancki, D. W., 4,52, 3 16,324 Landolfi, N. F., 222, 229,248,253, 381, 444 Landry, D. W., 283,287 Landsteiner, K., 177, 2 13,248 Lane, D., 347,446 Lane, E. B., 219,238 Lane, P. J . L., 477, 483 Lane, W. S., 16-18,4941 Lange, G., 60,128 Langmuir, V. K., 377, 444 Langridge, R., 181,253 Lans, D., 6, 49 Lanzavecchia, A., 10-1 1,35,53,55 Lapachet, S. S. G., 439,444 Lapham, C., 20,55 Laroche, Y., 436,443 Larson, S. B., 60, 68, 130, 164,245 Larson, T., 467,469,481 Lasch, S. J., 229,257 Laschinger, C. A., 70,129 Lascombe, M.-B., 61,130, 146, 148, 310, 326,38 1,444 Latharn Claflin, J., 465, 484 Lattman, E. E., 60, 129 Laudin, A. G., 59,68, I32 Laug, W. E., 223,244 Laukkanen, M. L., 224,257 Lauwereys, M., 436,443 Lavailee, D. K., 262-263,285 Laver, W. G., 61,85, 117, 126,129,131, 197,203,218-221,248-249,258,300301,326,370,441 Lavoie, T. B., 181, 210, 218, 232,243,248, 256,411,444 Lawrence, C. E., 165,239 Lawrence, M. C.,61,130, 161,225,247-248

AUTHOR INDEX

Lawrie, D. K., 223, 254 Lawson, A. D. G., 224-225,241,353,441 Layer, A., 52 Le, N., 377,447 Leach, S. J., 213-214,238, 300,328 Leach, S. L., 302,323 Leahy, D. J., 41,52,128, 137, 143-146, 148, 178,233,237,248 Leatherbarrow, R. J., 144,148,248 Lebecque, S. G., 456,483 Lebovitz, H. E., 163,245, 342,442 Ledbetter, J. A., 42,52, 222, 231,245,249, 318,320,324,328 Leder, L., 302,326 Lederberg, J., 453,483 Lederman, L., 360-361,445 Lee, B. K., 66,131, 157-158, 199, 227228,247-248,253 Lee, J. S., 61,63-64, 111,129,131,218219,253 Lee, L., 225,249 Lee, N. E., 233,240 Lee, S.-M., 223,238, 350, 353, 440 Lee, T., 223,238, 350, 353, 440 Lee, W., 63,131 Leggett, K., 4,55, 233,259 Lehr, R. E., 186, 270 Leinbach, R. C., 436,442 Leitner, O., 322,327 Lejeune, J., 21,52 Lemberg, L., 212,248 Lemer, M., 469,484 Lemmens, G., 436,441 Lemoine, C., 322,328 Lerner, R. A., 61, 123,131-132, 197, 211, 213-214,218,222,244,254,256-257, 261, 263-265,271,275,277-278,280281,283,284-287,356,396-397,416, 428,440,447 Lescar, J., 63, 106-107, 111,129, 131, 219, 248 Lesk, A. M., 11, 12, 49, 86, 129, 155, 161163, 165-167, 169-170, 176, 181-183, 230-23 1,233-234,238,240,248-249, 257-258,347-348,413,441,457458, 479-480,481,484 Lesley, S. A., 282,286-287 Letourneur, F., 40,52,55 Leung, D. Y. M., 319,325 Levin, W. J., 370, 448 Levine, L., 300,324

505

Levinson, D., 223-225,246,257, 350, 353, 355,361,363-364,366,368,443,448 Levinthal, C., 186-187, 190,243 Levison, S. A,, 305,326 Levitt, M., 86, 129, 137, 143-146, 148, 155, 157, 172, 178, 181-182,229231, 233,237,240, 249,253,259, 413, 441,458,481 Levrero, M., 43, 48 Levy, J. P., 225,250 Levy, N. S., 456,465,475,4831184 Levy, R., 144,148, 178,249, 391,444 Levy, S., 391, 444 Lewis, M., 199,246 Lewis, S. M., 458, 483 Ley, S., 39, 48 Leytze, G., 320,324 Li, T., 280-281,286 Li,Y., 62-63, 64,131,133, 171,259 Li, Y. W., 223,254 Liang, M. N., 267-268,285 Lieber, M. R., 455,470,482 Lieberman, S. A,, 43,52 Lifson, S., 155-156,245, 249 Light, D. R., 273-274,286 Lijnen, H. R., 431,434,436437,441,443, 448 Lilly, S. P., 229,254 Lin, L., 207,251 Lin, L.-C., 358,444 Lindsten, T., 4, 8, 49 Ling, Y., 79, I 3 0 Linsley, P. S., 42,52, 222, 231, 245,249 Linthicum, D. S., 63, 130, 307, 310,325 Linton, P. L., 477, 483 Lipman, L. N., 333,445 Lirsch, J. F., 203,247 Litman, G. W., 454,478,482-483 Litman, R., 454,483 Little, M., 231,247, 352, 367, 371, 444 Littman, D. R., 3 9 4 0 , 49,55 Litwin, S., 465, 484 Liu, H., 63, 131 Liu, J., 41,55 Liu, S., 352, 355, 364, 367-368, 370-374, 443,445,448 Liu, T., 20,56 Liu, X. L., 300,326 Liu, Y. J., 463,477,483 Livingston, P., 323,324 Livingstone, J. R., 204,256

506

AUTHOR INDEX

Ljunggren, H.-G., 20, 30,52,54,56 Llewelyn, M. B., 170, 181,240,479,481 Llewelyn, M. E., 347-348, 441 LO,C.-H., 281,286 Locke, E., 403,446 Loh, D. Y., 36,44,54,465,481 Loken, M. R., 4,52 Lonberg, N., 39,48, 439, 444 London, F., 156, 195,249 Lone, Y. C., 230,250 Longberg, N., 459,461,484 Loonteins, F. G., 309,324 Loontiens, F. G., 309,326 Lopes, A. D., 68,132 Lorber, M. I., 4,52 Lorenz, P., 439,440 Lotze, M. T., 21, 32, 49,54 Louie, D. M., 439, 442 Love, R. A., 63,131 Love, T. W., 432434,435,444, 446 Low, D. C., 60,128 Lowe, D. M., 197,200,243 Lowman, H. B., 249 Lozano, F., 11,52,458, 465,467, 473,483, 485 Lu, X., 62,128 Lucas, C., 222,239 Luecke, H., 396,444 Luescher, I. F., 21,52-53 Lund, J., 78, 131 Luo, M., 64, 64 Luong, E. T., 40,53 Luong, H., 43,51 Lurguin, C., 322,328 Lurquin, C., 2 1, 49,52 Lusch, M. J., 278,286 Luscher, M. A,, 19, 20, 30, 49 Luther, M. A., 188,203, 225, 235,251 Luthy, R., 165,238,249 Luton, F., 40,55 Luzzati, V., 66, 131 Lyons, D. S., 43,52

MacDonald, H. R., 44,50 Mace, J. E., 199,259 Machado, D. C., 79,130 Mackay, C. R., 453,456,478, 484 MacKenzie, C. R.,62,133

MacKenzie, R., 171,259 MacLennan, I. C., 461,463,477,483 Madden, D. R., 16-17,46,51-52,312314,326 Madison, E. L., 433,442 Madison, L., 469, 483 Madrenas, J., 42,52, 313, 315,326 Maeda, M., 304, 315,326 Maeji, N . J., 261, 283,284 Maertzdorf, B., 458, 483 Maeurer, M. J., 21, 32,49,54 Mage, M. G., 225,249 Mage, R.G., 455-456,481,483-484 Magnusson, G., 302,325 Maher, S. E., 25-27, 29, 49 Mahiou, J., 52 Mainhart, C., 181, 218,256 Maizels, M., 470,483 Maizels, N., 469,482 Mjek, O., 475-476,482 Major, J. G., Jr., 63, 131 Mak, T. W., 4,55,233,259 Makel, O., 462,475, 483 Malby, R. L., 61,85, 117,130-131, 197, 219-220,225,247,249 Malia, M., 227,244, 353,442 Malipiero, U. V., 456, 475, 483 Malissen, B., 10,40,52, 55, 223,244 Malissen, M., 10,52 Mallender, W. D., 231,249 Malmqvist, M., 357, 376, 447 Malone, C. C., 176,252 Mamlaki, C., 6,49 Manca, F., 302,326 Mandelboim, O., 21,52 Manjula, B. N., 307-310,326,328 Manser, T., 222,255,381,384-387,444445, 447,449, 456, 463, 465, 469, 475,477,482-484 Maoz, A., 317,325-326 March, D., 177,242 Marchand, A. P., 270,286 Marcu, K. B., 432,448 Marcuz, A., 478,484 Margoliash, E., 213-214,238, 302,324 Margolies, M. N., 61-62,130,132, 177, 189-191, 197,223-224,238,245-246, 252,255,329,350,353-355,361,363364,368,381,383-385,387,389-391, 393,395,397-398,400401,403404, 407-414,416-417,419-421,423427,

AUTHOR INDEX

432,434,4434453,456,465,470-471, 475,477,483484 Margulies, D. H., 16, 19-20, 25-27, 29, 32, 49-50,225,249 Marholies, M. N., 384, 444 Mariame, B., 21,52 Mariuzza, R. A., 15, 46, 48, 61-62, 94, 96, 126,128,130,133, 170, 185, 196, 201, 203,210-211,213,223,231,233-234, 237-238,240,243,249,259,305-306,

324,328,359,441,476,481 Mark,A. E., 151, 194, 197,241,249,259 Markham, A. F., 454,463,475,482 Markowitz,J. S., 319,323 Marks, J . D., 170, 181, 232,240,249, 261, 283,284,341,347-348,356-357,365, 376,441,445,447,479,481 Maron, E., 213,237, 301, 323 Marquart, M., 59, 68, 72, 74, 131 Marrack, J. R., 452, 483 Marrack, P., 4, 5,51, 297, 318-319,324326,328 Marrthyssens, G., 436,443 Marsh, D., 148, 177,257, 259 Marshak-Rothstein, A., 381, 445,448 Marsters, S. A., 222,239 Marsueda, G., 232,243 Martin, A. C. R., 188, 192,249 Martin, D. M., 21,49 Martin, F., 214,242 Martin, S., 316,326,328 Martinez-Yamout, M., 135, 140-141, 143144, 146,148 Marzec, U. M., 435,447 Mas, M. T., 190,249 Mashayekh, R., 439,444, 462,469,484 Mason, D., 10,52 Mason, D. W., 28,52 Mason, K., 22, 29,52 Mason, M. L., 61, 130, 185, 197, 202, 236, 245 Mason, T. J., 214, 218,244 Mathis, D., 40,49 Matis, L. A,, 12,50,53 Matsuda, F., 460,483 Matsueda, G., 7, 21, 48, 225, 234,237,245 Matsueda, G. R., 349,429-437,440441, 443444,446447,449 Matsui, K., 23-25,27, 28, 34-35, 41,52 Matsumura, M., 17, 19,46,50,52-53, 3 12, 314,325

507

Matsuoka, H., 459, 482 Matsushima, A., 298,327 Matsushima, M., 307,325 Mattei, S., 21, 49 Matthews, B. W., 170,236 Matthews, D. J., 418-419,445 Maxam, A. M., 341,445 May, R. D., 428, 449 Mayeda, J., 129, 230,242 Mayer, J., 19,50, 315,324 Maynard-Currie, C. E., 439,442 Mazor, G., 472,481 Mazza, G., 223,244 McAdam, S., 43,51 McCabe,J. G., 439,444 McCafferty,J., 356,445 McCall, A., 357, 376,447 McCammon, J. A., 189,250 McCartney,J., 350, 352, 354, 358-362, 364,366,372-373,443,445,449 McCartney, J. E., 224, 231, 236, 352, 355356,361,364-376,439,441443,445, 447448 McConnell, H. M., 22, 29,52-54, 135, 137, 139-140, 143-146,148, 178,2?7,315, 323-324,328 McCourt, D. W., 17,52 McCubrey,J., 4,50 McDermott, F., 39, 48 McDevitt, H. O., 300,326 McDonald, K. W., 229,254 McElligott, D. L., 12,50 McCann, J. K., 377,444 McGookey, D., 433,442 McGregor,J. M., 467,484 McGuiness, R. P., 439,442 McGuire, W. L., 370,448 McHeyzer-Williams,M. G., 455,470,482 McHugh, L., 225,249 McIntosh, P. K., 229,254 McIntyre, B. W., 4, 48,51-52 McKenzie, I. F. C., 321,327 McKimm-Breschkin,J. L., 61,85, 117, 131, 197,203,219-220,244,249 McKinney, E. C., 478,482 McLachlan, A., 157, 208,242 McLachlan, S. M., 59, 64 McLaughlin, A. C., 177,242,258 McLaughlin, C. L., 358,448 McLean, J., 234,238 McManus, S., 178,249,476,483

508

AUTHOR INDEX

MeMichael, A,, 30, 49 MeMichael, A. J., 7, 43,51,54 McPherson, A,, 60, 63, 68, 118, 128, 130, 164,245 McQueen, J. E., 156, 245 Medlin, J., 317,326 Meek, K. D., 384,445 Mehwald, P., 437, 440 Meidell, R. S., 433, 442 Meilijson, I., 472, 481 Meinhardt, G., 437, 440 Melief, C. J. M., 19-20, 30,50,54 Melton, R. G., 438, 448 Mendel, E., 391,444 Mendez, M. J., 439, 442 Meo, T., 235,246 Mertz, J. E., 198,247 Mescher, M. F., 44,51 Metropolis, N., 187, 208, 250 Metzger, D. W., 203,220-221,258 Metzger, J., 16-18, 21, 32,50,53 Metzler, W. J., 153,241 Meuer, S. C., 4,52 Meyer, E. F., 153,238, 359,440 Meyer, E. F., Jr., 66, 128 Meyer, S., 10-1 1,53 Meyer zum Buschenfelde, K.-H., 322, 328 Michael, J. G., 2 13-2 14,238, 302,324 Michaelides, M. C., 38,52 Michaelson, J. S., 469, 483 Michel, H., 16-17, 20-21,51, 314,325 Michelson, K. D., 433,444 Midgley, C . , 347, 446 Miethke, T., 320,326 Miglietta,J., 64, 64 Miki, T., 21,51, 322,325 Milenic, D., 224,258 Milenic, D. E., 353, 355, 449 Milich, D. R., 291, 299,326 Milili, M., 475, 484 Miller, A., 213-214, 238, 302,324,326 Miller, A. B., 459, 461, 484 Miller, J., 4, 53 Miller, J. F. A. P., 10, 51 Miller, L. S., 377, 447 Milligan, G. N., 17, 30,52, 319, 324 Millo, G. B., 322,323 Millward, A,, 223, 244 Milner, C . B., 384,445 Milstein, C . , 11, 28,50,52, 62, 128, 229, 232,258-259,311,325,341,346, 352,

367, 371,384,390-391,430,440, 442,444,448,451452,454456,458, 460463,465467,4691173,475-478, 480,481-485 Minnaar, R. P., 19,50 Mitchell, E. B., 222,250 Mitchell, R. C., 199,259 Mitsuya, H., 222,239 Miwa, T., 465,469,483 Mixan, B., 428,448-449 Miyashita, H., 283,287 Miyazawa, S., 250, 454, 482 Mol, C . D., 63-64,131 Mole, L. E., 343, 442, 445 Molinolo, A., 377, 447 Momburg, F., 20,52 Momo, M., 352,445 Monaco,J. J., 20,52 Mond, J. J., 317-318,324,326-327 Mondragon, A,, 214,258 Mongini, P. K. A,, 3 17-31 8,326 Monod, J., 307,326 Monrad, W., 319,325 Moore, G. P., 223, 229,254 Moorman, M. A., 318,327 Moras, D., 214,258 Mordenti, J., 222,239 Moreau, H., 434,441 Morgan, R. S., 171,259 Morissey, D. V., 229,254 Morris, P. P. N. R., 458, 481 Morrison, L. A,, 17, 30, 52 Morrison, S. L., 221-222, 229,250-251, 255,257 Morton, D. L., 322,325 Mosier, E. E., 316,326 Moskophidis, D., 6, 49 Moss, B., 7, 55 Mosser, A. G . , 63, 131 Motoyama, N., 465,469,481,483 Mottez, E., 186,250 Mottola-Hartshorn, C., 350, 443 Moult, J., 186, 198,243,247,250 Mountain, A,, 224-225, 241, 353,441 Mowat, A. M., 296, 324 Mozes, E., 289,293,317-318,325,327-328 Muchmore, D. C., 170,236 Mudgett-Hunter, M., 191, 211, 223-225, 238,246,250,255,257,350,352-355, 358-359,361-364, 366,368,373, 381, 398,400,403,407,410-412,

AUTHOR INDEX

423,426,432,443,445-448 Mueller, D. L., 42,52 Mueller, L., 153,241 Muir, A. K. S., 63-64, 131 Miiller, K., 232, 251 Muller, R. G., 453, 456, 478, 484 Miiller, S., 35,55 Mullins, D., 433435,444,446 Munoz-O’Reagan, D., 439,444 Murphy, D., 163, 233,251 Murphy, K. P., 199-200,204,206,250 Mushinski, E. B., 309,326 Muyldermans, S., 454,482 Myers, C. D., 318,328 Mylvaganam, S. E., 210,250

Nabholz, M., 44,50 Nadell, R., 231,256 Nadler, L. M., 42, 51, 291,325 Nagabhushan, T. L., 2 1 , 4 9 Nagaoka, H., 460,483 Nagel, E., 151,250 Naghibi, H., 206,250 Nahill, S. R., 36, 38, 44,52,54 Nahm, M. H., 291,325 Naik,V. M., 81, 132 Naito, T., 222,257 Nakagawa, H., 78,131 Nakamura, K. K., 63, I31 Nakanishi, M., 222,246 Nakatani, T., 230,250 Nakayama, G. R., 186, 275 Nall, B. T., 305-306,327 Nanni, R. G., 62,128 Napper, A. D., 263,285 Narang, S. A., 62, 133, 171,259 Nared, K. D., 267-268,271,285-286 Narhi, L. O., 19,50, 315,324 Nasholds, W., 43, 48 Nathenson, S. G., 16-18, 21, 46,55, 312, 328 Navaza,J., 61, 63, 100-101, 106, 124, 128, 130-131 Navia, M. A,, 68, 132, 257 Near, R. I., 191, 211, 223, 227,237-238, 250,255, 381, 384, 386, 398, 400, 407409,411,413414,417,420, 423,432,444-445,447

509

Necker, A., 223,244 Nedelman, M. A., 36 1,445 Needles, M. C., 261, 283,284 Neefjes,J.J., 20, 21, 30,52,54 Nell, L. J., 189, 250 Nelles, L., 436,448 Nelson, C. A., 17, 22, 36, 44,52,54, 163164,250,343-344,446 Neri, D., 352, 445 Neuberger, D. L., 349,432,445 Neuberger, M. S., 222,226,229,246,250, 346, 349, 432, 444, 449, 451, 458, 462,465469,471,478,480,481-485 Neumann, R. D., 377,447 Newberry, R. D., 36,44,54 Newell, 169, 250 Newell, J., 163, 233,251 Newell,J. B., 429430, 434435, 437, 440, 44 7 Newell, N., 432, 448 Newman, J. R., 151,250 Newton, D. L., 355,445,447 Newton, S. M. C., 298,323 Nezlin, R. S., 330, 445 Ng, S.-C., 191, 211, 227,237, 250,255, 398,407409,417,432,445,447 Nguyen, D. T., 156, 198,247,258 Nice, E. C., 203,244 Nicholls,A., 66, 126, 130, 132, 171, 196, 199,206,250,255,424,445 Nicholls, I. A,, 199, 259 Nicholls, P. J., 355, 367, 445 Nicklen, S., 341, 447 Nielsen, E. A,, 4, 39,51, 233, 245 Nishikata, H., 478, 482 Nisonoff, A., 61,67, 126, 130-132, 146, 148, 262,285,310,326,333, 380-381, 444-445 Nissen, M. H., 16, 19, 29,53 Nissirn, A,, 347, 446 Noelken, M. E., 163-164,250, 331, 337, 339,343-344,446 Noelle, R. J., 3 18,328 Noguchi, H., 230,250 Noguchi, M., 439,442 Noma, T., 222,257 Norcross, M. A., 4 , 5 3 Norda, M., 16-18,32,53 Nordt, T., 437,440 Norel, R., 207,251 Norley, S., 40,50

510

A U I H O R INDEX

Norris, N. A., 231,245 Norris, P., 467, 484 Northrop, J. H., 131 Northrup, S. H., 29,53 Nossal, G. J., 463,473,483 Nouri, S., 463, 473, 483 Novotny, J., 11,53, 149, 157, 159-160, 162-163, 166, 168-173, 176, 182, 184185, 188-191, 193, 195-196, 199-201, 209-205,210-211,213-216, 219-221, 223-225,231-236,237,239-240,243244,246,248,250-252,255-256,258, 298,300-301,326,347,350,353,355, 357,361,365-364,368,398,400401, 403,407414,417,420,423,426,440, 443,445-447 NUS, J. M., 203,210-21 1,220-221,251 Nussinov, R., 207,251 Nye, J. A., 170,236

Ochi, A., 22 1,251 O’Connell, M. P., 21 1, 230,247, 306,325 O’Donnell, S. L., 439, 444, 462, 469,484 Oh, J., 315-316,324 Ohlkn, C., 30,52,54 Ohlmeyer, M. H. J., 261, 283,285 Ohlson, A. J., 209,244 Ohta, N., 322,328 Ohtake, Y., 298,327 Oi,V.T., 163, 221-223,244,250-251, 255,327 Ojcius, D. M., 19,53 Okada, H., 465,469,483 Okamura, M., 4, 8 , 4 9 Oki, A,, 302,326 Olafson, B. D., 156, 188,239 Old, L., 322,328 Oldfield, S., 477,483 Oldstone, M. €3. A,, 22, 38,53 Oliver, K. G., 318,328 Oliveri, F., 24-25, 55 Oljak, R. J., 63, 100-101, 128, 170, 196, 201,210,213,237 Olsen, A. C., 16, 19, 29,53 Olsen, K., 60, 132 Olsen, M., 16, 19, 29,53 Olson, A. J., 213-214,257 Olson, N. H., 63,131

Oomen, R. P., 62, 132 Oppermann, H., 223-225,231,236,246, 257,350, 352-355,358-376,439,441443,445,448 Ortega, E., 315,326 Ortmann, B., 316,326,328 Oseroff, C., 41, 48 O’Shea, J. J., 43,51 Osmond, D. G., 461,483 Ota, A,, 300,326 Ouwehand, W. H., 356,445 Owen, F. L., 234,238

P Pabo, C . O., 227,251 Pace, P. E., 61, 122, 130 Pack, P., 232,251, 352, 446 Packalen, T., 67,133 Padlan, E. A., 9, 16, 46, 49, 58-61, 64, 64, 81,84,86-88,98, 104, 124-125, 127, 128-129,131-132, 138,148, 153, 170171, 176, 179, 181-182, 189, 196, 214,219,227,230-231,240,252,254255, 306,324,326, 342, 413,441, 447, 457458,481 Padovan, E., 10-1 1, 35,53,55 Page, L. B., 177,210,245 Pai, L. H., 227,239 Paik, C. H., 377, 447 Painter, R. G., 340, 446 Palm, W., 59-60, 68, 72, 74, 129, 131, 307, 325 Palmer, R. A,, 154,248 Pamer, E. G., 17-18, 53 Panagiotopoulos, N., 168,242 Pande, H., 221,239,349,441 Pang, R. H. L., 361,445 Panganiban, L. C., 261, 283,284 Panka, D. J., 191,255,398,400,403,410414,420,423,426,443,446-447 Pannell, R., 458,465,467,469, 480,481483,485 Pappenheimer, A. M., Jr., 331,446 Parfit, D. J., 222,241 Parham, P., 19,49 Parhami-Seren, B., 383, 385-387, 390, 393,395,444,446,449 Parker, C. W., 337,449 Parker, K. C., 19,53

AUTHOR INDEX

Parks, D. R., 191,255, 411, 413-414, 420, 446-447

Parmiani, G., 21, 49 Parnell, G. D., 352, 441 Parr, D. M., 70, 129 Partridge, L. J., 174, 176,242,259 Pascual-Ahuir,J. I,., 159, 252,258 Paskind, M., 460, 475, 481, 484 Passalacqua, E. F., 320,323 Pastan, I., 225, 227-228,239-240,247, 253,258,428,440-441

Pasternack, M. S., 44,51 Paterson, A., 213-214,257 Paterson, Y., 2 10, 2 13, 2 18,250,252 Patten, P., 233,252 Patten, P. A,, 282,286 Paul, L., 428, 448 Paul, S., 270,286 Paul, W. E., 290, 317-318,326 Pauling, L., 168, 195-196,252, 330, 446, 452,483

Payne, P. W., 229,253 Peabody, D. S., 70,129 Pecht, I., 148, 177, 179, 181,252, 258, 289, 303-31 0 , 3 15,324-328

Pedersen, J., 192,252 Pedersen, J. T., 218, 231, 252 Pederson, L. 8, 16, 19,29,51 Pelkonen, E., 476, 482 Pelkonen, J., 475, 482 Pellegrini, M., 209, 219,248,252 Pemberton, R. M., 17, 32, 48 Penna, A,, 43,48 Perelson, A. S., 472,482 Perez-Ramirez, B., 377, 447 Perisic, O., 64, 131, 224,252 Perkins, S. J., 177, 179-180,241-242 Perry, H. M., 67,130, 181,229,247,348, 400,404,444

Perry, J., 221,239, 349, 441 Perry, T., 199,259 Person, M. A. A., 356, 440 Perutz, M. F., 172,249 Petermann, M. L., 331, 446 Peters, A. M., 361, 368-369, 373, 375-376, 442-443

Peters, E. A., 261, 283,284 Peters, P.J., 21,52 Peterson, C., 176,252 Peterson, L. L., 41 1, 446 Pederson, L. 0., 16, 19, 29,53

51 1

Peterson, N., 2 19,248 Peterson, P. A., 17, 19-20, 23-29, 35-37, 41,44,46,50,52-54,312, 314,325

Petsko, G. A., 61-62,130,132, 189, 197, 246,354,381,383-384, 387,39 1, 400,403-404,408-409,411,413, 420,440,443,446,448 Petzold, S. J., 22,52 Pfitzinger, I., 227,244, 353, 442 Pflugfelder, U., 3 16,326 Pfliigrath, J . W., 396, 446 Phillips, A. F., 40, 53 Phillips, R. E., 43, 51 Phillips, S. E. V., 46, 48, 61, 94, 96, 130, 170, 185, 196, 201, 210, 213, 231, 233,237,240,243,359,441 Phizackerley, R. P., 64, 70, 75, 81, 128, 131,342-343,349,446 Pickett, S. D., 196, 199, 252 Pietersz, G. A., 321,327 Pigeon, M., 4,51 Pimpanean Golinielli, B., 261, 266,284 Pinella, C., 63, 64 Ping, J., 190-191,252, 401, 403, 446 Pink, J. R. L., 454, 483 Pirak, M. E., 321,323 Pircher, H.-P., 30, 36, 48 Planck, M., 152, 252 Pletcher, J., 320,328 Ploegh, H. L., 20-21, 30,51-52,54 Plow, E. F., 437,441 Pliickthun, A., 60, 132, 224-225, 227, 232, 243-244,251-252,259,306,325,350, 352-353,442,446,448 Plunkett, M. J., 261, 283,285 Poenie, M., 29,53 Pokkuluri, P. R., 63, 131 Polidoulis, I., 170, 246 Poljak, R. J., 46, 48, 58-59, 61-64, 64, 70, 75,81,86,94,96, 100-101, 106-107, 111, 117, 125-126,128-133, 146,148, 181-182, 185, 196,203, 211,219, 230-231, 233,238,240,243,248,259, 305-306,3 10,324,326,328,342-343, 349, 359, 381, 413, 439, 441, 444, 446,457458,476,481 Pollack, S. J., 124, 132, 261-263, 271,284285 Pollard, J. W., 465, 481 Ponder, J. W., 183,252 Pope, S., 223,238

512

AUTHOR INDEX

Pope, S. H., 350, 353,440 Popov, A. V., 462,4681169,484 Popov, N. V., 430,447 Porath, J., 370,446 Porter, J. P., 230,253 Porter, R. R., 74, 131, 173,253, 330-333, 342-343,442,445-446 Porter, T. G., 4 1,53 Portmann, A. J., 305,326 Portolano, S., 59, 64 Pospisil, R., 455, 483 Potter, M., 87-88, 124-125, 131-132, 170, 181,243, 254, 309,326-327, 342, 360, 441,447 Potter, T. A., 20,55 Poulik, M. D., 333, 441 Pound, J. D., 78, I31 Prager, E. M., 213-214,238,302,324 Pramanik, B. N., 21, 49 Prasad, L., 61, 111,132, 218-219,253 Press, E. M., 177,242, 333,442 Pressman, D., 177, 201,253, 262,285 Presta, L., 60, 129, 182, 230, 239,242,247, 306,325 Presta, L. G., 230,253 Preston, H. P., 316,327 Preston-Hurlburt, P., 17-18,53 Price, N. C., 177,242 Privalov, P. L., 196, 200, 204, 206,253 Prochnicka-Chalufour, A., 12, 15, 49, 234, 240 Procyk, R., 436,449 Profy, A. T., 63, 64, 130, 132, 197,256, 310,327,427,446 Prospero, T., 197,224,246, 352-353, 355, 442,445 Prudent, J. R., 263-265,267,283,285,287 Przybylska, M., 62, 132 Ptashne, M., 222,255, 385,447 Pulendran, B., 463, 473, 483 Pullen, A. M., 319,328 Pumphrey, R., 155,253 Punt, J. A., 39,53 Putnam, F. M., 163,257 Putnam, F. W., 358,444

Q Quai1,J. W., 61, 111, 131, 218-219,253 Queen, C., 225,229,240,253,428,441

Quertermous, T., 190-191,225,245,252, 349,401,403,432435,437,441, 444,446447 Quin Zong, S., 460,483 Quiocho, F. A,, 396,444,446

Rabbitts, T. H., 222,250,460,482 Rabinovich, D., 21 1-212,255 Rada, C., 11,52,465,467,472-473,475, 481,483 Rademacher, T. W., 173,239 Radhakrishnan, R., 63,131 Radioppi, L., 53 Radowicz-Szulczynska, E., 229,257 Raison, R. L., 59, 129 Rajan, S. S., 60, 68, 129, I32 Rajewsky, K., 390,439,456,463,467,471473,481432,484 Rajewsky, N., 390,439,472,481 Rajewsky, R., 475,481 Ramachandran, J., 301,327 Raman, C. S., 305-306,327 Rammensee, H.-G., 16-21,29-30,32,44, 46,49-50,53-54,311-312,327

Randal, M., 60, 129, 182, 230,242 Rao, D. N., 257,309,327 Rapoport, B., 59,64 Rashin, A. A,, 200,253 Rasmussen, M. H., 17, 30, 36-37,46,50 Rast, J. P., 454,483 Rathbun, G., 384,445 Rauffer, N., 170,210,253 Raulet, D., 40, 49 Raulins, N. R., 272,286 Raus, J. C. M., 367,445 Reay, P. A., 15, 23-25, 27-28, 34-35,41, 51,52 Rebai, N., 223, 244 Reber, J.-L., 283,287 Recny, M . A . , 166, 188,203,225,235,251, 259 Record, M. T., Jr., 204,256 Reddehase, M. J., 21, 32,52-53 Redpath, S., 43,48 Reed, G. L. 111, 437, 446 Reed, N. D., 318,326 Rees, A. R., 153, 171, 181, 188, 192, 211, 218-219,231,241,249,252-253,258, 350,441

AUTHOR INDEX

Rees, B., 62,133 Regoerson, B., 465, 482 Reichlin, M., 213-214,238, 302,324 Reid, K. B. M., 173,253 Reidler, J., 327 Reid-Miller, M., 181, 229,247 Reilly, E. B., 21,55, 455, 482 Reilly, P. E. B., 377, 442 Reinherz, E. L., 4, 41,52,55, 166, 188, 203,225,235-236,240,243,251,259 Reiter, Y., 227,253,258 Remy, M. H., 282,287 Renauld, J.-C., 21,49 Renny-Fledman, R. M., 315,324 Reth, M., 475,481 Reuben, J., 136,148 Rey, M., 221,239,349,441 Reyburn, H., 224,245,368,442 Reymond, A., 275,286 Reymond, J.-L., 280, 283,286-287 Reynaud, C. A., 453,455-456,478,484 Reynolds, J. A., 374, 376,446 Reynolds, J.-L., 279,286 Rhoads, S. J., 272,286 Ribado, R. K., 225,249 Riblet, R., 381, 448 Ricca, G. A,, 360,441 Rice, D., 22 1,253 Richards, F. F., 59, 128, 177, 210,245, 254,340,342,439,442 Richards, F. M., 66, 131, 157-159, 183, 199,248,252-253 Richards, J., 432, 448 Richardson, J., 66, 71,132, 163, 166,253 Richmond, T. J., 159,253 Ricordi, C., 320,324 Ridge, R., 223-224,246 Ridge, R. J., 350, 353, 355, 361, 363-364, 368,443 Ridgeway,J. B. B., 230,239 Riechmann, L., 178, 222, 229,249, 253, 349,352,441,446,476,483 Riesenberg, D., 232,251 Riethman, H., 460, 482 Riethmuller, G., 249 Riggs, A. D., 221, 239, 349,441 Ring, C. S., 181,253 Rini, J. M., 62-63, 64, 120-121, 125,132133, 192, 197,253,255-256,306,310, 32 7 Riordan, G. S., 223,238, 350, 353,440

513

Riottot, M.-M., 61, 63, 106, 117, 125, 128, I31 Rittenberg, M. B., 466,484 Rivoltini, L., 2 1,51, 322,325 Robbins, P., 3 15,325 Robbins, P. F., 21,51, 322,325 Roberts, G. C. K., 136,148 Roberts, J. L., 39,53 Roberts, N. A., 222,259, 349, 449 Roberts, S., 181,253 Roberts, S. M., 60, 128 Roberts, V. A., 182, 191, 209, 222,240, 243,254,300,327,411,441 Robey, E., 6, 49 Robinson, G., 454,482 Robinson, R. A,, 16,51 Robson, L., 365,441 Rocha, B. B., 461,482 Rochat, H., 214,216,237,242-243 Roche, P. A,, 2 1 , 5 3 Rochlitz, C., 322, 327 Rock, K. L., 20,50 Rodda, S. J., 214, 218,244 Roder, H., 213, 218,252 Rodgers, D. W., 41,55 Rodgers, J. R., 66, 128, 153,238, 359,440 Rodriguez-Rilo, H., 320,324 Roes, J., 390,439, 472, 481 Roess, W., 454, 483 Rogers, G. T., 438,448 Rogerson, B. J., 465,484 Rogozin, I. B., 467, 484 Roguska, M., 218, 231,252 Rojo, J. M., 42, 43,53 Rollence, M. L., 224,258, 352-353, 355,449 Romagnoli, P., 10,55 Roman, L. M., 433,442 Romero, P., 52 Ronchese, F., 53 Ronco, P. M., 61, 119-120,130 Roof, R. W., 17,21,52-53 Rosauer, R., 307, 310,325 Rose, D. R., 61-62, 119, 129, 132, 181, 185,241,381,383-384,387,391, 403,446,448 Rose, G. D., 2 14,243,251, 30 1,326 Rosen, E. M., 381,444 Rosen, F., 234, 239 Rosenberg, M., 41,53 Rosenberg, S. A,, 21, 48,51. 322,325 Rosenberg, W., 43,51

514

AUI'HOR INDEX

Rosenbluth, A. W., 187, 208,250 Rosenbluth, M. N., 187, 208,250 Rosenfeld, R.,199, 258 Rosenstein, R.W., 177,254 Rosenthal, A. S., 5.53 Roseto, A., 282,287 Ross, A,, 225,243, 306,325 Ross, P., 43,51 Rossi, G., 132 Rossmann, M. G., 161-162,254 Roth, C., 322,327 Roth, W. R.,272,286 Rothbard, J., 7, 21,51,54, 233,252, 31 1312,327 Rothbard, J. B., 17, 21, 32,40,42,48,53-54 Rothenberg, M. E., 434435,446 Rothenfluh, H. S., 465,484 Rothstein, T. L., 381,446 Rotzschke, O., 16-18, 20-21, 30, 32, 44, 46,50,53-54,296,s 11-3 12,327 Routledge, E. G., 229,244 Rowe, E. S., 360,446 Rowland, A,, 321,327 Rowland, A. M., 230,239 Roy, M., 318,328 Rudd, C. E., 40,53 Rudensky, A,, 316,327 Rudensky, A. Y.,17-18,53 Rudert, W. A., 320,324 Rudikoff, R.,87, 124, 131 Rudikoff, S., 88, 125, 131-132, 170,241, 254,257,309,327, 342,447,475,484 Rueckert, R.R.,63, 131 Ruef, J., 435,447 Rueker, F., 59, 130 Ruff, F., 273,286 Ruff-Jamison, 191,254 Rule, G. S., 137, 143-146, 148, 178, 218, 23 7-238 Runge, M., 225,245 Runge, M. S., 349,429435,437,440-441, 444,446-447 Ruppert, J., 19, 41, 48,54 Rusconi, S., 221,254 Russell, J. H., 36, 44,54 Russell, R.B., 160, 254 Russell, S. J., 203, 210,245 Rutishauser, U., 75, 129 Rybak, S. M., 355,445,447 R ~ uS.-E., , 41,53

S Sablitzky, F., 471472,481 Sacchettini, J. C., 17,46,55, 312,328 Sadegh-Nasseri, S., 22,53 Saga, T., 377,447 Sage, H. J., 340,446 Sahagan, B. G., 229,254 Saito, H., 4, 11, 39, 53, 233-234,251,254 Saito, T., 4 , 5 3 Saito, Y.,19,52-53 Sakaguchi, K., 16-17, 20-21,51 Sakai, T., 438, 447 Sakato, N., 300,326 Sakharov, D. V., 430,447 Saldanha, J., 229,247 Sali, A., 165, 179,254 Salinas, P. A., 132 Salter, C. J., 199,259 Salter, R. D., 32,54 Saltzgaber-Muller, J., 229,254 Saludjian, P., 63, 124, 130, 381, 444 Sambrook,J., 433,442 Samelson, L. E., 5, 40, 4243.50-53, 313, 315,326 Samraoui, B., 12, 15-16,48-49, 311,324 Sanchez, P., 455,481 Sancho, J., 39, 48 Sander, 190,247 Sander, C., 183,246 Sanders, C., 166-167,238 Sanders, S. A., 427,448 Sanders, V. M., 318,328 Sanger, F., 341,447 Sanstedt, S., 458, 481 Sanz, I., 381, 447 Saper, M.A., 12, 15-17,48-50,311,324325 Sarma, R.,59, 68, 132 Sarma, V. R.,67, 132 Sarvetnick, N., 282,287 Sasai, H., 439,442 Sasaki, H., 298,317 Sastry, 261,283,284 Sato, J., 377, 447 Sato, M., 222,246 Satow, Y.,60,132, 170, 189, 196,254 Sauer, J., 270,286 Sauer, R. T., 2 10,239 Sauer-Eriksson, A. E., 60, 75, 78-79, 132

AUTHOR INDEX

Saul, F., 59,64, 70, 81, 128, 131, 342-343, 349,439,446 Saul, F. A., 59, 132, 172, 196, 199-201,251 Saulnier, M. G., 438, 447 Sauma, S. Y., 20,56 Savard, C. E., 430-431,433-435,440,444, 446 Sax, M., 60,130,320,328 Sayers, I., 79, I30 Sayre, P. H., 166,240 Scanlan, T. S., 63, 124, 133, 261, 266,284285 Schad, V., 39,48 Schaefer, M., 318,326 Scharff, M. D., 170, 191,240-241,254, 396,411,441 Schearman, C. W., 223,254 Schechter, B., 292, 301,327 Schechter, I., 210,254, 292, 301, 318,327 Scheirle, A,, 41, 49 Schellekens, M. m., 317,328 Schepers, G., 308,324,327 Scheraga, H.A., 157, 187,244,257 Scherf, T., 144,148, 178,249,259 Scheurmann, M., 439,440 Schidder, M., 81, 132 Schier, R., 356-357, 365, 376, 447 Schiff, C., 475,484 Schiffer, M., 60, 70, 125, 128-130, 132, 168,242,343,349,447 Schild, H., 16-18, 24-25, 30, 32, 34, 41, 52-54 Schildbach, J. F., 130, 190-191,252,255, 398,401,403-404,407-414,417,420421,423427,443,446447 Schimmel, P., 427, 446 Schindler, D. G., 225, 228,242, 322,327 Schittek, B., 456, 484 Schlessinger, J., 307, 321,323,327, 370, 443 Schley, B. T., 59,129 Schlom, J., 224,258, 353, 355, 377,447, 449 Schlossman, S. F., 4, 40,52-53 Schmidt-Kessen, A,, 304, 315,326 Schmitt-Verhulst, A.-M., 29, 53, 223,244 Schneck, J. P., 222,241,315-316,324 Schnee, J. M., 349,432-435,444,446-447 Schneider, J., 2 1,49 Schneider, W., 163, 222,255

515

Schneider, W. P., 229,253 Schodin, B. A,, 225,255 Scholeder, D., 263,285 Schonermark, S., 430,440 Schott, M. E., 224,258, 353, 355,449 Schramm, H. J., 60,129 Schramm, S. R., 439,444,462,469,484 Schrauber, H., 183,255 Schreiber, G. J., 438, 447 Schreurs, W. M. J., 21,48 Schrodinger, E., 151,255 Schroeckh, V., 232,251 Schroeder, H. W., 460-461,484 Schultz, P., 123, 132 Schultz, P. G., 124,132, 261-265, 267269,271-273,275,278,280,282283,284-287,428,447 Schulze-Gahmen, U., 62-63,64, 120-121, 125,132-133, 192, 197,253,255,306, 310,327 Schumacher, T. N. M., 20, 30,52,54 Schwab, C., 302,326 Schwager, P., 60,129, 198,246 Schwartz, R. H., 21, 36, 4 2 , 5 2 , 5 4 Schwarz, F. P., 46, 48, 61, 96, 126, 128, I??, 196, 203,211,238,259,305-306, 324,328 Schweisguth, F., 223,244 Schweitzer-Stenner, R., 315,326 Schwick, G., 75,129 Schwitzer, P. A,, 465, 484 Scollay, R., 10,52 Scott, J. K., 261, 283, 284 Searcy, M., 283,287 Searle, F., 438,448 Searle, S. J., 192, 218, 231,252 Seasholtz, J. I., 361, 445 Seaton, B. A,, 403, 446 Sedlacek, H. H., 439, 440 Seeger, P. A,, 163,256 Seemann, G., 439,440 Segal, D. M., 87-88, 124,131-132,225, 231,248, 342, 355, 364, 366, 368, 377,441,443,447 Segesman, K. D., 223,244 Sehon, A. H., 303,305,325 Seidman, J. G., 234,239, 349, 407, 432, 434,445,447 Sekaly, R.-P., 319,325 Seki, J., 300,326

516

AUTHOR INDEX

Sela, M., 210, 213,237, 255, 289-290, 292293,298,300-301,305,317-318,321322,323-328, 331,340,428,440,442, 448 Selick, H. E., 229,253 Selin, L. K., 38,54 Selsing, E., 469-470, 484 Senter, P. D., 222,244,438-439,440, 442, 444,447-448 Sequar, G . , 462,469,484 Sercarz, E. E., 2 13-2 14,238, 302,326 Serra, H. M., 19,49 Servarz, E. E., 302, 324 Sette, A., 16-17, 19-21, 29-30, 32,41, 43, 48-51,54,315-316,324-325,327 Sevilir, N., 16, 21,51, 314, 325 Sgeriff, S., 193,246 Sha, W. C . , 36,44,54 Shabanowitz, J., 16-17, 20-21, 49,51, 314, 325 Shabat, D., 279,286 Shakked, Z., 211-212,255 Shamblott, A. J., 454, 483

Shan, L., 59,63,129-130,307,310,325 Sharma, P., 291,327 Sharma, S., 61, 111,131, 218-219,253 Sharma, S. K., 438,448 Sharon, J., 61,132, 201, 222, 229,247, 255-256,360, 381,383-391,447-448, 47 I , 484 Sharp, K., 66,132, 199, 204,239,424,445 Sharp, K . A . , 162, 171-172, 185, 196, 199,

204-206,231,239,247,250-251,255 Sharpe, M. J., 467, 484 Shastri, N., 302, 316 Shaw, A. S., 40, 42,54 Shaw, S.-Y., 190-191,252,255,401,403, 411,413-414,420,434-436,446-447, 449

Shealy, D. J., 361, 445 Shearer, G. M., 5,54, 289, 293, 317,327328

Shearwin, K. E., 377,447 Shenkin, P. S., 186-187, 190,243 Shepard, H. M., 230,239 Shepherd, D. M., 318,328 Shepherd, J. C . , 20,54 Sheriff, S., 9, 46, 49, 58, 60-62, 64, 86, 98, 104,129-132, 138,148, 181-182, 189, 191, 193, 197,219,230-231,237, 240,246,252,255, 306,324, 354, 398,

400,404,407-409,411,413~14, 417,420-421,423-427,441,443,447448,457-458,481 Sherman, D. A., 54 Sherman, D. H., 44,51 Sherman, L. A., 20, 44,51,55 Sherwood, R. F., 438,448 Shevach, E. M., 5,53, 223,242 Shevlin, C . G., 277-278, 280,286 Shi, J . P., 197, 200,243 Shields, R. L., 230,253 Shih, H. L., 186,256 Shimanouchi, T., 66, 128, 153,238, 359, 440 Shimizu, M., 301,317 Shively, J. E., 221,239, 349,441 Shoenfeld, Y., 302,327 Shoham, M., 62,132 Shokat, K. M., 269,285, 463, 473,484 Shopes, B., 74,133 Short, M. K., 416,419-420, 448 Short, M. T., 60,128 Shorter, A. M., 270,286 ShrefIler, D. C . , 5,51 Shulman, M. J., 221-222,238,251 Sibanda, B. L., 181,256 Sicari, S. A,, 381, 445 Siciliano, R. F., 188, 203, 225, 235,251 Sidkevitz, M., 381,445 Sidney, J., 19, 41,48,54 Siebenlist, 170,256 Siegall, C. B., 428, 448-449 Sieker, L. C., 62,130, 189, 197,246, 354, 400,404,408-409,411,413,420,443 Siekevitz, M., 381, 390, 439, 448, 4 7 2 4 7 3 , 481,484 Siekmann, D., 317-318,326 Sigler, P. B., 21 1-212, 255 Siler, K., 377, 447 Siliciano, R. F., 20, 50 Silla, E., 159,252,258 Silverton, E., 61, 64, 67-68, 98, 104, 127, 128,131-132,219,252,255 Simms, E. S., 360, 441 Simon, T., 47 1, 481 Simpson, E., 5,50 Simpson, N., 249 Sims, M. J., 197,237 Singer, A,, 39,53 Singer, S. J., 163, 256, 303,324 Singhal, A. K., 145-146, 148

AUTHOR INDEX

Sinha, S. C., 283,287 Sinigaglia, F., 41, 49 Sinitsyn, V. V., 430, 447 Sippl, M., 157, 165, 209,256 Sirotina, A., 20,56 Siskind, G. W., 337, 342,441 Sitkovsky, M. V., 44,51 Siu, G., 233,237 Sizmann, D., 224,257 Skakguchi, K., 314,325 Skehel,J. J., 62, 64 Skerra, A., 63,129, 182,243, 350,448, 47 1,482 Skidmore, B., 5 , 5 1 Skipper, J., 21,49 Slamon, D. J., 370, 448 Slanetz, A. E., 25-27, 29, 49,54 Slingluff, C. L., Jr., 21, 48 Sloan-Lancaster,J., 40-42,54 Smiley,J. A., 282,287 Smiley, S. T., 188, 203, 225, 235-236,243, 251 Smith, A. M., 218,256 Smith, A. T., 427,448 Smith, C. A,, 463,483 Smith, D. H., 222,239, 439, 442 Smith, G. D., 285 Smith, G. L., 7 , 5 5 Smith, G. P., 261, 283,284 Smith, J., 200,241 Smith, J. A., 214, 234,238,243,251, 301, 326 Smith, J. L., 426, 448 Smith, K. C., 188,256 Smith, K. G., 463,473,483 Smith, T. J., 63,131 Smith, T. W., 397-398,448 Smith-Gill, S., 61, 86, 98, 104, 127, 128129,131-132, 181-182,203,210,213214,218-219,230-231,238,240,247248,252,255-256,300-302,324,326, 411,413,441,444,458,481 Smithies, O., 68, 130 Smits, H. L., 19, 50 Smyth, M. J., 321,327 Smythe, M. L., 210,256 Snapper, C. M., 318,327 Snedecor, B., 230,247,306,325 Snoke, K., 41,48 Snow, M. E., 186,256 Soares, S., 231,256

517

Sogo, S. G., 285 Sohn, J., 469, 484 Sollazzo, M., 222,256 Solomon, A., 60, 128, 130, 132, 358, 448 Solomon, F., 29, 49 Somerville,J. E., 222,244 Sompuram, S. R., 201,256,386,390,448 Song, E. S., 19,52 Songa, E. B., 454,482 Sonnhammer, E. L. L., 160,244 So0 Hoo, W., 54 So0 Hoo, W. F., 225,256 Sopuchon, H., 63, 100-101,128 Sosnick,T. R., 163,256 Souchon, H., 46,48,61,63,96, 106-107, 111, 126, 129,131, 196,203,211, 219,238,248,306,324 Southwood, S., 19, 4 1,48,54 Spande, T. F., 87, 124,131 Spanopoulou, E., 6, 49 Spies, T., 20,54,55 Spinelli, S., 62, 86, 128-129, 181-182, 230231,240,413,441,476,481 Spirelli, S., 457-458, 481 Spolar, R. S., 204,256 Spragg, J., 177, 210,245 Spriggs, D., 429,442 Spring, S., 262,285 Springer, C. J., 438,448 Spruce, B. A., 219,238 Stabilizky, F., 390, 439 Stafford, W. F., 378,448 Stafford, W. F. 111, 224, 231,236, 352, 354355,358-359,364,367-368,370-374, 376,439,443,445,448449 Stam, N. J., 30,52 Stancovski, I., 321-322,323,327 Stanfield, R. L., 58, 61-63, 64, 130, 132133, 197,256,306-307, 310,327-328 Stassen,J. M., 429, 431, 436-437, 441-443 States, D. J., 156, 188,239 Stauffacher, C., 320,325 Stebbins, C., 465, 482 Steele, E. J., 465, 481, 484 Steffner, P., 23, 25, 27, 28, 35, 41,52 Steigemann, W., 60,129, 198,246 Steinberg, C., 478, 484 Steinberg, I. Z., 307,327 Steiner, L. A., 68, 132 Steinhauser, G., 474, 485 Steinmetz, M., 4, 10,50,55

518

AUTHOR INDEX

Steinrauf, L. K., 400, 443 Steipe, B., 60, 132 Stenkamp, R., 179, 237 Stenzel-Poore, M., 466, 484 Stephans, D. B., 283,287 Stephans, J. C., 273,286 Stern, L. J., 17-18, 22, 49,53-54, 311, 314, 320,324-325,328

Stern, P. S., 243 Sternberg, M. J. E., 173, 194, 196, 199, 209,239,246,252,258

Stevanovic, S., 16-18, 20, 32,50,53 Stevens, 170,256 Stevens, F. J., 60, 81, 128, 130, 132 Stevens, T. L., 318,328 Stewart, J., 182,254 Stillinger, F. H., 212, 248 Stockert, E., 322,323 Stollorz, V., 2 1,52 Stone, B. A,, 229,254 Storb, U., 465, 482 Storkus, W. J., 21, 32, 49,54 Stouch, T., 159-160, 172,201-202, 210, 220,248,256 Stout, G. H., 58,132 Strominger, J. L., 12, 15-18, 21-22, 38, 41, 48-51,54-55, 224,234,238,245,311312,314-316, 320,324-326,328,368, 442 Strong, R. K., 61-62, 130, 132, 189, 197,

246,354,381,383-385,387,390-391, 400,404,408-409,411,413,420, 443,446,448 Stryer, L., 163, 222,255 Stryer, L. J., 31 7 Stuart, D. I., 166, 246, 320,323 Studnicka, G. M., 231,256 Stump, D. C., 434, 448 Stura, E. A., 17, 46,50, 62-63, 64, 64, 123, 128,130,132-133, 147,148, 197,237, 261,266,268,284,312,314,325 Sturtevant, J. M., 206,250,257, 303, 324 Su, M. W.-C., 29,54 su, P. c., 438,447 Su, X. M., 315-316,324 Subbarao, B., 316,326 Subramaniam, S., 171, 188-189,238,248, 250 Suchdnek, E. G., 227,251 Suddath, F. L., 214,237

Suh, H., 55 Suh, J., 275,286 Suh, S. W., 257 Summers, N . L., 183,257 Sun, L. K., 229,257 Sunderland, C. A., 177,241,258-259 Suresh, M. R., 430,448 Sustmann, R., 270,286 Sutherland, R. M., 377, 444 Sutton, B. J., 148, 171, 176-177, 181,241, 257,259

Svensson, H. P., 222,244,438,448 Swaminathan, S., 156, 188,239, 320,328 Swat, W., 290,328 Sweet, R. W., 41,53 Sykulev, Y . , 20, 23-29, 31-34, 35-37, 41, 44, 46,51,54, 311, 314,325, 356

Szikora, J.-P., 21, 49,52 Szilard, L., 453,484 Szostak, J. W., 261, 283,284,287

T Tai, M A , 223-225, 231,236,246, 257, 350,352-355,358-359,361-364.366376,439,441443,445,448-449

Tainer, J . A . , 209, 211, 213-214, 218, 222, 243-244,254,257,300,327

Takacs, B., 41,49 Takagaki, Y., 4, 39,5?, 233,254,459,483 Takahashi, N., 78, 131 Takeda, S. I., 222,257 Takeshita, T., 32, 49 Takimoto-Kakimura, M., 197, 256 Takimoto-Kamimura, M., 63, 64, 310,327 Takio, K., 222,246 Takkinen, K., 224,257 Talluri, G., 315-316, 324 Tamp6 R., 22,54 Tamura, A., 206,250 Tanaka, S., 157,257 Tanaka, T., 222,246 Tanford, C., 163-164,250,331, 334,337, 339-340, 343-344, 346,358, 360, 377,440,443,446,448449 Tang, Y . , 282,286 Tarmontano, A,, 457458,481 Tarr, G. E., 4 1,55 Tasumi, M., 66,128, 153,238, 359, 440

AUTHOR INDEX

Taussig, M. J., 62, 128, 147, 148, 197,237, 293,328 Tawfik, D. S., 63, 124, 130, 282,287, 428, 448 Taylor, L., 465,481, 484 Taylor, L. D., 439, 444, 462, 469, 484 Taylor, M. G., 203,247 Taylor, W. R., 214,257 Teeri, T. T., 224,246,257 Teleman, O., 246 Teller, E., 187, 208,250 Tello, D., 46, 48, 61, 94, 96, 126, 128, 130, 185, 196, 203, 211, 219,238,243, 248,305-306,324,328,359,441 Terhorst, C., 39, 48 Teriault, T. P., 137, 143-146, 148 Terry, W. D., 67,132 ter Schegget, J., 19,50 Thammana, P., 223,254 Theriault, T. P., 144, 148 Thibodeau, J., 3 19,325 Thierry, J.-C., 62,133 Thirup, S., 170, 179-180, 183, 231,246 Thomas, D., 282,287 Thompson, C. B., 42,51 Thompson, K. S., 200,250 Thorn, S. N., 270,286 Thorneley, R. N., 427, 448 Thornton, J. M., 181, 212-213,238,256, 259 Thorpe, S. J., 356,445 Thorton, J. M., 214,257 Tidor, B., 200,241,257 Till, M., 428, 449 Timascheff, S. N., 58, 133, 377, 440, 447 Tipper, J. P., 127, 128,131 Tirado-Rives, 156, 209,246 Titani, K., 163,257 Titus, J. A., 231,248, 377, 441 To, R. J., 62, 119, 129, 132 Tobery, T. W., 20,50 Todd, P. E., 213-214,238, 300, 302,324, 328 Todd, R. J., 60, 128 Tolaini, M., 6, 49 Tollenaere, T., 436,443 Tomasello, J., 144, 148, 178, 237 Tomlinson, I. M., 170, 181,240, 346-348,

441,446,457,460,479-480,481-482, 484

519

Tonegawa, S., 4, 10-11, 20, 30, 36, 39, 48, 51,53-54,233-234,251,254,343, 432,448, 459,483

Toneguzzo, F., 229,254 Topalian, S. L., 322,325 Tormo, J., 197,241 Totrov, M., 199, 208,236,257 Tougard, P., 381,444 Townsend, A., 15-16, 19, 21, 29, 30, 49, 52,54,322, 328

Townsend, A. R. M., 7,54 Trail, P. A., 229,257, 428, 448 Tramontano,A., 86, 123,129,131, 181183,230-231,240,257-258,263,285, 413,441

Tranter, H. S., 320,323 Traub, W., 3 17,328 Traunecker, A,, 24-25,55 Travers, P., 43,48 Traversari, C., 21, 49, 322,328 Treffers, H. P., 332, 448 Trevillyan, J. M., 40,53 Trewhella, J., 163,256 Tribbick, G., 59, 129 Tristem, M., 341, 356, 445 Trounstine, M., 439,444 Trowbridge, I., 4,51 Trucco, G., 320, 324 Trucco, M., 320,324 Trucy, J., 10,52 Truneh, A., 41,53 Tsai, V., 19,49 Tsien, R. Y., 29,53 Tso, J. Y., 232, 248 Tsomides, T. J., 15-32, 35-37,44,46,5051,54-55, 31 1,314-315, 322,324325,328 Tsuda, H., 439,442 Tuaillon, N., 459, 461, 484 Tucker, P. W., 381,384,432,444-445, 448,459,461,484 Tuerk, C., 261, 283,284 Tulip, W. R., 61, 85-86, 117, 129, 131, 170, 181-182, 196-197,201,203,210211,219-221,230-231,240,249,258, 413,441,457458,481 Tulloch, P. A., 126,129, 370, 441 Tunon, I., 159,258 Turck, C. W., 40, 49 Tuveson, D., 222,241

520

AUTHOR INDEX

Udaka, K., 17-18, 21, 24-25, 36, 44, 55 Uhlen, M., 60, 75, 78-79, 132 Uhr, J. W., 428, 449 Ullrich, A., 322,323,327, 370, 443, 448 Umar, A., 465,484 Unanue, E. R., 7, 17, 20-22, 30, 48,50,5253,55,234,237,302, 325

Uno, T., 186, 269, 280, 283,285,287 Urban, J. L., 12,55 Urban, R. G., 17-18,49, Urban, R. G.,54, 31 1,314, 320,324-?25,328

Utz, U., 20,56

Vajda, S., 199,258 Valentine, R. C., 163,258, 343-344, 448 Valitutti, S., 35,55 Vallotton, M., 177, 210,245 van Bleek, G. M., 16-18,21,55 Van Buskirk, A. M., 318-319,324,328 Van Cauwenberge, R., 436,443 Vandamme, A. M., 436,441,448 Van den Eertwegh, A. J. M., 317-318,328 Van den Eynde, B., 48,322,324,328 van der Bruggen, P., 48, 322,323-324,328 Vandonselaar, M., 61, 111, 131, 218-219, 253

van Gunsteren, W. F., 151, 156, 194, 197, 241,249,258-259

Van Hoef, B., 436,443 Van Houtven, A., 436,443 Van Kaer, L., 30, 36, 48 Van Landschoot, A., 309,326 Van Meerwijk, J. P. M., 10,55 Vanne, L., 224,257 Van Pel, A,, 21, 48-49,52, 322,324 Van Regenmortel, M. H. V., 170,210,214, 253,258,357,449

van Rieschoten, J., 214, 237,242 van Schravendijk, M. R., 173,239 Van Vunakis, H., 300,324 Varga, J. M., 59,128, 342,439 Varghese, J. N., 126,129, 203, 220-221, 258,370,441

Vecchi, M . P., 188, 247 Velick, S. F., 337,449 Verhoyen, M., 229,258

Vernie, L. N., 20,54 Verroust, P. J., 61, 119-120, 130 Verstreken, M., 434,441 Vetterlein, D., 230,247, 306,325 Victor, K. D., 459,484 Vierboom, M. P. M., 19,50 Vignali, D. A. A., 17-18, 41, 49,55 Vignolli, D. A. A., 316, 328 Villa, L., 298,323 Villafranca, J. E., 63, 131 Villafranca, J. J., 232,243 Vitetta, E. S., 318,328, 428, 449 Vitiello, A,, 20,55 Vivier, E., 52 Vix, O., 62, 133 Voak, D., 356,445 Vogel, C.-W., 321,328 von Boehmer, H., 4, 36, 43,50,55, 290, 328

Von Bonin, A., 316,328 von Bonsdorff, B., 67,133 von Hodenberg, E., 437,440 von Itzstein, M., 210,256 Vorberg, E., 62, 132 Voss, E. W., 185, 197, 202, 225, 231, 236, 245,249,256

Voss, E. W., Jr., 61, 122, 130, 202,241, 304-305,325

Vrudhula, V. M., 438, 448 Vturina, I., 3 1,54 Vu, K., 459,484 Vuk-Pavlovic, S., 308-309,328 Vuong, T., 31 7

Wagner, G., 166,259 Wagner, H., 320,326 Wagner, S., 462,467-469,478,484 Wahl, C., 320,326 Wain-Hobson, S., 148, 177, 179-180,241242,257-259

Waks, T., 223, 225, 228,242,244, 322,327 Walden, P., 17-18, 24-25, 32,44,53,55 Walden, P. R., 29,54 Waldmann, H., 222, 229,244,253 Waldmann, T. A., 225, 229,240,253, 428, 441

Walker, B. D., 16-18, 20-22,29-31,32,55, 56

AUTHOR INDEX

Walker, G., 479, 481 Wall, M., 41, 48 Wallace, P. M., 438, 440, 448 Wallny, H.-J., 16, 32,53 Walls, P. H., 209, 258 Walsh, C. T., 273-274,286 Walter, G . , 170, 181,240, 347-348, 441, 460,482

Waltzinger, C., 40, 49 Wan, H., 428,448 Wang, A.-L., 380,444 Wang, B.-C., 60,128,130 Wang, H., 186-187, 190,243 Wang, J., 41,55 Wang, J. L., 42,52, 313, 315,326 Wang, J. Y., 460-461, 484 Wang, X., 300,326 Wange, R. L., 42,52, 313, 315,326 Ward, E. S., 225,258, 352,441,449 Warren, F., 350, 352, 361-362, 364, 366, 373,443,445

Warshel, A., 157,249 Waterfield, M . D., 341, 449 Wawrzynczak, E. J., 352,441 Waxdal, M. J., 75, 129 Waxman, D. J., 273-274,286 Waye, M. Y . , 197, 200,243 Waygood, E. B., 61, 111,131, 218-219,253 Webb, P. A,, 64, 131, 224,252 Webb, S., 22, 29,50 Webber, K. O., 227,253,258 Weber, G., 154,258 Weber, J. S., 465, 484 Weber, S., 24, 25,55 Webster, D. M., 153, 21 1, 258 Webster, R. G., 61, 85, 117, 126, 129-131, 170, 196-197,201,203,210-211,218221,225,247-249,258,300-301,326, 370,441 Wegener, A.-M. K., 40,55 Wei, M. L., 16, 55 Wei, T., 315-316,324 Weidmann, E., 320,324 Weigert, M., 472, 484 Weill, J.-C., 453, 455-456, 470, 478, 484 Weiner, L., 224, 231,236, 352, 355, 364,

367-368,370-374,439,443,445 Weiner, L. M . , 352, 355-357, 361, 365, 368-369, 372-373,375-376,442-443, 447449

Weiner, S. J., 156, 258

52 1

Weinhowe, M. I., 263,285 Weinstein, J. N., 377, 447 Weinstein, P. D., 456,484 Weisman, H. F., 361,445 Weiss, A., 4, 39-40, 49.51,53,55 Weiss, S., 4, 50, 455, 482 Weiss, U., 456, 467, 472,482,484 Wells, J.A., 204, 210-211, 216, 219,241, 246,249,418419,445

Welsh, R. M., 36, 38, 44,52, 54 Weltzien, H. U., 316, 326,328 Wenderoth, R., 232,251 Wendt, H., 302,326 Weng, J., 66, 128 Weng, Z., 199,258 Wenger, R., 170,210,253 Wensel, T. G., 163, 222,255 Wentworth, P. A., 19, 49 Werner, W., 436,442 Werther, W., 129, 230,242 Westhof, E., 214,258 Westholm, F. A., 60, 125,128-129 Wetterskog, D. L., 316,325 Wetzel, R., 221,239, 349, 441 Weyl, H., 151-152,258 White, A,, 400, 407, 445 White, A. I., 177, 242 White, F. H., 162,258 White, F. H., Jr., 331, 440 White, J., 4-5,51, 319,328 Whitley, R., 163,257 Whitlow, M., 223-224,238,258, 350, 352353,355,440,449

Whitney, P. L., 331, 334, 337, 340, 440, 449 Whittaker, M., 137, 144-145, 148, 178,237 Wien, M. W., 64, 133 Wigley, D. B., 63, 129 Wijdenes, J., 230,250 Wildgoose, R., 22, 29,50 Wiley, D. C., 12, 15-17, 21-22,46,48-54, 3 1 1-3 14,320,324-326,328

Wilkinson, A. R., 343, 445 Wilkinson, J., 197, 200,243 Wilkinson, M. F., 458, 481 Willan, K. J., 148, 177,257,259 Williams, A. F., 28,52, 166-167,246, 259 Williams, D. B., 19-20, 30, 49 Williams, D. C., 218, 238 Williams, D. H., 199, 259 Williams, G. J. B., 66, 128, 153,238, 359, 440

522

AUI'HOR INDEX

Williams, G. T., 349, 432, 445, 449, 463, 483 Williams, M., 469, 482 Williams, M. A., 212,259 Williams, R. C., Jr., 176, 252 Williams, R. E., 231,256 Williams, R. I.., 62, 64, 128, 131, 224,252 Williams, S. C., 460, 484 Williamson, A,, 20,48 Willimas, G. T., 222,250 Willingham, M., 227,239 Willner, D., 229,257 Willson, R., 6 1, 64 Wilson, A. C., 203, 213-214,238,247, 302, 324 Wilson, C., 199,259 Wilson, D. B., 44,50 Wilson, I., 312, 314,325 Wilson, I. A., 17, 46,50,52, 58, 61-63, 64, 120-121, 123, 125,128,130,132-133, 147,148, 192, 197,237,253,255-256, 261,266,268,284,306-307, 310,327328 Wilson, K.S., 61, 111, 131, 218-219,253 Wilson, M., 478,484 Wilson, P., 79, I30 Winer, G., 197, 224,246 Winoto, A,, 8, 12,50, 55 Winter, C., 229,258 Winter, G., 46,50, 64, 131, 170, 174, 176, 181-182, 197,200,203,210,222224,226,229,232,240,242-243,245246,249,252-253,259,341,347-350, 352-353,355-356,365,441442,444446,449,458,460,479,481-482,484

Winzor, D. J., 377,442 Winching, P., 263-265, 281,285-286 Wissler, F. C., 333, 445 Withka, J. M., 166,259 Witt, S. N., 315,318 Wittekind, M., 153, 227,237,241 Woernley, D. L., 333, 445 Wokaun, A,, 136,148 Wolf, E. J., 356, 365, 376, 443, 447 Wolfel, T., 318, 322 Wolfel, T., 21, 49 Wolfenden, R., 327,449 Wolff, E., 428, 448-449 Wolfson, C. A., 207, 251 Wong, C., 356,365,447

Wong, L. L., 4 0 , 5 3 Wong, S. G., 370,448 Wong, S. L., 227,237 Wong, W. L. T., 230,239 Wong, Y.-W., 383, 390, 397, 449 Wood, C. R., 220, 222,238, 259, 349, 440, 449 Wood, J. F., 224,258, 352-353,355,449 Wood, M. K., 6 0 , 6 8 , 1 2 9 , 1 3 2 Woodward, M. P., 218,256 Woodward, R. B., 270,286 Woof, J . M., 174, 176,242,259 Wraith, D., 7 , 5 4 Wraith, D. C., 22, 2 9 , 5 0 Wright, C., 177, 179, 181,242,252 Wright, C. E., 177,241 WU, G.-M., 225,257,353,355,360-361, 364,366,445,448 WU, M. X., 22,36-37,55 Wu, S., 181,259 Wu, T. T., 67, 90, 125,130,133, 168, 181, 229,247, 259, 342, 348, 400, 404, 444,449 Wucherpfennig, K. W., 22, 3 8 , 5 5 Wulfing, C., 259 Wung, J . L., 43, 48 Wurm, F. M., 222,239 Wiithrich, K., 136, 1 4 8 Wyckoff, H. W., 58,133 Wyman, J., 307,316, 377, 380, 449 Wymore, K., 439,444 Wysocki, L. J., 381, 384-386, 389-390, 392-393,395,441,444-447,449,455456,463,470-471,475,477,483-484 Wyss, D. F., 166,259

Xavier, A,, 61, 64 Xian, J., 462, 468-469, 484 Xiang, X.-D., 261,283-284,285 Xie, D., 199-200,206,250 Xu, B., 470,484 Xu, Y. Y., 176,240 XU, Z.-B., 60, 132 Xue, W., 1 0 , 5 6 Xue, Y., 355,447 Xuong, N.-H., 41,53

523

AUTHOR INDEX

Y Yamaguchi, H., 318,327 Yarnakawa, J., 230,250 Yan, Y., 41,55 Yanagi, Y., 4,55, 233,259 Yancopoulous, G. D., 55,460,484 Yang, G. X.Q., 283,287 Yang, W. P., 436,449 Yang, Y., 20,54 Yannelli, J. R., 21, 51 Yarden, Y., 321-322,323,327 Yarmush, D. L., 186-187, 190,243,249 Yarranton, G. T., 350,441 Yasuda, T., 436, 442 Yeatman, L., 398,448 Yklarnos, J., 465, 467, 485 Yelton, D., 60, 64, 130, 193,246 Yewdell,J. W., 7, 20,55 Yokota, T., 224, 233,252,258, 353, 355, 449 Yonath, A., 317,328 Yonkovich, S., 263-265,275, 278,285-286 Yoo, C. S., 60, 130 Yoon, S. T., 43,55 Yoshida, M. C . , 460,483 Yoshikai, Y., 4,55, 233,259 Youle, R. J., 355, 367,445 Young, A. C. M., 17,46,55,312,328 Young, C. G., 455,481,483 Young, I. G., 285 Young, N. M., 62, 119,129,132-133, 171, 259 Young, R . A . , 17-18,21,30,55 Ysern, X., 61, 133, 21 1,259 Yu, J., 282,287 Yun-yu, S., 151,259 Yuzuki, D., 322,325

z Zachau, H. G., 454,460,466,482,485 Zanetti, M., 222,256 Zappacosta, S., 67, 131 Zauhar, R. J., 171,259 Zavodny, P. J., 433-435, 444, 446 Zdanov, A., 62,64,128,133, 171,259 Zeder-Lutz, G., 170, 210,253 Zeh, H. J. 111, 32,54 Zemel, R., 63, 124, 130 Zeng, Y., 439,442 Zhang, A., 62,128 Zhang, J., 477,483 Zhang, L., 203,247 Zhang, W., 17,46,55,312,328 Zhang, X., 392,441 Zhao, D., 154,259 Zhao, K., 283,287 Zhao, Y., 300,326 Zheng, B., 10,56 Zheng, Y., 74, 133 Zhou, G. W., 63, 124,133,261, 266,284 Zhou, X., 20,56 Zidovetzki, R., 307-308, 310,328 Ziegner, M., 463, 474, 481, 485 Zilber, B., 144, 148, 178,259 Zilch, A., 454,483 Zinkernagel, R. M., 5, 30, 36, 48,56, 234, 260 Ziskind, A. A., 436, 442 Zisman, E., 318, 328 Zoebelein, R., 456, 467, 472, 484 Zvi, A,, 144,148 Zweerink, H. J., 20,48,56

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SUBJECT INDEX

Acylation, catalysis by antibodies, 263-265 Affinity maturation antibody gene organization, 454-455 antigenic selection mutated sequence selection, 470-474 repertoire shift, 474-477 hypermutation cis-acting DNA elements for recruiting mutation, 467-469 DNA target nature, 465 general characteristics, 463-464 mechanistic models, 469-470 target area, 464-465 types, 466 uneven distribution, 466-467 in immune response, 451-454 role of antibody gene mutations, 461-463 somatic diversification of germline, 45546 1 structural and evolutionary implications, 477-481 Allergens, as antigens, 297 Amino acid sequence relationship to 3D structure, 162-163 variability, and polymer solubility, 165 Antibodies affinity maturation, 45 1-454 AN02, crystal structure, 144-145 ANOn, production, 136-137 to arsonate effect of H chain junctional variation on binding, 386-389 mutations engineered ex uivo, 390-392 recurrent somatic mutation effects, 390 response in inbred mouse, 380-381 specificity alterations with phage display and random mutagenesis, 397 single mutation effects, 392-397 525

binding affinity and specificity binding modes, 196-198 concepts, 194 empirical Gibbs functions, 198-199 antigen-antibody docking simulations, 207-210 from calorimetric data, 204-207 functional epitopes, 210-21 1 functional forms and approximation limits, 199-200 individual complexes, 200-204 thermodynamics, 194-196 water-mediated binding, 21 1-2 12 binding electrostatics, 172-1 73 binding sites combinatorial libraries, 356 engineered sites development, 347-349 Fv architecture and sFv analog design, 349-358 Fv and sFv protein analyses, 358-372 equilibria and linkage, 377-380 molecular anatomy binding potential of surface cavities, 170-171 electrostatic perspective, 172-173 side-chain compositional bias, 171172 V~,-VHinterface /3 barrel, 168-1 70 targeting in vivo, 373-377 3D modeling canonical loop modeling, 182-1 83 conformational searches and Monte Carlo methods, 186-191 framework-loop relationship, 183-1 86 general stratagems, 179 knowledge-based methods, 179-182 NMR and computer modeling, 177179 protocols and future directions, 191193

526

SUBJECT INDEX

Antibodies ( c o d m u d ) catalytic applications, 283 chemical transformations, 275-280 evolving functions, 270-273 generation, 28 1-283 immunological evolution, 262-265 in rearrangements, 280-281 structural studies, 266-270 unnatural cofactors, 273-275 combining sites analysis with NMR and spin label haptens conformational heterogeneity, 145147 diamagnetic haptens, 141-142 difference spectra, 138 distance titrations, 143 early work, 135-136 selective deuteration, 138-139 signal assignments, 139-141 site dynamics and reaction kinetics, 143 Fab 36-71, crystal structure, 381-383 refolding and reassembly antidinitrophenyl Fab, 337-339 antiribonuclease Fab, 334-337 early theories, 333-334 intact IgG, 339-341 side-chain compositional bias, 171-172 specificity and affinity measurements, 356-357 in detection of protein conformations, 300-301 to digoxin antibody 26-10 Fab complexes, crystal structures, 413-416 spontaneous variants and sitedirected mutants, 403-413 structural constraints in H chain CDR1,416-421 antibody 40-50, structure and specificity, 421-427 antibody 40-150, variants, 400-402 diversity, 398-400 engineering development, contributing techniques, 220-22 2 disulfide-bonded Fv fragments, 227228

heterospecific polyvalent constructs, 231-232 mouse monoclonal antibodies, humanization, 229-231 single-chain Fv fragments and Fvtoxin conjugates, 223-226 via domain interchange, 222-223 formation, immunogenetics, 346-347 fragmentation and chain separation, 331-333 fragments, protein chemistry, 330-33 1 gene mutations, in affinity maturation, 461-463 HCDR2, mutations, 403-41 1 HyHEL-5, CONGEN computer modeling, 189-190 -1igand complexes, x-ray crystallography 1719 with hemagglutinin peptide, 120121 BV04-01 with d(pT)3, 122-123 catalytic antibodies with transition state analogs, 123-125 characteristics, 89-90 D1.3-chicken lysozyme, 94-98 D11.15-pheasant lysozyme, 107, 109111 D44. l-chicken lysozyme, 100-1 03 early analyses, 87-89 F9.13.7-guinea fowl lysozyme, 106-109 HyHEL-5-chicken lysozyme, 98-1 00 HyHEL-lO-chicken lysozyme, 104-106 idiotype-antiidiotype complexes 409.5.3 and antibody 730.1.4 Fab, 1 18-1 1 9 antilysozyme D1.3 and E225 Fab, 1 17-1 18 YsT9-1 and antibody T91AJ5 Fab, 119-120 Jel42-histidine-containing phosphocarrier protein, 111-1 14 NC10-influenza virus neuraminidase, 117 NC4 I-influenza virus neuraminidase, 112, 114-117 Se155-4 with carbohydrate, 121-122 structural data, 90-93 monoclonal mouse, humanization, 229-23 1 in T cell studies, 4 paradigms and primary structure analysis, 341-343

SUBJECT INDEX

primary repertoire genetic organization, 4 5 4 4 5 5 somatic diversification of germline, 455-461 structural and evolutionary implications, 477481 substrate-selective, effect on enzyme selectivity approaches, 4 2 7 4 2 8 bispecific antibodies, 430-43 1 chemically crosslinked antibodyenzyme conjugates, 4 2 8 4 3 0 fusion proteins, 431-437 targeted prodrug activation, 437439 surface cavities, binding potential, 170171 x-ray crystallography current studies, 57-58 domains, 70-72 Fab and Fc fragments, 70 general structure, 68-70 hinges, 72-74 whole antibodies, 67-68 Antigen-binding fragment, x-ray crystallography bend, 85 complementarity-determining region and hypervariable region, 86 surface properties, 87 general structure, 81 homologous domains, rotational symmetry, 81-85 size, 79-81 Antigenicity copolymers, 298-299 immunoglobulins, 295-296 major histocompatibility complex, 296297 molecular criteria, 298-300 protein, molecular basis, 213-214 cross-reactivity, 21 9-220 epitope, definition, 218-219 segmental flexibility and surface exposure, 214-218 role of conformation, 300-302 Antibody-antigenic epitope interactions, kinetics, 303-306 Antigen-antibody complexes, Gibbs free energy, 200-204 Antigen-antibody docking, simulations, 207-2 10

527

Antigen-antibody interactions kinetics, 303-306 linked functions, 378-380 Antigens allergens as, 297 and antibodies, conformational heterogeneity, 145 binding, effects of mutations, 190-1 91 binding regions of antibodies, protein chemistry, 330-331 CD3, interactions and properties, 39-40 CD4 in grouping of TCR, 6 interactions and properties, 40-41 CD8 in grouping of TCR, 6 interactions and properties, 4 0 4 1 complex antigens, 297 definition, 290-293 in immune response, 299-300 lipids as, 295 nucleic acids as, 294-295 polysaccharides as, 294 properties, 289-290 proteins as, 293-294 superantigens, 3 19-32 1 thymus-independent antigens, 3 16-3 19 tumor-specific classification, 32 1-322 description, 322-323 Arsonate antibody against effect of H chain junctional variation on binding, 386-389 mutations engineered ex vivo, 390-392 recurrent somatic mutation effects, 390 response in inbred mouse, 380-381 specificity alterations with phage display and random mutagenesis, 397 single mutation effects, 392-397 hapten contact residues, mutagenesis, 383-386

B cells, comparison to T cells, 3 4 Beta sheets, VL-VH interface /3 barrel, 168170

528

SUBJECT INDEX

Binding afinity, antibodies binding modes, 196-198 concepts, 194 empirical Gibbs fimctions, 198-199 antigen-antibody docking simulations, 207-210 from calorimetric data, 204-207 functional epitopes, 21 0-2 11 functional forms and approximation limits, 199-200 individual complexes, 200-204 thermodynamics, 194-196 water-mediated binding, 2 11-2 12 Binding potential, antibody surface cavities, 170-17 1 Binding sites antibodies binding equilibria and linkage, 377-380 combinatorial libraries, 356 engineered development, 347-349 Fv architecture and sFv analog design, 349-358 Fv and sFv protein analyses, 358-372 molecular anatomy binding potential of surface cavities, 170-1 7 1 electrostatic perspective, 172-1 73 side-chain compositional bias, 171172 VL-VH interface /3 barrel, 168-170 targeting in viuo, 373-377 3D modeling canonical loop modeling, 182-183 conformational searches and Monte Carlo methods, 186-191 framework-loop relationship, 183-1 86 general stratagems, 179 knowledge-based methods, 179-182 NMR and computer modeling, 177179 protocols and future directions, 191193 Clq, on Fc fragment, 173-174 T-cell receptor, engineering and mutagenesis, 235-236

C Calorimetry, in binding energy calculations, 204-207

Carbohydrates complexwith antibody Se155-4, 121-122 in Fc fragment, 78 Catalysis, by antibodies applications, 283 evolving functions, 270-273 immunological evolution, 262-265 rearrangements, 280-28 1 structural studies, 266-270 unnatural cofactors, 273-275 &-acting elements, DNA, for recruiting mutation, 467-469 Cofactors, unnatural, for catalytic antibodies in ketone reduction, 275 number and utility, 273 in oxygenation, 273-274 Complementarity-determining regions, antigen-binding fragments and hypervariable domain, 86 surface properties, 87 Complement Clq, structure binding site on Fc fragment, 173-1 74 as effector site, 173 Computer modeling definition, 150 immunology, structural data, 153-154 proteins potential energy, 155-157 structural superpositions, 16 1-162 surfaces and volumes, 157-161 3D, binding sites conformational searches and Monte Carlo methods, 186-189 hapten phosphorylcholine, 189-190 mutant effects on binding, 190-191 general stratagems, 179 knowledge-based methods, 179-182 canonical loop modeling, 182-183 framework-loop relationship, 183-1 86 NMR with model building, 177-179 protocols and future directions, 191-193 tools of analysis, 154-155 Computer programs, CONGEN, application to proteins, 186-191 Conformation antibody binding sites, computer modeling, 186-191 antigens and antibodies, heterogeneity, 145-1 47 protein, detection with antibodies, 300301

529

SUBJECT INDEX

role in antigenicity, 300-302 transitions, induction by hapten binding, 306-3 1 1 Cope rearrangement, catalysis by antibodies, 272-273 Crosslinking, chemical, antibody to enzyme, 428-430 Crystal structure antibody AN02, 144-145 antidignxin antibody 40-50,421-427 Fab 26-10,413416 Fab 26-10-digoxin complex, 413-416 Fab 36-71combining site, 381-383 Fc fragment, 75-78 proteins, analysis and presentation, 66-67 Cyclization, catalysis by antibodies, 277-

Domains antibody, x-ray crystallography, 70-72 Fv protein, isolation, 358 homologous, Fab fragment, rotational symmetry, 81-85 hypervariable, antigen-binding fragments, 86 interchange, in antibody engineering,

222-223 structure in IgC, 343-345 V in Fv, linker considerations, 350-356 T-cell receptor, hypervariable region, 9 Drugs, targeted activation, 437-439

E

278,280-281

D Deuteration, selective, antibody combining sites, 138-139 Diels-Alder reaction, catalysis by antibodies, 270-271,275-277 Digoxin, antibody against antibody 26-10 Fab complexes, crystal structures, 413-

416 spontaneous variants and site-directed mutants, 403413 structural constraints in H chain

CDR1,416-421 antibody 40-50,structure and specificity,

421-427 antibody 40-150,variants, 400-402 diversity, 398-400 Digoxin haptens, and analogs, structure and use as model, 397-398 Dinitrophenyl haptens binding by antibodies, 136-137 Fab against, refolding, 337-339 Diseases, human, role of superantigens,

320-321 Disulfide bonds, engineering into Fv fragments, 227-228 DNA cis-acting elements, for recruiting mutation, 467-469 recombinant methods, in derivation of MOPC 317 Fv, 360-361 as target of hypermutation, 465

Elbow joint, in Fab fragments, 176-177 Electrostatic fields, in antibody binding,

172-173 Energy, potential, computer modeling for proteins, 155-157 Enzymes, selectivity, effect of substrateselective antibodies approaches, 427428 bispecific antibodies, 430-43 1 chemically crosslinked antibody-enzyme conjugates, 428430 fusion proteins, 431437 targeted prodrug activation, 437439 Epitopes antigenic, interactions with antibodies, kinetics, 303-306 withTcells, 311-316 density, in T cell response to pepMHC,

30-32 functional, theory, 210-2 1 1 protein, definition, 218-2 19 types, 292 Equilibrium binding, in antibody binding site proteins linked functions, 378-380 linked functions and reciprocal effects,

377-378 T cell response to pepMHC, approach time, 29-30 Equilibrium constants peptide-MHC-I complex, 19 TCR-pepMHC reactions, 22-26 Esterification, catalysis by antibodies, 264265

530

SUBJECT INDEX

Esterolysis, catalysis by antibodies, 279 Evolution germline V gene sequences, 4 7 7 4 7 8 immunological, antibody catalysis, 262265

F Fab fragments 26-10 complex with digoxin, crystal structure, 413-416 crystal structure, 413-416 phage-displayed, random mutagenesis, 416-421 36-71, combining site structure, 381-383 antidinitrophenyl, refolding, 337-339 antiribonuclease, refolding, 334-337 bend, 85 conserved elbowjoint, 176-177 general structure, 81 homologous domains, rotational symmetry, 81-85 x-ray crystallography, 70, 79-81 Fc fragments C l q binding site, 173-174 carbohydrate in, 78 ligand complexes, 79 multispecies structures, 74-75 overall structure, 75-78 x-ray crystallography, 70 Fc receptor, binding sites, 174, 176 Fibrin, antibody against, fusion with single-chain plasminogen activator, 434437 with tissue plasminogen activator, 432433 Flexibility, segmental, in scorpion neurotoxins, 214-216 Fragmentation, antibodies, 33 1-333 Fv fragments architecture early discoveries, 349-350 linker considerations for bridging V domains, 350-356 specificity and affinity measurements, 356-357 structural homology between Fv regions, 357-358 disulfide-bonded, engineering, 227-228

domain isolation, 358 MOPC 3 15, derivation, 360-36 I sFv analog design early discoveries, 349-350 linker considerations for bridging V domains, 350-356 specificity and affinity measurements, 356-3 57 structural homology between Fv regions, 357-358 sFv protein anti-c-erbB-2 741F8, features, 370-371 antidigoxin 26-10 based on antidigoxin 26-10 IgG, 361 C-terminal peptide fusions, 367-369 expression and renaturation, 36 1-365 folding properties, 365 N-terminal polypeptide fusions, 365-367 sFv’ protein features, 370-371 preparation and analysis, 371-372 ( s F v ’ )protein, ~ preparation and analysis, 371-372 single-chain, production, 223-226 -toxin conjugates, production, 223-226

Genes antibody, mutations, role in affinity maturation, 461-463 encoding MHC-I, 7 T-cell receptors, assembly and structure, 8-9 V germline sequence, evolution, 477-478 immunoglobulin, as hypermutation target nature of DNA target, 465 target area, 464-465 Genetic organization, antibodies, 454-455 Gibbs free energy, empirical functionals antigen-antibody docking simulations, 207-2 10 binding constant approximations, 198199 from calorimetric data, 204-207 epitopes, 2 10-2 11

SUBJECT INDEX

forms and approximation limits, 199-200 individual complexes, 200-204

H Haptens -antibody reaction, kinetics, 143 binding, induced conformational transitions, 306-3 1 1 contact residues for arsonate binding, mutagenesis, 383-386 definition, 292 digoxin, and analogs, structure, 397-398 dinitrophenyl haptens binding by antibodies, 136-137 Fab against, refolding, 337-339 phosphorylcholine, CONGEN computer modeling, 189-190 spin label, in NMR of antibody combining sites conformational heterogeneity, 145147 diamagnetic haptens, 141-142 difference spectra, 138 distance titrations, 143 early work, 135-136 selective deuteration, 138-1 39 signal assignments, 139-141 site dynamics and reaction kinetics, 143 Hinges, x-ray crystallography, 72-74 Hybridomas, T-cell, specific for thymusindependent antigens, 318 Hypermutation cis-acting DNA elements for recruiting mutation, 4 6 7 4 6 9 DNA target nature, 465 general characteristics, 463-464 mechanistic models, 4 6 9 4 7 0 mutations unevenly distributed, 466-467 target area, 464-465 types, 466 Hypersensitivity responses, delayed-type response, 3 4

I Immune response with antigens, 299-300 characteristics, 291

53 1

maturation antigenic selection mutated sequence selection, 470474 repertoire shift, 4 7 4 4 7 7 evolutionary processes, 45 1-454 genetic and structural diversity of' primary repertoire antibody gene organization, 454455 germline somatic diversification, 455-461 hypermutation cis-acting DNA elements for recruiting mutation, 467-469 DNA target nature, 465 general characteristics, 4 6 3 4 6 4 mechanistic models, 469-470 target area, 4 6 4 4 6 5 types, 466 uneven distribution, 4 6 6 4 6 7 onset, relationship to available antibodies, 461-463 structural and evolutionary implications germline and somatic diversification complementarity, 479-48 1 germline V gene sequence evolution, 477-478 Immunocytes, types, 291 Immunogenetics, antibody formation, 346347 Immunoglobulins antidigoxin 26-10, 361 antigenicity, 295-296 domain isolation, 358 Fc fragment, crystal structure, 76-78 gross structure, 163-165 intact, refolding, 339-341 physicochemical analysis, 307-308 shape and domain structure, 343-345 structure, 1-2 superfamily structure, 166-168 and T-cell receptors, genetic differences allelic exclusion, 10-1 1 alternative RNA splicing, 9 hypervariable regions in TCR V domains, 9 isotype switching, 9 somatic mutation, 9-10

532

SUBJECT INDEX

Immunoglobulins (continued) V genes, as hypermutation target nature of DNA target, 465 target area, 464-465 Immunology computer modeling, structural data, 153154 molecular empirical and pragmatic approaches, 152-153 fundamental questions, 151-1 52 Immunotherapy, with tumor antigens, 32 1323 Influenza virus neuraminidase -antibody NClO complex, 117 -antibody NC41 complex, 112, 114-117 antigenicity, 216-218 cross-reactivity, 219-220

Ketones, antibody-catalyzed reduction, 275 Kinetics antibody-antigenic epitope interactions, 303-306 an tibody-hapten reaction, 143 control of T cell responses, 35 pepMHC-I reactions, 21-22 T cell response to pepMHC on- and off- rates, 28-29 rate constants, 26-28 temperature effects, 28

L Libraries, combinatorial, antibody binding sites, 356 Lipids, as antigens, 295 Lymphocytes B cells, comparison to T cells, 3-4 T cells, see T cells Lysozyme chicken, complex with D1.3, 94-98 D44.1xhicken lysozyme, 100-103 HyHEL-5,98-100 HyHEL-lo-chicken lysozyme, 104-106 egg white, antigenicity, 216-218

guinea fowl, complex with antibody F9.13.7, 106-109 pheasant, complex with antibody D11.15, 107, 109-111

Major histocompatibility complex antigenicity, 296-297 MHC-I, encoding genes, 7 in modeling of TCR structure, 12 pepMHC, T cell responses affinity model kinetic control of T cell responses, 33-35 TCR affinity, 32-34 TCR affinity ceiling, 33-34 degeneracy, 37 epitope density, 30-32 equilibrium constants, 22-26 kinetics, 26-29 molecular mimicry, 38 specificity, 35-37 time to approach equilibrium, 29-30 pepMHC-I complex with natural peptides, 17 equilibrium constant, 19 generation, 20 reaction kinetics, 21-22 restriction models, 5-6 by self and nonself MHC, 4 3 4 7 self and nonself, restriction of MHC, 4347 and T-cell receptors, 2 MHC, see Major histocompatibility complex Models affinity, TCR-pepMHC engagement kinetic control of T cell responses, 35 TCR affinity, 33-34 TCR affinity ceiling, 33-34 computer, see Computer modeling digoxin hapten as, 397-398 hypermutation mechanism, 469-470 major histocompatibility complex restriction, 5-6 T-cell receptors, 12 sequence-based outline structure, 233235

533

SUBJECT INDEX

Monoclonal antibodies mouse, humanization, 229-23 1 in T cell studies, 4 Monte Carlo methods, application to protein conformation, 186-191 Mouse, inbred, antiarsonate response, 380381 Mutagenesis antiarsonate hapten contact residues, 383-386 antidigoxin antibody 26-10 mutations in antibody HCDR2, 403-41 1 recurrent mutations at H chain position 35,411-413 spontaneous variants, 403 random alteration of antiarsonate antibody specificity, 397 phage-displayed 26-10 Fab, 416-421 T-cell receptor binding site, 235-236 Mutations antiarsonate antibodies engineered ex vivo, 390-392 antibody gene, in afinity maturation, 461-463 antibody HCDR2, 4 0 3 4 1 1 effect on antiarsonate antibody affinity noncontact residue mutations, 386-389 recurrent somatic mutation, 390 effect on antigen binding, 190-191 hypermutation, see Hypermutation recurrent, in antidigoxin antibody 26-10, 411-413 single, effect on antiarsonate antibody specificity, 392-397 somatic in Ig and TCR genes, 9-10 targeting, 477-478 somatic point, role in antibody repertoire development, 455-461

Neuraminidase, influenza virus -antibody NClO complex, 117 -antibody NC41 complex, 112, 114-1 17 antigenicity, 216-218 cross-reactivity, 2 19-220

Neurotoxins, scorpion, segmental flexibility, 214-216 Nuclear magnetic resonance and computer modeling binding sites, 177-179 conformational searches and Monte Carlo methods, 186-189 hapten phosphorylcholine, 189-190 mutant effects on binding, 190-191 general stratagems, 179 knowledge-based methods, 179-182 canonical loop modeling, 182-183 framework-loop relationship, 183186 protocols and future directions, 191-193 and spin label haptens, antibody combining sites conformational heterogeneity, 145147 diamagnetic haptens, 141-142 difference spectra, 138 distance titrations, 143 early work, 135-136 selective deuteration, 138-1 39 signal assignments, 139-141 site dynamics and reaction kinetics, 143 Nucleic acids, as antigens, 294-295 Nucleotide sequence, in T-cell receptor modeling and engineering, 233-235

Ouabain, complex with antidigoxin antibody 40-50, 421-427 Oxygenation, antibody-catalyzed,with unnatural cofactors, 273-274

P Peptides as altered ligands for T cell binding, 4143 hemagglutinin, complex with antibody 17/9, 120-121 immunogenic type, 291 pepMHC complexes, T cell responses affinity model kinetic control of T cell responses, 35 TCR affinity, 32-34

534

SUBJECT INDEX

Peptides (continued) pepMHC complexes, T cell responses (continued) degeneracy, 36 epitope density, 30-32 equilibrium approach time, 29-30 equilibrium constants, 23-26 kinetics, 26-29 molecular mimicry, 38 specificity, 35-39 pepMHC-I complex equilibrium constant, 19 generation, 20 with natural peptides, 17 reaction kinetics, 2 1-22 role in TCR-recognized antigenic structures, 11-12 synthetic, in TCR ligand analysis, 14 Phage display alteration of antiarsonate antibody specificity, 397 antibody 26-10 Fab, 416-421 Phosphocarrier protein, histidine-containing, complex with Je142, 111-1 14 Phosphorylcholine haptens, CONGEN computer modeling, 189-190 Plasminogen activator, fusion with antifibrin antibody single-chain PA, 434-437 tissue PA, 432-433 Polymers antigenic function, 298-299 solubility, and amino acid sequence variability, 165 Polypeptides, synthetic, in immunological research, 298 Polysaccharides, as antigens, 294 Polyvinylpyrrolidone, as thymus-independent type 2 antigen, 3 18-3 19 Potential energy, proteins, computer modeling, 155-157 Proteins accessory to T-cell receptors, 3 8 4 1 amino acid sequence and 3D structure, relationship, 162-163 antifibrin antibody-tissue plasminogen activator fusion, 432-433 antigenicity, molecular basis, 21 3-214 cross-reactivity,2 19-220 epitope, definition, 218-219

segmental flexibility and surface exposure, 2 14-2 18 as antigens, 293-294 computer modeling potential energy, 155-157 structural superpositions, 161-162 surfaces and volumes, 157-161 conformation application of Monte Carlo methods, 186-189 detection with antibodies, 300-301 crystal structures, analysis and presentation, 66-67 folding, role in antigenic specificity, 300 phosphocarrier, histidine-containing, complex with Je142, 111-1 14 refolding, antibody combining site antidinitrophenyl Fab, 337-339 antiribonuclease Fab, 334-337 early theories, 333-334 intact IgC, 339-341 (, interactions and properties, 39-40 Protein sequence, antibodies, 341-343 Proteolysis, limited in derivation of MOPC 315 Fv, 360-361 in Fv protein domain isolation, 358

R Radioimmunotargeting, in vivo with sFv antibody binding sites, 373-377 Rate constants, T cell responses to pepMHC, 26-27 Reduction, antibody-catalyzed, ketones, 275 Renaturation, 26-10 sFv proteins, 361-365 Responses hypersensitivity, delayed-type response, 3-4 immune, see Immune response Rheumatoid factor, reactive sites, 174, 176 Ribonuclease, Fab against, refolding, 334337 Ring opening, catalysis by antibodies, 278 RNA, Ig and TCR genes, alternative splicing, 9

S Solubility, polymers, and amino acid sequence variability, 165

535

SUBJECT INDEX

Solvents, exclusion from reactions by catalytic antibodies, 279 Superantigens activation pathway, 319-320 definition, 319 role in human diseases, 320-321 structure, 320 types, 3 19 Symmetry, rotational, Fab homologous domains. 81-85

T T-cell receptors accessory proteins, 38-41 binding of antigens, 3 11-3 16 binding site, engineering and mutagenesis, 235-236 gene assembly and structure, 8-9 grouping by cell surface glycoprotein types, 6 and immunoglobulins, genetic differences allelic exclusion, 10-1 1 alternative RNA splicing, 9 hypervariable regions in TCR V domains, 9 isotype switching, 9 somatic mutation, 9-10 MHC restriction of reactions models, 5-6 by self and nonself MHC, 43-46 modeling, 12 modeling and engineering, sequencebased outline structure, 233-235 -pepMHC reactions a6nity model kinetic control of T cell responses, 35 TCR affinity, 32-34 TCR affinity ceiling, 33-34 equilibrium constants, 23-26 on- and off-rates, 28-29 recognition, role of peptides, 11-12 recognized ligands, analysis characterization techniques, 16 with synthetic peptides, 14 with x-ray crystallography, 14-16 structure, 1-2, 11-14 T cells -antigenic epitope interactions, 3 1 1-3 16 binding of altered peptide ligands, 41-43

comparison to B cells, 3-4 hybridomas, specific for thymus-independent antigens, 3 18 responses to pepMHC affinity model kinetic control of T cell responses, 35 TCR affinity, 32-34 TCR affinity ceiling, 33-34 degeneracy, 36 epitope density, 30-32 equilibrium constants, 23-26 kinetics, 26-29 molecular mimicry, 38 specificity, 35-39 time to approach equilibrium, 29-30 studies using monoclonal antibodies, 4 TCR, see T-cell receptors Temperature, effects on kinetics of T cell responses to pepMHC, 28 Thermodynamics, antibody binding, 194196 Thymus, independent antigens, 3 16-3 19 Titrations, distance, antibody combining sites, 143 Toxin-Fv fragment conjugates, production, 223-226 Transacylation, catalysis by antibodies, 263265 Transesterification, catalysis by antibodies, 264-265 Transformations, chemical, with catalytic antibodies, 275-280 Transition state analogs, complexation with catalytic antibodies, 123-125 Trinucleotides, d(pT)3, complex with antibody BV04-01, 122-123 Tumors, specific antigens, 321-323

W Water, mediation of antigen-antibody binding, 2 1 1-2 12

X X-ray crystallography antibodies current studies, 57-58 definitions and conventions, 67 domains, 70-72

536

SUBJECT INDEX

X-ray crystallography (continued) antibodies (continued) Fab and Fc fragments, 70 general structure, 68-70 hinges, 72-74 whole antibodies, 67-68 antibody-ligand complexes 1719 with hemagglutinin peptide, 120121 BV04-01 with d(pT)3, 122-123 catalytic antibodies with transition state analogs, 123-125 characteristics, 89-90 D1.3-chicken lysozyme, 94-98 D11.15-pheasant lysozyme, 107, 109111 D44. I-chicken lysozyme, 100-1 03 early analyses, 87-89 F9.13.7-guinea fowl lysozyme, 106109 HyHEL-B-chicken lysozyme, 98-100 HyHEL-IO-chicken lysozyme, 104-106 idiotype-antiidiotype complexes 409.5.3-antibody 730.1.4 Fab, 118119 antilysozyme D 1.3-E225 Fab, 117118 YsT9-1-antibody T91AJ5 Fab, 119120

Jel42-histidine-con raining phosphocarrier protein, 11 1-1 14 NC 1 0-influenza virus neuraminidase, 117 NC41-influenza virus neuraminidase, 112, 114-1 17 Se155-4 with carbohydrate, 121-122 structural data, 90-93 antigen-binding fragment bend, 85 complementarity-determining region and hypervariable region, 86 surface properties, 87 Fab structure, 79-81 homologous domains, rotational symmetry, 81-85 catalytic antibodies, 266-270 Fc fragment carbohydrate in, 78 ligand complexes, 79 multispecies structures, 74-75 overall structure, 75-78 MHC structures, 14-16 precision, 65 resolution, 66 theory, 58,65

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