Frontiers in Drug Design and Discovery, Volume (1)

Frontiers in Drug Design & Discovery Bentham Science Publishers Ltd. http://www.bentham.org/fddd

Volume 1, 2005

Contents Editorial: Cutting Edge Tools in Drug Discovery G.W. Caldwell, Atta-ur-Rahman and B.A. Springer

i

Discovering Novel Antibacterial Agents by High Throughput Screening S. Donadio, L. Brandi, S. Serina, M. Sosio and S. Stinchi

3

Small Molecule Drug Targeting of RNA G.J.R. Zaman

17

Drug Discovery and Design via High Throughput Screening of Combination Phage-Display Protein-Peptide Libraries K. Gazarian

29

High Throughput Screening: Will The Past Meet The Future? P. Englebienne

69

Variety of the DNA Hybridization Rate and Its Relationship with High Order Structure of Single Stranded Nucleic Acids M. Tsuruoka

87

An Overview of High Throughput Screeninkg at G Protien Coupled Receptors R.M. Eglen

97

contd….

Development in Hyphenated Spectroscopic Methods in Natural Products Profiling S. urban and F. Separovic

113

The Role of Kinetics in High Through Screening for Drugs A. Gomez-Hens and M.P. Aguilar-Caballos

167

Assessment of Idea pkEXPRESSTM for the Prediction of Caco-2 Permeabilities C,-P. (Matt) Hsu, G.W. Caldwell, J.A. Masucci, Z. Yan and D.M. Ritchie

197

Exploring the Viability of Metabonomic Urinalysis as a Toxicity Screen Within a Pharmaceutical Drug Discovery Division G.C. Leo, g.W. Caldwell, W. Hageman, B. Hastings, B. Starosciak, K. Snyder, J. Scowcroft and A. Krikava

211

231 Partition of Solvents and Co-Solvents of Nanotubes: Proteins and Cyclopyranoses F. Torrens Automating Literature-Based Lead Discovery J.D. Wren

267

Structural Biology in Early Phase Drug Discovery R. Alexander and J. Spurlino

287

Whole Gene Synthesis: A Gene-O-Matic Future L. Stewart and A.B. Burgin

297

Contributors Subject Index

343 347

Editorial

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Editorial: “Cutting Edge Tools in Drug Discovery” The discovery of novel, ethical therapeutics for the treatment of unmet medical needs has never before been more rich with opportunities and at the same time more challenging with obstacles. The genomic revolution of the 1990’s unleashed a plethora of information on potential new drug targets and the drug industry has followed on with a frenzied attempt to unscramble the possible correlation of these new “targets” with specific disease syndromes. The massive amount of genetic information now available has overwhelmed all current industry mainstay approaches to target validation, confirmation and disease correlation. New techniques, technologies and approaches are under development everywhere in a harried attempt to catch up quickly. All of this is ongoing while financial markets have shifted their interest from developing technologies to delivery of drug products, stifling some of the technological creativity initiated in the 1990’s. Several decades ago it was common to have a wealth of background information available on a potential drug target thanks to years of basic, usually academic, research. In today’s world of drug discovery, targets are typically poorly understood, yet we forge ahead working to discover drugs as we define the target at the molecular level, and its’ potential correlation to disease, in parallel. As a consequence, the drug industry has become less successful (on a target by target basis) in moving compounds into the clinic than ever before. In addition to these challenges, the drug industry finds itself under more scrutiny than ever to provide efficacious drugs with no adverse side effects. Price controls are ever present on the political landscape adding additional pressure to an already overheated pot. Despite these tremendous hurdles consumers have an insatiable appetite for drugs to treat or cure not only the most obvious disease culprits, such as cardiovascular disease and cancers, but to treat lifestyle “conditions” as well, such as moderate obesity and directly related type II diabetes. The desperate need to achieve success drives innovation of new approaches to discover and develop new medicines. This series is dedicated to those on the front lines of drug discovery who seek to find better ways to bring novel drugs to patients faster and cheaper. Technology has always had a tremendous impact on the lifestyles we lead and have come to expect. This first version of Frontiers in Drug Design and Discovery presents some of the most up to date and exciting new technological approaches to speeding up the drug discovery process. Only a concerted effort to apply these new technologies to the discovery and development of new therapeutic drugs will succeed in modernizing the pharmaceutical industry. Although returns are often not realized from technical achievements for many years it is our constant hope for finding better ways to break down the barriers. Many of the chapters deal with advantages and limitations of screening techniques used in the drug discovery process. S. Donadio and colleagues prepared a chapter highlighting the power and limitations of high throughput screening for discovering novel antibacterial agents. The chapter by G.J.R. Zamam gives the reader a feel for the importance of targeting RNA instead of proteins with small molecule drugs. The targeting of human RNAs with small molecules is a relatively new approach in dealing with diseases. K. Gazarian introduces the reader to the design and high throughput screening of phage-displayed combinatorial libraries of proteins and peptides. This chapter describes very clearly the methodology and its main achievements. P. Englebiene has prepared an excellent chapter dealing with the past and future of high

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Editorial

throughput screening in a drug discovery environment. The chapter by R.M Eglen gives an excellent overview of high throughput screening of G protein coupled receptors. The chapter describes measuring signal intensity changes using a microtiter plate format and measuring cellular protein redistribution using imaging-based techniques. A. GomezHens and M.P. Aguilar-Caballos have written a chapter describing the importance of understanding kinetics in the high throughput screening for drug candidates. M. Tsuruoka describes the relationship between steric hindrance and slow hybridization of labeled oligomers mixed with the amplified DNA of genes. The chapter by S. Urban and F. Separovuic gives an overview of hyphenated spectroscopy methods in natural product profiling. C.-P. (Matt) Hsu and colleagues describes the advantages and limitations of in silico prediction of Caco-2 permeabilities using a commercial software package. G.C. Leo and colleagues introduces the reader to the applicability of metabonomic urinalysis as a toxicological screen in drug discovery. F. Torrens presents an interesting chapter on the partitioning of solvents and co-solvents into nanotubes. The chapter by J.D. Wren gives an excellent overview of the use of literature-based sources of knowledge as a tool for discovering novel connections between, for example, diseases, drugs and genes. R. Alexander and J. Spurlino describe in their chapter the role of protein crystallography in drug discovery. The chapter illustrates the contribution of a structure-based drug design approach even at the early phase of the drug discovery process. L. Stewart and A.B. Burgin have prepared an excellent chapter on whole gene synthesis. They illustrate how this powerful technology has the ability to distill a growing body of genetic and structural information into improved nucleic acid sequences that are impossible to obtain by traditional cloning and mutagenesis methods.

Garry W. Caldwell Atta-ur-Rahman Barry A. Springer

Frontiers in Drug Design & Discovery, 2005, 1, 3-16

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Discovering Novel Antibacterial Agents by High Throughput Screening Stefano Donadio*, Letizia Brandi, Stefania Serina, Margherita Sosio, Sofia Stinchi Vicuron Pharmaceuticals, Via R. Lepetit 34, 21040 Gerenzano, Italy Abstract: The increasing frequency of nosocomial infections due to multiresistant bacterial pathogens represents a serious health concern and is continuously threatening the therapeutic effectiveness of many antibiotics. This medical need calls for the discovery and development of novel antibiotics and for the improvement of existing compounds. Searching for novel chemical classes of antibiotics requires the identification of validated targets for structure-based design or for their transformation into assays suitable for high throughput screening. The power of bacterial genetics and the genomic revolution have provided us with hundreds of targets, which represent components of a bacterial cell essential for viability, well conserved in the desired range of pathogens, and significantly different from mammalian counterparts. In addition, several technological advances in automation and detection systems enable now the transformation of most validated targets into high throughput screening assays. Are these new targets and assays leading to the discovery of promising novel antibiotics? We will review the recent literature for new chemical classes discovered by high throughput screening, describing also the different assays and screening approaches. In addition, we will provide our own considerations on the need to integrate targets and assays with the type and novelty of the chemical diversity, highlighting the power and limitations of high throughput screening for discovering valuable drug leads.

INTRODUCTION In the mid 1980s infectious diseases were considered virtually conquered, thanks to the introduction into clinical practice, during the previous decades, of several antibiotics with different mechanisms of action. However, we are now well aware that pathogenic bacteria have become a major health concern: there are examples of Gram-positive bacteria resistant to virtually every clinically available drug, while the threat posed by some drug-recalcitrant Gram-negatives is also increasing. This resurgence of morbidity and mortality by bacterial pathogens can be ascribed to different causes, including a large fraction of elderly and immunocompromized individuals and the spread of antibiotic resistance due to extensive use (and sometime misuse) of antibiotics. These changes in the population, both human and bacterial, have been accompanied by the lack of novel antibiotic classes introduced into the clinics for many decades, which in turn is *Corresponding author: Tel: +39-0296474243; Fax: +39-0296474365; E-mail: [email protected] Garry W. Caldwell / Atta-ur-Rahman / Barry A. Springer (Eds.) All rights reserved – © 2005 Bentham Science Publishers.

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exacerbating the resistance problem through the use of the same antibacterial agents. It is worth mentioning that only two novel classes of antibiotics have been introduced into the clinic over the last thirty years. Two different approaches can be used to identify novel antibiotics: the modification of existing compounds, and the discovery of molecules not affected by the current mechanisms of resistance. Obviously, only the latter approach can eventually lead to new chemical classes and mechanisms of action. These new compounds can be identified either by screening a large collection of diverse chemical entities (defined as a library) in an approach referred to as high throughput screening (HTS); or by the design of putative inhibitors from structural data on a target receptor. There is a blurred distinction between these two approaches, especially since the introduction of in silico screening processes [e.g. 1]. In the anti-infective field, the same pathology may be caused by one or more pathogens, which may exhibit different sensitivities to antibacterial drugs. Ultimately, the effectiveness of an antibiotic will depend on a combination of factors, which include its spectrum, its efficacy and safety in the human host. However, the discovery, development and commercialization of a new antibiotic by the pharmaceutical industry will also depend on extrinsic factors, such as the cost of developing and producing the antibiotic, the number of patients for which the antibiotic will be prescribed, and the cost per prescription that can be charged. These latter factors often constitute a major concern in the industry, and novel antibiotics for life-threatening infections are generally considered niche products of limited market value. TARGETS FOR ANTIBACTERIALS An antibiotic, like any other drug, exerts its action by interacting specifically with a target, usually inhibiting its function, thereby blocking bacterial growth, or some other relevant function. A target is therefore any component of the bacterial cell whose inhibition leads to the desired effect. In the anti-infective field, a target can be validated without having first a compound inhibiting it. Indeed, a valid antibacterial target is any component essential for the viability of a target pathogen, at least under desired circumstances. In addition to targets essential for cell growth, one may also consider targets essential for pathogenesis, for production of a toxin, or for conferring resistance to a particular drug. (Recently, it has been debated whether virulence factors represent an unexploited source of novel targets [e.g. 2]. In our view, virulence factors are too species- or strain-specific to represent good targets, unless the pathology to be cured is caused by a single, well-defined agent). Apart from being essential, a good target must satisfy two additional criteria: it must be conserved, i.e. present and playing an equivalent role in the desired range of pathogens; and it must be specific, i.e. unique to the bacterial world, or at least significantly different in humans. These requirements are extremely important, since an infectious disease is usually caused by significantly different pathogens, which multiply within an animal host. THE IMPACT OF THE GENOMIC REVOLUTION During the last decade, rapid advances in DNA sequencing have made it possible to decipher whole bacterial genomes at unprecedented speeds. This has resulted in over a hundred fully sequenced bacterial genomes, covering the major human pathogens. In the

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early days, bacterial genomes were sequenced under the assumption that, since the clinically available antibiotics act on a limited number of targets (mostly translation and cell wall formation), additional targets were necessary to enhance discovery programs [3-5]. In fact, there was no lack of antibacterial targets, and many essential genes were well documented in the pre-genomic literature [6-7]. Furthermore, while many of the current antibiotics act on bacterial translation or cell wall biogenesis, these pathways require the concerted participation of tens of different factors, each representing a valid molecular target. There are therefore many more molecular targets in these pathways than those acted upon by the clinically available antibiotics. Finally, each multi-domain protein or RNA is likely to contain more than one binding site for potential antibiotics. It is now widely accepted that the products of essential genes represent a source of valid antibacterial targets. The combination of genome information with systematic mutagenesis of bacterial chromosomes has allowed the generation of inventories of essential bacterial genes. For example, Bacillus subtilis has been shown to contain 213 essential genes [8]. Through in silico approaches, each of these essential genes was queried against genomic databases to identify those genes that were conserved in other pathogens and absent from eucaryotic genomes, Fig. (1), leading to over a hundred essential, conserved and selective genes, whose products represent validated targets for novel antibacterials. This is an impressive number, and also an under estimation. Indeed,

Fig. (1). In silico approach at cataloguing bacterial genes for essentiality, conservation and specificity. See text for details.

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each of the genes encoding rRNA is individually dispensable [9], but rRNA is the target of useful antibiotics (e.g. aminoglycosides and macrolides). In addition, glycopeptide antibiotics interfere with intermediates in peptidoglycan formation, and not directly with a gene product [10]. The sequenced genomes have also spurred an interest in the identification of previously unknown essential genes, searching among the genes of unknown function [e.g. 11-12]. This approach was probably driven by the assumption that working on a proprietary target might increase the probability of finding a new antibiotic. While it is too early to evaluate whether essential genes of unknown function will actually provide novel antibiotics, this approach was also led by the lack-of-targets hypothesis. In addition, it should be noted that establishing essentiality for a given gene in one strain does not necessarily imply essentiality in another bacterial species. Examples of this sort exist in the literature, even when the function of the gene product is known [e.g. 13]. Thus, the essentiality of any potential target should be established over a range of relevant pathogens. Notwithstanding these cautionary notes, we should not forget that, prior to the genomic era, months of intensive lab work were required to obtain preliminary, and often inconclusive, data about conservation and selectivity of a chosen target. Nowadays, one can establish, within a day’s work of bioinformatic analysis, whether any target is present and well conserved in the pathogen(s) of interest; if it contains domains or sub-domains present in eukaryotic sequences. These rapid analyses enable the a priori definition of the potential spectrum exhibited by an inhibitor of the chosen target, and allow the design of effective counter-screens for detecting possible toxicity issues at early stages. Significant advances in target validation have come through genomic analyses. For example, while the essential role of MurA in peptidoglycan biosynthesis was well documented [14], Gram-positive cocci have been found to contain a second murA [15]. Streptococcus pneumoniae can survive with either one of the murA genes, while phosphomycin inhibits both MurA enzymes [15]. Clearly, a potential MurA inhibitor must possess inhibitory activity against both proteins to be effective against Grampositive cocci. Two-component signal transduction systems (TCSTS), typically consisting of a histidine kinase and a response regulator, play important roles in bacterial cells. Genomic information has allowed the identification of entire sets of TCSTS in different pathogens. For example, Throup et al. [16] identified 13 S. pneumoniae response regulators, many of which resulted important for adaptation and pathogenesis, while one was essential for growth. In eukaryotes and archaea, synthesis of isoprenoids proceeds through the mevalonate pathway. In bacteria, two distinct pathways are present: Gram-positive cocci make isoprenoids through the mevalonate pathway [17-18], while the glyceraldehyde 3phosphate-pyruvate pathway (called the nonmevalonate pathway) operates in most other bacteria [19-21]. Gene disurption experiments have identified five essential genes in S. pneumoniae, while sequence comparisons indicate a certain divergence between the corresponding five proteins and their mammalian counterparts [17-18]. Consistently, the S. aureus hydroxymethyl-glutaryl-CoA reductase is 104 fold less sensitive to fluvastatin than its human homolog [18]. On the other hand, since the enzymes of the

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nonmevalonate pathway have no orthologs in mammals, they represent attractive targets for new antibacterials. However, inhibitors of these enzymes will necessarily be ineffective against Gram-positive cocci. Although sequence comparison provides a powerful tool for target validation, it has limitations. For example, bacterial and archaeal Ile-tRNA synthetases (IleRS) are the targets for mupirocin, which does not inhibit the eukaryotic enzyme. Sassanfar and coworkers [22] established that the bacterial IleRS differs from eukaryotic and archaeal enzymes in the C-terminal domain sequence, while the catalytic domain, where mupirocin binds, is conserved in the enzymes from the three domains of life. However, in the Thermus thermophylus IleRS, mupirocin makes contact with two critical residues, which are not conserved in the eukaryotic enzymes [23]. In addition, several authors have used genomic information to identify genes that are essential and unique to particular bacterial pathogens (e.g. Chlamydia, Helicobacter), with the aim of developing selective antibiotics that would not affect the remaining bacterial flora. It remains to be established whether antibiotics of this sort, if they ever become available, will encounter the favor of the practicing physicians. FROM TARGETS TO SCREENS With a plethora of validated antibacterial targets, approaches to screening become extremely important for a successful drug discovery program. Three general types of assays can be used: a) cell-based assays, where a putative inhibitor exerts its action on a suitable cell; b) functional cell-free assays, where one measures an enzymatic activity; and c) binding assays, which depend on measuring the formation of a ligand-receptor complex. Enzymatic or binding assays offer the advantage of measuring the effect directly on the target receptor, thus providing also a measure of the inhibitor’s affinity for the target. In addition, cell-free systems are usually very sensitive, since they are devoid of the barrier(s) that might hinder an inhibitor from accessing its target within a bacterial cell. Cell-based assays, on the other hand, provide a response in the presence of these same barriers, a situation that is closer to an antibiotic’s desired effect. However, since growth inhibition of a bacterial cell can result from interference with any target, cell-based assays have been designed that respond only to the inhibition of selected target(s). We describe some examples of recent advances in screening technologies for both cell-free and cell-based assays, emphasizing their application to antibacterial programs. TECHNOLOGICAL ADVANCES In recent years, HTS miniaturization has substantially increased screening capacity. High density microplates, associated with small volume liquid handling robotics and improved detection technologies, allow nowadays HTS operations at low cost, fast turnaround time, reduced space requirements and high quality data [24]. The increase in the number of wells per plate from 96 to 1536 allows a reduction of working reaction volume from 200 to 5 µL, with a 100-fold drop in reagent costs [25]. The 1536-well format seems well established, judging from several validated screening campaigns [2628]. Limits to the increase and development of the well format miniaturization (from 96 to 384, 1536, 3456 or 20,000 wells/plate) are imposed by the advanced technological

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requirements (for nanovolumes handling and for optimized detection in a manner that is both sensitive and rapid [29]). In addition, the intrinsic characteristics of some assays are such that they cannot be adapted to run in small volumes with good signal to noise ratios and with false positives and false negatives minimized [30]. Some alternative approaches to the well format are reported in the literature [31-32]. For example, the gel permeation technology allows the screening of chemical compounds using an “assay sandwich” made of three sheets: a first sheet of gel matrix containing the diffused target is brought into contact with a second sheet of polystyrene containing discrete compounds. A third gel matrix sheet containing additional reaction components and the detection reactants allows the identification of a single compound that interferes with the target activity [33]. The gel permeation technology uses the gel matrix microenvironment as a reaction vessel where all assay components are mixed, maintaining humidity, compound location and allowing reagent addition in a sheet format. For these reasons the well-less format overcomes many problems of the well format, such as evaporation, plate-edge effects, complex liquid-handling requirements. In theory, any 96-well plate assay can be adapted to the gel-permeation format [33]. The throughput of this format is very high, in the order of 200,000 tests per hour [34], with a 17-fold cost savings with respect to the well technology [35]. Although technological advances in HTS miniaturization are widespread, most antibacterial assays found in the literature use the traditional 96- or 384-well formats. An example of antibacterial miniaturized HTS is represented by a coupled Transcription/Translation (T/T) assay [36]. A cell-free T/T bacterial system driven by the firefly luciferase reporter gene was adapted to run in 1536-well format, validated for the screening of inhibitors of transcription and/or translation and applied to an 183,000compound chemical library. The high throughput of this screening, over 20,000 compounds tested per hour, allowed the analysis of the entire library in triplicate, yielding data of high confidence and quality with a significant savings in reagents and time. Technological advances are important not only for the test format but also for the design of innovative assays (for example, those based on molecular structure-function details of a target) or simply to improve the assay detection with a better signal to noise. An example of a knowledge-based assay using a new technology detection system is described by Bergendahl et al. [37], who used Luminescence Resonance Energy Transfer to screen for inhibitors of protein-protein interactions in bacterial RNA polymerase. The interaction between the β’ and σ70 subunits is essential for polymerase activity. Using a β’ fragment and σ70 labeled with different fluorophores, the authors could measure any perturbation of their interaction at very low protein concentrations (1 to 100 nM) and in a small reaction volume (10 µL). Under their experimental conditions, the assay was robust enough to be compatible with a library consisting of marine sponge extracts. REPORTER GENE ASSAYS In recent years, considerable attention has been dedicated to whole-cell assays for antibacterial research. This renewed interest in whole-cell assays for HTS probably derives from the observed limitation of cell-free assays and from a deeper understanding of the workings of bacterial cells. In fact, post-genomic technologies have shown that

Discovering Novel Antibacterial Agents

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antibiotics with different structures and mode of action affect transcription of several bacterial genes, usually at concentrations lower than those necessary for inhibiting bacterial growth [38]. Indeed, transcriptional profiling is a useful and powerful tool to identify promoters that respond to specific antibiotic stresses [39]. It appears that most antibiotics exert a global transcriptional response within a bacterial cell, and that antibiotics acting on the same cellular pathway, elicit similar responses. At the same time, many inhibitors discovered with sensitive enzymatic assays were found to be incapable of effectively inhibiting their cytoplasmic targets within a bacterial cell. Thus, the attractive possibility existed of engineering bacterial cells, so that the expression of an easily measurable reporter gene was under the control of a promoter specifically induced by antibiotics of a defined class and/or mechanism of action. Reporter assays present in principle the advantages of both the enzymatic and the growth inhibition assays, since they are target-specific while measuring a response within a live bacterial cell. In addition, reporter assays usually require low concentrations of test compounds and relatively short incubation times, since transcriptional responses are sensitive and rapid in bacteria. The scientific literature describes many gene fusions between a stress promoter and a reporter gene, which respond to one or more classes of antibiotics. Some examples are listed in Table 1. These include reporter assays for inhibitors of transcription, translation, cell wall or other metabolic reactions. A sensitive and highly selective assay for the detection of antimicrobial compounds affecting DNA replication has been described [40], which takes advantage of the ability of DNA-damaging compounds to induce SOSresponse genes. It consists of an E. coli strain bearing a single-copy fusion between the Table 1.

a

Some Examples of Reporter Assays

Straina

Stress

Pathway

Promoter

Reporter

Reference

Ec

protein misfolding

cell envelope

P3rpoH

lacZ

[44]

Ec

unknown

cell wall

bla

lacZ

[56]

Bs

cell-envelope damage

cell wall

liaIH

lacZ

[43]

Bs

unknown

cell wall

vanH

lacZ

[42]

Sc

unknown

cell wall

sigEp

neo

[45]

Ec

DNA damage

DNA replication

sulA

lacZ

[40]

Bs

unknown

fatty acid synthesis

fabHB

lacZ

[46]

Ec

unknown

secretion

secA

lacZ

[41]

Ec

heat shock

translation

ibp

lacZ

[44]

Ec

cold shock

translation

cspA

lacZ

[44]

Bs

many

many

lux

[47]

Strain abbreviations: Bs, Bacillus subtilis; Ec, Escherichia coli; Sc, Streptomyces coelicolor.

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lacZ gene and the SOS-inducible sulA promoter. A similar approach, developed for secretion inhibitors, uses a secA-lacZ fusion [41]. SecA regulates the activity of its own promoter in response to changes in secretion levels. Thus, the activity of β-galactosidase in the reporter assay will respond to inhibitors of the secretion process. In B. subtilis, the vanRS system appears to respond to many cell-wall inhibitors [42]. Recently, it was found that the liaIH genes are strongly induced by vancomycin and bacitracin [43]. Both systems, using appropriate lacZ fusions, represent potential reporter assays for detecting new cell-wall inhibitors in B. subtilis. Other examples include: the heat shock (ibpA and ibpB) or cold shock (cspA) genes, which have been investigated for their potential to be used as reporter system for the detection of H- and C-type protein biosynthesis inhibitors, respectively [44]; the extracytoplasmatic sigma factor σE as an indicator of compounds affecting the outer membrane or interfering with peptidoglycan biosynthesis [44-45]; and the fabX system, which responds to fatty acid biosynthesis inhibitors in B. subtilis [46]. A list of antibiotic-responsive promoters has been identified through whole-cell transcriptional profiling in B. subtlis [47]. A common feature to most reporter assays is that the cellular response is, within limits, independent of growth inhibition, and often detectable at sub-MIC levels. In the presence of very high antibiotic concentrations, the signal may be lost, resulting in a typical bell-shaped curve of signal versus antibiotic concentration. Another feature of reporter systems is that they usually respond to a whole pathway, so these assays can potentially detect inhibitors of many targets acting on the same pathway. It should be noted that reporter assays measure the transcriptional response of an entire bacterial cell to a particular stress. Thus, they provide an indirect measure of the effect on the desired cellular pathway. Because a bacterial cell is actually a network of different signaling systems, extensive validation of a reporter assay must be performed to establish whether it responds only to the desired inhibitors, or if it sees other types of stresses. In addition, stress responses can be strain-specific, thus the same gene fusions may not work to the same purpose in different bacterial species. FROM ASSAYS TO LEADS It is reasonable to expect a certain lag between the introduction into HTS programs of the many targets available from genomics and of the new assay technologies, and the discovery of new drug candidates through their application on a sufficiently large chemical diversity. It should be noted that many genome sequences were performed by pharmaceutical companies well before they became available in the public databases, and it is safe to assume that most targets have been available to big pharma for almost a decade. Thus, the existing literature should reasonably well reflect the lead compounds identified with the technologies implemented up to the late 1990s. Selected examples of lead compounds discovered through HTS in the last few years are reported in Table 2. The reader is referred to a previous review [48] for antibacterial compounds described up to the mid 1990s. It is worth emphasizing that Table 2 does not report those antibiotics that resulted from the modifications of existing compounds (whether in clinical use of not), from a re-evaluation of old antibiotics, or from rational drug design. In compiling Table 2, we have considered the target, the type of assay, the nature of the library screened, the affinity of the inhibitor for the target, its antibacterial activity and selectivity. Most of the lead compounds identified act on well-established bacterial targets, such as transcription, protein synthesis and modification, cell division,

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DNA replication, cell wall formation or fatty acid biosynthesis. A common characteristic to most of the lead compounds described in Table 2 is that they have been identified using enzymatic assays. In a few cases, cell-based assays were employed. (To our knowledge, there are no reports of novel antibacterial agents identified through binding assays). The use of enzymatic assays as primary screening tools is probably the reason why some of the compounds are powerful inhibitors of their targets, but show limited antibacterial activity (Table 2). Chemical libraries, whether totally random or biased towards particular pharmacophores, have been the major source of chemical diversity employed in the screening programs (Table 2). It is likely that the few examples of lead compounds derived from natural sources, reflect a diminished use of microbial and plant extracts by the pharmaceutical industry, in comparison with chemical or combinatorial libraries. It should also be noted the use of biased chemical libraries, which are generated from a knowledge of the enzymatic class and/or the structure of the target enzyme. With peptide deformylase, this approach has led to the identification of compounds with the same core structure in three out of four inhibitors (Table 2), which also show antibacterial activity and good selectivity [49-51]. This core structure is actually related to that of actinonin, a known microbial metabolite. It remains to be determined whether biased libraries will be successful for other targets as well. Broad-spectrum compounds have been rarely identified: the saccharomicins, heptadecaglycoside antibiotics produced by Saccharothrix espanaensis, exhibit good activity against Gram-positive organisms and good to moderate activity against Gramnegative organisms [52]. In some cases, the inhibitory activity on a target enzyme did not translate into a meaningful antibacterial potency. It should be noted that an HTS program is expected to deliver a lead structure, which should be optimized through iterative steps of medicinal chemistry. In the case of one FabI inhibitor [53], chemical programs afforded a compound with good activity against Staphylococcus aureus and other Gram-positive pathogens, starting from a lead structure devoid of antimicrobial activity. This event, however, might represent an exception, and in many cases no further progress on the lead compounds has been reported. This suggests that many lead modification programs were either unsuccessful, or not undertaken at all. Thus, it should not be assumed that medicinal chemistry programs will eventually confer desired antibiotic property to any lead structure. HTS AND CHEMICAL DIVERSITY The recent literature shows a larger number of targets and assays for antibacterial discovery than of new chemical entities identified through HTS. In addition, there appears to be a recent bias towards cell-based assays, while most of the new chemical classes were discovered through the use of cell-free assays. While some lead compounds identified by HTS may have not yet surfaced in the literature, the overall impression is that the ability to identify targets, design assays and implement them in HTS has dramatically outpaced the productivity of HTS programs. The survey of new antibacterial leads, an analysis of overviews and commentaries recently appeared, and our personal feeling as scientists directly involved in the design of assays for discovering novel antibiotics by HTS, seem to converge onto a common

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Table 2.

Some Examples of Antibacterial Leads

Compound

Assayd Library (size)e

Target

IC50 (nM)

MIC (µg/ml)f

Reference

cpd 20

AcpS

enz

N.I.

15,000

12 (Sp)

[58]

cpd 1

DNA gyrase

rep

RC

372

64 (Sa); 64 (Ec*)

[59]

cpd 3

DNA ligase

enz

RC

0.14

1 (Sa)

[60]

SB418011

FabH

enz

N.I

16

N.R.

[61]

cpd 4a

FabI

enz

RC (305k)

47

0.008 (Sa); 8 (Ec)

[53, 62]

DHDPE

FabI

g.in.

RC

2,500

1 (Ec)

[63]

viriditoxin

FtsZ

enz

MPE (>100k)

12

4 (Sa); 25 (Ec*)

[64]

SB236049

β-lactamases

enz

E

≤2,000

N.R.

[65]

BB-78485

LpxC

hypers

BC

160

1 (Ec); 32 (Sa)

[66]

saccharomicin

membrane

N.R.

ME

0.1 (Sa); 16 (Ec)

[52]

α-pyrone I

b

membrane

rep

ME (46k)

1 (Sa); 128 (Ec*)

[67]

CHIR29498

membrane

N.R.

RC

10 (Sa); 20 (Ec)

[68]

RWJ cpds

MurA

enz

RC

4 (Sa); 8 (Ec)

[69]

INF

NorA

hypers

RC (10k)

g

[70]

VRC3375

PDF

enz

BC

4

1 (Sa); 0.25 (Ec*)

[51]

BB-3497

PDF

enz

BC

7

4 (Sa); 8 (Ec)

[49]

cpd 1

PDF

enz

RC

<5

128 (Hi)

[71]

41e

PDF

enz

BC

15

N.R.

[50]

cpd 1-7a

Phe-RS

enz

RC

5

0.2 (Ec); 0.4 (Sa)

[72]

A-692345

a

c

200

ribosome

enz

BC (300k)

14,000

16 (Sa)

[73]

CBR703

RNA polymerase

enz

RC (220k)

10,000

4.5 (Ec*)

[74]

GE23077

RNA polymerase

enz

ME

20

32 (Ec)

[75]

RpoE

N.R.

N.R.

N.R.

2.5 (Sa)

[76]

SPase I

enz

E (50k)

110

8 (Sp); 4 (Ec)

[77]

Sch419560

b

lipoglycopeptide

a

Donadio et al.

cpd 30

g.in.

BC

0.66 (Ec*); 4 (Sa)

[78]

kalimantacin

N.R.

E

25 (Ec); 0.2 (Sa)

[79]

cpd 1

g.in.

RC

0.4 (ONLY Hp)

[80]

derived from optimization of lead compound same chemical class identified with FAB screen d abbreviations: enz, enzymatic assay; g.in., growth inhibition; N.R., not reported; hypers, growth inhibition of hypersensitive strain; rep, reporter assay e abbreviations: BC, biased chemical library; E, extracts, microbial (M) or plant (P), when specified; RC, random chemical library. Sizes are in thousands. f the lowest MIC against one Gram-positive and/or Gram-negative are reported, where available. abbreviation: (Ec*), Escherichia coli hypersensitive strain, (Ec), Escherichia coli, (Sa), Staphylococcus aureus, (Hp), Helicobacter pylori, (Sp) Streptococcus pneumoniae, (Hi), Haemophilus influenzae. g the compound does not have an MIC, but exhibits synergism with ciprofloxacin. b c

Discovering Novel Antibacterial Agents

Frontiers in Drug Design & Discovery, 2005, Vol. 1 13

conclusion. Reading with hindsight the literature of the last decade, it appears that the limiting factor in discovering new lead compounds was not the lack of adequate targets and of effective screening technologies. It seems that the discovery efforts in the pharmaceutical industry were mostly driven by the assumption that what was important was how (in terms of targets and assay technologies) to screen, and little attention was paid to what (in terms of chemical diversity) to screen. This was probably due to the impression that an infinite variety of chemical compounds was available, consisting in part of the impressive number of chemical entities synthesized by medicinal chemists during the previous decades and in part supplied by combinatorial chemistry. Since these libraries could be screened quickly with robotics, the driving force has thus far been the identification of any lead compound in a relatively short time, under the assumption that these leads could be transformed into drug candidates by chemical intervention. In fact, the chemical diversity represented by the existing synthetic libraries represents a very small fraction of the theoretical chemical space [54], thus the existing screening technologies can only search a small and often biased chemical diversity. As any scientist who has worked with frustration on attempts to transform a poor lead compound into a potential drug candidate can testify, lead optimization can only go that far. In this framework, two possible extreme scenarios can be envisioned. One is based on the assumption that the existing chemical diversity cannot be expanded at reasonable costs. Since the probability of discovering a valid lead compound represents a rare event, the chances of success can be increased by expanding the number of data-points. This requires the introduction of as many as possible HTS programs, very efficient HTS operations and the use of strict selection criteria. Advancement and optimization of novel screening technologies will be essential for coping with automation demands and for reducing reagent costs through volume miniaturization. Thus, this scenario will rely mostly on technological advances and in project management to increase output per cost unit. This approach might be successful in the short-term. However, it will inevitably lead to an exhaustion of the existing chemical diversity, and still relies on the how-toscreen paradigm. In our opinion, the successful search for novel antibacterial agents by HTS can only derive from a substantial renovation of the chemical diversity available for screening. This renovation cannot keep ignoring natural products just because they do not allow HTS programs as rapid as chemical libraries. However, we must also be aware of the fact that both plant and microbial products have been intensively screened for antibacterial activities. Thus, the chemical diversity produced by the previously screened plants and microbes cannot be expected to be infinite either. New valid natural sources are needed to increase our chances for success, as they did in the part [55-56]. Fortunately, we are now aware that just a fraction of the existing biodiversity is known and has been sampled. If these unexploited sources can be identified and introduced rapidly into screening programs, then we might be lifting the lid on a Pandora’s box of hitherto unknown chemical compounds. ABBREVIATIONS HTS RS T/T TCSTS

= = = =

High Throughput Screening tRNA synthetase Transcription/Translation Two Component Signal Transduction System

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Small Molecule Drug Targeting of RNA Guido J.R. Zaman* N.V. Organon, Molecular Pharmacology Unit, P.O. Box 20, 5340 BH Oss, The Netherlands Abstract: Targeting at the RNA level is considered as an alternative approach to traditional drug discovery focusing on proteins. The targeting of bacterial ribosomal RNA with aminoglycoside antibiotics has provided clear precedence for the targeting of RNA with small molecule drugs. Aminoglycosides can also bind to human cytoplasmic ribosomal RNA and suppress premature termination codons in human messenger RNAs. This suppression activity is explored for the development of novel therapies for genetic disorders caused by premature stop codon mutations, such as cystic fibrosis and Duchenne muscular dystrophy. While aminoglycosides act on ribosomal RNA, certain small molecule metabolites, including vitamins, lysine and purines, can regulate gene expression by binding to messenger RNA at so-called ‘riboswitches’. Riboswitches consist of complex three-dimensional structures, located in the 5’-untranslated region of bacterial and fungal messenger RNAs, coding for proteins involved in the uptake, biosynthesis and export of these metabolites. It is unknown whether riboswitches also occur in human cells. Riboswitches provide yet another proof that small molecules can influence biological events by binding directly to RNA. The targeting of human messenger RNAs with small synthetic chemical molecules is a relatively new approach, but may create new and unique opportunities for drug discovery. By using messenger RNA as a target, all genes in the human genome may be considered, including those that encode proteins that are not amenable to highthroughput screening, but for which clear associations with disease processes follow from (molecular) genetic or pharmacological investigations. In this area, progress has been made recently in the targeting of the Alzheimer’s βamyloid precursor protein messenger RNA, and the tumor necrosis factor-α messenger RNA.

INTRODUCTION Modern drug discovery is a highly industrialized process in which the chance of finding good drug leads is enhanced by screening high numbers of protein targets against large collections of synthetic chemical molecules. To further reduce the risk of failure of this high-throughput screening (HTS) operation, many pharmaceutical companies confine themselves more and more to certain families of targets that have proven to be particularly successful, as evidenced by the number of marketed medicines interacting with these protein classes. These ‘druggable’ protein families include *Corresponding author: Tel: +31-412-661043; E-mail: [email protected] Garry W. Caldwell / Atta-ur-Rahman / Barry A. Springer (Eds.) All rights reserved – © 2005 Bentham Science Publishers.

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G-protein coupled receptors (GPCRs), nuclear receptors, ion channels, transporters and enzymes [1]. Generic technologies to assay these druggable proteins are available, and greatly speed up the process from gene-to-screen [2-4]. Screening assays can either be biochemical or cell-based. Biochemical assays are based on (partly) purified proteins, or membrane preparations, and are used to measure receptor binding or enzyme activity [4]. Cell-based assays use functional or phenotypic read-outs [2,3]. In the case of receptor targets, these assays measure ligand ‘efficacy’ [5]. Since the start of HTS in the early 1990s, this factory-like approach for drug discovery has yielded a limited number of new drugs and several tens of new drug candidates [6]. Sequencing of the human genome has revealed the DNA code of many new members of the druggable protein classes [1]. However, the human genome project has also identified many proteins that are not amenable to HTS, because assay technologies are not available, or because the biochemical function of these proteins are not yet known [7]. In fact, the major drug target classes cover only 17 % of the human genome [7]. Furthermore, in more than half of all instances, the screening of druggable proteins does not deliver a good lead compound [6]. It is therefore not surprising that targeting at the RNA level is gaining interest in pharmaceutical industry and biotech as an alternative approach to traditional drug discovery focusing on proteins. RNA has been targeted with antisense oligonucleotides, small inhibitory RNAs (siRNA), or RNA enzymes (ribozymes). Until now, the success of these sequence-specific targeting approaches has been limited to one approved therapeutic, Vitravene™ (fomivirsen) (http://www.isispharm.com). Vitravene™ is an antisense drug for treatment of cytomegalovirus retinal infections in people with AIDS. The development of nucleic acid-based therapies is significantly hampered by delivery problems of these large molecules. The targeting of RNA with small organic molecules holds great promise. A characteristic feature of RNA is that it can fold into complex three-dimensional structures comprising loops, bulges, pseudoknots and turns [7]. These structures are responsible for the diverse actions of RNA molecules within cells. In this respect, RNA resembles more a protein than DNA, which is less flexible and has a less diverse tertiary structure. The unique shapes in various target RNAs create potential binding sites for small molecules [7]. A property of messenger RNA (mRNA) that makes it an attractive target for drug discovery is that mRNA molecules are usually present in cells at relatively low copy numbers, as compared to proteins. mRNA is therefore highly sensitive to small changes in the concentrations of regulatory signals, such as proteins and small molecules. PROOF-OF-CONCEPT PROVIDED BY NATURE The aminoglycoside antibiotics have provided clear precedence for the targeting of RNA with small molecule drugs. Aminoglycosides bind to the RNA component of the small ribosomal subunit, the 16S ribosomal RNA (rRNA) [8]. They exert their antimicrobial activity by inducing misreading of the genetic code. This results in the loss of functional proteins and the accumulation of abnormal proteins in the bacterial membrane, which compromises its barrier function and finally results in cell lysis [9]. In 1943, streptomycin was the first member of the aminoglycoside family discovered to have antimicrobial activity against gram negative bacteria and Mycobacterium tuberculosis, the causative agent of tuberculosis [10]. In contrast to the discovery of penicillin by Alexander Fleming in 1929 [11], which was largely due to a matter of

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chance, the isolation of streptomycin was the result of a long-term, systematic effort by Selman A. Waksman and co-workers, who tested the antimicrobial activity of 10,000 different soil microbes for their antibacterial activity [10]. In fact, streptomycin was the first drug that was discovered as the result of ‘screening’, as opposed to ‘rational design’. Since the breakthrough discovery of streptomycin, which was awarded with the Nobel Prize to Dr Waksman in 1952, more than 150 aminoglycosides with highly diverse chemical structures have been isolated from the culture filtrates of bacteria. In addition, many semi-synthetic variants have been derived from these natural products, with the aim to develop more selective RNA targeting drugs, or to combat drug resistance. MECHANISM OF ACTION OF AMINOGLYCOSIDE ANTIBIOTICS The study of the binding of aminoglycoside antibiotics to rRNA has revealed the basic principles of RNA – drug interactions. Small RNA oligonucleotides derived from the decoding A-site bind aminoglycosides similar to the whole ribosome [12]. Binding is primarily determined by electrostatic interactions [13-15] and relatively non-specific [16]. Affinities for 16S rRNA fragments range from 300 nM for neomycine to 5 µM for other aminoglycosides, such as paromomycin and kanamycin B [15]. Aminoglycosides also bind to human 18S rRNA, with affinities that are only two- to six-fold lower than for the binding to bacterial 16 S rRNA [15]. In view of the success of the aminoglycosides as antibacterials for over half a century, this may come as a surprise. It should be noted, however, that aminoglycoside therapy could cause severe side effects. Of these, renal toxicity is the most common. Despite changes in treatment regimens and monitoring procedures, still 5 to 25 % of patients suffer from this side effect, as has been reported in clinical studies [17]. The second main side effect is ear toxicity, which can result in reversible or irreversible deafness [18]. Both side effects are explained by the specific accumulation of aminoglycosides in renal tubular epithelial cells or in hair cells of the inner ear, which express a specific membrane receptor for aminoglycosides, megalin [19]. There are two main factors that determine the selective cytotoxic action of aminoglycosides on bacterial cells. The first is the sequence differences between bacterial and human rRNA. This is illustrated by the fact that a ‘pseudo-eukaryotic’ rRNA can be created by mutation of Escherichia coli rRNA at one specific residue in the A-site [20]. Expression of this ‘pseudo-eukaryotic’ rRNA renders bacteria 100 times more resistant to neomycin. The second important factor is the occurrence in prokaryotes of transporter proteins that actively take up and concentrate aminoglycosides in the cytoplasm [21]. The mechanism by which aminoglycosides, through binding to ribosomal rRNA, interfere with the fidelity of the translation machinery is understood in great detail by the co-crystal structure of the characteristic example paromomycin, and the 30S ribosomal subunit [14]. Aminoglycoside binding shifts the equilibrium between two conformations of the rRNA towards a confirmation that is more prone to the binding of non-cognate (incorrect) transfer RNAs (tRNA), thus resulting in an increased error rate of the ribosome. Thus, like compounds that act on protein receptors, aminoglycosides exert their action by directing the conformation of an RNA target.

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RIBOSWITCHES While aminoglycosides act on ribosomal RNA, certain small molecule metabolites can regulate gene expression by binding to messenger RNA (mRNA). Binding occurs at defined target sites within so-called ‘riboswitches’, Fig. (1). Riboswitches consist of complex three-dimensional structures, located in the 5’-untranslated region (UTR) of bacterial and fungal mRNAs, coding for proteins involved in the uptake, biosynthesis and export of these metabolites, Riboswitches have been found that bind flavin mononucleotide (FMN) [22,23], thiamine pyrophosphate (TPP) [22,24], coenzyme B12 [25], S-adenosylmethionine (SAM) [26,27], lysine [28,29], guanine [30], adenine [31], and glucosamine-6-phosphate (GlcN6P) [32].

Fig. (1). Structure of riboswitch aptamers with their corresponding metabolites, from reference [66].

Riboswitches are composed of two parts: an ‘aptamer’, which is a high affinity binding site for the metabolite, and an ‘expression platform’, which translates ligand binding into regulation of gene expression. The mechanism of riboswitches is very

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similar to that of aminoglycosides acting on rRNA. Binding of the metabolite ligand induces a switch between two conformational states of the RNA target. This switch either results in termination of transcription, or in inhibition of translation initiation. In the first case, the riboswitch involves formation of an intrinsic translation terminator in the 5’-UTR, which causes transcription to terminate before the coding region is reached. In the second mechanism, a stable alternative stem-loop structure is formed, in which the Shine and Dalgarno sequence is closed, thus preventing translation initiation. In a very recently described example, GlcN6P, the binding site in the glmS mRNA consists of a ribozyme [32]. This RNA performs self-cleavage, which is enhanced 1000-fold in the presence of GlcN6P [32]. The affinities of several ligands that bind to riboswitches are in the same range as those of small molecule drugs binding to proteins, Table (1). For the few cases studied, binding was also specific. For instance, for FMN and TTP almost 1000-fold differences in binding constants were observed compared to riboflavin and thiamine, which lack the phosphate groups [23,24]. For SAM a 100-fold discrimination against S-adenosylhomocysteine, which lacks a single methyl group and one positive charge, and 10,000fold against S-adenosyl-cysteine was observed [27]. The guanine and adenine aptamers are identical, except for one nucleotide to which they owe their specificity [30,31]. The GlcN6P riboswitch also shows specificity, as analogs such as glucose-6-phosphate and glucosamine do not stimulate cleavage [32]. Table 1.

Affinities of Metabolites for their Cognate Riboswitches

Metabolite:

Kd

Reference

Flavin mononucleotide

5 nM

[22,23]

Thiamine pyrophosphate

100 nM

[24]

Coenzyme B12

300 nM

[25]

S-adenosylmethionine

4 nM

[26,27]

L-lysine

1 µM

[28,29]

Guanine

5 nM

[30]

Adenine

300 nM

[31]

Glucosamine-6-phosphate

200 µM

[32]

Riboswitches are widespread among bacterial species. In Bacillus subtilus, at least 69 genes are predicted to be under the control of riboswitches [30]. This comprises approximately 2 % of the total genome of this bacterium. Riboswitches also occur in fungal mRNAs [33], and have been predicted to occur in the mRNA of plants [34]. However, most of the genes in which riboswitches have been found in prokaryotes are absent in the genome of ‘higher’ species, such as man. It is therefore unknown whether riboswitches, or similar mechanisms occur in human cells.

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Riboswitches create entirely new opportunities for the development of novel antimicrobials [7,35]. Since many of the genes in bacteria that are regulated by riboswitches are involved in fundamental biochemical processes, metabolite analogs that interfere with riboswitch function can be expected to impair vital metabolic functions and cause cessation of growth. If the phylogenetic distribution of riboswitches indeed is limited to ‘lower’ species, riboswitches are attractive targets for the development of specific bacterial anti-metabolites TREATMENT OF AMINOGLYCOSIDES

HUMAN

GENETIC

DISORDERS

WITH

Based on their ability to bind not only to bacterial, but also to human rRNA, aminoglycosides are being applied for the development of novel treatment of human genetic disorders. The antibiotics G-418 and gentamicin have been shown to cause readthrough of a premature stop codon in the gene for the cystic fibrosis transmembrane conductance regulator (CFTR), a transmembrane chloride transporter [36,37]. These premature stop codons in the CFTR gene occur in a 5 % subpopulation of cystic fibrosis patients. Read-through resulted in increased levels of full-length CFTR and restored CFTR-mediated chloride transporter activity in a CF bronchial epithelial cell line [37]. There were no immediate detrimental effects on other cellular functions. Topical administration of gentamicin to the nasal epithelium of patients with cystic fibrosis resulted in the expression of functional CFTR [38]. The suppression of stop codons with aminoglycosides is also being explored as a potential treatment for Duchenne muscular dystrophy (DMD), which is caused by the absence of dystrophin protein in striated muscle [39]. In DMD, 6 % of all cases arise from premature stop codons in the dystrophin gene [39]. Promising data were obtained with a mouse model of DMD. Aminoglycosides increased the expression of full-length protein from a dystrophin allele carrying a stop codon mutation [38]. However, these results could not be reproduced in patients with DMD [40]. Aminoglycosides also have been shown to cause read-through of premature stop codons in genes involved in other human genetic disorders, such as Hurler syndrome, which is a lysosomal storage disease [41], cystinosis [42], late infantile neuronal ceroid lipofuscinosis [43], and in disorders involving the p53 gene [44]. Read-through resulted in increased levels of full-length proteins [41-44]. TARGETING OF HIV-1 VIRAL RNAs Besides rRNA, aminoglycosides can bind in a saturable fashion and with similar micromolar affinities to a variety of other RNA structures containing non-duplex elements. Based on this property, aminoglycosides have been used as lead compounds for the development of more selective RNA targeting drugs. In human immunodeficiency virus-1 (HIV-1) RNA, there are two structures that are bound by aminoglycosides: i.e. the Rev protein response element (RRE) and the transactivationresponsive element (TAR), Fig. (2). RRE is the binding site of the viral Rev protein in the envelope gene of HIV-1, and plays a role in the transport of unspliced viral RNA from the nucleus to the cytoplasm. The TAR RNA hairpin is present in all HIV-1 mRNAs and plays an important role in the viral replication cycle. TAR is bound by the viral Tat protein, which is essential for transcriptional activation and elongation of HIV1 mRNA synthesis. This protein – RNA interaction has been recognized as an important target for the development of new therapies against AIDS and has been studied

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extensively [45]. A number of molecules, varying from heterocyclic compounds, peptides and peptidomimetics have been reported to interfere with the Tat – TAR interaction [46,47]. Some of these have been shown to inhibit HIV-1 replication in cells [48], but none has led to new drugs.

Fig. (2). Target sites of aminoglycosides in HIV-1 RNA.

TARGETING OF ALZHEIMER’S β-AMYLOID PRECURSOR PROTEIN mRNA Targeting human mRNAs with small synthetic chemical molecules is a relatively new approach. In general, tertiary structures in mRNA, such as hairpins or pseudoknots, are expected to provide more selective binding sites than single-stranded regions or stable double-stranded domains [7]. Although the structure of mRNA is considered to be less complex than that of rRNA, there are a few well-defined secondary structure elements in mRNA and drug target sites described in literature. One example of a welldefined secondary structure in mRNA is the iron response element (IRE), Fig. (3), which is contained in several mRNAs involved in iron homeostasis [49]. At low cytosolic concentrations of iron, the IRE is bound by the iron sensor protein aconitase. When the concentration of iron in the cell increases, the protein dissociates from the IRE. In some mRNAs, such as the mRNA that codes for the iron-storage protein ferritin, the IRE is located in the 5’ leader, where it functions as a translational silencer. In other mRNAs, such as the mRNA that codes for the transferrin receptor, the IRE is located in the 3’UTR. Here the function of the IRE is to increase the stability of the mRNA. At low cytosolic concentrations of iron, aconitase binds to the IRE in both the ferritin and transferrin receptor mRNA. This results in inhibition of ferritin translation. At the same time, the stability, and consequently the translation, of the transferrin mRNA is increased. In response to increased levels of iron, aconitase dissociates from both mRNAs. This results in increased synthesis of ferritin and iron storage, while the synthesis of the transferrin receptor and the cellular uptake of iron are decreased. Recently, IRE has been identified in the 5’-UTR of the Alzheimer’s β-amyloid precursor protein (APP) [50]. APP is the precursor protein of the main component of the

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neurological amyloid plaques that are formed during the progression of Alzheimer’s disease. Reduction of the intracellular concentration of iron using chelators resulted in a decrease of APP 5’-UTR controlled translation [50], Fig. (3). A cell-based assay consisting of a luciferase reporter whose translation is driven by the 5’-UTR of APP mRNA, has been used to identify APP inhibitors by screening [51]. Several compounds with activities in the (sub)millimolar range have been identified [51].

Fig. (3). Iron response element in the 5’ leader of ferritin mRNA, the 3’-UTR of transferrin receptor mRNA, and the 5’-UTR of the mRNA coding for Alzheimer’s β-amyloid precursor protein (APP).

TARGETING OF TUMOR NECROSIS FACTOR-α mRNA Tumor necrosis factor-α (TNFα) is a pro-inflammatory cytokine involved in various immune diseases. Like other cytokines and proto-oncogenes, TNFα is regulated at the post-transcriptional level through adenylate/uridylate-rich elements (AREs) in the 3’UTR of its mRNA [52]. Several proteins have been identified that bind AREs to mediate RNA decay, and hence translational efficiency [53,54]. It has been shown that the synthesis of TNFα can be inhibited by thalidomide [55]. Thalidomide is a glutamic acid derivative that was introduced as a sedative hypnotic in 1956, but was withdrawn in 1961, due to the development of grove congenital abnormalities in babies born to mothers using it for treating morning sickness. The compound was re-introduced as a therapeutic for leprosy and more recently has demonstrated potency in the treatment of a variety of cancers [56]. The initial mechanism underpinning the action of this compound was shown to be inhibition of TNFα protein expression and it was further demonstrated to act at the post-transcriptional level to facilitate turnover of the mRNA [57]. The action

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of thalidomide to lower TNFα levels is not particularly potent, but analogues have been synthesized that inhibit TNFα production in peripheral blood monocytes in the low micro molarrange [56]. By using luciferase reporter assays, it was shown that the thalidomide analogs act through the ARE-containing sequences in the 5’-UTR of the TNFα mRNA [56]. CONCLUSION The targeting of human mRNAs with small synthetic chemical molecules is a relatively new approach, but may create new and unique opportunities for drug development. Proof-of-concept that small molecules can influence biological events directly, without the interference of protein receptors has been provided by the mechanism of action of aminoglycoside antibiotics and by the riboswitches. By using mRNA as a target, it will be possible to target any gene, including those that encode proteins that are not amenable to HTS, but for which clear associations with disease processes follow from (molecular) genetic or pharmacological investigations. PERSPECTIVE While targeting RNA creates unique opportunities for drug discovery in many therapeutic areas, it may be in particular attractive for the development of new male contraceptives [7]. Spermatogenesis is a strictly regulated cellular development process, in which several RNA binding proteins play a critical role [58]. This is evidenced from genetic deficiencies that cause male sterility. For instance, deletions in the Y chromosome encompassing the genes coding for the RNA binding proteins RBM [59] or DAZ [60,61] correlate with severe impairment of spermatogenesis. Also based on studies with transgenic mouse models, sperm cell specific RNAs have been identified that could be used as targets for the development of new male contraceptives [7]. What makes drug discovery for RNA different from drug discovery for proteins? In many cases, the binding of compounds to protein receptors or enzymes has been shown to result in a change of the conformation of the target. This conformational change is essential and determines the nature of the biological effect [5]. For example, different drugs that act through the nuclear estrogen receptor induce distinct conformations of the receptor, which have been visualized by X-ray crystallography [62]. The different receptor conformations result in the recruitment of different associating co-factors, and exerts different biological effects [63]. Also for GPCRs different receptor conformations have been proposed to explain the different behavior of ligands of these receptors [64]. Aminoglycosides and metabolites that bind to riboswitches act through a similar mechanism, as they exert their action by directing the conformation of the RNA. Methodologies to discover small molecules that bind to RNA targets by HTS are based on the same principles and read-out technologies that are applied for drug discovery on proteins [7]. Usually, the RNA molecules are radio labeled or labeled with fluorescent probes. RNA binding proteins [7], or allosteric ribozymes [65] can be used to monitor the binding of small molecules. The screening of large chemical libraries for compounds that fortuitously bind to RNA has, however, not delivered new drug leads that have entered clinical trials. It may be that this approach is not the most optimal. Recently, some successes have been reported in the identification of compounds that inhibit the synthesis of APP or TNFα at the post-transcriptional level by applying cell-

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based reporter assays [51,56]. However, whether these compounds actually work by binding to RNA remains to be determined. ABBREVIATIONS APP

=

β-amyloid precursor protein

ARE

=

Adenylate/uridylate-rich element

CFTR

=

Cystic fibrosis transmembrane conductance regulator

DMD

=

Duchenne muscular dystrophy

FMN

=

Flavin mononucleotide

GlcN6P

=

Glucosamine-6-phosphate

HIV-1

=

Human immunodeficiency virus-1

HTS

=

High-throughput screening

IRE

=

Iron response element

mRNA

=

Messenger RNA

RRE

=

Rev protein response element

rRNA

=

Ribosomal RNA

SAM

=

S-adenosylmethionine

siRNA

=

Small inhibitory RNA

TAT

=

Transactivation-responsive element

TNFα

=

Tumor necrosis factor α

TTP

=

Thiamine pyrophosphate

UTR

=

Untranslated region

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Rogers, J.T.; Randall, J.D.; Eder, P.S.; Huang, X.; Bush, A.I.; Tanzi, R.E.; Venti, A.; Payton, S.M.; Giordano, T.; Nagano, S.; Cahill, C.M.; Moir, R.; Lahiri, D.K.; Greig, N.; Sarang, S.S.; Gullans, S.R. J. Mol. Neurosci., 2002, 19, 77-82. Kruys, V.; Marinx, O.; Shaw, G.; Deschamps, J.; Huez, G. Science, 1989, 245, 852-855. Kruys, V. ; Huez, G. Biochemie, 1994, 76, 862-866. Chen, C.-Y.; Shyu, A.-B. Trends Biol. Sci., 1995, 20, 465-470. Sampaio, E.P.; Sarno, E.N.; Gallily, R.; Cohn, Z.A.; Kaplan, G. J. Exp. Med., 1991, 173, 699-703. Zhu, X.; Giordano, T.; Yu, Q.-S.; Holloway, H.W.; Perry, T.A.; Lahiri, D.K.; Brossi, A.; Greig, N.H. J. Med. Chem., 2003, 46, 5222-5229. Moreira, A.L.; Sampaio, E.P.; Zmuidzinas, A.; Frindt, P.; Smith, K.A.; Kaplan, G. J. Exp. Med., 1993, 177, 1675-1680. Venables, J.P.; Eperon, I.C. Curr. Opinion Genet. & Dev., 1999, 9, 346-354. Elliott, D.J.; Millar, M.R.; Oghene, K.; Ross, A.; Kiesewetter, F.; Pryor, J.; McIntyre, M.; Hargreave, T.B.; Saunders, P.; Vogt, P.H.; Chandley A.C.; Cooke H. Proc. Natl. Acad. Sci. USA, 1997, 94, 38483853. Reijo, R.; Lee, T.Y.; Salo, P.; Alagappan, R.; Brown, L.G.; Rosenberg, M.; Rozen, S.; Jaffe, T.; Straus, D.; Hovatta, O. et al. Nat. Genet., 1995, 10, 383-393. Reijo, R.; Alagappan, R.K.; Patrizio, P.; Page, D.C. Lancet, 1996, 347, 1290-1293. Brzozowski, A.M.; Pike, A.C.; Dauter, Z.; Hubbard, R.E.; Bonn, T.; Engstrom, O.; Ohman, L.; Greene, G.L.; Gustafsson, J.A.; Carlquist, M. Nature, 1997, 389, 753-758. Shang, Y.; Brown, M. Science, 2002, 295, 2465-2468. Kenakin, T. Trends Pharmacol. Sci., 2003, 24, 346-354. Soukup, G.A.; Breaker, R.R. Proc. Natl. Acad. Sci. USA, 1999, 6, 3584-3589. Soukup, J.K.; Soukup, G.A. Curr. Opin. Struct. Biol., 2004, 14, 344-349.

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Drug Discovery and Design Via High Throughput Screening of Combinatorial Phage-Display ProteinPeptide Libraries Karlen Gazarian* Department of Molecular Biology and Biotechnology of the Institute of Biomedical Research, Mexican National University, Mexico D.F, Mexico Abstract: The advent in the mid to late 80s of the concept and methods of construction and high throughput screening of phage-displayed combinatorial libraries of proteins and peptides is a revolutionary step in the modern history of molecular biology and its area dedicated to make deep insights into the principles of inter-molecular recognition, the cornerstone of all mechanisms and processes in the living systems. High throughput screening of combinatorial libraries is a miniature model of selection of “best among many candidates” occurring everyday in the nature and resulting in this laboratory scale in new substances, peptides and proteins, with capacities of recognition of their partner molecules of extreme physiological significance required for the basic studies and resolution of chronically persisting and newly emerging biomedical concerns. In this review I intend to give a summary of the emergence of the methodology and its main achievements, focusing on the perspectives it shows for the drug design and discovery via the use of its highly effective protein-peptide engineering and selection techniques. The analysis is directed towards the most troubling infectious and autoimmune diseases (AIDS, hepatitis, cancer, diabetes, parasitological, toxicological). The objective of this review is to give a sketch of the frontiers in drug design and discovery based on the actual state of the research, the tendencies that are seen and the limitations that should be overcome to direct the potential of highthroughput screening technology to resolution of major medical problems.

INTRODUCTION During their evolution, animals and plants have developed systems and mechanisms stabilizing normal, “physiological” homeostasis necessary for each individual to realize its genetically determined ontogenetic program. The cumulative evidence that the program is realized lies in the life span with gradual aging and death after the exhaustion of the programmed resources. Microorganisms and parasitic uni- and multi-cellular species, which use human organism as their milieu of reproduction and evolution, cause permanent diseases and premature aging. Hosts and pathogens evolved together in an equilibrium that was maintained throughout evolution by natural selection but has

*Corresponding address: Tel: 5255 5622 3821; Fax: 5255 5550 0048;E-mail: [email protected] Garry W. Caldwell / Atta-ur-Rahman / Barry A. Springer (Eds.) All rights reserved – © 2005 Bentham Science Publishers.

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destabilized in the evolution of humans due to the non-natural social factors that gradually replace the natural factors. The medicine is faced with large list of anomalies of human organism, which exist mostly in animals (cancer, pandemic infections, etc) but are extended and deepened by specific human style of the life. In the last century, globalization of human activity has promoted the extensive evolution of the pathogenic viruses and bacteria that existed and that emerge as zoonotic events. These changes raise the crucial question whether or not the modern medicine is equipped to meet this reality. In the context of these challenges, medicine seeks materials, drugs, and methods to address the major problems: diagnosis and treatment, and, ideally, the prevention When one wants to speak about the discovery and design of drugs, he or she becomes aware how unlimited the notion of drug is. It includes any kind of material that can cure but not damage, the principal dilemma of the medicine. Actually, there is no need for a precise definition of the notion because everyone knows what it means from personal experience. For simplicity’s sake, drugs may be defined as substances which are introduced into organism with a particular anomaly to stop the pathological process, and, if possible, to restore the norm. Initially, materials mostly of plant origin were used as drugs in empirical public medicine. Nowadays, plants continue to provide a large list of pharmacological materials. The discovery of antibiotics became the first step in the industrial production of the naturally evolved biologically active substances. Venom of snakes and scorpions, rich in specific channel blockers, in enzymes, were another source of the pharmacological industry. In the recent times bioorganic compounds from animals and humans became more and more usable in the therapeutic practices. As animal and human tissues can be source of infectious agents such as HIV or new viruses like SARSCoV, a large group of medicines of this origin should be produced in cultured cells under controlled conditions. The advent of the recombinant methodologies opened new perspectives in the use as producers genetically modified microorganisms, somatic cells, plants and animals; however this route can only satisfy the minor part of the demanded drugs. Organic chemistry industry remains the major drug producer, which resolves the actual problems but suffers from the adverse effects of these substances due to their inability of distinguishing between normal and pathologcal cells, and a low specificity of the interaction with biological macromolecules. Nevertheless, they are widely used because cannot be substituted with new generation of effective and highly specific and safe substitutes. There is expectations that the newly developed concepts and thechnique that use large libraries of bio-molecules and methods for their throughput screening with human origin reagent molecules, form the frontiers of the future drug design and discovery to which this review is dedicated. Emergence of the Principle of Phage Display and Its Realization The advent of phage display was one of the several lines of the progress in biological sciences, which, after having accumulated information and techniques in the areas of biochemistry, genetics, and molecular biology over decades, entered in the mid-seventies in the period of a burst of fundamental discoveries: nucleosomes, intron-exon organization of eukaryotic genes, mobile elements in animals originally found in plants by McClintock in the early fifties, restriction enzymes and DNA recombination

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techniques which permitted the cloning and expression of guest genes in transformed bacteria, somatic cells, in transgenic animals and plants, manipulation of mammalian embryos with first reports on the cloning of mouse and culturing of embryonic stem cells. The gene cloning in plasmids, phagemids, generation of genome-scale libraries in lambda cloning system, provided structurally defined genetic material for expression in in vitro and in vivo transcription and transcription-translation systems to elucidate the coding and surrounding them regulatory sequences in cloned DNA fragments. Expressed proteins have to be purified using time and material consuming chromatographic procedures, followed by the assessment their properties, modification and new rounds of expression of the genes. The demonstration in 1985 by George Smith [1] of the feasibility of expression and surface display of a foreign protein fused with filamentous phage coat protein appeared to be a key step towards efficient combination of these procedures, expression, assessment, selection, modification, and amplification of proteins in a single and relatively simple system. The work became the cornerstone of the phage display technology that revolutionized protein engineering. Subsequent demonstration that recombinant phage can be enriched via the screening (biopanning, [2]) of the phage population with binders recognizing the displayed foreign protein, and the idea that libraries of random peptides can be expressed in this way and screened, has promptly been realized in his and other laboratories for peptide, antibody and non-antibody protein display [5-8]. De la Cruz et al. [9] and Ilyichev et al. [10] constructed recombinant phage displaying proteins and shown that they are immunogenic. Felici and coworkers [11] developed their vector for gpVIII-fusion random peptides and focused on selection of mimotopes with monoclonal [11] and polyclonal serum antibodies [12, 13]. Antibody fragments selected in combinatorial libraries served for mapping epitopes, and for generating by affinity maturation mutagenesis HIV-1 neutralizing Fabs. Cunningham, Wells [14, 15] used the phage display of growth hormone to impulse and extends their developed Ala-scanning mutagenesis strategy of identification of amino acids involved in protein function, in epitopes, in particular. After the implementation of phage display, this permitted to accelerate drastically the rate of mutagenesis and screening procedures using randomized amino acids. This opened a possibility of protein engineering for reducing (“minimizing”) the protein structure leaving only amino acid groups required for the function [16]. Another strategy of “minimization” was developed through selection of hormone substitutes in random peptide libraries screened with receptors of hormones. The selected peptides were modified by randomization of particular amino acids to obtain finally peptides capable of inducing erythropoiesis [17-18]. The display of enzymes permitted to discover substrate analogs and elucidate the structure of catalytic amino acid groups. Projects on generation of vaccines based on peptide-mimotopes selected by mAbs [19] or patient serum [20] have been proposed and are currently underway [21]. Thus, in few years many lines of experimentation with phage display system gave representative examples demonstrating the power of the methodology and establishing the general potential of the peptide and protein engineering-fusion-expression-displayselection-amplification using a single multi-step procedure. In subsequent years, these

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lines have been exploited, extending these results but at the same time revealing limitations of the practiced methodology. This created an impression that the methodology has exhausted its initial resources of the “infancy” [22] and requires new ideas and/or techniques to reach maturity so as to resolve complicated problems of the modern biotechnology and medicine. In recent years, some of the branches of the methodology accumulate hidden force for the new explosion of discoveries. One of these is seen in the intensified cell-surface directed screening [23] with recent intravascular library screening in a patient [24] with perspectives of organism-level search for ligands in their most natural state. The earlier proposed landscape library system [25] becomes actively exploited [26-28] for the descovery of tumor-specific mammalian cell surface receptors and for large-scale probing on bacterial surface markers for diagnostic purposes and for highly specific and safe detection of dangerous bacteria including species potent in bioterrorism [27,28]. These and other publications document that the methodology continues movement towards its main goals: diagnosis and treatment. Phage Display Libraries After the description by G. Smith of the filamentous phage display-expressionselection principle, first libraries of protein fusion to the coat proteins, major gpVIII and minor gpIII, have been constructed and screened (reviewed by [29-31]). Vectors based on the phage genome only give libraries in which every protein, gpIII or gpVIII, displays the fusion product (“full display”), and vectors derived from phage-bacterial recombinant genomes, phagemids, displaying the foreign molecule in a part of the gpIII or gpVIII proteins (“hybrid display”). Display of many proteins or peptides containing amino acid differences, each on separate phage is a library that can be screened (panned) on a selector molecule, e.g. an antibody, and, after washing out the phage unbound to the selector, to release (elute) the bound protein or peptide recognized by the selector. This basic principle is exploited via many procedures to yield proteins or peptides containing specific sites of recognition as contiguous or, mostly, discontinuous, amino acid groups. Full display discriminates the functional activity of the gpIII (infectivity) and gpVIII (phage particle assembly) proteins, posing limitations on the size of the displayed molecule and not permitting the display of amino acid sequences exceeding certain length. In case of the gpVIII-type libraries made using the 50aa-long capside protein interacting with each other (and possibly with DNA inside the particle), the size of display is limited to 6-8 residues. In case of the gpIII-type involving no more than five host protein molecules, each consisting of three domains, the size of the fused protein is less restricted because the foreign molecule is located on the N-terminus, whereas the gpIII function (interaction with the E.coli pili) is accomplished by the internal domain forming knob. It also made possible due to the strategy of using only one of the gpIII molecules (monovalent libraries) by means of superinfection with helper phage providing wild-type gpIII for the recombinant phage. gpIII-fusion peptide (these are the sequences of less than 50 amino acids) libraries have been so far constructed displaying from 6 to 43aa-long peptides. Linear and Constrained Libraries The first libraries contained linear peptides which are flexible and form high number of non-stabilized configurations. Then it was demonstrated that by inserting cysteine

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residues at appropriate distance (typically at the termini of the random peptide sequence) the flexibility can be constrained [32,33]. Peptides containing two cysteines usually form loops [33] and in many instances such disulfide-bond constrained libraries yield higher affinity peptides than linear libraries [34]. The protein folding in periplasm of E.coli favours the interaction of the neighbour cysteines existing in the guest peptide or protein, but the possibility of their interaction with the phage gpIII cysteines (8 residues) is not completely prevented. In order to minimize the formation of such cys-cys bonds, random libraries can be designed with a lower cysteine content (e.g. in libraries provided by Biolabs, New England, USA). Despite this reduced cysteine content, binders with affinity to loop-structures can find in such cysteine-deficient libraries peptides with two cysteines [35]. Landscape Libraries Using gpVIII gene-derivative vectors [29, 36], landscape phage library displaying peptides on every protein has been constructed [25,26]. An alpha-landscape library has also been constructed in which sub-terminal gpVIII helical positions are random [37]. Since this is a novel construction we give a brief description of its characteristics. The library carries six degenerate codons in gene VIII, specifying amino acid residues 12, 13, 15,16,17, and 19, and is characterized by a great diversity of amino acids at these randomized positions, which is maintained during repeated subculture. It is suggested (corroborated by circular dichroism spectroscopy) that due to the fact that the variegated segments lie in an extended alpha-helical portion of the protein, the library sequences should be strongly conformationally constrained and stabilized by numerous inter- and intra-subunit contacts. The authors indicate that the conformational homogeneity of diverse elements in this library allows the selection of ligands with α-helical organization. Also, due to their alpha-helical constrain, peptides from this library are rigid structures, which may be of high importance for particular goals in phage display studies, for example, (a) selection of mimotopes on fibrous proteins forming coiled coil alpha- helical structures, and (b) act as a source of new fiber materials for nanotechnology with highly ordered physical and chemical properties. Such materials are expected to contribute to the development of diagnostics, bio-detectors, biosensors, vaccines. Primary (Random) and Secondary-Generation (Biased) Libraries Two type screening strategies, single-phase and two-phase, were developed [36]. In the first of them, fully random (primary, naïve) gpIII or gpVIII library is subjected to three (sometimes more) consecutive rounds of selection (Fig. (1)). In the two-phase strategy, first, a gpVIII random library is screened to collect relatively low affinity (due to the polyvalent display) peptides, then a second generation gpIII library is constructed in which the selected amino acids are conserved and remaining positions are randomized. The new library is screened for the selection of high affinity peptides. Combiantorial Oligonucleotide Libraries. Tuerk and Gold [38] and Ellington and Szostak [39] published in 1990 their pioneering work on oligonucleotide library construction and selection. The methodology [40] is known as SELEX (Systematic Evolution of Ligands by Exponential Enrichment).

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Although these combinatorial libraries are beyond the scope of the review, they are to be briefly mentioned here because are designed for the same purpose as phage display, selection of ligands, here aptamers. Vast libraries of 1014-1015 of single chain nucleic acid sequences, RNA, DNA or modified nucleic acid sequences are subjected to iterative screening with various molecules including proteins, followed by PCR-amplification of selected subsets to isolate after many cycles (up to 14) populations of molecules tightly binding to the selecting molecule. The outstanding feature of this selection strategy is the immense number of variant sequences that are screened. Another important property is that the nucleic acid sequences (RNA and single-stranded DNA) work at all three structural levels, primary, secondary, and three-dimensional, which is not the case in amino acid libraries. Owing this property, nucleic acid sequences comprising libraries for SELEX fold into a huge variety of shapes formed by secondary-structure elements, providing a wide spectrum of binding possibilities for the molecular surfaces presented by the selecting molecules. Ligands were selected both by protein natural binding sites

Yu, Smith (1996) Fig. (1). Two peptide selection strategies.

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and by their regions, which are not destined for such kind interactions. This distinguishes SELEX from Phage Display, where natural intermolecular contact regions are normally selectors. Libraries of natural RNAs are screened for defining their sites interacting with proteins [41-45], for example, binding of mRNA loops to T4 DNA polymerase, to the rho translation-terminator factor of E. coli, tRNA sites of interaction with synthetases and elongation factor EF-Tu. A number of aptamers have been selected using HIV-1 proteins Rev, Tat, RT. In particular, the known region in viral RNA interacting with Rev was randomized and the resulted library was selected to find Rev-binding sequence and design its three-dimensional model. RNA ligands for HIV-1 Tat and RT proteins were also isolated from a library of 32 random nucleotides. High affinity aptamers of RT were isolated that did not interact with RT of other retroviruses. Notably, aptamers selected for RT of avian mieloblastosis virus and Molony Murine Leukemia Virus had a biological activity - inhibited the polymerase and RNase H enzymatic activities. Of interest in the context of the drug discovery are the selected aptamers to proteins, normally known not to interact with nucleic acids, which can be potent inhibitors or promoters of their biological activity; for example, binders selected for thrombin able to inhibit its clothing function. In this experiment, a 96-base oligonucleotide was selected that bound to thrombin which then was “minimized” to derive a small molecule with 100-fold higher affinity (see below for similar phage display protein “minimization” strategy). The bFGF (basic Fibroblast Growth Factor, involved in angiogenesis) was used to select aptamers. In SELEX, powerful computer-assisted analytical programs are implemented for processing of selected aptamers and identifying in them consensus patterns and predicted secondary stricture [45]. RESULTS OF THE SCREENING OF PHAGE DISPLAY COMBINATORIAL LIBRARIES WITH VARIOUS SELECTORS Since 1990, general principles, methods, applications, and results of phage display have been described in many manuals and reviews, to which the reader is referred for the detailed and comprehensive knowledge of the methodology [29, 30, 46, 47, 48]. Below, we describe representative results of these studies most relevant to the aim of this review - drug design and discovery. Protein Display and Engineering to Minimize the Structure Immunoglobulins Hybridoma technique permits generation of murine origin mAbs, which to be used as drugs are “humanized”. Human origin mAbs became available after the implementation of procedures permitting immortalization of human lymphocytes by Epstein-Barr virus [49]. Many well-known antibodies of therapeutic significance, such as the 2F5 to the gp41 ELDKWA epitope, 447-52 to gp120 V3 principal neutralizing epitope, were of this origin [50]. Phage libraries of immunoglobulins are an independent source of antibodies. In these libraries are displayed variable, VH and VL, domains of the Ig molecule that either associate non-covalently (Fab) or connected covalently (scFv). The first libraries exploiting PCR-copies of variable genes encoding sequences of Fab fragments were from mice. A large series of Fabs have been selected to various antigens with purposes of their laboratory and clinical usage. Further engineering of the fragments via generation of minibodies, dibodies is done. Resulting recombinant antibody fragments can show lower affinity than parental Ab or the same affinity as in case of the scFv

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against p53 [51] or may even exceed [52] in affinity the original antibody. The enhanced affinity can be achieved using the CDR walking procedure of directed mutagenesis as has been done for the anti-HIV-1 Fab b12 [53, 54], and for anti-oncogen erb-2 scFv [55], which permitted to reach picomolar affinity level. Paratope-Derivative Peptides Displaying the Specificity of Their Parental Antibody Continuing the “minimal antibody” strategy, researchers started to further dissect the variable parts of IgG by using short peptides carrying their paratope sequences. Peptides derived from paratopes have been assayed with the antigens and shown that they are still carriers of the antibody specificity. One of the first systems was scFv to angiotensin, an octopeptide hormone representing the primary active component of the renin-angiotensin system that plays a central role in the regulation of blood pressure. Cohen et al. [56] used the scFv generated from high affinity (1011M-1) mAb 4D8 to angiotensin II for investigation of the antigen-binding capacity of the paratope sequences. This scFv had the same specificity profile and affinity constant as the intact antibody and was investigated further to know whether paratope-derivative peptides will retain these functional activities. It has been found that several overlapping peptides are still able to bind angiotensin II [57, 58]. The capacity of peptides derived from the V(H) and V(L) sequences of two other antibodies, anti-thyroglobulin, and anti-lyzozyme, have also been investigated. Of high interest are the data obtained with the anti-lyzozyme antibody HyHEL-5, as the results of the peptide analysis could be compared with the information from X-ray crystallography of the antibody-antigen complex. Small peptides were found to display the whole antibody binding specificity. Of the 38 residues identified as critical for the paratope binding to lyzozyme, 22 corresponded to the residues found in the interface by the X-ray crystallography. In other papers from this group [59], synthetic peptides derived from the variable regions of an anti-CD4 mAb have been shown to bind to CD4 and inhibit HIV-1 promoter activation in virus-infected cells. The combination of the paratope-derivative peptide assay with site-directed mutagenesis permitted also to map functional amino acids in paratopes of neutralizing antibodies to HIV-1 [60]. More recently, the crystal structure of complexes of several paratope–derivative peptides of the broadly neutralizing IgG 2F5 were resolved by X-ray and the obtained information was used for the elucidation of conformation of the ELDKWA epitope [61]. Thus, the developed peptide approach permits to map short sequences in paratopes displaying the antibody binding function and provide information complementing data from other structural studies. Its advantage over the traditional structural methods is that it allows physical dissection of the structure-function relationships in antibody paratopes and to use short sequences from binding domains for designing miniaturized therapeutic mono-specific molecules. Its next step is seen in the generation of phage libraries of paratope sequences with randomized amino acid positions and selection sequences with properties of both antibodies and epitopes. Scaffolds for Engineering Novel Binding Sites in Proteins The Emergence and Principle of Scaffold Strategy The use of combinatorial protein chemistry along with powerful selection techniques had led to the development of novel ligands for non-antibody proteins using the strategy

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of randomization of surface residues of a parental protein, which is used as a scaffold. With the 3D structure of a suitable starting protein, variants with affinity to a desired target can be selected from combinatorial libraries constructed via random but yet targeted amino acid substitutions directed to the molecular surface. Such new proteins, based on different protein frameworks of various topologies selected from libraries via specific binding towards a given target, have perspectives to complement, substitute or modify natural proteins, antibodies, hormones, etc. in several biomedical applications relevant to the diagnosis and the therapy of diseases. This section of the review will deal with the results from combinatorial approaches used to obtain proteinaceous ligands derived from an original protein of beneficial features. Many groups have recruited naturally existing proteins or domains for engineering via display, randomization and optimization (reviewed by [62]). A prerequisite for the success is that the protein should comprise regions at the molecular surface that can be manipulated via amino acid replacement or insertion maintaining the characteristic scaffold parameters (the specific secondary and 3D structure) and can be expressed and purified. Structural information on the scaffold candidate is of great importance in defining the target regions for the randomization. In cases in which the native template protein itself has a binding function, residues involved in that interaction were the first candidates for the randomization. Successful randomizations to improve on a native binding function have been started by the use of the strategy of amino acid substitution with alanine (“alanine scanning”), indicating the importance of the residue in the protein function, described in protein engineering papers [63-66]. The obtained information indicated the ways towards the engineering of new binding specificities. This is a further challenge because the success requires, apart from the individual amino acid data, preliminary structure-function knowledge of the proteins with various topologies obtained from special investigations. This is required to enhance the probability of obtaining a complementary surface, protrusion or crevice, as interface for the binding. Several groups have taken the first step towards the selection of such 'artificial binding molecules', employing native or engineered presentation scaffolds of different overall topologies for combinatorial randomization of surface residues. Using such approaches, sequences capable of, for example, serving as substrates [67-69] or inhibitors [70], or sites for binding of antibodies [71], or receptors [17] have been identified. Immunoglobulin-Like Scaffolds The first engineering procedures with the hypervariable region forming the paratope interface has been done for enhancing the binding function which resulted in picomolar affinity not existing in natural antibodies (cited above). The immunoglobulin scaffold, present in Fab fragments offers also excellent possibilities for other type engineering but also may lead to complications due to the two interacting molecules to be engineered and assessed. The use of single-chain antibody fragments containing only three loops which can bind antigen (like antibodies of camels devoid of light chains [72]), eliminates the difficulty. Scaffolds of minibodies have been extensively used for partial randomization [73, 74]. In the first of these works, a minibody scaffold of 61 residues derived from a mAb was used for randomization of parts corresponding to the exposed hypervariable loops H1 and H2 [73]. Martin et al. [74] used a phage library of 5x107 variants with random sequences in the loops for screening against human IL-6 and

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isolated a minibody (MB02) that inhibited IL-6 receptor through the binding to H2 loop with micromolar affinity and contained a sequence matching well seven consecutive amino acid stretch in the receptor of the IL-6. Randomization of the H1 loop permitted to develop a higher affinity to IL-6. Loop libraries based on the tendamistat scaffold (a 74 amino acid Ig-like protein [75] that inhibits amylase) have been constructed and screened. A phagemid library of variants obtained via randomization of loops and subjected to panning against an endothelin-specific mAb yielded among many different sequences one found in about 50% of the analyzed clones possessing α-amylase binding activity. Its activity was mediated by the non-variegated “loop one,” which implies a native-like fold involved in the binding. The loop insert sequence in this variant had no obvious similarity to endothelin. This supported the results of alanine-substitution performed on endothelin indicating that the sequence recognized by the mAb is a nonlinear α-helical epitope. Staphylococcal Protein A Bacterial staphylococcal protein A, an Ig-binding protein composed of five homologous domains has been attractive system as a source of shorter single-domain scaffolds for engineering due to peculiar features such as several ordered alpha-helical structures folding without cysteine bridges (can occur also in the cytoplasm) and the high contribution of hydrophobic surface areas binding to Fc. The 58aa domain B composed of three helices, of which two have binding interfaces, has been a source of the small scaffold derivatives extensively used for generation of gpIII libraries of Fcbinding helical structures via randomization of the amino acids (see [62]). Synthetic “Z” domain of 38 amino acids containing the two α-helices with the Fc-binding sites was produced and used for engineering. Structurally equivalent to the original domain Fcbinding variants (Z38, Z34C) were selected and investigated by various methods including NMR [76]. In another series, the synthetic gene for the whole 58aa domain was variegated at 13 amino acid encoding sites of which seven are on the Fc-binding interface, to produce a library of 4.5 x 107 variants with conserved hydrophobic residues important for the protein stability. The library was a source of proteins binding Tag DNA polymerase, human insulin, human apolipoprotein A-1. Circular dichroism has shown their significant proportion still maintain the high helical content, suggesting an overall fold similar to the native domain. The important advantages of the system as a scaffold are: small size of the proteins permitting the use of synthetic versions and introducing non-natural amino acids, and its relatively flat binding surface for the selection of ligands to relatively large molecules. The elimination of the third a-helix devoid of the Fc-binding site but important for the stability necessitated the inclusion of an inter-helical cysteine bond in case of Z34C. Libraries of Zinc-Fingers Zinc finger [77] found first in transcription factor TFIIIA as its DNA-binding domain [78] is also scaffold of a great interest for randomization engineering. Zinc fingers of the Cys2His 2 (or TFIIIA) motif are abundant in eukaryotic transcription factors. They are represented by domains of around 30 amino acids structured as pair of anti-parallel β strands followed by a α-helix, in which two cysteines and two histidines coordinate a zinc atom stabilizing the protein structure. The amino acids in the N-terminal part of the helix are responsible for the DNA sequence-specific binding. Each amino acid specifically recognizes three base pairs of the DNA sequence [79]. The use of phage

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libraries for manipulating zinc fingers is successfully used for generating fingers with novel specificity. Libraries of fingers with randomized DNA-contacting residues were constructed and screened with hair-pin-like DNA binders containing different three-base sequences (codons), and clones recognized by each DNA binder were isolated as novel zinc-finger variants [80-83]. A large number of zinc fingers capable of binding new and defined DNA targets were obtained from the libraries with variegated DNA-binding region that permits deciphering the amino acid recognition three-nucleotide code. The information gained in these studies is useful for designing novel transcription regulators, as, for example, has been done for the exogenous erb-2 promoter [84]. Furthermore, by designing transcription factors, Barbas’ group reported on the successful modulation of the activity of endogenous genes [85,86]. The use of this potential of zinc fingers and that of the combinatorial phage display machinery opens a new avenue in the programmed regulation of the genomic functions through newly designed and engineered zinc-finger transcription regulators. The zinc-finger scaffold also provides a framework useful for elucidating proteinprotein interaction. Employing a parental Cys2His2 zinc finger (CP-1) as a scaffold, Bianchi et al [87] generated libraries of variants with variegated five discontinuous positions in the α-helical subdomain. The screening of the libraries with a mAb to Shigella flexneri bore a common consensus epitope His-Fen-Val-Gln-His/Arg. This study demonstrates that zinc fingers provide a possibility of epitope identification on the folded well stabilized protein context, which cannot be identified with conventional phage display epitope mapping approach. One limitation of this approach is a low diversity that can be achieved by randomization a small area on the protein surface. Speaking of the potentials of this scaffold, worth of mentioning is the report on a smallest, 23-residue, zinc-finger-like peptide able to fold in the absence of the metal [88]. Phage-Display Engineering of Loops and Helices in Proteins Cytochrome E. coli cytochrome b562, a 106aa four-helix bundle, devoid of cysteines [89] was used to construct a library of about 108 phage clones expressing its variants with mutations in two loops produced via randomization at five and four positions; the library was panned on a conjugate between N-methyl-p-nitrobenzylamine derivative and BSA. Sequencing of the variants revealed in each of the loops two conserved amino acids. In the second library the non-conserved positions were fully and the conserved positions slightly randomized. When panned on the same conjugate, an additional consensus amino acid was identified to complement the four previous. Despite the long procedure, newly obtained cytochromes failed to bind free V-methyl-p-nitrobenzylamine ligand as well as that conjugated to ovalbumin or BSA alone, suggesting that the BSA was a participant of the putative epitope. In a series of studies α-helical regions have been used as targets for randomization. For example, Houston et al. [90] used a synthetically produced 24aa-long helices forming coiled-coil that was stabilized by insertion of two lactam bridges, and used for grafting a discontinuous five-residue epitope recognized by a IgA mAb which retained its epitope specificity to the antibody. The disadvantage of this kind otherwise interesting small scaffold was the absence of stabilizing inter-helix loop that should be compensated by the introduced lactam. In another work [91], a 56-residue coiled-coil

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stem-loop miniprotein was constructed, avoiding the necessity of additional stabilizers and permitting better possibilities: the use of both the α-helical and loop positions as targets for engineering via randomization. A conformationally constrained synthetic library represented by an 18-residue α-helical peptide consisting of leucine and lysines was used for the selection of functional proteins [92]; it was found that some of the replaced amino acids increased the helical content of the original peptide. The introduction of randomized positions along α-helically constrained frameworks is expected to yield biased helical libraries from which proteins with desired functions are expected to be isolated. Recent development [37] of alpha-helical-type library is a promoter of these perspectives, permitting to carry out basic studies with α-helical structure and design helix-containing proteins as scaffolds. Protease Inhibitors The characteristic feature of protease inhibitors is the highly constrained structure stabilized with intramolecular disulfide bonds. The inhibition is achieved by binding their cognate protease with high affinity via exposed loops that mimic the substrate but resist the cleavage by the protease. Loops in general (as shown above) are suitable targets for engineering and in case of protease inhibitors, where they are the recognition regions in the protein, the randomization strategy is productive, generating a spectrum of modified loops differing in their binding and protease-resisting properties for selection of variants that may also be used for discovery of non-protein protease inhibitors. Wang et al. [93] constructed a phage library of 4x102 clones expressing an E. coli serine protease inhibitor, ecotin, in which the positions of the reactive residues, Met 84 and Met85, were randomized. The screening with human urokinase-type plasminogen activator yielded ecotin variants enriched in basic amino acids at the random positions, of which one variant with arginine in the both randomized positions, had a 2800-fold higher urokinase-binding ability than the original ecotin. Röttgen and Collins [94] have used libraries of the 56-residue human pancreatic secretory trypsin inhibitor (PSTI) with exposed-loops for selection of proteins with chymotrypsin-binding specificity. Sequences were selected that could also be predicted via computer-aided design but with no reported binding properties. Using a Kunitz inhibitor domain of human lipoproteinassociated coagulation inhibitor (LACI-DI) as phage displayed scaffold variants for iterative optimization of two loops, and plasmin as a selector, a variant was found with a 12,500-fold higher inhibition power compared with the parental LACI-DI [95]. The authors reported on the selection from this library of a high affinity plasma kallikrein inhibitor. In this experiment proteins selected against human thrombin bound to noncatalytic region. Phage Display Engineering of Proteins of Signal Transduction Cytokines and Growth Factors Another group of extensively engineered functional proteins are cytokines and growth factors, which interact with their receptors and initiate the signal transduction. The importance of physiological functions in which cytokines participate in many physiological systems including regulation and coordination of immune responses and inflammatory processes, as well as the hope that a detailed understanding of such protein–protein interactions and generation of proteins with new properties will lead to

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new therapeutic possibilities motivated extensive engineering projects. The success of the structural modifications in ligands, maintaining their function, is in direct dependence on the elucidation of the structures, epitopes, interacting with the receptor. This is why a major focus in these studies has been on the identification of epitopes in ligands and their cognate receptors responsible for interaction and elicitation of biological effects. One of the first targets was human growth hormone, hGH, a cytokine which binds to two identical receptor subunits via its two different epitopes [96]. Consequently, the complete hGH receptor complex is assembled sequentially: once the complex of hGH with the first receptor subunit is formed via site I, the binding site to the second receptor subunit is formed by the residues of hGH and the receptor subunit. The contribution of alanine scanning to elucidation of structural determinants of the binding function of hGH is well recognized [97]. In the experiments by Wells, Cunningham and their coworkers [65, 96, 97, 98, 99] the amino acids important in the ligand–receptor interactions were identified by alanine scanning of the hGH region involved in binding. The development of the multiple amino acid testing using the phage display and the information on 3D structure of the hGH-receptor complex [100], and in the IL-receptor complex [101, 102], allowed more efficient and rapid structure-function characterization and modification of the determinants to have access to the regulation of their and their cognate receptors activity. Elucidating the ligand–receptor interactions was critical for designing cytokine (or receptor) antagonists in such a way that the protein primary receptor-binding site is intact and the region interacting with the second receptor subunit is modified and such ligands become unable of initiating signal transduction and convert into receptor antagonists blocking the activity of cytokines [103,104]. The gp130 cytokine receptor was a focus due to its central role in the formation of high affinity receptor complexes for a family of cytokines involved in the regulation of various processes: hematopoiesis, immune response and inflammation. When IL-6 and IL-11 are acting, it homodimerize, when LIF, oncostatin M, ciliary neurotrophic factor, or cardiotrophin-1 are effectors it associates with receptor, LIFRβ. The binding of cytokine triggers dimerization of large-size receptors initiating the signaling cascade by inducing a phosphorylation and activation of the tyrosine kinases phosphorylating the tyrosine residues on cytoplasmic domains of cytokine receptors thus initiating intracellular pathway of the signal transduction leading to activation of transcription by transcription factors which migrate into the nucleus and activate the transcription of the IL-6 family of target genes. One of the aims pursued in the engineering of this complex physiological system is to generate antagonists blocking the activity of the cytokines. Fusion ligand-receptor protein was produced able to bind directly to gp130 and to block the biological activity of all gp130 family cytokines (“hyper-antagonists”) [105, 106]. The phage display has much to propose for a scaled manipulation of these systems of cell regulation and induction [107]. First of all, peptide selection by these factors would be used for identification of critical amino acids in the epitopes and their engineering via randomization. An example of this is the work reported by Oliver et al. [108] in which the screening of a phage display library of small cyclic peptides with anti-gp130 antibodies, that neutralize the function of oncostatin M, permitted isolation of a consensus motif that is also found in the elongation factor (EF)loop of the D2 domain of gp130. The alanine scanning identified gp130 residues that are involved in binding oncostatin M but not leukemia inhibitory factor (LIF). Other examples of the successful engineering are described below. Fibroblast growth factor (FGF) receptor agonist was produced by fusing a leucine-zipper motif (mimics the

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heparin-binding segment of the factor) to small cyclic peptides from phage-display that induced dimerization of the FGF receptor [109]. Here, structural considerations combined with a combinatorial approach permitted the generation of molecules that are structurally unrelated to fibroblast growth factor but have similar specificities. New cytokines and growth factors with altered specificities were produced based on molecular modeling of protein regions involved in the interaction that permitted to switch the enzyme activity [110]. Gene Shuffling for Generating Novel Proteins Gene shuffling is a combinatorial gene-recombination approach to modify proteins [111-113]. Homologous genes are recombined by cutting down individual genes to fragments of 50-100 base pairs and then reassembled by a self-priming process similar to PCR. Subsequent amplification of the recombinants is achieved using conventional PCR followed by isolation of products of interest under the condition of stringent selection. Chang et al. [114] used eight human interferon-alpha genes for multigene DNA shuffling and generated a chimeric interferon-α with 285000-fold higher affinity than human interferon-2α. The improved clone was derived from only five parental genes and did not contain point mutations, in contrast to earlier DNA shuffling procedures, in which point mutations that were introduced by the PCR reactions were also found in the selected clones. PEPTIDES SELECTED FROM COMBINATORIAL PHAGE LIBRARIES WITH PROPERTIES OF LIGANDS OF PROTEIN BINDING SITES Numerous Examples of Isolation of Interesting Peptide Sequences have been Reported Using Different Types of Libraries Peptides Selected by Receptors Phage-presented peptide libraries have been screened for binding to the receptors. This has led to the identification of small peptides able to mimic large protein interfaces of cytokine proteins and function either as antagonists or agonists. Erythropoietin. The outstanding results with this hormone have been obtained by researchers at Affymax -R.W. Johnson Research Laboratories (Palo Alto) and the Scripps Research Institute (San Diego). The Affymax group screened random libraries with the receptor of erythropoietin (EPO) and isolated a disulfide-bonded cyclic peptide with no similarity to the EPO sequence able to induce erythropoiesis in mice by binding to, and activation, the EPO receptor [17, 115]. This was the first cytokine agonist selected from combinatorial libraries. To isolate the peptides with affinity to the erythropoietin receptor, the sequential strategy of selection from different libraries [36] was employed, Fig. (2). First, a highly polyvalent gpVIII library was screened with purified receptor to select relatively low-affinity peptides sharing particular amino acids (motif). Then, monovalent gpIII secondary libraries based on these sequences were constructed, in which the nonmotif residues are randomized. Selection from this type of library permitted the isolation of high affinity binders that acted as peptide agonist that binds to the EPO receptor to form an activated peptide-receptor dimeric complex. Livnah et al. [115] resolved the EPO-receptor complex at 2.8A describing structural details of the interaction of the

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peptide with receptor promoting its dimerization. Thus, the obtained cyclic peptide mimicked the function of the natural hormone.

Wells, 1996 Fig. (2). The two-stage strategy used for selection of erythropoietin (EPO) mimics binding to the receptor (EBP).

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Other peptides selected for cytokines and displaying agonistic or antagonistic activities are: (1) peptide-mimics of the 332 amino acid thrombopoietin with agonist activity leading to platelet production [116]; (2) the IL-1 receptor antagonist peptides binding the extracellular domain of the human type 1 IL-1 receptor and preventing the activation of the IL-1-driven responses in human and monkey cells [101,102]. Thrombin receptor. The thrombin receptor of platelets is an integral membrane protein and is cleaved by thrombin to expose a "tethered ligand" that binds to, and triggers, the receptor. Doorbar and Winter [117] isolated a peptide antagonist of this receptor by panning the library directly on platelets and using for its elution from the complex the peptide agonist of the thrombin receptor. The obtained peptides had a consensus sequence MSRPACPNDKYE, and displayed some features common with the tethered ligand (in particular, an arginine residue followed by a proline) and showed about ten-fold higher anti-aggregating activity compared with the previously described peptide antagonists of the thrombin receptor. N-methyl-D-aspartate receptor. Li et al. [118] investigated by phage display the brain oligomeric N-methyl D-aspartate receptor (NMDAR), which is a ligand-gated ion channel that becomes selectively permeable to ions upon binding to ligands. Aimed at the finding peptide modulators of NR1, one of the subunits among the five implicated in the channel, the authors selected cyclic peptides (Mag-1) able to associate with the receptor that contains the putative ligand binding domain with a consensus sequence of CDGLRHMWFC; its synthetic form inhibited in a non-competitive manner the receptor channel activity. Estrogen receptor. Paige et al. [119] selected peptides acting as sensitive probes of estrogen receptor conformation and demonstrated that their ability to produce distinct biological effects owes to the conformational changes in the receptors they induce. The biological effects of estrogen receptor agonists and antagonists acting through these receptors are suggested to be different. Tumor Necrosis Factor - alpha (TNF-a). TNF-a is one of the cytokines among humoral factors with immunoregulatory function produced by immune system. Its enhanced plasma concentrations in various infectious and inflammatory diseases (rheumatoid arthritis, bacterial sepsis) exert deleterious effects [120]. TNF-a is a trimer interacting with two receptors displayed on membranes of many cell types: R-1 and R-II, 55kDa and 75kDa, respectively. The TNF-a sites interacting with the receptors [121] are potential targets for selecting peptide substitutes of the receptor with antagonistic potentials. Partidos et al. [21] screened a 15-mer gpIII phage display library with recombinant TNF-a and isolated peptides presumably mimicking certain TNF-a receptor binding site(s). Despite showing no structural similarity to the receptors, the peptides inhibited the TNF-a-induced cytotoxicity (apoptosis). Synthetic peptide version of one of the mimotopes retained this ability to inhibit the cytotoxicity of mouse and human TNFa. In other selections, mimotopes blocking the binding of TNF-a to its receptor were obtained [122,123]. Mimotopes with agonistic and antagonistic activities for various other cytokines or hormones have been generated. Some of them are described below. Streptavidin. Low-affinity peptide ligands with the common sequence His-Pro-Gln were isolated from linear peptide libraries screened with streptavidin [124], a model receptor system. Giebel et al. [125] screened with streptavidin cyclic peptide gpIII libraries and isolated sequences with HPQ motif. Analysis of binding kinetics and

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affinities showed that the conformationally constrained cyclic peptides bound streptavidin with affinities up to 3 orders of magnitude higher than their linear variants. These results demonstrated the potential of screening conformationally constrained peptide libraries for high-affinity novel receptor ligands or enzyme substrates that were repeatedly observed by others. Ribonuclease SS. Smith et al. [126] isolated from a random hexapeptides phage library clones displaying peptides that bind S-protein, a 104-amino-acid fragment of bovine pancreatic ribonuclease (RNase). The selected peptides showed a consensus sequence motif, (F/Y)NF(E/V)(I/V)(L/V), bearing a little resemblance to S-peptide, a 20-aa fragment of RNase that is natural ligand for S-protein. The chemically synthesized peptide with sequence YNFEVL bound S-protein and behaved as antagonist of the Speptide regarded as a new RNase-specific 'drug'. Concanavalin A. Oldenburg et al. [127] selected peptides with consensus sequence Tyr-Pro-Tyr as ligands for the carbohydrate-binding protein Concanavalin A. The peptides had a affinity comparable to that of the natural ligand, methyl α-Dmannopyranoside, and were able to inhibit precipitation of the α-glucan dextran 1355 by Concanavalin A. Scott et al. [128] isolated from a hexapeptide library peptides mimicking the binding specificity of methyl-D-mannopyranoside (Me Man) to Concanavalin A. The peptides shared a motif MYWYPY, competed with Me Man for binding to Concanavalin A and showed only weak cross-reactivity with a closely related D-mannose-binding lectin. This work was the first to demonstrate that the phage display may be used for obtaining highly selective sugar-mimics for lectins. Neutrophil elastase inhibitors. Roberts et al. [129] engineered inhibitors of human neutrophil elastase by designing and producing a library of phage-displayed protease inhibitory domains derived from wild-type bovine pancreatic trypsin inhibitor; by screening with the target protease a mimic of human neutrophil elastase was selected with a affinity (Kd = 1.0 pM) that was 3.6 x 106-fold higher than that of the parental protein and exceeded by a factor of 50 the highest affinity reported to that time for any reversible human neutrophil elastase inhibitor. Gal80 repressor. Phage display was employed for isolation of peptides with the ability to bind Gal80 protein and mimic the active site in the activation domain of the yeast Gal4 protein that binds specifically to the Gal80 repressor (Gal4 supposedly associates with co-activators in the RNA polymerase II holoenzyme). The selected Gal80 protein-binding peptides competed with the native Gal4 activation domain for the repressor suggesting that they bind to the same site [130]. Calmodulin. The potential of the phage library screening for obtaining peptideantagonists of calcium-binding protein, calmodulin was explored. Dedman et al. [131] identified in a 15mer library peptides with a Trp-Pro motif. Then, a library displaying cyclized octamer random peptides with immobilized bovine calmodulin was used for the screening [132] and resulted in peptides with better specificity for calmodulin with antagonist activity. The peptides contained the sequence Trp-Gly-Lys and required Ca2+ to bind calmodulin. One of the peptides, SCLRWGKWSNCGS, has been shown to bind calmodulin better than its reduced form or an analogue in which the cysteine residues were replaced by serine. The functional test has shown the peptide to inhibit calmodulindependent kinase activity. Systematic alanine substitution of residues in this peptide indicated tryptophan as most critical residue for the binding. The study has demonstrated

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the importance of the conformational constraint of these phage library origin peptides in their activity as specific, Ca2+-dependent calmodulin ligands. Adey and Kay [133] screened with calmodulin a longer (26mer) peptide library and isolated peptides with three consensus sequence motifs, +W-OlambdaR, WRAAV, WRXXAAAL (where +,-, O, lambda and X are positively charged, negatively charged, hydrophobic, leucine or valine, and any residue, respectively). The results of these selections demonstrated that the type of the identified calmodulin-binding motif can vary between peptides selected from different types of combinatorial libraries. Nevalainen et al. [134] reported on the isolation of two peptides, AWDTVRISFG and AWPSLQAIRG, that bound to supposedly distinct putative regions of calmodulin involved in activation of different calmodulin-dependent enzymes. In the more recent work, Demartis et al. [135] developed a general strategy for the isolation of enzymatic activities from large phageenzyme repertoires using specific anti-product affinity reagents. By displaying enzymecalmodulin chimeric proteins on phage as gene III fusions, they achieved the conditional anchoring of reaction substrates and products on phage. Insulin-like growth factor 1 (IGF-1)-binding proteins. IGF-1 is a hormone with diverse mitogenic and metabolic functions, which it accomplishes via a high affinity binding to its cell-surface receptor. The binding is influenced by a set of IGF-1-binding protein co-factors regulating its activity. Using these factors, high affinity peptides were selected, blocking their interaction with IGF-1. The important result in these selections is that the human IGF-1 apart from the site for its receptor contains six overlapping epitopes for binding to IGF-1-binding proteins, whereas each of the selected peptides was specific to only one of them [97]. Their fine specificity demonstrated the potential of mimotopes in dissecting the overlapping epitopes of crossreacting ligands into individual epitopes (also displayed by mimotopes selected by crossreacting antibodies [136,137]). Isolating peptides to each of the proteins and to the receptor is a way to generate a multiple-epitope map of the IGF-1 and use the peptides for the site-specific intervention into the complex hormonal functions. Caveolin. Couet et al. [138] used the caveolin-scaffolding domain as a receptor to select from phage display libraries tryptophan-rich peptides using also a known caveolininteracting protein, Gi2α , as a native ligand. The authors suggest that caveolin (a principal component of caveolae membranes) functions as a scaffolding protein to organize and concentrate certain caveolin-interacting proteins within caveolae membranes as signaling molecules, including G-proteins, Src-like kinases and others. The study aimed at elucidating of how the caveolin-scaffolding domain recognizes these molecules have shown that the peptides selected by them separate the multi-component interacting systems into individual interactions. Enzyme-Substrate Engineering Substrate-Phage To define substrate sites of enzymes, Matthews and Wells [139] proposed the use of phage-display system for selection of protease substrates. Smith et al. [140] described efficient discovery in a hexamer library of highly active and selective substrates for the matrix metalloproteinases stromelysin and matrilysin. The library containing a “tether” recognized by mAbs was treated in solution with protease and the cleaved phage were separated from uncleaved using a mixture of tether-binding mAbs and Protein A. The

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procedure identified phage encoding peptide sequences susceptible to cleavage by the enzymes and to the selection of stromelysin and matrilysin substrates. Enzyme-Phage. Phage-displayed enzymes have been shown to retain their enzymatic function permitting their engineering. The first report on “enzyme-phage” has been on E. coli alkaline phosphatase. McCafferty et al. [141] described the expression of wild–type enzyme and its mutant with a mutation in the active site on phage surface as gpIII fusions and demonstrated that they display catalytic and kinetic properties comparable with those of free enzyme. Siemers et al. [142] constructed a library of Enterobacter cloacae P99 beta-lactamase mutants and investigated the effects on the catalytic function of substitution of residues in a putative enzyme active site. After random mutagenesis, the phage library could be enriched for active beta-lactamase by incubation of infected bacteria with beta-lactam antibiotics. The authors show the significance of the obtained data for the therapy. Corey et al. [143] generated gpIII and gpVIII M13 libraries expressing the serine protease, trypsin, which possessed kinetic parameters approximating those of the wild type enzyme. Ecotin, an endogenous E. coli protease inhibitor was found to co-purify with the trypsin-phage and proposed as selective binder of the phage. Phage display of glutathione transferase was used for engineering novel binding specificities onto the pre-existing protein framework of the enzyme. Novel glutathione-S-transferases were obtained with varying affinities. A library of mutant glutathione-S-transferases with differences in the active-site region was generated by random mutagenesis of 10 amino acid residues involved in the binding of electrophilic substrates. Novel glutathione transferases with altered specificity for active-site ligands were isolated by adsorption of the fusion protein on the surface of phage to analogs of an electrophilic substrate [144]. Protein phosphatase -1 (PP1) mediates signaling pathways that regulate a variety of the eukaryotic signal transduction pathways. Peptides with the motif sequence VX(F/W (X= H,R,S,T) existing in PP1-binding proteins were selected; synthetic peptides with this motif inhibited PP1 in vitro (IC 50 3-10uM). The peptide from the muscle glycogenbinding subunit containing this motif sequence bound to the region in PP1 opposite to the active site, i.e. the inhibition was not due to the competition with its ligand but acted distantly. The work demonstrates how selection of ligands uncovers the protein-protein interaction in complex system and provides peptides for the regulation of these interactions [145]. Dihydropholate reductase (DHFR) converts dihydropholate to tetrahydropholate and is a target for cancer, antimalarial, and antibacterial chemotherapy [146]. Peptides sharing the motif sequence (K/R/F/W) (D/E) XWLXXY bound to DHFR and the binding was blocked by inhibitors of the DHFR methotrexate or trimethoprim, suggesting that the peptides bind at, or near, the active site [147]. Troponin C. Pierse et al. [148] selected from a gpIII library 10 distinct novel peptides specifically binding to troponin C. The peptides shared consensus sequence V/L)(D/E) XLKXXLXXLA that could be involved in the binding. The clone with the highest activity had a 62.5% homology to troponin C and to the N-terminal region of troponin I isoforms. In the presence of calcium, the peptide formed a stable complex with troponin C and was able to inhibit the maximal calcium-activated tension of rabbit psoas muscle fibers.

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Peptides with Anti-Tumor Activity Angiogenesis Inhibitors Peptide antagonists to angiogenin able of inhibiting its interaction with actin has been isolated [149]. Combined effects of this peptide and the earlier generated neutralizing mAb to angiogenin [150] is a way to inhibiting the growth of solid tumors. VEGF (Vascular Endothelial Growth Factor) is involved in development and permeability of blood vessels [151]. VEGF binds to the kinase domain receptor and mediates vascularization and tumor-induced angiogenesis. To control the VEGF function in the angiogenesis of solid tumors [152] the selection of high-affinity peptides that block its binding to its receptors is very important. Several peptides were selected by screening against VEGF and shown to interact specifically with it and replace the natural ligand KDR (see [97]). Further selections from secondary libraries of partially randomized obtained sequence yielded better peptide clones. Fairbrother et al. [153] produced peptides that inhibit binding of VEGF to its receptors, KDR and Flt-1. Using phage display libraries of short disulfide-constrained peptides, three distinct classes of peptides were obtained that bind to the receptor-binding domain of VEGF with micromolar affinities. The highest affinity peptide was able to antagonize the VEGFinduced proliferation of primary human umbilical vascular endothelial cells. The peptides bind to a region of VEGF known to contain the contact surface for Flt-1 and the functional determinants for KDR binding. In the following work with this system, Binetruy-Tournaire et al [154] sought to identify in phage libraries peptides able to block the VEGF-KDR interaction and isolated peptides binding to membrane-expressed KDR and a anti- VEGF neutralizing mAb. One of the clones displaying the ATWLPPR sequence completely abolished VEGF binding to cell-displayed KDR and, when tested at cellular level, inhibited the VEGF-mediated proliferation of human vascular endothelial cells in a dose-dependent and endothelial cell type-specific manner. In vivo, ATWLPPR totally abolished VEGF-induced angiogenesis in a rabbit corneal model. These results demonstrate that ATWLPPR is an effective antagonist of VEGF binding and may be a potent inhibitor of tumor angiogenesis and metastasis. Oncogen MDM2. Bottger and colleagues [155] isolated from phage libraries 12mer and 15mer peptide ligands for hdm2 which would interfere with its binding to p53 and act as anti-tumor agent. The peptide sequences showed striking homology with the previously established mdm2 binding site on p53, confirming that the 18-TFSDLW-23 site is crucial for the interaction. Free synthetic peptides with the selected sequences inhibited 100 times stronger the interaction of p53 with mdm2 than the p53-derivative peptide. Taxol. Rodi et al. [156] selected peptides binding to the anticancer drug paclitaxel Taxol, small non-protein molecules binding to beta–tubulin. The selected peptides had no significant similarity with tubulin but included a subset that exhibited similarity to a non-conserved region of the anti-apoptotic human protein Bcl-2. The peptide binding was accompanied with conformational change in tubulin. In vivo, treatment with paclitaxel leads to inactivation of Bcl-2 and concomitant phosphorylation of residues in a disordered, regulatory loop region of the protein. Similarity between paclitaxelselected peptides and this loop region suggest that the apoptotic action of paclitaxel may involve the binding of paclitaxel to Bcl-2. The results demonstrated that phage-displayed peptides can mimic the ligand-binding properties of disordered regions.

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Cell Adhesion Integrin Ligands A large number of phage display studies aimed at selection of peptides recognizing integrins, which had led to the discovery that RGD is a critical sequence for the binding. Integrin family of heterodimeric, transmembrane cell surface receptor molecules consist of an alpha (120-180kDa) and beta (90-110kDa) subunits [157]. In a series of phage display studies, purified integrin [32, 158], alpha v beta 3 [159] and alpha v beta 5n [34] have been used for selection of its ligands and a large group of peptides sharing RGD motif has been isolated from linear or constrained libraries; selected sequences displayed considerable amino acid variations in the regions flanking RGD. It is supposed that the diverse composition around RGD is due to the role of the ligand in vivo as a versatile receptor for RGD-containing extracellular matrix proteins. Peptides recognized by the cell surface receptors of fibronectin (alpha 5 beta 1 integrin), vitronectin (alpha v beta 3 and alpha v beta 5 integrins), and fibrinogen (alpha IIb beta 3 integrin) could be isolated using phage libraries expressing different sized cyclic peptides, CX5C, CX6C, CX7C, as well as a library with only one cysteine (CX9). The importance of the cyclic conformation of the ligand affinity was clearly demonstrated in the selection from this library: the integrin-binding sequences derived from it contained another cysteine. A cyclic synthetic peptide ACRGDGWCG effectively inhibited cell attachment to fibronectin. The most interesting structure appeared to contain two disulphide bonds. One such peptide, ACDCRGDCFCG, was synthesized chemically and was shown to be at least 20-fold more potent inhibitor of alpha v beta 5- and alpha v beta 3-mediated cell attachment to vitronectin than similar peptides with a single disulphide bond, and 200fold more potent than commonly used linear RGD peptides. All these results emphasized the importance of conformational restriction for the affinity of integrin-binding RGD motif-peptides. E.selectin Ligands E. selectin, an inducible cell adhesion molecule, mediates rolling of neutrophils on the endothelium, an early event in the development of an inflammatory response. Inhibition of selectin-mediated rolling is a possible way of controlling inflammationinduced diseases. Martens et al. [160] described phage library-derivative ligands binding to E-selectin, which were able of blocking E-selectin-mediated adhesion of neutrophils and to reduce the neutrophil transmigration to the site of inflammation in mice. The peptides are considered candidates for anti-inflammatory therapeutic agents. Internalization Via Phage-Displayed Ligands The phage display methodology has stimulated the research into the mechanisms of internalization and their use for targeted drug delivery, including gene therapy [161,162]. Among distinct subgroups of cell surface receptors responsible for intracellular penetration with the cell-type specificity, integrins were the first that were exploited to target the intracellular translocation of a filamentous bacteriophage particle [163]. RGD-containing ligands to integrins are used by viruses whose internalization is mediated by integrins via specific recognition of an RGD (or related motif), expressed on the surface of the pathogen. This natural mechanism of intracellular translocation used by pathogens has been exploited in experimental internalization. Sequences with

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RGD were utilized for the integrin-mediated internalization of a filamentous bacteriophage particle into cultured mammalian cells [163,164]. These studies encouraged the use of the phage display methodology for identification of cell-typespecific integrin-binding ligands and stimulated the research into the internalization mechanism and the intracellular fate of the integrin-phage complex (reviewed by [165]). Along with this approach, a second strategy was developed based on the mechanisms used by growth factors [166]. It consists in display of specific growth factors on the surface of bacteriophage to target cancer cells, which overexpress their receptors. One possibility that also was exploited is the display of scFv with the specificity to growth factor receptors, permitting the intracellular penetration of certain phage constructs as vectors. A special phage vector expressing scFv to ErbB2 was constructed for internalization [167,168] and procedures were designed for direct selection of phage displaying peptides that recognize and bind to motifs on the surface of mammalian cells [161,162]. Panning on Live Cell Surface Markers Cultured Cells Along with the routinely done phage library selections against purified molecules, raising concerns as to how these molecules reflect their properties in cells, in recent years experiments on selection of peptides recognized by cell-surface proteins have been started. This was primarily directed to target cell-surface specific receptor molecules in various normal and pathological tissues. One aim of the selection of cell-specific peptides is to extend the list of cell-specific internalizing vehicles for gene therapy [161]. Spear et al. [169] described successful use of the peptide phage display to target viable malignant glioma cells. Samoylova et al. [170] panned a landscape f8-1/8-mer type phage display library on viable glial cells and isolated, apart from the phage that bound to cell surface, a subset of internalized phage. The sequencing of peptides displayed by these phages have shown that they contain RGD-containing motif E(L,V,S)RGDS. This latter group has been apparently bound to integrin that resulted in the internalization of the phage. Remarkably, RG2 glioma cells could uptake them 63-fold more efficiently than astrocytes. The authors note that these properties of selected peptides could be beneficial in the design of effective combinations of drugs for anti-glioma treatments. This opens a possibility to select from peptide libraries clones with this and other “internalizing” motifs and use them as vehicles for drug delivery. Information on cell surface markers is commonly obtained in experiments with cellsurface-specific antibodies [171]. Peptides from phage display libraries provide new possibilities for detection of cell-surface markers that are not sites for antibodies [172]. In the above cited work, Samoylova and coworkers [170] have selected ligands for unknown glioma cell surface binders and describe two families of surface-bound peptides, one, containing motif V(T,S,L)P(E,T)H recognized by a marker common for glioma cells as well as normal brain cells and cells of non-brain origin, and the other, D(T,S,L)TK, with a pronounced glioma-selective properties. Intra-Vascular Biopanning of Phage-Peptide Libraries In these experiments two-month-old Balb C or C57Bl/6J mice were perfused with gpIII-fusion random peptide libraries of 10 8-109 different sequences to target the markers

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propagated by endothelial cells of vasculature (reviewed by [173]). The authors report that endothelial markers in vasculature of each organ are tissue-specific and, after the library is introduced, peptides recognized by these markers are bound and home. In each analysed tissue the authors recovered peptides that supposed to bind specific receptors that represent markers of angiogenic vessels [174-176]. It is expected that peptides can be found that home to tumors and may be used as vehicles for delivery of anticancer drugs directly to tumors. Arap and coworkers [24] extended these in vivo screenings to humans. An C7C library with diversity approximately 2x108 different sequences (dose: 1014 transducing units in 100 ml of saline) was intravenously infused to a patient with macroglobulinemia, and after 15 min tissue biopsies were done. Phage recovered from probes was used for the determination of sequences they display. The sequences were analyzed using a high-throughput pattern-recognition software. In total, 4,716 sequences were processed to find out tripeptide motifs frequent in each of the tissues. Some of these motifs were then found to appear within known human proteins and finally compiled a panel of candidate human proteins that could be mimicked by the motifs. Diagnostic Peptides Peptide Detectors of Pathogenic Bacteria Selection of peptides able to detect infectious viruses and bacteria is a relatively recent application of phage display but has already recommended itself as one of the most perspective branches of the methodology able to bypass traditional methods [177180]. Diagnostic phage-displayed peptide probes selected among billions of variants are more specific and easier to manage. Peptides specifically bind highly pathogenic bacteria distinguishing between spores and vegetative cells in a highly selective manner. Petrenko and coworkers initiated extensive exploration of the issue using the developed landscape-type gpVIII libraries and selected high-affinity peptides binding to Salmonella typhimurium, and other bacteria including the B. antracis Sterne [27, 28]. Apart from the utility for routine hospital sanitary and food monitoring purposes, the probes are of high importance in the rapid detection of the bacteria recognized as biological weapon. Peptides Mimicking Immunodominant Epitopes of Pathogens Hepatitis. Hepatitis B was the first disease to which the phage display mimotope selection has been applied. Motti et al. [181], using murine mAb raised to HbsAg, selected from a random peptide library mimotopes and found a peptide that was recognized by serum of 30% of investigated individuals infected with the virus. This was an indication that the epitope mimicked by this peptide was immunodominant. Folgori et al [12] developed a multi-step procedure of biopanning on serum of Hepatitis B patients and demonstrated the possibility of selecting disease-specific mimotopes able to recognize HbsAg. Based on this possibility, the authors propose mimotope selection as a general strategy in studies of diseases. The procedure described in this and in subsequent publication from this group [182] includes a series of counter–screening with positive and negative sera for depleting Ig from disease-irrelevant Ab species and from diseaserelated but weak binders, so as to have finally a selected library containing tightly binding peptides recognized by sera of around 60% of tested patients.

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Epitopes of hepatitis C were identified by phage display using mAbs based on the sequence similarity with the proteins shown by selected mimotopes [183]. Using sera from hepatitis C virus (HCV)-infected patients and non-infected subjects to screen random peptide libraries displayed on phage, the authors selected peptides specifically reacting with sera from infected patients; this indicated that the peptides mimicked distinct HCV determinants and can serve as diagnostic markers. In addition, these phage-displayed HCV mimics were able to induce specific response against HCV when used as immunogens in mice. These results support the search for HCV mimics with the potential to elicit a protective immune response as leads for the development of a mimotope-based vaccine against viral infection. Human Immunodeficiency virus type 1 (HIV-1). Soon after the mimotope selection approach became available it was applied to HIV-1 epitopes. Fabs to gp120 [52,53] and gp41 [184] were isolated and used for mapping their epitopes on viral proteins and for purposes of neutralization. Fab “b12” that binds the site on gp120 recognized by CD4 with picomolar affinity is of high therapeutic value because of the sensitivity to neutralization of the gp120-CD4 interaction. Peptides selected from libraries by the b12 had no structural similarity to the gp120 [185]. By contrast, the mAb 447-552 elicited by the principal neutralizing determinant located on the apex of gp120 V3 loop efficiently selected epitope-similar GPGR motif [186]. Another broadly neutralizing antibody, IgG 2F5, recognizing the ELDKWAS sequence on the gp41 transmembrane domain, has also been used and retrieved from libraries epitope-similar sequences [33,187]. Sera of individuals infected with HIV-1 were used for peptide selection. Two types of sequences were found in the selected peptides: one showed no structural similarity to any of HIV-1 antigens but recognized sera of many infected individuals suggesting that they mimic conformational epitopes [188]. The second type of selected mimotopes has a similarity to the immunodominant and conserved loop-epitope on gp41 [189, 190]. The antibody elicited by this epitope is unable to neutralize HIV-1 and even can enhance the viral infectivity [191]. Respiratory sincitia virus. A neutralizing and protective mAb19 recognizing conformation-dependent epitope on the fusion protein of this virus selected peptides reactive with the mAb; the peptides were subjected to amino acid substitutions, which resulted in a higher affinity (4,93x10 9 for one of them) as determined by surface plasmon resonance method. The authors noted that Tyr to Ser substitution in one peptide was responsible for the enhanced affinity. Antibodies induced in mice by these mimotopes competed with the mAb19 for binding to the virus and were able to neutralize the virus [192]. Lyme disease. Peptides for the diagnosis of the disease caused by spirochete Borrelia burgdorferi, (about 15,000 infections in the USA each year) require for its control an early diagnosis. Kouzmitcheva et al. [193] panned phage libraries on sera from patients and chose in the recovered population 17 peptides with a diagnostically useful binding pattern taking as a high stringent criterion the ability to recognize at least three positive sera and no reactivity with any of negative sera. Despite the apparent relevance to the infection these peptides show no sequence similarity to the pathogen, B. burgdorferi. Peptides selected in this work represent highly sensitive reagents for the diagnosis of the Lyme disease. Multi-cellular parasites. The cestode warm Taenia solium infects pigs and humans and homes in brain of a large contingent of population in South regions causing severe

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neurological pathology, neurocysticercosis, which is also the etiological cause of epilepsia in these regions. Although the parasite is a multicellular organism, particular antibodies to its antigens dominate in serum and especially in cerebrospinal fluid. Using the fluid several families of peptides with consensus motifs were isolated [194,195]. Schistomiasis is widely distributed disease caused by Schistsoma mansoni. Peptides isolated by a highly protective mAb to S mansoni antigens, when conjugated to BSA and used for immunization of mice, induced complement-mediated anti-parasite effect that led to 40% reduction of the parasite burden [196]. These mimotopes are considered candidates for generation of synthetic anti-parasite vaccine. Autoimmune Diseases Rheumatoid Arthritis Dybwad et al., [197] screened a gpVIII library with Ig purified from individuals with RA and described peptides that were able to recognize sera from other individuals with the RA better than control sera. There was a peptide carrying GGA resembling the repetitive sequence AGGGA which is recognized by autoantigens (collagen, cytokeratines). In the following publication [198], the group reported on data showing that sera of patients with rheumatoid arthritis containing antibodies against type II collagen recognize mimotopes selected by a mAb to the protein. It was suggested that an epitope in the type II collagen induced this mAb and also the antibody in patients i.e. might be related to the disease. Mimotopes were also selected by means of TNF-specific autoantibodies [199]. Multiple Sclerosis Cortese et al. [200] reported on the selection of peptides by the screening with cerebrospinal fluids of patients with multiple sclerosis. Although the peptides could not distinguish between sera of patients and healthy individuals, the lack of the specificity is not an indication against the conclusion of the authors on the disease relevance of selected sequences because the antibodies related to the disease are predominantly produced locally and those in the sera could be irrelevant antibodies of broad specificity. Diabetes Mellitus Two disease-related peptides were selected from a gpVIII library upon screening with Ig purified from patient sera, which recognized sera of 20-26% of patients with insulin dependent diabetes mellitis and only less than 5% of normal serum IgG [201]. Trombocytopenia Purpura Using affinity purified autoantibodies to platelets to screen a gpIII-type library; mimotopes were selected for two epitopes on autoantigen GPIIb/IIIa. One of the epitopes is linear and map to the cytoplasmatic tail of GPIIIA. The second epitope was conformational and could not be mapped [202]. Antiphospholipid Syndrome (APS) APS leads to recurrent fetal loss, thromboembolic phenomena and thrombocytopenia. By selection from a hexapeptide library of peptides and their lengthening to correspond with the site of the β2GPI involved in the autoimmune syndrome, Blank et al. [203] described the peptides NTLKTPRVGGC and KDKATFGCHDGC that bound

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to ILA-3 mAb, and the peptide CATLRVYKGG mimicking the epitopes recognized by the mAbs to β2GPI and to ILA-1, ILA-1 3 and H-3, respectively. The peptides were able to inhibit the biological functions of these anti-β2GPI mAbs and prevented mice from developing experimental APS. The Epitope-Mimicking Potentials of Peptides Selected from Combinatorial Libraries Antigenic Mimicry Antibody epitopes represent protein sites that elicit antibody and cytotoxic responses in higher vertebrate organisms, which are destined for recognition and neutralization of pathogens but sometimes can also be induced by self proteins under pathological circumstances. The peptides selected by these induced molecules, antibodies or receptors on the surface of cells, are sources of information on their potentials and limits of structural and functional mimicry of epitopes. The epitope-paratope interface resolved by X-ray crystallography shows that 14 to 20 or some more residues are involved in the interaction [204, 205]. Short peptides are capable of reproducing the antigenic specificity of epitopes because a small group of the interface residues is critical for the binding and the remaining only contribute to the affinity of the interaction. The small group of the critical residues is known as “mini-epitope” [206] and can be represented by various protein regions, continuous stretches, loops, alpha-helices, turns and sometimes more complex three-dimensional conformations [207,208]. These latters represent conformational epitopes whose structure peptides are unable to present [209] except for some epitopes containing short contiguous stretches. The majority of the epitopes has conformational structure. They are usually composed of amino acids from different parts of the polypeptide that are brought together by its folding. In most selections, peptides bound and retrieved by antibodies to these regions from libraries lack amino acid similarity to the epitope, even when they are able to bind the antibody and compete with the epitope for the binding [210,211]. Peptides with these characteristics have been first described and termed mimotopes by Geysen et al. [212]. Mimotopes are peptides able to mimic the specificity of the epitope using other amino acid combination than is in the epitope. Identification of the protein sites where conformational epitopes are located based on sequence of peptides selected by antibodies is generally beyond the capacity of peptides. Mimotopes can sometimes contain individual discontinuous amino acids with a similarity to the epitope. If the 3D structure of the protein is known and the amino acids can be replaced to test their importance for binding, the epitope can be identified [13]. Mimotopes selected by anti-carbohydrate antibodies are perhaps the best in presenting the mimicry without structural similarity [213]. As carbohydrates are poor immunogens and only can induce strong T-cell specific responses when are coupled to carriers, mimotopes selected from phage libraries by their induced antibodies are of interest because they can be used for inducing anti-carbohydrate responses [214]. Peptides selected by some antibodies reflect only a part of its epitope. Phalipon et al. [215] isolated peptides recognized by a mAb to Shigella flexneri and concluded that the antibody selected mimotopes representing only part of the complex epitope. Neutralizing antibody BCF2 to the scorpion toxin Cn2 selected three motifs each presumed to mimic a part of this complex epitope [35].

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Thus, peptides selected from random peptide libraries displayed on phage include both sequences that show similarity and no similarity to the epitope sequence. An example of the perfect epitope mimicry by peptides is shown in Fig. (3).

Arnaud, Gazarian, Palacios Rodríguez, Gazarian and Sakanyan (2004), modified.

Fig. (3). Peptides mimicking the HIV-1 gp41 immunodominat epitope that were selected by serum of HIV-1-infected patients from a 12mer gpIII non-constrained library ( = marks disulfide bridge). The upper part of the scheme in the Fig. (3) presents the sequence from the HIV-1 gp41 region (“cluster 1”) where locates the immunodominant loop-epitope. Below are 20 sequences selected from a 12mer non-constrained library by serum antibody of two patients with AIDS progression. The antibody exclusively selected in the library rare peptides that contained two cysteines embodying five epitope positions residues, of which one, lysine, is conserved at the same position and the remaining are variable. Immunogenic Mimicry In the first experiments with phage-displayed peptides it has been shown that these peptides are immunogenic [9, 10, 216], furthermore, the experiment indicated that the

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display on phage improves the peptide immunogenicity [9]. Apart from the better presentation to immune system, phage-displayed immunogens do not require adjuvant [217] for efficient immunization and have been considered vaccine candidates [20]. Keller and coworkers [186] immunized rabbits with mimotope sequence of the HIV-1 V3 loop principal neutralizing epitope in form of synthetic peptide and observed a strong anti-peptide response able to neutralize the virus in vitro . Chen et al. [218] immunized rhesus macaques with mimotopes selected by serum of a Long-Term Non-Progressor. The mimotopes were immunogenic and induced HIV-1- envelope-specific antibody responses. Protective responses against the Human Respiratory Syncitial Virus were observed upon immunization with mimotopes followed by the challenge with the virus [192]. Nevertheless, until now, mimotopes failed to demonstrate that they can protect against pathogens, especially against such diversifying pathogens as RNA viruses. The principal deficiency of mimotopes selected in phage libraries is that although they are able to induce antibodies, which recognize the original epitope on the antigen, these antibodies do not possess the ability of neutralizing the pathogen. In the recent purposeful work by Leslie Matthews, Robert Davies and George Smith [219] the issue has been a subject of special experimental trial and led to the conclusion that peptides selected from libraries of random sequences lack what is defined as “immunogenic fitness” as contrast to peptides selected from natural antigen fragment libraries. The question that stands at present is whether or not after the application of the two-phase selection strategy and of all possible engineering strategies the mimotopes selected from random libraries by anti-pathogen antibodies can acquire the fitness to become real vaccine candidates? PROSPECTS Practical Significance of Peptides and Proteins Generated Using Combinatorial Approaches Fifteen years of exploration of the high throughput screening methodology have demonstrated its outstanding possibilities in many fields of the biotechnology and biomedicine. In each of the applications, the experiments on protein engineering have shown results that either cannot be obtained by other methods or are obtained more easily. The results selectively presented in this review show that starting from a suitable protein domain, the use of combinatorial approaches coupled with a powerful selection strategy permits to obtain novel substances capable of binding a desired target molecule. By the involvement of structural data from X-ray crystallography, NMR or computer modeling one can find residues of the functional sites for variegation, generate libraries of variants maintaining the overall structure of the original protein, and select variants with desired binding properties. Highly diverse scaffolds with different binding and structural characteristics (a-helical, beta-sheet, turn, loops, 3D folds stabilized or not with cysteine bridges) have been utilized. A major interest in the protein engineering is generating minimal versions of ligands by using two strategies: “minimization” through elimination of parts non-involved in the binding function and selection from combinatorial libraries of peptides recognized by receptors of these ligands. The success in the selection and affinity evolution of short peptide-mimics of the binding function of these ligands is demonstrated by their three

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properties: specificity (and affinity) of the binding to the receptor, ability to dimerize it and the ability to induce ligand-specific biological effect, the erythropoiesis in case of the EPO, Fig. (4). A large spectrum of peptides with antagonistic and agonistic properties specific to biologically active proteins involved in the physiological and pathological processes has been selected by the screening of phage libraries. The principal property of these peptides is the binding specificity, and the ability to produce biological effects similar to their natural counterparts or, sometimes, exceeding them in strength. Indeed, some of these peptides surpass their natural parental ligands in the binding affinity.

Fig. (4). Mimetic peptide. The dimeric peptide with hair-pin-like strcuture (blue) flanked by two molecules of the extracellular domain of the EPO receptor. F93, F205, M150 are hydrophobic contact residues [230].

In most experiments each of these proteins has been only probed once just to test the potential of the engineering procedures. For practical use of the obtained binders in potential applications, features such as proteolytic stability, folding efficiency, productivity, and solubility are of great importance, and these should be considered in the choice of starting scaffold. Some scaffolds represented by large families of homologous proteins of similar structure are of interest in future experiments, such as scorpion toxins [220]. Scorpion toxins, small (29-76aa), compact molecules, evolutionarily developed to bind receptors via their active sites on gates of membrane channels and block conductivity, are envisaged to present excellent scaffolds stabilized by three or four cysteine cross-links, containing loop, turn, alpha-helical and beta-sheet

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elements and overall similar 3D structure known for some of them from X-ray and NMR studies [221]. They are perspective scaffolds for designing and fabrication of ligands with new specificities not requiring “minimization” (already done by the nature). Besides, engineered molecules generated from these and other scaffolds can be genetically fused to other domains of desired regulatory function (with sites for interaction with effectors, inductors, enzymes, anticancer agents) to yield novel multifunctional reagents of great potential in various biomedical applications. Besides, the display phage method has contributed to the high throughput selection and amplification of these engineered protein derivatives that exhibit greatly increased affinity for a pre-determined targets. Despite these properties, the minimized proteins and peptides selected from combinatorial libraries do not make themselves good drugs. Actual and future collections of peptide mimics represent primary raw material for further refinement of their structure and activity, taking their exclusive advantages such as small size, known structure suitable for engineering for rational design of drug candidates and converting to peptidomimetics via elongation, modification of the peptide backbone, substitution of amino acids by analogues or chemical mimics, addition of D-amino acids to stabilize against proteases or inclusion of carbohydrate moieties and conformational constraints (through cyclization, etc) to enhance the immunogenicity. The main requirement in the modifications of many proteins is to maintain the initially determined specificity to the target [222]. A serious problem that can arise with minimized ligands is that, although small size offers many benefits for these engineered drugs concerning their clinical application (permitting oral route of administration, better stabilization, immunological safety, tissue penetrating ability), they will also be devoid of the evolutionarily acquired ability of interaction with the co-factors and the ability to be integrally involved in complex physiological mechanisms. In the multi-component processes equilibrated by various factors, the effects of these foreign participants may shift this equilibrium unless their dosage, time-coarse of the action is regulated. One problem is the unnecessary interactions with surfaces and molecules. The majority of the surface of a protein is protected from “undesirable” interactions with other proteins or substrates within a cell where they exist in high concentrations, compartmentalized and protected by special chaperons. For example, the active site of an enzyme is characterized by a large, deep shape to establish favorable interactions with the substrate [223]. The clefts in active sites contain solvent-exposed hydrophobic residues that order water molecules [224], which are displaced during substrate or ligand binding. Although some of the peptides can be supplied with these properties, other formats of their implication in drug discovery are being considered. One of them is to bind the peptide to protein carriers developed specially to meet all these requirements. Besides, filamentous phage, displaying the ligand peptide, is not only a source of this peptide but, since the peptides are surface-displayed and reactive, the phage can be used [225] as a new giant macromolecular “carrier” where the peptide is its active site among many other active sites of the phage. Further engineering of the phage can convert it into a multi-functional macromolecule. Due to the multivalent potential of the phage coat proteins, phage can contain additional engineered sites for its programmed successful odyssey within the organism, permitting penetration into the target cell in pre-determined site of the organism directed by sequences recognized by internalizing receptors, factors of the intracellular translocations in different compartments, including the organelles, mitochondria, nuclei or even nucleoli. These factors are well known for many such

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intracellular movements: specific internalizing scFv [167,168] or RGD-carrying peptides [164]. Such peptides exist in random libraries and when a library is panned on live cells they are recognized and internalize the phage [170]. Another application not requiring these special characteristics of peptides is their use as probes in proteomic and genomic studies. The further progress in cloning and expression of human genes requires for their characterization in high throughput DNA and protein array techniques an arsenal of specific probes with binding function of known specificity. Peptides selected from libraries by natural binders, antibodies, receptors, can be such probes. The use of the peptides selected for known proteins and the further selection of new peptides to unknown protein binding sites can be exclusively effective in functional characterization of these proteins, definition of their functional profiles [226,227]. This post-selection work with collections of peptides as leads for designing and developing drugs is a separate chapter in medical biotechnology that is beyond the scope of this review but is to be clearly seen for the predetermined selections of peptides to facilitate their future conversion to drugs, which, apart from their own use as material, can include their use as lead structures for the development of small non-peptidyl molecules that mimic or block specific ligand–receptor interactions [228]. By using peptides and various organic compounds competing with them for the binding sites, new small non-protein carriers of their specificity but with better drug characteristics can be produced. A recently reported example from the use of this strategy is the identification of a small nonpeptidyl fungal metabolite that exerted an anti-diabetic activity in mice, mediated specifically via the insulin receptor, as reported by Zhang et al. [229]. Combinatorial Processes in the Nature and in Laboratory Tube In his commentary on the work from the Affimax and the Scripps Institutes that resulted in the generation of the EPO peptide substitute, James Wells noted: “Deciphering the “rules” for how proteins bind to small molecules or other proteins is largely an empirical science” [230, p.449]. The goal of an empirical science is to describe the natural processes and to learn how to use them. Hence, technical progress is the major indicator of scientific advances in biology, which in concentrated form is demonstrated by this and similar successful generation of peptides capable of reproducing the effect of the hormone that has been created during millions of years by the nature. A generalization from the results in the area of the combinatorial manipulation of bio-molecules is that the principles and methods of molecular evolution that occurred in the nature are becoming realized and reproduced in laboratory. Once this is done, the evolution in the tube can exceed in the rates of the natural molecular evolution. This is because in nature the evolving systems are species of organisms whose molecules are only elements, whereas the within-tube evolution of the same molecules is an independent system able to realize all its potential, one of the most outstanding aspects of which is the power of combinatorial rearrangements of genes and their expressed proteins. From the beginning of the biological evolution, this potential has been the driving force of the adaptation of species. Its simplified manifestation may be seen in generation of diversity via mutations coupled with the unequal recombination mechanism to give homologous genes and proteins. In bacteria homologous proteins do not form within-cell families, each cell contains typically one protein, whereas multi-

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cellular organisms generated families of homologous proteins within each individual. The multitude of the homologous proteins in an individual forms the arsenal accomplishing physiological functions in different conditions. In higher organisms whose complex ontogenesis and diversified tissues require many protein variants for functioning at different developmental stages and in differentiated tissues the number of homologous proteins in the families have grown much more. The immune system has especially been advanced in this respect because its defense function required more homologous proteins. Genes of non-immune systems encode the relatively limited number of proteins with predetermined structure. In invertebrates, the genes of immune system also encode fixed number of proteins but subsequent evolution of vertebrates generated repertoires of precursors for engineering genes whose final structure and the structure of the protein they will encode is formed at demand via developed combinatorial shuffling mechanism. Recombination of genes in the sexual reproduction is a representation of the combinatorial mechanism but is limited to a low number of genes and, most importantly, very rarely and slowly creates new proteins. The somatic gene recombination developed in the immune system is the natural mechanism, which generates new genes. After the genetic engineering in tubes has become possible and at the first stage reproduced the individual gene recombination similar to that in sexual reproduction, it would be logical to expect that the next step would be to reproduce the natural combinatorial mechanism: this means not simply to recombine the existing genes but to generate new genes from the large repertoires of precursor sequences either of the same as in the nature [231] or even higher diversity. The next point, which is an integral part of the combinatorial principle in molecular biology, is the notion and the concept of mimicry. This phenomenon also came from the natural processes generating homologous proteins. Every protein evolutionarily destined to accomplish a function has a multitude of other proteins, homologous and analogous, that are its mimics i.e. able to do the same as it does albeit with a difference. The natural phenomenon of mimicry has been first reproduced in tube by Geysen [212], who applied the term in the biological practice. Geysen worked with the structures able to substitute antigenic determinants, epitopes, and the term that he proposed is mimotope. The most remarkable property of the mimicry is that it designates inter-protein relationships not requiring amino-acid-level similarity. It is now well recognized that this type of relationship is a rule, whereas the mimicry with structural resemblance is seldom. This is amply demonstrated by the peptide substitutes isolated so far. The phenomenon of mimicry in the nature and in laboratory experiment is a universe of structures from which using high throughput screening procedures one can draw substitutes of biomolecules with drug potential. ACKNOWLEDGEMENTS The author gratefully acknowledges grants from Dirección General de Asuntos del Personal Académico, Mexican National Autonomous University, Mexico (# IN210402); and Consejo Nacional de Ciencia y Tecnología, Mexico (#251166N). The author is grateful to Valery Petrenko for discussions on the subjects of the article, and to R. Hernández and G. Gazarian for assistance in the preparation of the manuscript.

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ABBREVIATIONS mAb

=

monoclonal antibody

EPO

=

Erythropoietin

EBP

=

Erythropoietin-binding protein

HIV-1

=

Human Immunodeficiency Virus Type 1

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High Throughput Screening: Will The Past Meet The Future? Patrick Englebienne* Biomedical Consultant, Englebienne & Associates, Strijpstraat 21, B-9750 Zingem, Belgium, and Biocybernetics Unit, Laboratory of Experimental Medicine, Free University of Brussels, Place Van Gehuchten 4, B-1020 Brussels, Belgium Abstract: High throughput screening (HTS) was developed over the last decades with an aim at selecting interesting drug candidate leads within the huge libraries of compounds obtained by combinatorial chemistry. From the early days, the technique consisted in detecting molecules capable of interacting with specifically selected target receptors, enzymes or antibodies so as to sort out the ones susceptible of further development. In the early days, radioactive, enzyme or fluorescent detection techniques were commonly applied in plate reader formats. Throughput was progressively enhanced by increasing the number of wells per plate and by automating the procedures. A further development of the throughput capacity was obtained with the switch from inhomogeneous to homogeneous technologies, where the detection signal is generated directly from the biomolecular interaction, without the need to separate bound from free fractions within the reaction mixture. This advance reduced the manipulation steps, reducing the costs and further improving screening throughput which culminates today in ultra-high-throughput methodologies. The increase in data generated by such technological improvements required a parallel development of softwares capable of handling and analysing the information, at the expense sometimes of missing false negatives. The drug discovery process now faces a new bottleneck resulting directly from HTS developments. Although HTS allows to rapidly identify new drug candidates, the technique does not address the possible applicability of the hits to a biological system. The technology does not give any insight into the possible cellular toxicity of the hit, which is a minimal requirement for further development. Thus, the bottleneck is currently shifting from hit identification to toxicity and biodisponibility evaluation. This new challenge will require a further effort in inventiveness from the part of pharmaceutical scientists.

INTRODUCTION During the last half-century, the pharmaceutical industry has faced several new challenges, including the increasing cost of bringing new drugs to market, and the needs for more efficient therapies for high incidence lethal or debilatating chronic diseases *Corresponding author: Tel/Fax: +32-495-773-006; E-mail: [email protected] Garry W. Caldwell / Atta-ur-Rahman / Barry A. Springer (Eds.) All rights reserved – © 2005 Bentham Science Publishers.

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such as malignancies and autoimmune diseases, or emergent new plagues such as the infections by the human immunodeficiency virus [1, 2]. These new challenges required cost reductions and an increase in new drug candidates output, which were met during the last decades with the advent of combinatorial chemistry technologies [3]. The combinatorial chemistry revolution provided the industry with series of compound libraries the size of which could not be thought of with the synthetic chemistry technologies available before. This situation created a bottleneck at the level of compound evaluation which was solved by a progressive increase in screening speed by the advent of high throughput screening (HTS) technologies [4]. HTS consists in identifying rapidly compounds exhibiting a given biological activity, such as affinity, toward a given pharmaceutical target (enzyme, receptor), from libraries containing from hundred-of-thousands to millions of compounds [5]. The recent advances in genomics and molecular biology have produced an increasing number of drug molecular targets, so that the demand is now shifting from a single to multiple target screens of a given library [6]. The technological advances made in the field during the few last years have permitted to test more and more compounds at faster and faster rates. Unfortunately, this was not as productive as expected because of the new challenges presented by the abundance of data that need to be analyzed, and the difficulty to detect specific from non-specific hits within assay results [7]. Failure to recognize such early problems results in a vast majority of early hits to fail progressing at later stages of the drug development process [8]. Moreover, a biological hit compound does not necessarily fulfill all the requirements for a successful drug in terms of absorption, metabolism, distribution, elimination, and toxicity (ADMET) and consequently, the current trend demands a departure from the unique process of identification toward fast and costeffective and more integrated parallel strategies guaranteeing improved clinical prospects and successes [9]. This review will address the progressive evolution of HTS with a particular emphasis on the technological developments, and the possible application of the latest discoveries in the field to the emerging challenges faced by this early phase of the drug discovery process. HTS, TARGETS AND LEADS HTS is an early step in the drug discovery process. As presented in Fig. (1), HTS is at the cross-road of the pharmaceutical target identification process and the synthesis of compound libraries by combinatorial chemistry. The whole process (Fig. (1)), usually starts with the identification of a suitable and validated biological target, which plays a role in the etiology or pathogenesis of a disease and the activity of which can be modulated by a drug [2]. The target is then confronted during HTS campaigns to libraries (collections) of small molecules obtained by combinatorial synthetic chemistry, or of natural origin, in order to identify hits. The next hit-to-lead development process is intended to identify a lead compound which is active in the cellular context and displays drug-like properties in terms of ADMET characteristics. Finally, the lead development process involves in vivo testing and the further optimization of the lead compound in terms of pharmacokinetics and pharmacodynamic properties to make a series of clinical candidates. Combinatorial chemistry is out of the scope of this chapter and will not be addressed. The reader may refer to recent excellent reviews covering the major advances in the field [3, 10-15].

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However, it is important to say a word about the drug targets because not only their nature, but also their cellular function, directs the technology to be used in an HTS campaign.

Fig. (1). Algorithm presenting the central place of HTS in the drug discovery process.

Pharmaceutical targets are usually proteins which are differentially expressed or activated in a diseased versus normal tissue [1]. The information gathered by sequencing the human genome (genomics) and the ability to identify every expressed gene will lead to the identification of many new protein targets relevant to the pathogenesis and/or persistence of diseases [1]. The identification of a prospective protein target (proteomics) is currently effected by three means, namely: by evaluating the differential profile of a given protein expression [16] or activation [17] between diseased and normal tissues (profiling proteomics); by understanding protein interactions and functions (functional proteomics) individually [16, 18, 19] and between each another in cellular pathways [17, 20]; by elucidating the tertiary structure of proteins and domains so as to understand the mechanisms of their interactions within cells (structural proteomics) [21]. The cellular target proteins might be enzymes such as kinases and in most cases, the HTS campaign will attempt at identifying inhibitors of the enzymatic activity [22]. However, cellular kinases such as protein kinase C interact also with other cellular proteins within signal transduction pathways, in which case the HTS campaign will attempt to identify small molecules capable of inhibiting such interactions [23]. The target protein might also be a nuclear or membrane receptor, such as a chemokine receptor [24], in which case the HTS campaign will hunt for small molecules modulating

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the binding of the natural ligand. But a membrane receptor can also display an associated enzymatic activity, such as the G-protein-coupled-receptors (GPCR), and in such a case, the screen will evaluate the drug-receptor interactions in terms of effects on the downstream enzymatic activity [25]. These downstream cellular events lead to the differential expression of specific gene products [26, 27]. Finally, the protein target might be an ion channel and the HTS run will address the capacity of the library compounds to modify ion fluxes [28]. Besides proteins, RNA molecules are also emerging pharmaceutical targets. RNA possesses the double property of being a repository of genetic information and of displaying either catalytic activity like enzymes [29], or protein interaction capacity [29, 30]. Therefore, RNA molecules intervene in many cellular activities, from gene expression [29] to signal transduction [30]. The identified target involved will consequently govern the HTS methodology and hence the technology to be applied, depending on the results and type of information expected from the assay. These can be either mechanistic, such as in enzymatic or binding assays [31], or functional, such as in protein interaction or ion flux assays [32]. Table 1 presents a summary of the information that can be expected from mechanistic and functional assays, depending on the type of target considered. Table 1.

Information Obtained from Mechanistic and Functional Assay Systems Information expected from the compounds tested

Target:

Examples: Mechanistic Assay

Functional Assay

Serum enzyme

Cyclooxygenase, Thrombin, proteases.

Kcat, Km, Vmax, inhibition of natural substrate binding (KI), selectivity.

Production of mediators Capacity to interact with other blood components.

Cellular enzyme

Kinases, phosphatases, caspases, proteases.

Kcat, Km, Vmax, inhibition of natural substrate binding (KI), selectivity.

Capacity to interact with other cell proteins or peptides, capacity to hetero- or homodimerize, apoptotic induction.

Membrane receptor

Growth factor receptors, Chemokine receptors, G-proteincoupled receptors.

Nuclear receptor

Thyroid, steroid, retinoid receptors.

Affinity (KD), inhibition of natural ligand binding(KI), selectivity.

Interaction with coactivators, gene expression regulation, distinction between agonist, partial agonist and antagonist ligands.

Cellular binding proteins

p53, Bcl-2, BclXL

Affinity (KD)

Protein-protein interactions, apoptotic induction.

Ion channels

K+, Ca++ channels, ryanodine receptors.

Affinity (KD)

Ion flux through cellular or cell compartment membrane, downstream effects.

Affinity (KD), inhibition Downstream effects (c-AMP, inositolof natural ligand 3-phosphate, Ca++, GTP-binding, binding (KI), selectivity. oligomerization, localization); distinction between agonist, partial agonist and antagonist ligands.

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STATE OF THE ART IN HTS METHODOLOGY AND TECHNOLOGY Assay Type and Format Before deciding on a specific technology, the type of assay must be selected between a cell-free or a cell-based assay system [33]. Cell-free assays are simple and amenable to ultra-HTS (u-HTS), but instead of cell-based assays, they do not present the target in the cellular context and consequently do not allow to measure the downstream signal transduction effects of a compound. In contrast, cell-based assays permit to gather more useful information but usually at the expense of throughput [34]. Both cell-free and cellbased assays are usually adapted to plate formats. The continuous trend toward higher thoughput has seen the number of wells per plates to increase progressively from 96 to 384 and 1536-well plates [35]. Currently, new systems allow for handling up to 3456well plates [36]. This trend was continuously associated with the development of robotics and high performance liquid-handling devices permitting to rapidly add volumes reduced down to several micro- or even nanoliters per well [37 – 41]. The main objective of this trend was, besides increase in assay speed and efficiency, to reduce the cost of reagent usage [35]. However, going to greater plate formats involves also a substantial capital investment in equipment, which include not only liquid-handling, but also specific high-throughput readers [35, 42]. Another difficulty presented by u-HTS results from the fact that due to labor intensiveness, most cell-based assays are hardly applicable to formats beyond the 96/384-well plates [43]. Some of these difficulties have been overcome with the development of protein biochips and microarrays which involve the automated production of small reagent spots on hydrophobic membranes by inkjetting technologies [44]. This new advance in u-HTS was made possible thanks to the parallel development of large capacity scanners and readers [45]. Recently, cell microarrays have also been developed that allow to increase the throughput capacity of cell-based assays [46, 47]. Cell-free assays are in most cases mechanistic. They are particularly suited to the measurement of enzymatic activities and their inhibition by the test compounds. The measurement of kinases [48], phosphatases [49], caspases [49] activities, as well as many other serum or cellular enzymes of which a catalytic substrate-product transformation can be monitored at end-point or in kinetic mode in absence or presence of the test compounds [50 - 52], have been adapted to HTS and u-HTS. Although the assay format usually requires enzyme immobilization, which changes substrate turnover relative to what happens in solution, this is not likely to have a tremendous impact on the determination of relative inhibitory activities [51]. Cell-free assays provide also useful mechanistic informations on ligand-receptor interactions and have been applied to both membrane receptors such as GPCRs [53] and nuclear receptors such as the estrogen receptors [54]. These assays use the recombinant receptor proteins and evaluate the binding characteristics and inhibition of peptide or small molecule ligand-binding [53, 54]. HTS cell-free assays are similarly applied in the evaluation of DNA and RNA hybridization [55, 56] as well as RNA-protein assembly modulation by library compounds [57]. Recent advances in cell-free assay methodology have been able to alllow the evaluation of functional assay end point elements in the presence or absence of drug candidates, such as transcriptional activation [58, 59] and more recently, even translation and protein expression [60] . These recent improvements were made possible thanks to the commercial availability of cell lysate systems allowing to perform

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automated coupled transcription-translation reactions in high yield from a given gene introduced as a polymerase chain reaction (PCR) product [61]. Cell-based assay system are more complex to implement and more labor-intensive than cell-free assays [34]. However, they present the advantage over cell-free assays to permit the investigation of a wide array of functional properties exerted by compounds from libraries, including effects on intracellular signalling pathways, protein-protein interactions and subcellular localization of the targets [62]. Moreover, since the test compound is put in presence of a complete and fully functional cell, it is subjected to cellular entry barriers and catabolic processes [62]. Although cell entry barrier is not critical with small organic molecules, it might be an essential part of the library effectiveness, particularly with larger molecules such as peptides, nucleotides and oligosaccharides. The critical differences in terms of design and type of information provided between cell-free and cell-based assays are schematically presented in Fig. (2). Among the cells used in HTS, the yeast Saccharomyces cerevisiae has become a prominent model organism, particularly with the emergence of the two-hybrid system screen for protein-protein interactions [63]. Recently however, two-hybrid screening systems using mammalian cells have been developed in order to override the limiting drug permeability differences existing between yeast and mammalian cells [64].

Fig. (2). Schematic presentation of the critical differences between cell-free and cell-based assay systems.

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The gene-reporter assays are also in wide use in the drug discovery process. They allow to monitor the transcriptional activation of specific genes resulting from ligandbinding to and activation of membrane [65] and nuclear receptors [66] alike. The most recent technological developments of this assay system even allow to discriminate receptor agonists from antagonists [67]. Specific functional cell-based assays are also being developed that, by monitoring the concentration of secondary messengers such as inositol 1,4,5-triphosphate in living cells, allow to follow in real-time the activation by compounds of given signalling pathways [68]. The evaluation of libraries against ion channel targets is most probably a field that benefits most from cell-based HTS assays. The conventional patch clamp technique is slow and labor-intensive [69]. Therefore it is being progressively replaced by cell-based, rapid assays that monitor ion transport within living cells using electrophysiological techniques [69], voltage- or ion-sensitive dyes [70 - 72]. Signal Detection Whether cell-free or cell-based, the low labor, reduced cost and short time requirements of any HTS assay calls for a “mix and read” capacity. Various strategies have been designed over the last decades to gain such advantage in signal detection, from the scintillation proximity to smart materials and biosensors [73]. The different signal detection technologies are based on various physico-chemical principles leading to the generation of a physical signal upon interaction between the molecules of interest. They are best classified depending on whether they use a label or not, a distinction which is cartooned in Fig. (3). Label-based assays use a tracer molecule or atom with specific physical emission characteristics (e.g. radioactivity, fluorescence), which is coupled to one reactant and can be detected (traced) and quantitated by its emission during complex formation with the cognate molecule. Conversely, label-free assays detect directly the changes occuring in a physical characteristic of respectively either one reactant (Fig. (3), bottom part A, e.g. mass spectrum), or of a supporting layer to which it is attached (Fig. (3), bottom part B, e.g. sensor), that allows to monitor and quantitate the biomolecular interaction of this reactant with a cognate molecule. Label-Based Detection Among the labels, radioactive isotopes have been in use from the early days of binding assays and assay homogeneity has been made possible with the development of the scintillation proximity assay design. Currently available homogeneous assay designs and labels are extensively described and reviewed in ref. [73]. Although still applied to HTS [74], the security requirements and the cost of waste disposal associated with radioactive labels lead many laboratories to prefer using optical labels [75]. Enzymatic assays usually rely on the subsequent reaction of the product generated by the catalytic activity with a label present in the mixture or within the cell and capable of generating a fluorescent [76], chemiluminescent [77], or colorimetric [78] signal upon interaction. Nowadays, many cell-free binding assays use fluorescent labels. Protein-protein [79] and nucleotide-nucleotide [80] interactions are usually monitored by fluorescence resonance energy transfer (FRET). FRET also allows to monitor conformational changes within a given protein and has been adapted to microscopic examination in living cells [79]. Even with the FRET technology which relies on the specific energy-dependence of a pair of fluorophores, the key problems associated with the detection of the

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fluorescence signal are of two natures. Quenchers possibly present in the reaction can inhibit signal generation and autofluorescence from contaminants or compounds in the mixture can mask the signal [81]. In FRET, these limitations have been overcome mainly by time-resolved (TR) fluorescence detection, which permits to eliminate the short-lived non-specific fluorescence signals, and by the use of rare earth cryptates which present the prolonged time emissions, spanning over milliseconds, required for proper TR detection [81-83]. In single fluorophore assay design, fluorescence polarization (FP) is probably the most popular technology in use for HTS, particularly because of the ease to assay miniaturization with this signal detection technology [84]. Quenching and autofluorescence reduction can be achieved by fluorescence lifetime discrimination [85]. Besides its use in classical competitive ligand-binding assays [86], FP has also been recently applied in HTS format to the detection of inhibitors of protein interactions in such cell signaling pathways as apoptosis (Smac/DIABLO, Bcl-XL) [87 89], or signal transducers and activators of transcription (STAT) [90].

Fig. (3). Cartoon presenting the conceptual differences between label-based and label-free assay designs.

Fluorophores are also in progressive use for HTS cell-based assays. A fluorometric imaging assay has recently been developed for the detection of calcium mobilization by cells stably expressing various subtypes of GPCR, with an aim at identifying and

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characterizing agonist ligands activating distinct intracellular second messenger pathways [91]. Flow cytometry with fluorescent probes is becoming an increasingly attractive platform for homogeneous HTS of cells, that can be further enhanced by multiplexing on color-coded beads or cell-suspension arrays [92]. In the area of ion channels, although attempts to automate electrophysiological measurements and patchclamping are progressing [93], the FRET technology using membrane potential-sensitive dyes allows for higher capacity screening assays [94, 95]. Other technologies are however emerging, such as the automated detection by atomic absorption spectroscopy of rubidium flux across the cell membrane [96]. Label-Free Detection Among the label-free screening technologies, nuclear magnetic resonance (NMR) spectroscopy has been in use for close to a decade for hit to lead development (see Fig. (1)) [97]. NMR is particularly suitable to cell-free assay systems. The main interest in NMR results from the fact that it allows to distinguish binding sites of different affinities on a same protein or nucleic acid target receptor, that are involved in binding different ligands. This advantage is particularly useful in structure activity relationship studies which further allow to optimize the lead structure for enhanced activity [98, 99]. However, recent efforts have been made to develop new instrumentation and methodologies to increase throughput and apply NMR also in cell-based HTS [99, 100]. Besides NMR, mass spectrometry (MS) has also been developed as a method for quantitative studies on biomolecular interactions between low molecular ligands and proteins in cell-free assays. Electrospray ionization (ESI)-MS allows to infer the affinity of ligand-protein complexes in direct as well as competitive experiments. In some cases, however, the interactions occuring in the gas phase may differ from those found in solution. The technique has now matured and several means have been designed to counter this problem, such as nanoflow electrospray formation on microchips, which were recently fully automated for HTS [101, 102]. Matrix-assisted laser-desorption ionization (MALDI) MS generally complemented by time-of-flight (TOF) analysis has also become an outstanding technique for the study of biomolecular interactions and has been proposed for HTS [103]. The capacity of MS in HTS is further empowered by its combination with high-performance liquid chromatography (HPLC). Several methods have been proposed to screen libraries, involving such combinations as ESI-MS with size exclusion and reverse phase (RP)-HPLC [104], or evaporative light scattering-TOFMS with RP-HPLC eventually coupled with NMR for compound identification [105]. Such methods can be applied in 96- or 384-well plates and currently compete for screening throughput with the most advanced label-based assay methodologies [104]. Optical biosensors are currently emerging as a further label-free alternative for the study of biomolecular interactions [106]. Several technologies have been recently proposed for HTS in cell-free systems, such as reflectometric interference spectroscopy [107] and colorimetric resonant grating [108]. Currently however, the most popular optical sensing technology applied to screening for biomolecular interactions is undoubtedly surface plasmon resonance (SPR) [109]. SPR biosensors have been applied to the quantitative real-time analysis of various biomolecular interactions such as peptide-antibodies [110], receptor-ligand [111], including imaging of peptide and nucleic acid arrays [112, 113]. Quite early, we have shown that the real-time detection of the SPR phenomenon occuring during biomolecular interaction could be implemented,

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not only on sensor chips, but also on colloidal gold nanoparticles in solution, and in such a case, the SPR signal is read by a common UV-vis spectrophotometer [114]. We have eventually extended this system to cell-free HTS [115]. Because of their similar optical properties [116], SPR detection applies also to nanoparticles made of other noble metals such as silver, in liquid [117] as well as on solid-phase [118, 119]. The surface of such nanoparticles can be functionalized with various ligands or chemical groups to enable their recognition by cognate biomolecules [120]. Gold and silver nanoparticles are progressively emerging as particularly interesting sensors for microscopy, since the discovery by the Yguerabide’s of their capacitiy to scatter colored light when illuminated with white light, and to behave like highly fluorescent analogs [121, 122]. The frequency of the scattered light results directly from the SPR and is thus a function of the size, shape, and composition of the nanoparticle. These nanoparticles have a tremendous application potential in HTS, as in vivo extra- and intracellular sensors for protein recognition detection by light microscopy [123]. THE WHEREABOUTS OF TODAY HTS The advances made over the past decade in drug discovery technologies have not yet delivered the increase in productivity that was expected from HTS. Overall, less than one in fifty projects succeed through discovery and development to produce a marketable drug and in the discovery phase, the cumulative attrition is around 80% [124]. Such high level of attrition can be attributed to several factors [124], which span over the whole discovery process (Fig. (1)). As far as HTS is concerned in the process, the trend seeking a continuous increase in the throughput of mechanistic assays has generated new bottlenecks that still reduce the speed of the whole process. First, the deluge of screening data generated needs the necessary logistics for their interpretation and analysis [125, 126]. The throughput obtained by using computerized data analysis is however hampered by the need to still use manual curve fitting in some complex cases suspected to result from false negative interpretation. Second, the functional assays which are subsequent in the process have usually remained at a lower throughput [34, 125]. Third, the relatively high rate of false positive hits compromises the efficiency of HTS and constitutes an important reason for attrition at a later stage. These false-positive results (promiscuous agonists or inhibitors) can be generated by mechanisms that are independent from the HTS assay design, such as non-specific compound aggregation [127]. Despite and notwithstanding these limitations, some advocate a further evolution in capacity involving the simultaneous screening of different targets in single assays [128]. On the opposite, others advocate the progressive emergence of a lower throughput pharmacogenomic approach, which involves the elucidation of interindividual differences in drug effects and mechanism-based approaches to the development of new drugs [129]. In-between, are the tenants of a combination of mechanistic and functional assays in cell-based systems, which allow to gather complex information on the physiological effects of hits without compromising exceedingly on throughput [130 132]. This latter trend is likely to gain more and more supporters. For instance, an adaptation to molecular pathology with human tissue has been proposed to have higher potential in distinguishing the effects of drug candidates between normal and pathological cells, enabling informed decisions to be made with respect to success potential [133]. These different trends respond to some, but not all of the current challenges of present day HTS. These current challenges include also a need for a more integrated approach of HTS, which involves not only the evaluation of activity, but also

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of preliminary pharmacological (ADMET) properties so as to avoid attrition of unsuitable compounds at a later stage and increase overall productivity [134]. The integration of the various assay concepts and designs, along with the challenges they currently face are schematically summarized in Fig. (4). The general challenge toward higher throughput that has prevailed up to recently in HTS laboratories is therefore currently modulated by more exhaustive and thoughtful strategies. In the past, the technologies available have been successful in meeting the demand for higher throughput assay design and for cost containment, by delivering sensitive reagents, multiple platforms, automation and miniaturization. Today, the question remains as to whether the past will meet the future in appraising the new HTS challenges in the drug discovery process. WILL THE PAST MEET THE FUTURE? Deciphering the human genome has provided a huge amount of genetic information in health and disease [34]. However, genes code for proteins which effect their specific tasks in the signal transduction pathways that make cells the prime movers of life. Genes can be targets for genetic therapies but in classical pharmacotherapy, proteins are the targets and therefore, the genomic information available must be translated into proteomic information for full exploitation. Consequently, the first line challenge that faces HTS nowadays is the identification of targets, the characterization of their physiological effects, and the elucidation of their respective mechanisms of action (see Fig. (4)). Several advances have been made to this respect among which the RNA interference [135] and the high throughput western blot screening technologies [136, 137] constitute important breakthroughs allowing to rapidly identify and study new targets. These important advances are however applicable to isolated cells and do not necessarily reflect the in vivo situation. New means are therefore needed to better apprehend this gap. Mouse knockout technology is an appealing approach in this context but todate, knockouts exist for only about 10% of mouse genes. Hence, the knockout mouse project recently proposing to mount an international effort to produce a genomewide collection of mouse knockouts is particularly welcome [138]. The second line challenges (Fig. (4)) are directly concerned with HTS assay strategy. There is a need to reduce the high false-positive rates of the classical mechanistic cellfree assays which can be limited by an affinity- rather than activity-based approach [115, 139]. New directions tend however toward the integration of bioinformatic and experimental technologies allowing for a confrontation of virtual with experimental screening results [140 - 142]. Such integration has been successfully applied in such remote areas as the characterization of enzyme inhibitors [142, 143] and of GPCR or nuclear receptor agonists and antagonists [142, 144]. The pharmaceutical industry is also strongly avid to gain pharmacological and pharmacodynamic information early in the drug discovery process and possibly during a HTS campaign, so as to counter the attrition rate at later stages. This is another domain where in silico methods are particularly useful, as they allow to integrate the characterization of hits in terms of ADMET properties with in vitro screening [145 - 147]. Such methods are based on correlations between a given physical characteristic of the drug candidate and an ADMET property, as established using training sets of known drugs. These mathematical models are then used in order to deduce the pharmacological and pharmacodynamic characteristics of libraries. Such models have been established to

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infer absorption [148, 149] and oral bioavailability [150, 151], distribution and pharmacokinetic [152 - 154], metabolic stability [155 - 158], aqueous solubility [159], drug-drug interaction potential [160], and binding promiscuity [161]. Currently, except when HPLC/MS is selected as HTS technology [153, 154, 162], ADMET characterization occurs in parallel to HTS, using different techniques. As examples, metabolic profiling can be deduced from the relationship between the inhibition capacity of cytochrome 450 by known drugs [155, 156], oral bioavailability and absorption can be deduced from the drug permeability to cells in culture [148 - 150] and pharmacokinetic data from lipophilicity [152]. Although this improves the quantity and quality of information gathered during a campaign, the use of parallel technologies decreases the throughput, which still remains the focus of any laboratory, as reminded during the 2nd Conference on Advances in HTS, held in London last January [163].

Fig. (4). Schematic presentation of the current challenges faced by integrated HTS assay concepts and designs.

Although new sophisticated in silico quantitative structure-activity relationship models are being developed for ADMET prediction of novel chemical compounds [164], they still present weaknesses and therefore, new imaginative reagents are needed, allowing to gain such information in a multiplexed format. In this respect, sensors or labels based on

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conducting polymers are in our opinion an interesting avenue. A few years ago, we and others have adapted such labels to homogeneous biomolecular recognition [165]. Such reagents are however also sensitive to various physico-chemical characteristics of the molecules with which they interact [73, 165], a feature that could be considered in early ADMET analysis, alone or in combination with other sensitive reporter materials such as colloidal metals. The combination of these latter with other reporter reagents such as fluoroprobes has indeed been shown to be highly beneficial [166]. The combined sensitivities of noble metal colloids to refractive index changes [109] and of conducting polymers to oxido-reduction [73], probably deserve further valorization in such a context. Colloidal metal nanoparticles are also becoming reagents of choice in the currently developing trend to drive HTS to living cell-based functional assays [167, 168]. Fluorescent probes have quite early been exploited in this context [169], although their further optimization has required important research investments in associated technologies such as microarraying and imaging [170 - 172]. Nuclear magnetic resonance imaging of conjugated iron oxide nanoparticles has recently emerged as a non-invasive cell screening technique for HTS [173]. However, despite the tremendous screening potential that they offer, multiplexing remains difficult to conceive using these technologies. Colloidal noble metal nanoparticles made of silver or gold are more susceptible to present breakthrough advances in the field. Their exquisitely sensitive reactivity to changes in their dielectric environment alter their light scattering and surface plasmon resonance spectra, a property which has very recently been exploited for imaging biomolecular recognition [174] and membrane transport [175] in living cells by light microscopy. The application of such nanoparticles to imaging membrane transport is remarkable, since the current technologies used in this HTS field, such as dyes or fluorescence, present disadvantages including false positivity, slow response, assay complexity and high cost [176]. Moreover, it is possible to synthesize nanosized cylindrical particles with different Ag-Au striping patterns [177], which will probably allow, in a very near future, for multiplex imaging in a single cell. Finally, these emerging technologies are non-invasive and are adaptable to screening in intact living animal organisms [178], which constitutes probably the next challenge facing HTS technology [179]. The potential of these emerging technologies for living cell-based and whole organism functional screening are compared to FRET in Table 2. Table 2.

Comparative Analysis of Emerging Technologies for Living Cell-Based Functional HTS with FRET

Technology

Imaging Technique

Adaptation to microarrays

Multiplexing capacity

Membrane transport study

Adaptation to living organisms

FRET

Fluorescence microscopy

Yes

No

Yes

No

Colloidal iron oxide

Light microscopy

Yes

No

Yes

Yes

Colloidal gold or silver

Light microscopy

Yes

Yes

Yes

Yes

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The past has seen advances in technological capacity that have successfully allowed to bring drug screening to a level of throughput meeting progressively the demands of the pharmaceutical industry. The present demand is driving toward cell-based and functional assays incorporating a parallel evaluation of ADMET. The future will call for early screening in the drug discovery process using whole living organisms, while maintaining a high level of throughput. The technological advances that have been made during the recent years along with those currently emerging are likely to indicate that the past will successfully meet the future. ABBREVIATIONS ADMET

=

Absorption, Distribution, Metabolism, Excretion, Toxicity

ESI-MS

=

Electrospray Ionization Mass Spectrometry

FRET

=

Fluorescence resonance energy transfer

GPCR

=

G-Protein-Coupled Receptors

HPLC

=

High-Performance Liquid Chromatography

HTS

=

High Throughput Screening

MALDI

=

Matrix-Assisted Laser-Desorption Ionization

MS

=

Mass Spectrometry

NMR

=

Nuclear magnetic resonance

RP

=

Reverse Phase

TOF

=

Time-Of-Flight

u-HTS

=

Ultra-HTS

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Variety of the DNA Hybridization Rate and Its Relationship with High Order Structure of Single Stranded Nucleic Acids Makoto Tsuruoka* School of Bionics & School of Engineering, Tokyo University of Technology, Katakura 1404-1, Hachiouji, Tokyo, 192-0981 Japan Abstract: The hybridization of oligo-DNAs complementary to the sequences of the genes for verotoxins (Shiga toxins) type 1 and 2 of enterohemorrhagic Escherichia coli (EHEC) was monitored using fluorescence polarization under the reaction condition of high salt concentration (0.8 M NaCl), which had been optimized to obtain a high rate of hybridization. The time courses of fluorescence polarization for the fluorescently labeled oligomers (probe DNAs) mixed with the amplified DNA of the genes were recorded. The secondary structures of the amplified single-stranded DNAs were forecasted based on the calculation for minimum free energy at a specified minimum stacking length. Five probe DNA sequences were designed, some of which hybridized extremely rapidly with an amplified product for the gene of Shiga toxin type 1. In the cases using the two different probe DNAs, the hybridization was 90% complete in less than 1 min, considerably faster than that of the 3 min reported previously, while with another probe it was not complete in more than 14 min. The variety of the rate for hybridization could not be explained by melting temperature or G + C content of the probe sequences. It was suggested that the reason for the slow hybridization would be a steric hindrance, comparing the hybridization rates with the shapes around the binding sites for the probes in the secondary structures.

1. INTRODUCTION This paper describes the development of a rapid assay, based on detection of fluorescently labeled probe following hybridization with target sequence using fluorescence polarization. The assay aims to identify specific gene sequences; examples used are those for Shiga toxin type 1 and 2 of enterohemorrhagic Escherichia coli. The system has potential for rapid screening of clinical samples for the presence of infectious agents. Equally, the method may be of benefit to those interested in screening environmental or food samples for the presence of contaminated microorganisms, but may also find use as a rapid process monitoring tool, for example, the production of plasmid DNA for gene therapy under consensus.

*Corresponding address: E-mail: [email protected] Garry W. Caldwell / Atta-ur-Rahman / Barry A. Springer (Eds.) All rights reserved – © 2005 Bentham Science Publishers.

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Many methods have been reported for detecting specific nucleic acid sequence or following nucleic acid hybridization. In fluorescence polarization analysis (FPA), almost real-time monitoring of association between nucleic acids in solution can be performed. Hybridization reaction between the fluorescent-labeled oligo-nucleotide probes, and the complementary single-stranded nucleic acids has been already observed, using fluorescence polarization in some reports [1-3]. They employed quite simple architecture of DNA detection, in which a fluorescent-labeled probe DNA was mixed with a target DNA and fluorescence polarization or anisotropy was monitored. In this type of FPA, optimizing such conditions as NaCl salt concentration and the temperature of reaction mixture was possible in order to maximize the rate of hybridization, because the reaction conditions for hybridization could be organized in wider ranges [4]. Under the optimized conditions of high salt concentration (0.8 M NaCl) at the temperature of 46 °C, it was shown that the hybridization reactions were 90% completed within 5 minutes of mixing the probe DNAs with the synthesized complementary oligo-DNAs or the complementary gene DNAs of microorganisms amplified by the asymmetric PCR [5]. The aims of this report are to describe the several DNA probes inducing extremely high rates of nucleic acid hybridization under the conditions, to make basic consideration on the reasons for the rapidity, and to comment on the possibility of high throughput screening for nucleic acids. Hence, the time courses of fluorescence polarization, the rates of hybridization and the secondary structures of the segment DNAs for the genes are mainly brought into focus here. 2. EXPERIMENTAL 2.1. Instrumentation Fluorescence polarization values were determined using Beacon 2000 (Panvera Corporation, WI, U. S. A.) to observe the time courses for the genes of Shiga toxin type 1 (stx1) & type 2 (stx2). The samples were measured in a disposable test tube. The measured polarization values were multiplied by 1000 times and plotted in the arbitrary unit of mP, although polarization itself has no unit of dimension. DNA amplification by PCR was performed using a PCR thermal cycler (model 9600, Perkin-Elmer Co. Ltd., CA, U. S. A.). 2.2. Reagents and Samples Two original samples including the template gene DNAs of Shiga toxin type 1 (stx1) and type 2 (stx2) were prepared from the two strains of EHEC O26 and O157, respectively, in the Hiroshima City Institute of Public Health, Japan. Negative control samples for FPA were prepared, which were salmon sperm DNA (Funakoshi Co. Ltd., Tokyo, Japan) at the concentration of 800 ng/ml, and the PCR samples using DEPCtreated water instead of the positive templates. In addition to using FPA, the positive template samples subjected to the amplification protocols of the asymmetric PCR were analyzed using electrophoresis, and the expected bands for each sample were observed (data not shown). TE buffer (10 mM Tris-HCl (pH 8.0) and 1 mM EDTA disodium salt) was used to dilute the solutions. The concentrations of the DNAs were estimated from their absorbance at 260 nm.

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2.3. Sequences of the Primers and the Probes The chemically synthesized primers (a) and (b), and probes (e) - (g), whose sequences were shown below, were obtained from Sawadee technology (Tokyo, Japan). The probe DNAs were purified with HPLC. F in (e) - (g) represents a fluorescein label. The primer pair (a) & (b) was used to amplify universally the genes of stx1 and stx2 [6] by the asymmetric PCR. The probes (c), (d) and (e) were independently designed to be complementary to the amplified gene DNA of stx1, and those (f) and (g) were also designed for stx2 in the laboratory. (a) MK1; 5' TTT.ACG.ATA.GAC.TTC.TCG.AC 3' (b) MK2; 5' CAC.ATA.TAA.ATT.ATT.TCG.CTC 3' (c) PBST10; 5' F- GAT.AGT.GGC.ACA.GGG.GAT.AAT 3' (d) PBST11; 5' F- ATA.GAT.CCA.GAG.GAA.GGG.CGG 3' (e) PBST12; 5' F- ATT.CGC.TGA.ATG.TCA.TTC.GCT 3' (f) PBST20; 5' F- CAG.GCG.CGT.TTT.GAC.CAT.CTT 3' (g) PBST21; 5' F- AAC.CAC.ACC.CCA.CCG.GGC.AGT 3' 2.4. Amplification of the Genes of Shiga Toxins To amplify the segments of stx1 and stx2 genes and produce much single-stranded DNA, primers MK1 and MK2 were used in 10 pmol and 100 pmol, respectively. In the asymmetric PCR [7], the single-stranded DNAs with which the probes (c) - (g) could hybridize were amplified much more than the other ss-DNAs, which would compete with the probe DNAs in the course of hybridization [5]. Each template volume was 10 µl and the total volume of reaction mixture was 50 µl. The mixtures were initially denatured for 2 min at 94 °C, then they were subjected to 35 temperature cycles, which consisted of denaturation for 30 sec at 94 °C, primer annealing for 60 sec at 48 °C and extension for 30 sec at 72 °C. The last cycle was primer annealing for 60 sec at 48 °C after the denaturation. DNA polymerase used was Ex (Takara Shuzo Co., Ltd., Kyoto, Japan). The amplification of the genes of stx1 and stx2 using the asymmetric PCR was confirmed with agarose gel electrophoresis (data not shown). 2.5. Detection of the Amplified Products The probe DNAs were diluted to 0.6 nM with TE buffer containing 0.8 M NaCl. 100 µl of each probe reagent was mixed with 10 µl of each PCR product, and fluorescence polarization was measured every minute for 15 min at 46 °C. 2.6. Secondary Structures of the Amplified Products The forecast for the secondary structures of the amplified ss-DNAs was performed using Genetyx-Mac Ver.10 (Genetyx, Tokyo, Japan). The calculation based on the minimum free energy at a specified minimum stacking length for ss-RNA was substituted for that for ss-DNA, due to the restriction in the software. Minimum stacking length means the minimum chain length of the continuous or straight base pairs, when the complementary binding is formed within a single-stranded nucleic acid.

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3. RESULTS AND DISCUSSION 3.1. The Time Courses of Polarization Using the Probes for Shiga Toxin Genes Figure (1) shows the time courses of the polarization using the probe DNAs for stx1 immediately after being mixed with the asymmetric PCR product of stx1 gene of EHEC. In the figure, the time courses for the probes PBST10 and PBST11 with the positive sample were obviously different from those with the negative sample, where the polarization values of the former were much higher than the latter. The extremely rapid hybridization between these probes and the positive sample was observed, thus, the distinction between the positive and the negative would be possible in one minute of mixing the probes with samples. In contrast, the polarization value of PBST12 with the positive sample was not as high as those of PBST10 or PBST11, and its rate of hybridization was rather low.

Fig. (1). Time courses of polarization of the probe DNAs for stx1 gene. Probes: PBST10, PBST11 and PBST12 complementary to the segment of stx1 gene. Samples: stx1-gene positive and negative samples. To distinguish a group of data clearly, they are connected by simple straight lines.

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Figure (2) shows the time courses of the polarization of the probes for stx2, mixed with the asymmetric PCR product of stx2 gene. The time courses for the probes PBST20 and PBST21 with the positive sample were also obviously different from those with the negative sample. The polarization values of the former were higher than the latter in 1 4 min and reached saturation faster than the latter. Nevertheless, hybridization of these probes was not completed faster than as that of PBST10 or PBST11 in Fig. (1).

Fig. (2). Time courses of polarization of the probe DNAs for stx2 gene. Probes: PBST20 and PBST21 complementary to stx2 gene. Samples: stx2-gene positive and negative samples. To distinguish a group of data clearly, they are connected by simple straight lines.

3.2. Tm, G + C Content and the Rates of Nucleic Acid Hybridization Table 1 shows the melting temperature Tm, the G + C content and the time for hybridization to reach 90% completion, which was depicted as t90, for all the probe DNAs in this report. The values of t90 were simply calculated using the graphs of time course, which effectively show the rate of hybridization, although kh was more precisely defined in the previous report, using the curve fitting of time course data [4].

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Table 1.

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Tm, G + C Content and t90 for the DNA Probes

Probes

Tm /°C

G+C /%

t90 /sec

N /mers

PBST10 PBST11 PBST12

70.8 74.7 68.9

47.6 57.1 42.9

60 or less 60 or less 840 or more

21 21 21

PBST20 PBST21

72.8 78.7

52.4 66.7

180 480

21 21

Tm = 81.5 + 16.6(log10[Na+]) + 0.41(%G+C) - (600/N). [8] t90: the time for the hybridization to reach 90% of completion. N: chain length.

The table indicates that the t90 was short, typically 60 seconds or less, for the two probes PBST10 and PBST11. They were hybridized extremely rapidly with the amplified product DNA for stx1 of EHEC (Fig. 1). In the time courses of these two probes, t 90 could not be determined well, because the time resolution of the polarization measurement was not high enough, and in the same manner, kh could not be calculated. As far as I could see, such high rate of hybridization under the condition of high salt concentration (0.8 M NaCl; about five times higher than mammalian physiological concentrations) was originally reported in the paper [9], while temperature dependence of fluorescence anisotropy was observed in high time-resolution, using the selfcomplementary DNA decamer duplex [10]. For the interest, even under the optimized conditions of salt concentration and temperature (0.8 M NaCl, 46 °C), much variety was clearly observed in the rate of hybridization, when the probes with different sequences were hybridized with the same segment of stx1 or stx2 (Fig. 1 or 2). Moreover, the variety of t90 was regarded, independent of Tm or G + C content (Table 1). Therefore, t90 was considered strongly dependent on the nucleic acid sequences, rather than the binding energy of double helix, thus, t 90 would be varied according to a site or region of the individual amplified product of the genes. 3.3. Secondary Structures of the DNA Segments of Shiga Toxin Genes and the Rapidity of Probe Hybridization Figures (3) and (4) show the samples which forecast the secondary structures for the single-stranded DNA segments of stx1 (228 base section) and stx2 (228 base section), where the calculation was executed at the specified minimum stacking length (MSL) of 6 and 7, respectively. In the figures, the binding sites of hybridization for the five probes, PBST10, PBST11, PBST12, PBST20 and PBST21, were shown by halftone screen. As for the binding sites of both PBST12 and PBST21, 3' terminus of the probes was overlapped with an end of the stacking parts with continuous 10 base pairs in the secondary structures for both stx1 and stx2 (Fig. 3 and Fig. 4). In contrast, the binding sites for PBST10, PBST11 and PBST20 were free, and there was no stacking part in the distance of 3 bases or less from their termini (Figs. 3 and 4).

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Fig. (3). A secondary structure model for the segment of stx1. Minimum stacking length: 6.

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Fig. (4). A secondary structure model for the segment of stx2. Minimum stacking length: 7.

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Here, it was thought that the slower hybridization of PBST12 and PBST21 than the other probes was related with the shapes in the secondary structures. The stacking parts especially with the continuous 10 base pairs shown in both structures would not get loose to a single strand smoothly, because they were stable in energy. Besides, the structural distortion in the vicinity of the stacking parts would be strong. Therefore, it was considered that it would take longer time for PBST12 and PBST21 to hybridize and that the hybridization rate for the probes would be slower (Table 1 in Section 3.2). 4. CONCLUSION Under the condition of high salt concentration (0.8 M NaCl), two probe DNAs were obtained that rapidly hybridized (less than 1 min) with the segment of Shiga toxin type 1 gene (stx1) for enterohemorrhagic Escherichia coli (EHEC). Variety of the rate of hybridization was observed to be independent of Tm or G + C content which could represent the binding energy of double helix, thus, the rate would be varied according to a site or region of the segment for stx1 or stx2. It was considered that one of the greatest reasons for the variety would be a kind of steric hindrance with the three-dimensional structure of the single-stranded gene segment, and that it would become easier to design the probe oligo-DNA if the prediction of high-order structure becomes more accurate. However, it should be noted that there is no method of clearly forecasting the three-dimensional structure of a segment of single-stranded nucleic acid in various solution conditions including salt concentration, pH and temperature in the present situation. The fluorescence polarization method described here has the characteristics that two or more different reactions such as nucleic acid hybridization and ligand-receptor reaction can be monitored almost at the same time in one series of measurement operation and, in the hybridization reaction, nucleic acid samples through different amplification methods and those without amplification can be measured at a time [9]. Thus, as applications of the research, high throughput detection or screening of nucleic acids may be proposed, preparing a combination of the high rate probes for hybridization. Recently, the soluble receptors which maintain sufficient activity in solution have been developed [11]. Screening of nucleic-acid or peptide ligands for receptors in vitro/solution may be also proposed, because the ligand-receptor reactions could be evaluated in solution under almost the same conditions of salt concentration and pH, with those of biological liquids using the receptors. ACKNOWLEDGEMENTS This study was performed in support by ASTL of Hiroshima and the Hiroshima City Institute of Public Health, Japan. ABBREVIATIONS EHEC

=

Enterohemorrhagic Escherichia coli

FPA

=

Fluorescence polarization analysis

kh

=

The rate constant for hybridization

MSL

=

Minimum stacking length

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PCR

=

Polymerase chain reaction

ss-DNA

=

Single-stranded DNA

ss-RNA

=

Single-stranded RNA

stx1

=

The gene of Shiga (Vero) toxin type 1

stx2

=

The gene of Shiga (Vero) toxin type 2

TE

=

10 mM Tris-HCl/1mM EDTA

t90

=

The time for hybridization to reach 90% of completion

Makoto Tsuruoka

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An Overview of High Throughput Screening at G Protein Coupled Receptors Richard M. Eglen* DiscoveRx Corp., 42501 Albrae St., Fremont, CA 94358, USA Abstract: Technologies used for high throughput screening (HTS) at G protein coupled receptors (GPCRs) comprise two major approaches; those generally conducted measuring signal intensity changes using a microtiter plate format, and those measuring cellular protein redistribution via imaging-based analysis systems. Several homogeneous assays, i.e. those without wash and fluid phase separation steps, measure changes of second messenger signaling molecules including cAMP, Ins P3 and calcium. Imaging based assays determined the translocation of GPCR associated proteins such as β arrestin, or internalization of the receptor labeled with fusion tags. Generally, the former assays are used in a primary screening campaign, whilst the latter are used in secondary screening and lead optimization. However, increasing use of automated confocal imaging systems and prevalence of modified cell lines has expanded use of protein redistribution assays. Finally, radiometric techniques are widely used, frequently to measure GPCR ligand binding, using a scintillation proximity assay format. In this paper, the various assay methods used for HTS at G protein coupled receptors are compared and contrasted.

G PROTEIN SCREENING

COUPLED

RECEPTORS

AND

HIGH

THROUGHPUT

G protein coupled receptors (GPCRs) are a proven class of targets for drug discovery and are frequent targets entering high throughput screening (HTS) laboratories. Modern HTS is a highly automated approach to compound identification using robotic, fluid dispensing systems and sensitive signal detection instruments [1]. Several assay techniques for GPCR screening employ non-radiometric assay platforms. Radiometric techniques dominate in assays in which ligand binding to the GPCR per se is measured, [2]. There is increased adoption of functional assays in which the effects of the activated GPCR on function are determined, with concomitant development and implementation of cell based assay technologies, and automated cell culture and dispensing [3]. Compounds active at GPCRs have therapeutic benefit in many diseases ranging from central nervous system disorders, including pain, schizophrenia and depression, and metabolic disorders, such as cancer, obesity or diabetes [5]. GPCRs are considered a highly ‘druggable’ class of proteins, with over 40% of marketed drugs (such as Zyprexa, Clarinex, Zantac and Zelnorm) acting to modulate their function. Interestingly, approximately 9% of global pharmaceutical sales are realized from drugs targeted *Corresponding author: Tel: 510 979 1415 x 103; Fax: 510 979 1650; E-mail: [email protected] Garry W. Caldwell / Atta-ur-Rahman / Barry A. Springer (Eds.) All rights reserved – © 2005 Bentham Science Publishers.

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against only 40-50 well-characterized GPCRs. As there are between 800-1000 genes in the human genome belonging to the GPCR superfamily, it is likely that many more GPCRs remain to be validated as drug targets. Furthermore, endogenous ligands have been identified for only 200 GPCRs, even though the human genome contains many more GPCR genes. When the sensory classes of GPCRs are excluded, many of the remaining GPCRs are ‘orphan’ in nature, in that no ligand or function is presently known. There is therefore, intense interest in identifying novel ligands for orphan GPCRs, both as potential therapeutics, or as pharmacological probes to refine physiological function [6]. The primary function of GPCRs is to transduce extracellular stimuli into intracellular signals. GPCRs are a large, diverse and highly conserved class of membrane-bound proteins. On the basis of homology with rhodopsin, they possess a single, serpentine, polypeptide chain with seven transmembrane helices, comprising of three extracellular loops and three intracellular loops. The amino terminal is located extracellularly, and the carboxy terminal intracellularly. GPCRs are divided into three broad classes, based upon the similarity of the transmembrane sequences and the nature of their ligands. Class 1 includes rhodopsin-like receptors, and the ligands that activate them are biogenic amines, chemokines, prostanoids, and neuropeptides. Class 2 includes secretin-like receptors, and are activated by ligands including secretin, parathyroid hormone, glucagon, calcitonin gene related peptide, adrenomedullin, calcitonin, etc. Class 3 includes metabotropic-glutamate-receptor-like and calcium sensing receptors [7]. Agonist binding to the GPCR promotes a conformational change in the protein, specifically an ionic interchange between the 3rd and 4th transmembrane domain. This induces coupling of the GPCR to the G protein, initiating signaling to the cell interior. Although a diverse protein class, the diversity of GPCR pathways activated in the cell is relatively small, and often involves modulation of two membrane bound enzymes, adenylyl cyclase and phospholipase C. GPCR signaling induces coupling of the liganded receptor to a heteromeric G protein. These are composed of α, β and γ subunits, also a diverse protein group, comprising 18 Gα, 5 Gβ and 11 Gγ subunits. The GPCR/G protein interaction accelerates exchange of guanosine triphosphate (GTP) for guanosine diphosphate (GDP) on the α subunit, leading to the dissociation of the complex from the βγ subunits. The free α or βγ subunits then interact with second messengers; the precise nature of which is dependent upon the GPCR subtype, and the G protein subunits mobilized [8]. GPCR coupling to Gαs and Gαi /o proteins activate or inhibit, respectively, adenylate cyclase, the enzyme responsible for converting adenosine triphosphate (ATP) to 3’ 5’ cAMP and inorganic pyrophosphate. cAMP then acts at several downstream targets including ion channels, kinases that modulate gene transcription and cell metabolism. GPCRs coupling to G αq/o proteins, alternatively, activate phosphoinositol phospholipase Cβ, which hydrolyzes phosphatidylinositol 4, 5 bisphosphate (PIP2) forming sn 1, 2 diacylglycerol and inositol 1, 4, 5 trisphosphate (Ins P3). Ins P3 binds and opens endoplasmic Ins P3 gated calcium channel, causing release of bound calcium into the cytosol. Metabolic products of Ins P3 also modulate cellular function including inositol (1, 3, 4, 5) P4 (Ins P4), which acts to facilitate Ins P3, mediating calcium release synergistically [8].

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In the presence of continued agonist activation of the GPCR, signaling is attenuated by a coordinated process of desensitization, inactivation and internalization occurs, resulting in GPCR phosphorylation by specific GPCR kinases (GRKs), and subsequent association with the adapter molecule, β arrestin. This complex then initiates the internalization and recycling processes of the receptor: ligand complex [9]. The protein, β arrestin, also facilitates formation of multimolecular complexes, and provides the means by which liganded GPCRs influence numerous cell pathways. By this means, GPCRs activate interconnected pathways, including those involving MAP kinases, nonreceptor tyrosine kinases, receptor tyrosine kinases, phosphatidylinositol 3-kinases, and JNKs [10]. In the context of assays for HTS, several aspects of GPCR signaling described above have been utilized in various assay formats. Thus, ligand binding, guanine nucleotide exchange, second messenger mobilization, ancillary protein recruitment and receptor internalization have all been used as the basis for HTS assays. In the present review, various high throughput approaches for GPCR screening are assessed and are summarized in Table (1). Several reviews on this subject have been published, and the reader is referred to these for additional references [1-4]. Cellular Expression of GPCRs The cell background imposes phenotypic selectivity on GPCR ligand pharmacology [11], which implies that the cell type used to express the receptor for screening is critical. Phenotype-specific pharmacology arises from several causes. Firstly, several GPCRs, particularly those from classes 1 and 3, form dimers or higher order oligomers at the plasmamembrane. Although GPCRs dimerize early in the synthetic pathway, the addition of agonists or antagonists influences formation of higher order oligomers [12]. It is now evident that GPCR oligomer formation depends on both the cell type, as well as the ligand. [13] Secondly, ancillary proteins expressed in the cell also modulate receptor function, and therefore, ligand pharmacology. Specifically, GPCRs interact with several transmembrane and soluble proteins, collectively termed GPCR-interacting proteins or GIPs. These GIP complexes couple to the carboxy terminal of the receptor, linking GPCR activation to a diverse network of pathways termed ‘receptorsomes’; the co-localization of which provides defined spatial and temporal motifs that are highly cell dependent [14]. One example of the effect of such ancillary proteins are the RAMP (receptor activity modifying proteins) class of proteins, the nature of which determines the level and pharmacology of GPCR activity. Thirdly, the cell phenotype influences the action of allosteric GPCRs ligands. Such ligands, in contrast to surmountable agonists and antagonists, act at sites additional to the ligand binding site on the GPCR. They thus modulate receptor function, while maintaining important temporal aspects of cell signaling [15]. Allosteric ligands can have high selectivity between GPCR subtypes, and may even exert actions in their own right by modulating constitutive receptor activity. Since neither all allosteric ligands block receptors similarly, nor all agonists are blocked equally, the allosteric function of the GPCR ligand also varies according to the cellular phenotype [15]. Overall, compound efficacy, previously considered to be an exclusive property of GPCR and its ligand, is now also an essential property of the cell or tissue in which the receptor is expressed [16]. These considerations highlight the importance of the choice of cell for use in screening of novel GPCR ligands. Furthermore, the ability of the phenotype to modulate cell function specifically provides a level of complexity to the

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pharmacology of the ligand being screened. This is one of the reasons why cell based functional assays have increased in use in HTS campaigns. Table 1.

Comparison of Various Approaches Used in GPCR Functional Assays (Adapted from Ref. 3)

Assay type

Gq coupled receptors

Gi or Gs coupled receptors

Reporter genes

Protein redistribution

Receptor internalization

Technique

Changes in intracellular calcium

Changes in intracellular cAMP

Changes in NFAT (calcium signaling) or CRE (cAMP signaling) reporter gene activity

β arrestin redistribution

Internalization of CypHer dyeGPCR epitope tags

Highly sensitive Highly sensitive automated automated screening system to screening system to detect agonists and detect agonists and antagonists. antagonists.

Highly sensitive and Automatable screening systems

Many GPCRs induce arrestin translocation upon activation including several orphans

Allows measurement of ligand induced internalization

Advantages

Allows use of promiscuous G proteins to couple to PLC or chimeric GPCRs and G protein constructs

Detect elevations in basal cAMP due to constitutive activity

Disadvantages No changes in basal Only detects Gs and levels in Gi coupled intracellular GPCRs calcium with constitutive activity. Difficult to detect inverse agonists. Need to assess agonist efficacy and potential changes in agonist pharmacology

Generic screening system for agonists and antagonists

Downstream from ligand activation and requires prolonged incubation with GPCR ligands, results in many false positives.

Cells require over expression of both the GPCR and β arrestin Modification of the carboxy termini may influence ligand pharmacology.

Can detect constitutive internalization

Requires the use of epitope tagged GPCRs and internalization of antibody / receptor complex.

Extensive amounts of data generated during screening campaigns.

Most GPCR HTS assays employ non-recombinant or recombinant stable cell lines, as opposed to native tissues, partly due to the need for a large number of clonal cells of constant phenotype in the screen. Several non-recombinant cells have the major advantage that they endogenously express GPCRs, presumably in a background appropriate to expression and function of the receptor. However, the endogenous GPCR expression levels are often too low to be successfully used in ligand binding assays, and sensitive functional assays remain the only viable option for their use in HTS. Recombinant cells, alternatively, can be constructed to express specific GPCRs in mammalian systems, such as HEK (human embryonic kidney) or CHO (chinese hamster ovary) cells. Here, the high expression levels are easily adjusted, particularly when using

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plasmid expression vectors harboring viral promoters. Typically, these promoters are derived from cytomegalovirus virus (CMV) or Rous sarcoma virus (RSV), and contain antibiotic resistant genes allowing for detection of positively transfected clones. Mammalian bicistronic expression vectors are often used with the advantage that there is two open reading frames from one mRNA. In some cases, particularly where cell membranes may be used in a binding assay, the GPCR is transiently expressed. This increases the speed at which cells are produced for the screen, but allows receptors to be expressed at similar levels, facilitating easier comparison between multiple receptors. In instances where very large numbers of cells are needed as in, for example, a large cell based HTS campaign, stably transfected cells are preferred. The high expression levels of GPCRs are also optimized for several HTS assay formats, including both membrane binding and cellular functional studies. Very high level of expression of GPCRs can be attained using Baculovirus-insect expression systems. Currently, recombinant baculoviruses, where the insect cell specific promoter is replaced with a mammalian cell active expression cassette, provide very efficient gene delivery in many mammalian cell types [17]. A recent report [18] has shown simultaneous expression of multiple GPCR genes in HEK 293 or U-2 OS osteosarcoma cells, using a GPCR and a G protein chimera, coupling the receptor to a calcium response. Similar observations have been shown in Sf 9 cells, using co expression of GPCRs with the promiscuous Gα16 subunit and a luminescent protein aequorin [18]. High levels of receptor expression, such as baculoviral recombinant techniques, also render them very useful for isolation of membranes for use in binding studies, enhancing the specific binding of the ligand. However, when such membranes are used in low assay volumes, ligand depletion may occur that will complicate analysis. Indeed, membrane binding assays may yield different pharmacological data than that derived from binding studies with whole cells, particularly since inverse agonists bind more slowly and with lower affinity to GPCRs. This can cause the membrane-based assay to miss compounds acting in this manner; an issue of high relevance, when the screen is directed at finding inverse agonists at constitutively active orphan GPCRs [11]. HIGH THROUGHPUT LIGAND BINDING ASSAYS Measurement of GPCR Ligand Binding Radioisotopic labeling of GPCR ligands are widely employed in GPCR screening and utilize three general approaches [19] Firstly, saturation experiments in which the affinity of the radioligand is determined, secondly, inhibition studies in which the affinity of a competing unlabeled compound is measured and thirdly, kinetic experiments in which the association or dissociation rates of the radioligand are defined [19]. Radioligand binding assays use [3H] or [125I] isotopes incorporated into ligands which are then used in low, tracer, concentrations, to monitor specific binding. A competition displacement format is often used in HTS, involving a fixed concentration of radioligand, and its displacement from the GPCR by the library compound. Historically, this approach has utilized wash and filtration procedures to separate the bound ligand from the unbound material, with the residual activity measured by liquid scintillation spectrometry. This approach has the advantage that it is very quantitative in terms of ligand pharmacology, and widespread adoption of the technique over the years has resulted in the broad commercial availability of radioligands for several GPCRs. The

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need to minimize filtration and resultant radioactive waste has also driven adoption of a scintillation proximity assay (SPA) format. In an SPA assay, radiolabeled molecules binding to the GPCR membrane preparation activate the scintillating beads, triggering red or blue light emission. Several polystyrene beads, optimized for HTS are available such that non-specific ligand binding is reduced. These include beads with a yttrium core covered by hydrophilic coatings, or those with Wheat germ agglutinin covalently attached to the bead surface, enhancing capture cell membranes and further reducing non specific binding [20]. A limited number of non-isotopic approaches have been developed for GPCR ligand binding assays, the majority of which employ fluorescence polarization (FP) detection. GPCR ligands labeled with fluorescent dyes, such as fluorescein or BODIPY TMR, have been used to determine binding to GPCRs via FP detection. FP is the ratio of fluorescence emissions in the vertical and horizontal planes. When fluorescent molecules are excited with polarized light, the degree to which the emitted light retains polarization, reflects the rotation that the molecule underwent between excitation and emission. Small molecules rotate rapidly, and emitted light is random with respect to the plane of emission. When bound to a large protein (such as a GPCR), the ligand rotates slowly, and the emitted light retains more of its polarization, which is measured as an increase in FP. The extent of polarization increase is linearly dependent on the extent of binding [21]. FP assays, apart from eliminating radioactivity, are homogeneous, allowing for a real-time, continuous readout of binding activity [22]. However, the approach requires the use of amounts of cell membrane or high levels of expression of GPCRs than those generally required for radioligand binding protocols [23]. Moreover, FP based assays, with few exception, are mostly restricted to peptidergic GPCR ligands, in contrast to the wide variety of isotopically labeled ligands. Fluorescence intensity distribution analysis (FIDA) allows single molecule detection that is sensitive to changes in intensity, which occurs when fluorescent ligands bind to membranes. Indeed, the approach appears to require lower GPCR expression levels than FP. When used in a confocal mode, FIDA allows the use of extremely low assay volumes to approach those volumes used in ultraHTS [24, 25]. Measurement of Guanine Nucleotide Binding GPCR binding assays do not easily differentiate between those compounds that bind and activate the receptor (agonists), from those that bind and occlude the receptor, preventing subsequent activation (antagonists). A radiometric binding approach used assesses GPCR activation measures of guanine nucleotide binding to the liganded GPCR [19, 26]. Agonist binding to GPCRs promotes the exchange of GDP for GTP at the a subunit of heterotrimeric GTP binding proteins (G proteins). Poorly hydrolysable GTP analogs, such as GTPγS, or its isotopic analog, [35S] GTPγS, are used, to monitor the agonist-dependent activation of G proteins in membranes from cells expressing GPCRs. This technique has been widely used over the years, and a fully automated SPA assay using this technique was reported using GPCRs coupled to Gαi subunit [27, 28]. Moreover, the use of GPCR-G protein fusion proteins, expressed as bifunctional polypeptides allow [35S] GTPγS binding assays to be developed that explore the extent of GPCR oligomerization. When used with complementary pairs of non-functional mutants that reconstitute function when co-expressed, studies can be designed that discriminate between homo and heterodimerization [29].

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Three different approaches enable measurement of [35S] GTPγS binding to specific Gα-subunit families: (i) co expression of G proteins and receptors in Sf9 insect cells; (ii) construction of GPCR-Gα fusions in cells; (iii) immuno-capture techniques. Immunocapture methods, notably, do not require cell engineering for co expression of receptors and G proteins or the creation of fusion constructs. De Lapp has recently reviewed a technique combining immunocapture with SPA technology [30]. This method is easily automated and allows analysis of agonist, partial agonist, antagonist and inverse agonist activity at the level of specific interactions between GPCRs and Gα subunits. However, the productivity of antibody-capture SPA requires the use of large amounts of diluted antibody for 96-well plate incubations, making antibody considerably costly [30]. The identification of non radiometric alternatives to [35S] GTPγS is difficult, principally due to problems of incorporating a detectable label that does not impair G protein binding [31]. A time resolved fluorometric GTP-binding assay has been described, using a GTP analog labeled with a Europium chelate, followed by a filtration washing step [32]. Currently, however, there are few reports in the literature, relating to the use of the technique in HTS. GTP binding assays in general, provide only data at discrete intervals and are not always able to resolve the rapid kinetics of heterotrimeric G-protein signaling applications. Real time, fluorescence-based analyses of G protein and RGS-protein signaling offer some advantages in this regard. Currently, the most important fluorescence-based assay uses BODIPY-FL-GTPδS. Upon binding Gδ protein BODIPY-FL-GTPδS exhibits up to a six-fold increase in fluorescence emission at 510 nm, following excitation at 490 nm [33]. HIGH THROUGHPUT FUNCTIONAL ASSAYS In the last decade, the use of cell based assays to analyze GPCR ligands interactions has accelerated [34]. Although isotopically based techniques to measure ligand binding are still widely used (see above), numerous cell based assays are now in mainstream HTS use [35]. Measurement of liganded GPCR effects on cell function, as opposed to binding per se, permits characterization of compounds that modulate receptor activity in the cell environment. Thus, novel agonists are easily discerned from antagonists. Moreover, agents acting on GPCRs by other mechanisms, such as allosteric regulators or G protein activators, can be easily identified. These functional modulators, collectively, are difficult to characterize using binding methods alone [36]. Functional GPCR assays are also a prerequisite for the identification of endogenous or synthetic ligands for orphan GPCRs [1], including those compounds acting as inverse agonists to reduce constitutive G protein coupling [38]. Functional GPCR platforms typically utilize either reporter gene approaches, or assays monitoring the mobilization of cAMP or intracellular calcium [4]. In high throughput screening, all these approaches need to be amenable to automated fluid handling, scalable to different fluid volumes for use in high density microtiter plate formats, and generate a signal, generally free from artifactual interference. Since wash and separation steps are an impediment to automated fluid dispensing, HTS functional assays also require protocols to be homogenous. Reporter Gene Assays to Measure GPCR Function GPCR activation is well known to alter gene transcription [4]. Several genes contain responsive elements to second messengers, mobilized by GPCRs that can modulate gene

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expression, providing the basis for reporter gene assays [4]. In reporter gene assays, GPCR signal transduction is monitored using expression systems engineered with cisacting enhancer elements, DNA sequence motifs targeted by binding partners promoting gene expression and upstream of a reporter gene. These include β lactamase [39], β galactosidase, luciferase [40] and green fluorescent protein (GFP) [41]. GPCR signaling via changes in cAMP are assayed using the CRE (cAMP response element) enhancer of gene expression, while GPCRs coupled to changes in calcium utilize the calciumsensitive AP1 (activator protein 1) or NFAT (nuclear factor of activated T cells) elements [39]. The principal advantages of reporter gene assays are the wide linearity and sensitivity of the technique, making them very suitable for detection of weak GPCR agonists, or allosteric modulators. Reporter gene assays can also be used in the extremely low assay volumes used for 1536 or 3456 microtiter plate assay formats [4, 39]. However, the potential for false positives in the assay, arising from ‘off target’ actions of library compound on gene transcription during prolonged incubation times, necessitates the use of numerous controls or follow up assays. Second Messenger Assays to Measure GPCR Function Measurement of GPCR second messengers usually involves assays to determine accumulation of cAMP [41] or calcium [42]. Intracellular changes in these second messengers are undertaken in either the broken cells following lysis or in intact cells using cell-penetrant dyes, respectively. Although spatial information is lost in such ‘end point’ protocols, in contrast to the imaging based assays (see below), assays of this type provide highly quantitative pharmacological information on ligands that modulate the GPCR function. Data, such as this, is important in defining the action of the novel compound and thus, the structure activity relationships of a chemical series [43]. Accumulation of 3’ 5’ cAMP Cyclic AMP, specifically 3’ 5’ cyclic AMP, plays an important role in many signal transduction pathways. Consequently, the intracellular levels of cAMP are tightly regulated via the activity of the adenylyl cyclase enzyme family, some of which can be activated or inhibited by G proteins subunits, mobilized by GPCR activation. Changes in the intracellular cAMP levels correlate with GPCR activation and measurement of cAMP levels, a simple functional assay for GPCR screening. There are several assays for the measurement of cAMP, including those in which the accumulation of cAMP is assessed in a homogenous assay format. These have been reviewed in detail [41] and for the sake of brevity, will not be further discussed in the present review. However, one that aspect was highlighted, is based upon β galactosidase (β Gal) enzyme fragment complementation (EFC) [44, 45]. β Gal is an enzyme extensively used in cellular biology as a biological reporter. EFC occurs, when fragments of β gal complement in trans by intracistronic combination to form active enzyme [46, 47]. The commercial availability of numerous β gal substrates enables colorimetric, fluorescent or chemilumescent signals to be generated. In a competitive immunoassay approach, β gal EFC is now widely used for high throughput detection of cAMP [41]. Here, cAMP is chemically conjugated to a small (~5Kd) peptide fragment derived from the β gal α peptide. This conjugate complements to an inactive β gal ω peptide forming active enzyme. Steric hindrance of EFC occurs when

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an antibody is added to the assay that binds conjugated cAMP, such that little or no active β gal is formed. However, free cAMP generated by the cell competitively displaces the conjugated nucleotide from the antibody, allowing it to freely complement and thus generating a signal. Accumulation of Inositol Phospholipids Assessment of Gq coupled GPCRs, is undertaken by measurement of changes in phosphoinositide phospholipase C activity. This is often done by measuring turnover of the inositol phospholipids cycle [48], using tritiated inositol incorporated. Activation of the GPCR, increases the incorporation of the radioactive inositol in the presence of lithium. This ion uncompetitively blocks inositol monophosphate phosphatase, thereby abrogating the cycle and increasing accumulation of the tritiated isotope at the monophosphate form [48]. This approach has been recently used in conjunction with immobilized metal ion affinity and SPA techniques, to provide a homogenous platform suitable for HTS automation [49, 50]. The measurement of the second messenger, Ins P3 specifically, is undertaken differently, using mass assays with GLC (gas liquid chromatography), anion exchange chromatography or HPLC. These techniques, while sensitive, are not adaptable to assays requiring high throughput. The recognition that Ins P3 binds to a specific intracellular receptor provides the basis for a radiometric competition-binding assay. Here, [3H] labeled Ins P3 is displaced from a crude preparation of the Ins P3 receptor, using a competition radioligand binding protocol [51]. This format, again when used with SPA, is high throughput [52], but the economics of isotopic waste disposal emanating from high volume screening, remains a significant issue. A non-isotopic assay for Ins P3 is now available using the ALPHAscreen technology [53]. This technique is an amplified luminescence assay that employs a donor and acceptor bead. When the donor bead is excited with light at 680nm, a photosensitizer coverts O 2 to single oxygen. When two beads are in close proximity, the single oxygen produces a chemiluminescent signal in the acceptor bead, activating bead fluorophores and amplifying the signal. In an Ins P3 assay, the two beads are held in close proximity by a biotinylated Ins P3 molecule, as the donor bead is coated with streptavidin, and the acceptor bead is coated with an Ins P 3 binding protein. In the absence of cell stimulation, a signal is seen. In the presence of free Ins P 3 from the cell, the donor and acceptor beads dissociate and the signal proportionally decreases [53]. Despite the advantage of ALPHAscreen approach as a non-isotopic homogeneous assay technology, the signal can be sensitive to compound quenching and ambient fluctuations in light and temperature. The ALPHAscreen Ins P3 assay is also limited in the number of cells per well, as matrix interferences from cell lysates reduce the signal. Echelon Biosciences have recently utilized the ALPHAscreen assay format, using a binding protein that binds several inositol phosphates, including IP2 and IP4. These cellular metabolites compete with a biotinylated inositol phosphate analog as described above [54]. This assay has an advantage that it detects several phosphoinositols, resulting in slower kinetics and an assay that is more easily automated. However, an extensive evaluation in HTS screens has not been reported to date. A novel assay has been developed at DiscoveRx Corp to measure Ins P3, which uses a fluorescent polarization format. The Ins P3 assay is a competitive binding assay, in

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which cellular Ins P3 displaces a fluorescent derivative of Ins P3 from a specific binding protein. The assay measures changes in fluorescence polarization (FP), a single wavelength ratiometric technique, in which a fluorescent derivative of Ins P3 is used as a tracer. The FP Ins P 3 assay is performed in crude cell lysates, thereby avoiding laborious separation and filtration steps. It is therefore important that the Ins P3 binding protein exhibits high affinity and selectivity for the D-myo-1, 4, 5-inositol-Ins P3 isomer, over other inositol polyphosphates. The buffer used in the Ins P3 assay is optimized to ensure high affinity binding, and competition binding studies with several substituted inositol phosphates demonstrate that the Ins P3 binding protein is specific for the D-myo inositol 1, 4, 5 Ins P3 isomer. Accumulation of Calcium Measuring changes in intracellular calcium, mobilized by GPCR activation, provide a highly sensitive assay technique to measure ligand function. [55] Platforms such as the fluorometric imaging plate reader (FLIPR) or functional drug screening system (FDSS) are used with dyes compatible with HTS applications, generally the fluorescent calcium sensitive dyes, Fluo-3, Fluo-4 or Calcium 3 [56, 57]. When bound to calcium, enhancements of 5-10 fold are seen between the resting cytosolic calcium levels and those induced by GPCR activation. Real time changes in the GPCR induced calcium transient signal are then determined in microtiter plate using the imaging instruments above. Recently, the assay using the FLIPR has now been miniaturized to a 1536 well format, reducing the cost of such assays [58]. The sensitivity of the technique is such that functional studies using calcium transients are often undertaken in cells endogenously expressing the GPCR of interest. Alternatively, the technique can also be adapted to cell lines engineered to over express both the GPCR and promiscuous calcium coupling G-protein Gα15/16 [59, 60]. Other studies have been conducted using Gαq proteins modified with the C-terminal amino acids, replaced with that from Gαi/o, or Gαs. The substitution permits appropriate receptor/G-protein recognition, and measurement of the functional response via calcium mobilization [61]. A promiscuous G αq subunit, lacking the highly conserved six amino acids amino terminal extension, yet possessing four residues of the Gαi sequence has also been reported [61]. This sequence is both palmitoylated and myristolylated, resulting in a G protein that specifically targets the plasmamembrane [61]. When co expressed with the GPCR, the functional responses of GPCRs are enhanced, increasing the sensitivity of the assay. Although measuring calcium transients is an important HTS technique, the protocols can be time consuming, particularly, when the experimental parameters must be varied from cell to cell. Furthermore, calcium is a second messenger downstream from Gαq coupled GPCR induced activation of PLC. Some compounds in the screening library may modulate intracellular calcium levels by means other than binding to the receptor; or may alter dye fluorescence, resulting in false positive or negative hits. Consequently, HTS platforms using the calcium sensitive bioluminescent protein, aequorin, have been developed [62, 63]. The approach utilizes the calcium ion binding property of the protein, causing in oxidation of the substrate, coelenterazine, with concomitant light emission. However, the approach requires a pre-incubation period of between four hours at room temperature or 18 hours at 4°C, prior to the addition of test compounds. The length of the incubation may also depend on the cell line and GPCR type.

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PROTEIN REDISTRIBUTION ASSAYS Measurement translocation of GPCR and/or associated proteins employ clonal cells expressing the GPCR of interest, labeled with a suitable fluorescent protein. Activation of the receptor causes redistribution of the label, which is monitored by automated confocal systems and analyzed by imaging algorithms [64]. Analogous experiments are undertaken in fixed cells, in which the proteins are visualized by immunostaining techniques. Here, antibodies are used that recognize either the native protein or an epitope tag fused to the protein. In either of these assays approaches, spatial information on the proteins after pathway activation is derived, and in the case of intact cell studies, temporal data may also obtained [64]. Direct visualization of GPCR internalization, a ubiquitous property of GPCRs, occurs as part of the processes of receptor desensitization and inactivation [7]. The technique is facilitated by tagging the receptor with a fluorescent biomarker, generally, green fluorescent protein (GFP) [65]. Upon agonist activation, the GPCR-GFP fusion protein moves from the plasma membrane to internalized recycling compartments, forming intense bright spots [65]. Automated image capture and quantification of these trafficking events permits screening for both natural and surrogate receptor agonists [66]. Although a seemingly straightforward approach, issues are frequently presented including inappropriate targeting of the GPCR-GFP construct to the plasma membrane, and/or high levels of internalized receptor under basal conditions due to constitutive recycling. Furthermore, the pharmacological properties of a GPCR can be altered by the presence of a GFP-tag. Functional cell based GPCR assays also require labels attached to the GPCR or ancillary protein that do not affect function, yet possess sufficient sensitivity such that the GPCR is not required to be over expressed. Due to the relatively low quantal yield of fluorophores, the use of several fluorescent proteins is limited. Immunostaining procedures whilst sensitive, are highly dependent upon the quality of the antibodies used, and the immunostaining protocols can be lengthy and cumbersome for automation. A strategy focused on the internalization pathway, exploits the acidic nature of the endosomal recycling compartments [67]. The pH-sensitive cyanine dye CypHer 5 is non-fluorescent at pH 7.4 and brightly fluorescent in acidic environments. This approach utilizes a small amino-terminal epitope tag on the GPCR, recognized by a CypHer 5 conjugated antibody. Binding of the antibody to cell surface GPCRs fails to produce a fluorescence signal, and upon ligand-dependent internalization to endosomal compartments, intensely bright fluorescence spots of CypHer 5 are observed [67]. Monitoring cellular translocation of proteins participating in the GPCR desensitization/internalization cycle, specifically β arrestins has been developed as an assay format [68]. This approach monitors the change in distribution of a β-arrestin-GFP construct, from a diffuse intracellular localization to aggregated pit- like compartments, as a consequence of ligand-dependent internalization. Theoretically, the technique is applicable across GPCRs, and may overcome limitations associated with direct GPCR tagging [69]. Provided some degree of plasma membrane localization of the GPCR of interest is achieved, β arrestins translocation follows only those receptors committed towards the internalization pathway, offering a high signal-noise ratio [69]. β Arrestin translocation has also been monitored using bioluminescence energy transfer (BRET), in which a luciferase donor protein transfers energy to a green fluorescent protein [70]. In

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this assay, the green fluorescent protein is fused to arrestin and the GPCR to the luciferase, and translocation of the arrestin to the vicinity of the GPCR induces BRET and thus, a signal [70]. Indeed, biophysical techniques involving resonance energy transfer, namely FRET (fluorescence resonance energy transfer) or BRET enable monitoring of the formation of GPCR/protein complexes in living cells, in real-time [71]. Both FRET and BRET can be detected by microscopy, scanning spectroscopy or a suitable plate reader capable of sequential or simultaneous detection of filtered light emitted within two distinct wavelength windows. Microscopy is often used for detecting FRET, being most suitable for studies involving photobleaching. In contrast, microscopy is rarely used to detect BRET, with the majority of studies utilizing plate reading instrumentation. BRET assays have recently been modified using β arrestin mutants [71]. Here, the BRET2 signal is enhanced, using a phosphorylation independent mutant or β arrestin mutants deficient in their ability to interact with clathrin coated vesicles. Since both mutants, dissociate slowly from the GPCR, the BRET signal is enhanced, markedly improving the assay signal and allowing it to be adapted as an HTS tool. Alternatively, weakly interacting β Gal α and ω deletion mutants are fused to the interacting G protein: β arrestins. After enrichment by FACS analysis, clones are identified with low background expression of β Gal activity, but with a ligand dependent increase in enzyme activity, reflecting ligand induced association. Since the signal is generated by enzymatic amplification, over expression of labeled proteins is not necessary, and the cellular environment not grossly perturbed. Collectively, the approach appears suitable as an HTS system for detection of GPCR agonists or antagonists, and configured to perform in 384 well microtiter plates [72]. The assay exhibits agonist potencies similar to those detected in other GPCR assays and is capable of detecting receptor inhibitors with precision characteristics appropriate to HTS. OTHER GPCR SCREENING ASSAYS Melanophore cells derived from the neural crest of Xenopus laevis have been developed as a highly sensitive system for GPCR screening, since GPCR activation results in dispersion of the pigment melanin [73]. This occurs irrespective of whether adenylyl cyclase or phospholipase C is activated, whereas inhibition of activation results in aggregation, causing the cells to lighten in color. The sensitivity of the assay is such that in transiently expressed systems, constitutive activity of the GPCR can be determined, and the activity of inverse agonists readily determined. When use in conjunction with mutations of the GPCR that induce constitutive activity, such as the CART (constitutive active receptor technology) approach [74], it can provide a very simple means to assess novel ligands interacting at orphan GPCRs, as well as compounds that allosterically regulate GPCR activation. There are several other assay technologies now emerging for use in HTS at GPCRs. Although space limitations do not permit full evaluation of each, several are described for the sake of completeness. Cellular dielectric spectroscopy is a label free analysis system, in which changes in radio frequency spectrometry and bioimpedance exhibit a characteristic pattern when GPCRs are activated by an agonist. Potentially, this may provide a generic assay for GPCRs, without the need for chimeric or promiscuous G proteins and without the incorporation of radiometric of fluorometric detection systems. Other analytical techniques to measure ligand binding to membrane receptors such as acoustic, optical surface plasmon resonance biosensing, sedimentation, isothermal

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titration calorimetry and differential scanning calorimetry are now emerging. These have been recently reviewed by Cooper [76]. SUMMARY Functional analysis of GPCR responses is a common approach for high throughput screening of libraries of compounds. Measurement of second messengers (cAMP, Ins P3 or calcium) is readily achieved using homogeneous assays requiring neither radiometric techniques nor heterogeneous assay formats. Moreover, all these assays can be automated for robotic fluid dispensing. Other assay formats measure GPCR activation, using the redistribution of labeled protein, (β arrestin or receptor). These assays tend to have lower throughput and are applicable to many GPCR classes. Nonetheless, the ease and robustness of radioligand binding assays, as well as the limited non-radiometric alternatives, will ensure that isotopic techniques will also continue to be used. In practice, it is likely that a combination of all these HTS assay formats will be employed in compound identification, optimization and elucidation of mechanism of action. REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31]

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Lerner M.R. Trends. Neurosci 1994, 17, 142-146. Behan, D.P. Chalmers, D.T. Curr. Op. Drig. Disc. Devel., 2001, 4, 548-560. Cooper, M.A. J. Mol. Recog., 2004, 17, 286-315.

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Developments in Hyphenated Spectroscopic Methods in Natural Product Profiling Sylvia Urbana* and Frances Separovicb a

School of Applied Sciences (Applied Chemistry), RMIT University, GPO Box 2476V Melbourne VIC 3001, Australia and bSchool of Chemistry, The University of Melbourne, Parkville Melbourne VIC 3010, Australia Abstract: Overviews of the principal techniques that have found application in the profiling of natural products are given, including advances in capillary and column trapping LC-NMR-MS. Single hyphenated spectroscopic techniques, like LC-NMR and LC-MS, currently offer robust and efficient approaches for the rapid dereplication of natural product extracts. Multiple hyphenation techniques, such as (HP)LC-UV-NMR-MS-FTIR, now give an effective and comprehensive method for the deconvolution of complex mixtures. Ongoing improvements include miniaturization and cryogenic NMR probes and the hyphenation to capillary scale LC separations to analyse smaller quantities of samples. Extensions in hyphenation techniques required for natural product and other drug discovery programs include the need for LC-13C NMR and the combination of bioassays with already well-established hyphenated separationspectroscopic techniques, coupled with automated database searching capabilities (data libraries for LC, UV, NMR, MS and other search criteria).

INTRODUCTION Natural products have served as a major source of drugs for centuries with about half of the pharmaceuticals in use today derived from natural origins [1,2]. Nature is unrivalled in the ability to produce molecules of structural complexity and biological potency and the earth can be claimed to have been conducting its own combinatorial chemistry for thousands of years. Natural products continue to play a dominant role in the discovery of leads for the development of drugs for the treatment of human diseases. Much remains to be explored, particularly the marine and microbial environments, from which a host of novel bioactive chemical entities await discovery [3]. The search for new drugs from natural origins (either terrestrial or marine) involves screening of extracts for the presence of novel compounds and an investigation of their biological activities. Suspected novel or bioactive compounds are usually isolated in order to elucidate the structure and to perform further biological and toxicological testing. The path that leads from the intact terrestrial or marine organism to the pure constituents is long, involving work that might last from weeks to years. The general steps include: *Corresponding author: E-mail: [email protected] Garry W. Caldwell / Atta-ur-Rahman / Barry A. Springer (Eds.) All rights reserved – © 2005 Bentham Science Publishers.

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•

Collection of the marine or terrestrial organism(s)

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Identification or taxonomic classification of the species

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Review of the literature for any previous studies conducted on the species being targeted

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Extraction using different solvents

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Biological screening of the extract

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Purification of these extracts by different preparative and analytical chromatographic techniques, usually with a bioactivity-guided isolation strategy

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Structure elucidation of the constituents using a combination of various spectroscopic (UV-Vis, IR, 1H and 13C NMR, 2D NMR experiments, X-ray diffraction, and MS) and chemical methods

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Pharmacological and toxicological testing of compounds

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Synthesis or semi-synthesis of the bioactive natural product

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Synthesis of analogues with the aim of establishing Structure-Activity Relationships (SAR) and to produce more potent variants of the natural product

The characterisation of natural products in complex mixtures is aided by the application of sophisticated hyphenated spectroscopic techniques, which provide the necessary sensitivity and selectivity as well as structural information on the constituents of interest. Hyphenated techniques offer an efficient scheme for the chemical screening of extracts required to detect new leads, which potentially can be interesting from a chemical viewpoint. Recognition of natural products at the earliest possible stage of separation is also essential in order to avoid the time-consuming isolation of common constituents. With the introduction of High Throughput Screening (HTS) programmes, there is an even more urgent need for efficient and sensitive methodologies to give sufficient on-line information for metabolite structure determination. This review provides an outline of the range of hyphenated spectroscopic methods currently applied to the study of natural products as well as discussion of future advances in the field. Origin of Natural Products The use of natural substances, particularly plants, to control disease is an ancient practice that has led to the discovery of more than half of all “modern” pharmaceuticals [4]. Documentation of the use of natural substances for medicinal purposes can be found as far back as 78 A.D., when Dioscorides wrote “De Materia Medica”, describing thousands of medicinal plants [5]. Despite this knowledge, it was not until the early to mid 1800s when a number of important pharmacologically active natural products such as the cardiac glycosides and a variety of bioactive alkaloids (eg. morphine, atropine, reserpine and physostigmine) were discovered. Many of these biologically active natural products became important not only for their use directly as therapeutic agents or as prototype lead compounds for the development of new drugs, but also as biochemical probes to unravel the principles

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of human pharmacology [6]. We follow with an overview of some important terrestrial and marine natural products that have been discovered. Higher Plants Originally, plants were the almost exclusive therapy available to humans. With the development of medicinal chemistry in the early nineteenth century, plants were also the first source of substances to be developed as drugs. For a discussion of the potential of higher plants as a source of new drugs, see the reviews by Hostettmann and Wolfender [7-9]. Classical examples of drugs of plant origin include the antimalarial agent quinine from the bark of Cinchona officinalis (Rubiaceae), the analgesics codeine and morphine from Papaver sonniferum (Papaveraceae), atropine from Atropa belladonna and other Solanaceae species, and the cardiac glycoside digoxin from Digitalis sp. (Scrophulariaceae). Natural compounds have been particularly successful in the field of anticancer drug research. The bisindole alkaloids vinblastine and vincristine from the Madagascar periwinkle (Catharanthus roseus, Apocynaceae) were developed as effective anticancer drugs in the 1960s and are of great importance in the treatment of leukaemia. Further, a semi-synthetic derivative called vinorelbine was developed for the treatment of breast cancer. The diterpenoid paclitaxel, previously known as Taxol, was discovered as part of an NCI (National Cancer Institute, USA) sponsored program. Taxol was first isolated from the stem bark of the Pacific yew Taxus brevifolia (Taxaceae) in the late 1960s, but has since been found in other yew species such as the European yew T. baccata. Development of this product was approved by the FDA (Food Drug Administration) in 1992. Taxol was used for the treatment of ovarian cancer resistant to chemotherapy but its therapeutic applications have been applied in relation to other gynaecologic cancers. For many years the NCI has carried out a program whereby thousands of plant extracts are tested annually [10]. Some of the plant metabolites discovered in the NCI program for the treatment of AIDS include michellamine B from the West-African liana Ancistrocladus korupensis (Ancistrocladaceae), the coumarin derivative calanolide A from the African tropical rainforest tree Calophyllum lanigerum (Guttiferae), the phorbol ester prostratin obtained from Homolanthus nutans (Euphorbiaceae), which is a plant used in the traditional medicine of Samoan islands for treating yellow fever, and the naphthoquinone trimer conocurvone from the Australian shrub Conospermum incurvum (Proteaceae). In recent times, plant products have also played a role in the development of new antimalarial agents. An example is the discovery of artemisinin, a sesquiterpene lactone isolated in 1972 by Chinese scientists from qinghao (Artemisia annua, Asteraceae). This plant had been used for over 2000 years in China for the treatment of malaria. Artemisinin represented a completely new chemical class of antimalarial compounds, which showed high activity against resistant Plasmodium strains. Due to the high lipophilic nature of artemisinin, problems were encountered for its administration as a drug and consequently a series of derivatives were synthesised and are now licensed as drugs. The potential of higher plants as sources for new drugs is still largely unexplored. Among the estimated 400,000-500,000 plant species worldwide, only a small percentage

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has been investigated phytochemically and an even smaller fraction submitted to biological or pharmacological screening [11]. The rapid disappearance of tropical forests and other important vegetation areas means that it is essential to have access to methods for the rapid isolation and identification of bioactive natural products. In spite of the exponential development of synthetic pharmaceutical chemistry, including the use of combinatorial chemistry and microbial fermentation, over 25% of prescribed medicines in industrialised countries are derived directly or indirectly from plants [12]. This proportion can reach 50% for the over-the-counter market, which may include Chinese and naturopathy based products for self-administration. Micro-Organisms Antibiotics are among the most important classes of therapeutic agents and have had an enormous impact on both life expectancy and quality of life. With the discovery of the natural penicillins, secondary metabolites of species of the fungus Penicillium, the course of medical history was dramatically changed and the antibiotic era was born. Following Alexander Fleming’s observations in 1928 and the subsequent isolation and characterisation of the active constituent by Howard Florey and Ernst Chain, hundreds of antibiotics have been isolated from numerous micro-organisms [13]. Marine Organisms Marine natural products are commonly released by organisms as defence agents against predators. These agents are rapidly diluted and, therefore, need to be highly potent to have effect. Due to this and the immense biological diversity in the sea, it is increasingly being recognised that a huge number of natural products and unique chemical entities with novel biological activities exist in the oceans. Bioprospecting of marine natural products has yielded a considerable number of drug candidates [14]. Most of these molecules are still in preclinical or early clinical development but some, like cephalosporins, cytarabine (Ara-C) and vidarabine (Ara-A), are already on the market [15]. In a 2003 review, Haefnerin presented an update of the marine natural products and derivatives currently in clinical development [16]. Mechanisms of action for the compounds (eg. microtubule-interfering agents) were included along with their marine source, chemical class, disease area for treatment, clinical phase status and the pharmaceutical company developing the compound. Among the marine natural products and derivatives in advanced stages of preclinical development are the cone snail venoms, which act as selective peptide antagonists or agonists of ligand or voltage-gated ion channels and G-protein coupled receptors [17,18]. The high potency of these toxins, which are potentially lethal to humans, in the future may be turned to our advantage. Pharmacologists have been investigating the potential use of these toxins as adjuncts in anaesthesia, analgesics, or as drugs for the treatment of conditions such as epilepsy, cardiovascular disease and psychiatric disorders [18]. The bryostatins, which are a family of Protein Kinase C (PKC) inhibitors, were isolated from the bryozoan Bugula neritina and are currently undergoing trials for cancer treatment. Bryostatin-1 has been granted Orphan Drug Status by the FDA and has been designated an Orphan Medicinal Product in Europe for treatment of oesophageal cancer in combination with paclitaxel [19,20]. Of the many novel microtubule-interfering agents discovered in marine organisms, dolastatin 10, dolastatin 15, three derivatives and discodermolide have

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reached clinical development. Of the marine DNA-interactive compounds active in cytotoxicity screens, only ecteinascidin 743 (ET743, Yondelis), obtained from the colonial ascidian Ecteinascidia turbinata has gone into clinical development. ET743 was granted Orphan Medicinal Product designation by the European Agency for the Evaluation of Medicinal Products in 2001. Other marine natural product drug candidates in clinical development include APL (dehydrodidemnin B, Aplidin), from a tunicate Aplidium albicans, and kahalalide F, from the sea slug Elysia rufescens (but most probably is derived from Bryopsis sp., its green algal diet), both of which are candidates in clinical development at PharmaMar. Coproverdine, obtained from a New Zealand ascidian, is one of many examples that have just begun the long process of investigation as a bioactive anticancer lead compound, with an aim to either develop it or a related analogue into a potential drug candidate [21,22]. Some of the natural products isolated from marine invertebrates have been shown or are suspected to be of microbial origin. Marine micro-organisms, whose immense genetic and biochemical diversity is only beginning to be appreciated, are likely to become a rich source of novel chemical entities for the discovery of more effective drugs. In addition, the chemistries of insects and other terrestrial invertebrates are still relatively unexplored as drug discovery leads. Another area of interest is in the manipulation of plant genomes in an effort to express a host of natural products that have not been seen before. According to a recent survey by Newmann, Cragg and Snader of the NCI, 61% of the 877 small-molecule new chemical entities introduced as drugs worldwide during 19812002 can be traced to or were inspired by natural products [2]. These include natural products (6%), natural product derivatives (27%), synthetic compounds with natural product derived pharmacophores (5%) and synthetic compounds designed on the basis of knowledge gained from a natural product or a natural product mimic (23%) with the remaining 39% being of total synthetic origin, Fig. (1).

Fig. (1). Small-molecule new chemical entities introduced as worldwide drugs during the period 1981-2002.

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The component is higher in certain therapeutic areas, where 79% of antibacterials and 74% of anticancer compounds are natural products or have been derived from, or inspired by, a natural product, Fig. (1). These numbers are not surprising if we assume that natural products evolved for self-defence. The influence of natural products is significant even in therapeutic areas for which they might not seem directly relevant, such as cholesterol management, diabetes, arthritis and depression. When a new biologically active compound is discovered, it is still far from being accepted as an effective therapeutic agent. Natural product profiling is only the beginning of the drug discovery pipeline, which may last for years and also involves animal, clinical and toxicological testing. Presently, only one of 20,000 new molecules investigated by the pharmaceutical industry is estimated to reach the stage of commercialisation [23]. NATURAL PRODUCT PROFILING Bioactivity-Guided Isolation Strategy Since the 1980s, many of the active marine and terrestrial natural products undergoing investigation as drug candidates have been discovered using standard procedures involving biological screening followed by activity-guided fractionation. All fractions are biologically evaluated and those continuing to exhibit activity are carried through further isolation and purification steps until pure active compounds are obtained. The large numbers of pure compounds and natural product extracts generated require a rapid biological screening evaluation process. Specific biological screening, usually based on interaction with selected enzymes or receptors, is the approach known as High Throughput Screening (HTS), which relies heavily on robotics and automation, enabling routine evaluation of tens of thousands of samples. Subsequently, new assays using a specific target enzyme or receptor are rapidly developed and adapted for HTS which then makes it possible to rapidly screen very large libraries of compounds. These advancements have led to very short “turnovers” of about every 2-6 months of assays in industry, wherein a new assay is developed, the entire library is evaluated, another new assay developed, the library screened again and so on [6]. The growing interest in natural products is exemplified by the number of attempts by the pharmaceutical industry to introduce them into drug discovery programs. With the introduction of HTS strategies, there is a potential to test large numbers of natural product extracts in a wide variety of bioassays. Since organisms are able to synthesise and produce an unpredictable range of chemical skeletons and novel substances, it is of prime importance to evaluate as many natural products as possible in order to find sources of new drugs or lead compounds. One main strategy in the isolation of new leads consists of the so-called bioactivity-guided isolation, in which pharmacological or biological assays are used to target the isolation of bioactive compounds. A major drawback of the bioassay-guided fractionation strategy is the frequent isolation of previously described compounds. Chemical screening of crude extracts, therefore, constitutes an efficient complementary approach allowing localisation and targeted isolation of new types of compounds with potential bioactivity. This screening procedure also enables recognition of known metabolites at the earliest stage of

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separation, thus avoiding time consuming and expensive isolation of common constituents. A combination of chemical and biological screening is the fastest way to arrive at new lead compounds from biological sources. Relatively simple biological or pharmacological tests are needed in order to localise the particular activity of interest in the extract or in the numerous fractions resulting from the different purification steps. The assay also needs to be sensitive as the active substances may be present in the extract at low concentrations of assays. Chemical screening or the dereplication of crude natural product extracts can be achieved using a number of techniques such as bioautography, counter-current chromatography or by the use of various solid phase chromatography supports followed by HPLC and bioassays. Another method of dereplication is by spectroscopic techniques using either classical individual techniques like UV, MS and NMR or hyphenated techniques like LC-UV-DAD, LC-MS, LC-NMR and LC-NMR-MS. Dereplication Strategies for Natural Product Profiling Bioautography Bioautography combines TLC with a bioassay in situ and allows for the localisation of active constituents in an extract. Spore-producing fungi, such as Aspergillus, Penicillium and Cladosporium spp. can all be used as the target organisms in direct bioautographic procedures. In this method, a TLC plate is run and the solvent allowed to dry. The TLC plate is then sprayed with a mixture of the micro-organism and the nutrition medium. The plate is then incubated in a humid atmosphere and zones of inhibition appear where fungal growth is prevented by the active components of the extract. Direct bioautography is not possible with yeasts such as Candida albicans and thus a rapid agar overlay assay is used. Here an agar layer containing the micro-organism is spread over the TLC plate, enabling transfer of active compounds from the stationary phase into the agar by diffusion. After incubation the plate is sprayed with methylthiazoyltetrazolium chloride (MTT), which is converted into a purple MTT formazan dye by the yeast [7,8], for visualisation. An advantage of such TLC bioautographic methods is that bioactivities can be associated with specific spots on the plate. This simplifies the localisation of active compounds and helps with the design of subsequent isolation strategies. Counter-Current Chromatography Another method, which has been applied to the chemical dereplication of natural product extracts, is that of counter-current chromatography. Molecules present in natural product mixtures cover the whole spectrum of polarity and can vary in hydro- and lipophilicity, charge, solubility, stability and size. Counter-current chromatography operates under mild conditions preventing decomposition and denaturation of valuable components. The absence of solid supports rules out catalytic surface effects and irreversible binding of compounds. In addition, both normal and reversed-phase chromatography (dual mode) can be performed in a single run.

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In 2001, Alvi reported an integrated biological-physiochemical system for the identification of active compounds in fermentation broths. Preliminary fractionation of the microbial extract by dual-mode high-speed counter-current chromatography (HSCCC) was coupled with photodiode array (PDA) detection and bioassay [24]. Using Solid-Phase Cartridges and a Bioassay In the early 1990s the NCI published a chemical screening strategy for the dereplication and prioritization of HIV-inhibitory aqueous natural product extracts [25]. The NCI’s chemical screening protocol utilized various solid-phase extraction cartridges (C4, C18 and G25 respectively). By using these support packings, information on the relative polarity and molecular size and weight of the bioactive compound(s) of interest could be ascertained. The chemical screening procedure is simple, rapid and relatively inexpensive. In addition, the method is versatile whereby other phases can be added or substituted to expand or alter the elution matrix or fingerprint. For example, an additional cartridge containing polyamide resins [26] is utilised to screen plant extracts for tannins since polyphenolics have long been known to be irreversibly retained on polyamide resins, while compounds with fewer phenolic residues, such as flavonoids, can be eluted from polyamide gels with MeOH [27]. An ion exchange cartridge could be added to give information on whether the bioactive compound of interest is charged. The related concept of “chemical screening” was used previously and described by Hammann [28] and Zeeck [29] for secondary metabolites by means of functional groupor compound-class-specific TLC detection reagents. These methods are independent of biological activity or do not take biological activity into account. As already mentioned, a chemical screening protocol that is coupled to a bioassay is the most appropriate and efficient overall strategy for selection of priority extracts and targeting of potentially novel active chemical classes. Further developments in the NCI chemical screening protocol include HPLC analysis and microtitre plate collection of one of the bioactive solid phase cartridge fractions. From this master plate, daughter plates are created to submit for biological testing. Once active wells are identified, MS of the corresponding microtitre plate fractions is carried out on the master plate. These microtitre plate well positions represent regions of the HPLC chromatogram, which can be used to identify the region of bioactivity. The information gained from this chemical screening strategy aims to obtain the relative polarity, size and molecular weight of any bioactive compound, followed by UV chromophore information (from PDA detection on HPLC) and, finally, a possible molecular weight for the active natural product(s) present in the extract [Munro, 30. private communication]. Classical versus Hyphenated Dereplication Strategies In the search for new natural products, crude extracts are typically subjected to multistep work-up and isolation procedures, which include various separation methods (including HPLC, column, gel or counter-current chromatography), in order to obtain pure compounds whose structure is then elucidated by using off-line spectroscopic methods such as NMR and MS [31]. The characterisation of a natural product can be summarised by the information obtained from each of the individual spectroscopic techniques as detailed in Fig. (2). With the application of one or more of these individual techniques a dereplication by partial characterisation is possible.

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Fig. (2). Characterisation of a natural product by information obtained from individual spectroscopic techniques.

The combination of UV, MS and NMR spectroscopic data has often permitted unambiguous structure determination of pure constituents [21, 32-36]. Other techniques, such as IR or X-ray crystallography, have been used less often and mainly when the other spectroscopic methods failed to give complete structural assignment. As natural product extracts often contain a large number of closely related, and thus difficult to separate compounds, this classical approach may become very tedious and time-consuming. The direct hyphenation of an efficient separation technique with powerful spectroscopic methods has great potential in order to speed up the dereplication process. HPLC has been by far the most useful tool for the separation of complex mixtures of small molecules. Reversed-phase HPLC on octadecylsilane (ODS or C 18) has come to be recognised as the most broadly applicable of the bonded phases for this purpose. When

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interfaced with Diode Array Detection (DAD), HPLC allows an analyst to identify known compounds by comparison of their HPLC retention time and UV spectra. The advent of Electrospray Ionisation Mass Spectrometry (ESI-MS) has provided a MS interface, which is applicable to the analysis of a wide range of molecules and is compatible with liquid chromatography [37]. In the last ten years LC-MS has become a widely used tool for the dereplication of natural products [38-40]. LC-MS has become the dereplication tool of choice because the nominal molecular mass of a compound can be used as a search query in nearly all databases. Unfortunately, database searching using only the molecular mass frequently produces a large answer set and rarely results in a definitive identification. LC-MS is often combined in series with DAD thereby providing UV data to narrow down the answer set or sometimes a single answer. However, in many cases, more information is required for a confident identification. Advances in NMR methodology have allowed the direct interface of HPLC with NMR. NMR spectral data provide a great deal of structural information about a compound of interest. NMR is capable of discerning structural differences between compounds of the same molecular mass (isobars) or even the same molecular formula (isomers), with the ability to differentiate between constitutional and geometric isomers. The chemical screening of extracts using individual or hyphenated spectroscopic techniques generates a huge amount of information. In order to rationalise and use this approach efficiently with a high sample throughput, the challenge is to find a way to centralise the data for rapid pattern recognition by reference to standard compounds or databases. There are several commercially available natural product databases currently available, including Berdy Bioactive Natural Product Data Base, AntiBase, Dictionary of Natural Products by Chapman & Hall and the marine natural products database MarinLit. These databases can be used to primarily search by molecular weight, UV and taxonomic classification. Some databases, such as MarinLit, include the ability to search functional groups and NMR data. The combination of the LC-hyphenated techniques, LC-UV, LC-MS and LC-NMR, should ideally enable the complete structural characterisation of any natural product directly within an extract, providing that the corresponding LC peak is clearly resolved. In practise, however, this is not actually so and many factors may hinder on-line detection and structure determination of a natural product. Often only partial structure information will be obtained, but this data will already provide valuable information for targeting the isolation of new compounds or for the dereplication of known constituents. INTRODUCTION TO HYPHENATION The role of hyphenated spectroscopic techniques has played an important part in the dereplication of natural products. Hyphenation refers to the online combination of a separation technique, primarily Liquid Chromatography (LC) or Capillary Gas Chromatography (GC) and a spectroscopic detection method, which provides structural information of the analytes concerned [41]. LC-MS and GC-MS are the most popular hyphenated techniques in use today. Further to this, the use of LC-MS-MS, LC-NMR and, more recently, LC-NMR-MS has been rapidly increasing. A multi-hyphenated system, LC-UV-NMR-MS-FTIR, has also been successfully implemented [42,43]. The following sections describe the mechanism of operation of these and other hyphenated

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spectroscopic techniques, including examples of applications to natural product profiling. (HP)LC HYPHENATED WITH LC DETECTORS High Performance Liquid Chromatography (HPLC), as the best-suited technique for an efficient separation of crude extracts, is routinely used in natural product chemistry. Traditionally Reversed-Phase Liquid Chromatography (RPLC) has served as an effective technique for the separation of many of the components in complex natural product mixtures. The application of Normal-Phase Liquid Chromatography (NPLC) has been extremely limited due to problems associated with dissolving hydrophilic materials in nonaqueous mobile phases. HPLC can be coupled with different spectroscopic detection methods in order to obtain structural information on separated compounds. Although different types of LC detectors exist, such as UV, Refractive Index (RI), fluorescence, electrochemical, Evaporative Light Scattering Detector (ELSD), each method having its own specificity, none permits the detection of all the secondary metabolites encountered in a natural product extract within a single analysis. UV Detectors HPLC coupled with UV detection (LC-UV) has now been used for over two decades for screening natural product extracts and is widely used in many laboratories [44]. The UV spectra of natural products give useful information on the type of constituents and also, as in the case for polyphenols, information on the oxidation pattern. UV spectra of reference compounds or previously isolated bioactive compounds can be placed in a spectral library to create an “in-house” database. This allows known or commonly encountered natural products to be identified or dereplicated very early in a study. Diode Array Detectors UV(DAD) The single wavelength detector has long been replaced by the DAD or PDA detector for the analysis of natural product extracts. LC-UV(DAD) plays an important role in many research areas and, specifically, (RP)LC-UV(DAD) is a robust and user-friendly technique, which has become a tool of natural product chemists. LC-UV with Combined Use of UV Shift Reagents In order to determine the position of the hydroxyl groups on the polyphenol skeleton, LC-UV with the aid of post-column addition of UV shift reagents can be performed [45]. These UV reagents have been extensively used for the characterisation of pure constituents. In this method, extracts are first analysed by LC-UV-MS and then the separation is repeated five times by LC-UV(DAD), each time using another type of UV shift reagent. The procedure has been used for the characterisation of numerous xanthones and flavonol glycosides [45,46]. Refractive Index (RI) Detectors The RI detector is considered to be a universal detector and has been extensively applied to the isolation of natural products, but has “gone out of fashion” due to having

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less sensitivity compared to UV or UV(DAD) detectors and because RI detectors are not tolerant of gradient elutions by HPLC. Fluorescence and Electrochemical Detectors Both fluorescence and electrochemical detectors have gained least in their popularity since these approaches are restricted to compounds displaying native fluorescence or the presence of an electroactive group, thereby seriously limiting the applicable range of these techniques. This is particularly true when considering natural product extracts. Evaporative Light Scattering Detector (ELSD) The ELSD is a popular detection method for profiling of natural product extracts as it can be applied to compounds that contain no chromophore(s). ELSD is considered a universal detector, which can tolerate HPLC gradients and give a quantitative measure of constituents, but it is a destructive technique. (HP)LC HYPHENATION TECHNIQUES Over the years there have been three major HP(LC) hyphenated spectroscopic techniques that have found increasing use for natural product profiling: (HP)LC-FTIR, (HP)LC-MS and (HP)LC-NMR. (HP)LC-FTIR LC-FTIR systems can be either of the flow-cell or the solvent-elimination type [47]. LC flow-cell-FTIR is useful for the specific detection or recognition of functional groups in major constituents of mixtures but LC solvent elimination-FTIR is the more powerful technique. Until now, most LC-FTIR interfaces have been used only by their designers and so have not found wide application due to limitations in compatibility for optimised separation and detection conditions and the rather complicated interfacing that is required. Recently, FTIR has been incorporated into a multi-hyphenated system to give LC-UV-NMR-MS-FTIR (mentioned above). (HP)LC-MS Liquid chromatography combined with Mass Spectrometry (LC-MS) has advanced rapidly from early developments in the 1970s and is now a standard technique [48,49] for determining molecular weights and structures. There are many commercial systems available and the detection sensitivity can reach very low levels (e.g. ng-µg range is readily attainable). The coupling between LC and MS has not been straightforward since the normal operating conditions of a mass spectrometer (high vacuum, high temperatures, gas-phase operation and low flow rates) are diametrically opposed to those used in HPLC [50]. Hence, on-line coupling of the two techniques has been difficult and different LC-MS interfaces have been built, each with its own characteristics and range of applications. The four most common interfaces used for LC-MS of natural products include thermospray (TSP), continuous flow Fast Atom Bombardment (CF-FAB), Atmospheric Pressure Chemical Ionisation (APCI) and Electrospray Ionisation (ESI) [38]. TSP and APCI allow satisfactory ionisation of moderately polar compounds such as polyphenols

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or terpenoids in the mass range of 200-800 Da. For larger polar molecules, such as saponins (MW > 800 Da), CF-FAB or ESI are the methods of choice. All these LC-MS interfaces result in soft ionisation and useful fragment information is obtained by tandem mass spectrometry (MS-MS) or by multiple stage MS-MS experiments (MSn) on ion trap systems [51,52]. Hostettmann and co-workers report that high-resolution mass spectrometers, such as Q-TOF instruments, also have been used recently for the LC-MS analysis of crude plant extracts allowing on-line determination of accurate masses. Accurate MS-MS experiments were also recorded and the on-line molecular formula assignments of different plants were determined. LC-MS response is strongly dependant on the nature of the compounds to be analysed, the solvent and buffer used for the separation, the flow rate and the type of interface used. A natural product crude extract represents a complex mixture of metabolites having various physico-chemical properties, thus making it difficult to find LC-MS conditions that are optimum for the ionisation of all constituents. Often it will be necessary to analyse the extract under different ionisation conditions. However, the specific detection of given constituents can be performed at very low detection limits, provided that the correct ionisation method is used. For a comparison of different interfaces and ionisation conditions for the analysis of crude plant extracts, see Wolfender [38, 53-55]. Reversed-phase HPLC in combination with PDA and ESI-MS are the most important combinations for natural product extracts analysis due to the inherent diversity of compound classes present. For the more polar compounds, the use of hydrophilic interaction chromatography has been evaluated [56]. Some applications of (HP)LC-PDA-MS(ESI) include: the screening of annonaceous acetogenins in bioactive plant extracts [57]; the evaluation of Q-TOF and multiple stage ion-trap MS-MS for the dereplication of flavonoids and related compounds in crude plant extracts [58]; HTS of tocopherols [59]; and the characterisation of the asterosaponin fraction of the starfish Asterias rubens using a combination of matrixdispersion SPE and direct on-line LC-NMR-MS-MS [60]. Recent Advances An important development in ESI ionisation and interfacing is the production of low flow rate (<1 µL/min) devices. The main objectives of this are either a reduction in sample consumption or on-line coupling to low flow rate techniques such as capillary electrophoresis (CE) and nanocapillary LC. Although ESI and APCI are used in the majority of applications, two alternative API interfacing ionisation techniques have been proposed: sonic-spray ionisation interface and atmospheric pressure photoionisation (APPI). APPI is found to significantly extend the application to less polar compounds. Natural product extracts require both ESI and APCI analyses to be performed in order to have the widest applicability. A report by Niessen (2003) describes a recently proposed ESCI source [61]. The system enables scan-wise switching between ESI and APCI during LC-MS acquisition [62,63]. Multichannel Electrospray inlets as well as microfabricated microfluidic Electrospray devices have been proposed. Microchip-based separation techniques are expected to play an important role in future HTS strategies as are mass spectrometers capable of more accurate mass determination such as Fourier

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Transform Ion-Cyclotron Resonance Mass Spectrometry (FT-ICR-MS). Future interests propose to combine bioactivity screening in parallel with MS. Implementing Bioactivity Screening in LC-MS The on-line combination of MS characterisation and biological screening based on ligand-receptor or antigen-antibody interactions is an attractive application for natural product drug discovery. A number of on-line approaches have been reported including affinity Capillary Electrophoresis (CE) coupled to MS (CE-MS) [64], the use of on-line immunoaffinity extraction in combination with coupled column LC-MS-MS [65], and on-line monitoring of biospecific interactions in a homogeneous biochemical assay using ESI-MS [66]. A recent patent describes an invention that provides details for a structure dereplication process utilizing technology such as HPLC-PDA-MS coupled with high throughput bioassay data [67]. This method for generating, screening and dereplicating natural product libraries for the discovery of therapeutic agents was proposed by Unigen Pharmaceutical Incorporated (USA). A recent review by Niessen outlines the progress of LC-MS in HTS [61]. Flow NMR Flow NMR spectroscopy is increasingly being utilised in drug discovery and development [68-72]. LC-NMR has become a routine method to resolve and identify components in a mixture with broad applications in natural products, biochemistry and drug metabolism, and toxicological studies. Recently, Direct Injection (DI) NMR (DI-NMR), Flow Injection Analysis (FIA) NMR (FIA-NMR) and LC-NMR have been developed as ways to acquire NMR data without the use of the traditional precision-glass sample tubes. With DI-NMR and FIANMR techniques, robotic autosamplers and liquid handlers are interfaced to the NMR spectrometer. Samples in disposable vials and 96-well microtitre plates can be routinely analysed in this way by NMR. DI-NMR has been applied to the analysis of biofluids, combinatorial chemistry and protein/small molecule mixtures and, to some extent, natural product libraries. Flow NMR techniques can be classified into either of two categories. The first category subjects the sample to a separation technique, such as chromatography or capillary electrophoresis, before the NMR analysis (LC-NMR and CE-NMR). The second category uses the liquid flow simply as a means to transport the sample into the NMR analysis coil (DI-NMR and FIA-NMR). In the first category, since the NMR relies on the separation technique, this makes the NMR spectrometer a sophisticated chromatographic detector and is epitomized by techniques such as LC-NMR and LCNMR-MS. Hence, if the separation is not adequately performed, the NMR spectroscopy is of limited use. In the second category, NMR spectroscopy is the main rationale of the analysis and the liquid flow becomes a way to deliver the sample conveniently. The samples may have undergone chromatography before NMR analysis but not necessarily performed on-line. Techniques in this category include DI-NMR and FIA-NMR. The use of a stationary flow-cell has advantages over NMR tubes in that locking and shimming are more uniform from one sample to the next and the Radio Frequency (RF) coils for NMR can be placed closer to the sample (directly on the glass flow-cell

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surface), resulting in higher sensitivity. The use of NMR tubes can be circumvented, saving both money and time compared to a conventional NMR tube auto-changer. Automated Data Analysis Tools The ability to process and analyse the vast amounts of data generated through the application of flow NMR spectroscopy is a potential bottleneck to realising its full analytical capacity. This can result from the fast throughput already possible as well as the complex and information rich data generated from biochemical applications (e.g. metabonomics). There has been much development in data handling and interpretation methods, such as AMIX-Viewer and AMIX-Tools software packages (Bruker BioSpin) [73]. Acquired spectra can be coupled to spectral prediction programs, such as the software developed by Advanced Chemistry Development (ACD) Laboratories, either interactively or automatically. Such software is not only useful for generating organic structures from 1D (1H and 13C) data, but is useful for analysis of NMR data from combinatorial libraries. FIA-NMR FIA-NMR was first demonstrated in 1997 and described as ‘column-less LC-NMR’ [74-76]. The sample is injected as a plug into a fluid stream and swept into the NMR detector coil by the motion of the liquid. In FIA-NMR, no additional detectors (other than the NMR) are needed. FIA-NMR uses the mobile phase as a hydraulic push solvent, like a conveyer belt, to carry the injected sample from the injector port to the NMR flowcell. After the pump stops, the spectrometer acquires the scout scan, analyses it and acquires the signal-averaged data (using the Water suppression Enhanced through T1 effects (WET) solvent suppression technique). After completion, a start signal is sent to the solvent pump to flush the old sample from the NMR flow-cell and introduce the next sample. In classic FIA-NMR, as in LC-NMR, the sample always flows in one direction and enters and exits the NMR flow-cell through different ports. The flow-cell is always full of solvent. An interesting hybrid technique has been developed, called Bruker Efficient Sample Transfer (BEST)-NMR, which is referred to as an FIA technique even though it uses air bubbles to separate plugs of solvent but the air bubbles are usually removed just prior to the analysis. However, the combination of FIA with NMR is a relatively new unexplored technique. DI-NMR In contrast to FIA-NMR, DI-NMR injects the sample solution directly into the detector coil of the NMR probe and, since no other solvents are used, the sample, if desired, can then be recovered (without dilution). The DI-NMR injection process is typically performed with a robotic liquid handler, which is controlled by the NMR spectrometer. The advantage of using this kind of hardware for DI-NMR is that it allows the samples to be stored in disposable micotitre plates or vials instead of using the precision glass sample tubes of conventional solution-state NMR. An integrated system for running DI-NMR is commercially available and is known as the Versatile Automated Sample Transport (VAST) sample changer (Varian Inc.). These systems are normally capable of analysing samples ranging from 150-350 µL with concentrations ranging from one to 50 mM and which are stored in multiple 96-well

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microtitre plates. A typical analysis time may range from 2-7 min, depending upon the solvent viscosity and the sample concentration and volume. The sample is withdrawn from the flow probe in the same way as it entered into the flow probe and returned to either the original sample container or an alternative, or even flushed to waste. The probe is emptied completely and then rinsed in a similar manner in preparation for the next sample. Comparison of DI-NMR and FIA-NMR FIA-NMR and DI-NMR are essentially NMR spectrometers with sample changers that exploit the speed and robustness of flow NMR. Neither technique uses chromatography so are not designed to analyse mixtures. However, off-line HPLC microtitre plate analyses of natural product extracts can be evaluated using these techniques. FIA-NMR and DI-NMR have different advantages and disadvantages. Advantages of DI-NMR are higher signal-to-noise per sample and the consumption of less solvent. The disadvantages of DI-NMR are that a minimal sample volume is needed (if the sample volume is less than the NMR flow-cell, the line shape rapidly degrades) and the sample is not filtered. The advantages of FIA-NMR are that no minimal sample volume is required (since the flow-cell is always full), samples can be filtered (with an in-line filter) and the NMR probe can be rinsed. The disadvantages of FIA-NMR are a lower signal-to-noise (due to sample dilution) and that more solvent is consumed. Both techniques suffer from some degree of carry over and are subject to blockages from solid particles. FIA-NMR is more useful for repetitive analyses where there is sufficient sample and the sample can be discarded. In contrast, DI-NMR is more appropriate when there is a limited amount of sample and the sample must be recovered. (HP)LC-NMR HPLC coupled with NMR (LC-NMR) has taken time to become accepted due to initial high costs and lack of sensitivity. LC-NMR was developed in 1978 but, for the first 10-15 years, was regarded more as an academic curiosity rather than a robust analytical tool. Improvements in pulse field gradients, solvent suppression, probe technology and the construction of high field magnets have resulted in greater implemenation of LC-NMR instruments. The improved sensitivity has reached a point where LC-NMR is now well established [77,78]. Developments of LC-NMR during the mid 1980s to mid 1990s saw the technique evolve into an effective method for the structural analysis of complex mixtures of compounds [79]. The unique advantage of LC-NMR over other NMR techniques is in the ability to separate components within a sample in situ. If the component for analysis is unstable to light, air, time or the environment, LC-NMR will most probably be the preferred NMR technique and has the potential for on-line structure identification of natural products. NMR spectroscopy is the most powerful spectroscopic technique for obtaining detailed structural information about organic compounds in solution. LC coupling is straightforward compared to LC-MS, with the samples flowing in a non-rotating glass tube (usually 60-180 µL) connected at both ends with HPLC tubing. The main problem of LC-NMR is the difficulty of observing sample resonances in the presence of the much

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larger resonances of the mobile phase. This problem is even greater in the case of typical LC reversed-phase operating conditions, where more than one protonated solvent is used and when the signals change frequencies during a typical gradient HPLC analysis. These problems were overcome with the development of fast, reliable and powerful solvent suppression techniques such as the WET sequence [80]. In reversed-phase LC-NMR conditions, non-deuterated solvents such as methanol (MeOH) or acetonitrile (MeCN) can be used while water is replaced by deuterium oxide (D2O). High quality 1H NMR spectra can be recorded in two ways, namely using either the stop-flow or the on-flow modes, while two-dimensional (2D) NMR spectra can also be obtained in the stop-flow mode. HPLC Component of LC-NMR LC separations are classified as isocratic or gradient with isocratic elution employing a single unchanging mobile phase to separate analytes in a mixture. For more complex samples gradient elution, in which the mobile phase composition is systematically changed with time, is typically used for analysis. This change in solvent phase composition optimises the retention factor of individual analytes thus resulting in better and/or faster separation. As a result, gradient elution has become an integral part of LC separations, particularly for the analysis of natural product extracts. The full utility of gradient LC-NMR has been hindered due to deterioration of NMR spectra by solvent gradients. The changing mobile phase composition in gradient elution creates a solvent gradient across the NMR observe volume. Also, commonly used LC solvents possess different magnetic susceptibilities and, therefore, the solvent gradient causes significant changes in magnetic susceptibility and affects the magnetic field homogeneity. Consequently this can result in NMR line broadening, loss of coupling information, chemical shift changes and decrease in signal-to-noise. One way to reduce these effects is to perform stop-flow NMR so that constant solvent conditions are obtained. A similar method involves trapping of analyte bands inside the NMR coil and acquiring data after a suitable delay time to stabilise the gradient. Specifically designed flow-cells with appropriate length transfer lines can also be used to obtain high resolution NMR spectra with shallow solvent gradients (for example, a 1-3% change in solvent composition per minute) [81]. All these techniques result in longer analysis times. The use of pulse sequences based on solvent suppression has also been explored as an alternative method to remove the negative features of gradients [82]. A specific pulse sequence is required for each solvent system and gradient. Even minor changes in temperature and flow rate may result in inefficient solvent suppression and line broadening In an approach by Jayawickrama and co-workers (2003), two identical LC systems are used to deliver the gradient and reverse gradient, configured in such a way so that the solvent gradients are combined before the detector [81]. One LC delivers the separation gradient while the other delivers the exact reverse gradient to the post column connector. The two fluids are combined using nanoliter volume connectors and delivered to the NMR coil where, ideally, the solvent gradients reaching the NMR detector have a constant composition after mixing, irrespective of the initial solvent composition. The concept was validated using a FIA-NMR without the use of a column. NMR Component of LC-NMR A modern LC-NMR system consists of a high resolution NMR instrument (400-800 MHz) with a dedicated LC-NMR flow probe connected to an HPLC system, equipped

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with a valve or a loop collector for stop-flow experiments. The HPLC control unit is connected to the data acquisition system of the NMR for synchronisation of different operations. A sensitive detector, such as a UV, is usually coupled to the HPLC before the NMR via a stop-flow valve in order to trigger stop-flow measurements. The HPLC system is located at a distance of approximately 3 metres from the magnet, which is connected to the LC-NMR probe via a long capillary of polyetherketone (PEEK) with the smallest available internal diameter. The flow-cell consists of a non-rotating glass tube surrounded by the RF coil and connected at both ends with HPLC tubing. The homogeneity is acceptable in the small cell volumes of the flow probes because modern NMR methods reduce the requirement for spinning to optimise field homogeneity [83]. The use of relatively high volume flow probes may cause LC-peak broadening and loss of resolution. Hence, over the years, there has been a trend to reduce the volumes of LC-NMR detection cells. Volumes in the range of 200-500 µL normally used for 1H NMR have been reduced to 40-200 µL for higher field magnets [84]. NMR Flow Probe Design Conventional NMR flow-cells have an active volume of 60 µL and a total volume of 120 µL. This means that NMR will only “see” 60 µL of the chromatographic peak. If the flow rate in the HPLC is 1 mL/min, when 4.6 mm columns are used, only 3.6 seconds of the chromatographic peak will be “seen” by the NMR. One disadvantage of LC-NMR is that chromatographic peaks generally take more than 4 seconds to elute, so that the entire peak is not simultaneously detected by the NMR [85]. Synchronisation of both HPLC and NMR is needed, especially for performing accurate experiments in the stop-flow mode. Software integrating NMR and HPLC is available (VnmrJ software for Varian and integration of Hystar software and XWINNMR for Bruker) making full automation possible. There are several challenging aspects to acquiring LC-NMR data. Firstly, all mobile phases in LC-NMR are mixtures and the solvents are rarely fully deuterated. Usually several solvent resonances need to be suppressed in addition to the resonances of 13C satellites of organic solvents. Also, when the samples are flowing through the probe, solvent suppression sequences such as presaturation can take too long to run. These problems were solved with the development of the WET solvent suppression experiment [86]. Another challenge in LC-NMR is that by definition the solvent composition changes during the experiment. In reversed-phase LC-NMR one of the cosolvents is almost always water and the chemical shift of water changes as the solvent composition changes. Also, if the mobile phase is fully protonated (nondeuterated) there will be no 2 H lock to keep the frequency constant. Together, these two facts mean that the frequencies for solvent suppression are constantly changing. To compensate for this and to automatically optimise the frequency, the use of a scout scan was developed [86]. LC-NMR Modes of Operation The types of data acquisitions used in LC-NMR include: (i) on-flow or continuous flow (ii) stop-flow (iii) time-sliced acquisition, where a peak is moved incrementally through the probe with stop-flow spectra taken at each step, and (iv) on-line collection of peaks in storage loops. There is a fifth technique known as pre-concentration. With the

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stop-flow, time-sliced acquisition and on-line loop collection alternatives, peak selection requires the use of a monitoring device, which is typically an LC detector. Stop-flow acquisition is a simpler mode but the repeated stop/go disturbances of the LC gives rise to peak diffusion during long-lasting experiments as well as memory effects if a large peak precedes a small peak. With storage in loops these problems virtually disappear but decomposition/isomerisation of labile compounds can still create problems when storage is prolonged. Continuous or on-flow acquisition mode measurements occur under dynamic conditions and standard LC equipment can be used, whereby the entire chromatogram is obtained with incremented NMR spectra. However, the very short period of time available for data acquisition and the reduced stability under flowing conditions limit the operation to acquiring spectra for the major sample constituents. In their review, Wilson and Brinkmann suggest that an improvement is to run an initial experiment overnight at a much reduced flow rate of about 0.05 mL/min [87]. With conventional LC-NMR systems, up to 128 scans can then be recorded per spectrum, which is a useful way to obtain an overview of mixtures of closely related natural products. On-Flow LC-NMR On-flow LC-NMR measurements are mainly restricted to the direct measurement of the main constituents of a crude extract often where the LC injection has been overloaded. Wolfender and co-workers have indicated that typically 1-5 mg of crude plant extracts needs to be injected on-column [88]. However, the detection limits can be improved by performing the analysis at low-flow or by running time slice experiments over a whole chromatogram where the flow is stopped at defined time intervals. Both modes of operation enable a higher number of transients per increments to be recorded and, thereby, a significantly better signal-to-noise ratio is obtained. Another way to improve sensitivity is to perform on-line trace enrichment whereby one-line Solid-Phase Extraction (SPE) prior to LC-NMR analysis is carried out. Stop-Flow LC-NMR Stop-flow mode is more sensitive and allows 2D NMR experiments with longer acquisition times for low concentration components. The stop-flow mode can employ any one of three different kinds of sample handling. First, the samples may be analysed directly as they elute from the column, one chromatographic peak at a time. Second, the LC pump may be programmed to “time-slice” through a chromatographic peak, stopping every few seconds to acquire a new spectrum [70]. Time Slice “Time-sliced” involves a series of stops during the elution of the chromatographic peak of interest. Time-sliced is used when two analytes elute together or have close retention times or when separation is poor [85]. Time slice is useful for resolving multiple components within a peak that are not fully resolved chromatographically or for the verifying of purity of a chromatographic peak. The third method is to collect the chromatographic peaks of interest into loops of tubing (off-line) and then flush the intact fractions into the NMR flow probe one at a time as needed [70].

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Loop-Collection In this case the analytes must be stable inside the loops during the extended period of analysis. Capillary tubing should be used to avoid peak broadening and loss of analyte “seen” by the NMR spectrometer [85]. A variation of this technique is to trap the eluted peaks onto another chromatographic column to allow concentration of the solute and then re-elute with another solvent into the flow probe as a more concentrated sample [70]. The stop-flow mode gives the possibility to acquire a number of transients on a given LC peak. Satisfactory LC-1H NMR spectra of compounds present in the low µg range can be obtained. In this mode, 2D correlation experiments such as Correlation Spectroscopy (COSY), nuclear Overhauser effect Spectroscopy (NOESY), Rotational nuclear Overhauser Effect Spectroscopy (ROESY), Heteronuclear Single Quantum Coherence Spectroscopy (HSQC) and Heteronuclear Multiple Bond Coherence Spectroscopy (HMBC) are also possible provided that the concentration of the metabolite is high enough (generally more than 100 µg of sample is required) [85,88]. Stop-flow requires the calibration of the delay time, which is the time required for the sample to travel from the UV detector to the NMR flow-cell, and which depends on the flow rate and the length of the tubing connecting the HPLC with the NMR. Experiments such as WET-COSY, WET-TOCSY (Total Correlation Spectroscopy) can be run since the sample can remain inside the flow-cell for days. LC-NMR Resolution, Sensitivity and Limits of Detection Since NMR is a low sensitivity technique, analytical columns are often overloaded when a sample is injected and this will affect the chromatographic resolution and separation. Another factor that can affect chromatographic performance is the use of deuterated solvents, where in many cases analytes show chromatographic peak broadening and occasionally different retention times from protonated solvents. More chromatographic development is then required in order to obtain reasonable resolution. For the period 1985 to 1994, Hicks compares the amount of sample that could be measured successfully in 2 hours by 1H NMR (with double solvent suppression) using the same experimental conditions in the stop-flow mode (for a compound with molecular weight of approximately 400, in CH3CN/D2O, with a signal-to-noise of around 10:1 at 500 MHz) [79]. Evidently, the amount of sample has significantly decreased due to technological improvements. In 1985, 2 µg was required for this analysis. In 1987, 1 µg could be measured with the introduction of a modified coil design. By 1990, this was reduced to 500 ng with the introduction of optimised LC pathways and a modified flowcell. In 1992, with the introduction of automatic stop-flow timing, 300 ng could be measured, and in 1994 150 ng, due to the introduction of digital filtering and over sampling, Fig. (3). The limits of detection in 2002 for 500 molecular weight analytes at 1 H observation frequency of 600 MHz was reported to be ~ 100 ng in stop-flow and loop-storage mode, Fig. (3) [89]. Although continuous flow or on-flow modes use NMR as the real-time detector, sensitivity and resolution are limited by the short residence time of the analytes at 0.51.5 mL/min, and typically >10 µg per analyte are needed for quality results at the 1H observation frequency of 500 MHz [90]. Given sufficient material in stop-flow and loop-

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storage mode, 2D NMR experiments, which are used routinely for characterisation and structural elucidation of natural products, are feasible, e.g. COSY, TOCSY and HSQC.

Fig. (3). The amount of sample able to be measured successfully using LC-NMR.

Typical stop-flow detection limits at the 1H observation frequency of 600 MHz using micro coil probes and capillary systems are in the 5 ng range but these require an overnight acquisition, with high concentrations of analyte required in the 1.5 µL NMRactive probe volume, as reported by Albert (2002) [90]. Data Handling The presentation of the resulting LC-NMR data depends upon the type of experiment run. On-flow LC-NMR data are usually displayed as a contour map, like a conventional 2D NMR dataset but the Fourier transformation (FT) is only applied along one axis (the F2 axis) to give a frequency-versus-elution time plot. Stop-flow LC-NMR data are usually presented as a series of individual 1D spectra, plotted one spectrum per page, although stacked-plot presentations are also used. NMR Pulse Sequences Diffusion-ordered spectroscopy (DOSY) has become a popular tool for determining which compounds bind to large-molecule receptors and is referred to as ‘NMR screening’. DOSY can deconvolute the one-dimensional proton spectrum of a mixture into individual 1D sub-spectra on the basis of the diffusion rate of each compound [91]. NMR screening is being performed using flow NMR and it is logical to try to use DOSY in DI-NMR to verify compound purity [71]. The combination of DOSY and LC-NMR, however, has had limited application to date. LC-NMR (Other Detectors) In LC-NMR, other types of in-line detectors (such as UV, fluorescence, radiochemical, RI or ELSD) have been used, either to obtain additional data or to trigger

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the HPLC pump to stop at a particular peak. The advantage of incorporating a MS in this detector chain is that a sensitive and selective signal can be provided to trigger stop-flow NMR analysis. Size-Exclusion Chromatography NMR (SEC-NMR) has also been demonstrated, as has Ion-Exchange Chromatography NMR (IEC-NMR) [92]. Limitations of LC-NMR Although LC-NMR is now practically applicable for the direct observation of metabolite resonances in LC reversed-phase systems, not all the information obtained by conventional measurement in standard deuterated NMR solvents can be obtained. Another problem is the use of solvent suppression where the signals of analytes of interest that reside under the solvent peak will also be suppressed. This can be a major downside when dealing with unknown constituents. In order to detect all analyte signals, an alternative is to carry out solvent suppression using two independent solvent systems such as MeCN-D2O and MeOH-D2O [93]. A further problem is that the chemical shifts recorded in a reversed-phase solvent will slightly differ from those reported in standard deuterated NMR solvents and this can be a drawback if precise comparisons with literature data need to be made as in the case of identification of previously reported natural products (dereplication). Despite these limitations, the technique is impressive for providing on-line information in crude natural product extract analyses. This technique alone will not provide sufficient spectroscopic information for a complete identification of natural products and other techniques, such as LC-UV-DAD, LC-MSMS, LC-IR and LC-CD, are needed for providing complementary information. Ideally the integration of all these hyphenated techniques in a single set-up with centralised acquisition of the spectroscopic data would permit the complete spectroscopic characterisation of the different metabolites with a single analysis. LC-13C NMR LC-NMR mainly implements 1H NMR spectra or 1H-1H correlation experiments. Access to 13C NMR information is possible, but is restricted only to a very limited number of cases where the concentration of the LC peak of interest is high and 13C NMR data can be deduced indirectly from inverse detection experiments [94]. Due to the low abundance of the 13C isotope (1.1%) the sensitivity for direct measurement in the LCNMR mode is not sufficient. Approaches involving transfer of spin polarisation from immobilised nitroxide radicals, known as ‘dynamic nuclear polarisation’, have been reported, allowing LC- 13C NMR detection of a mixture of halogenated hydrocarbons but at present this technique has not been applied to LC-13C NMR of natural products [95]. The inability of LC-NMR to provide reasonable amounts of sample for 13C NMR is still an important limitation of this technique for natural product analysis and full on-line identification of unknowns. Many secondary metabolites, especially those with characteristic 1H signals, which are not well separated in the NMR scale, are difficult to analyse by LC-1H NMR. Compounds, which exhibit very few 1H signals and with mainly quaternary carbons or hydroxyl substituents in their structure also yield little structural information by LC-1H NMR. However, LC-1H NMR information may be sufficient for the on-line identification of previously known constituents or for studying derivatives of a known core skeleton that are likely to be present in a given extract.

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Structure elucidation of unknown organic compounds is usually performed by the combined use of 1H and 13C NMR spectroscopy. The latter spectroscopy provides direct information about the carbon skeleton of molecules, thus revealing valuable structural features, such as carbonyl and carboxyl moieties, which cannot be deduced by 1H NMR spectroscopy. In on-line HPLC-NMR coupling, the commonly recorded nuclei are 1H and 19F due to their high natural abundance, 99.9 and 100%, respectively. Sensitivity factors currently preclude the direct detection of 13C resonances as previously discussed. Indirect access to the information content of 13C NMR spectra is obtained in the stopflow mode, where ‘inverse’ detected 1H-13C correlation spectra can be recorded. Quaternary carbons without any directly attached protons are not detected and, therefore, it is of major interest to record 13C NMR spectra. In principle, high quality 13C NMR spectra of neat liquid samples or highly concentrated solutions of organic molecules can be obtained using a flow probe with a 13 C RF coil (DI-NMR and FIA-NMR) [90]. However, this technique is not feasible for recording continuous or on-flow 13C NMR spectra of chromatographic peaks (LCNMR). A major increase in sensitivity needs to be achieved for this application. Increasing the Sensitivity For metabolites or natural products present in low concentrations that are too low for on-flow studies, pre-concentration is the way forward. Alternative strategies are presented: a) SPE-NMR In Solid-Phase-Extraction coupled to NMR (SPE-NMR), a HPLC system performs an initial separation of the analytes but as they elute, the HPLC peaks are individually diverted to an in-line SPE cartridge. Solvent conditions are adjusted so that the solutes are retained on this small cartridge (or column) and, once the column trapping is complete, the solutes are eluted with an appropriate solvent (which can be deuterated for ease of NMR analysis) as a concentrated plug that is pumped directly into the NMR detector flow-cell. This idea, published in 1998 [96,97], has been applied to the analysis of natural products [98,99] and resembles FIA-NMR but has the added feature of an initial HPLC separation step. b) 2D-LC-NMR Another method of pre-concentration is the technique referred to as 2D-LC and has to date been applied to LC-NMR-MS [100]. Two columns are connected in series whereby compounds eluting from an HPLC column are trapped using D2O on a second column by means of a diverting valve and back flushed into the LC-NMR flow-cell using an appropriate deuterated organic solvent. This approach has the advantage of concentrating the chromatographic peak, which improves the sensitivity of LC-NMR and minimises the spectral overlap between solvent and solute. This process can be timed using automatic switching so that transfer to the second column occurs only when a target peak is eluting from the first column. This results in trapping and, as with SPE, multiple injections increase the amount trapped and, therefore, improved NMR spectra. The second column used is smaller in diameter, which helps to concentrate the sample to an appropriate NMR volume. The procedure

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employed for column trapping requires the chromatogram to be run twice where on the first occasion elution times are noted. c) Column Trapping Strategies to increase the sensitivity of LC-NMR by trapping minor components on the chromatographic column, and subsequent elution, were described in 1998 [96,97]. Each of these pre-concentration techniques has advantages and result in a several fold increase in sensitivity. In LC-SPE the chromatography is separated from the spectrometry by the SPE step so that the HPLC peak shape is not of importance. Nondeuterated solvents can be used for the chromatography so that the MS is not affected by molecular weight changes and deuterated solvents are introduced for NMR spectrometry. In 2D-LC, peak shape retains significance since the eluting peaks are being analysed. However, the overall length of time of an experiment is probably less than for LC-SPE where multiple trapping and cartridge drying are often involved. d) Column Switching Technique An on-line sample preparation system using a column-switching HPLC for the structure elucidation of compounds in mixtures by NMR was described in 2000 [101]. The system consists of three HPLC sections, one separating the compounds of interest, another trapping the separated compounds on a trapping column using H2O, and the third replacing H2O with D2O or a deuterated solvent. The system allows easy separation of a trace amount of compounds from a mixture. The procedure can also achieve concentration of the separated compounds and allows for the use of a deuterated solvent such as CD3OD for NMR measurement. Overview of LC-NMR to Natural Product Profiling LC-NMR hyphenation combines a separation step with the acquisition of spectroscopic data of individual compounds. In the past, the technique has been used for “speeding up” the structural elucidation of compounds in complex mixtures and several applications have been reported in the field of natural product analysis (see review by Wolfender and Hostettmann, 1998) [72]. More recently, a number of applications of LCNMR for the analysis of both plant and marine natural products have been reported [102-104]. The traditional way to separate a complex mixture such as a natural product extract and examine its individual components is to perform a chromatographic separation offline, collect the individual fractions, evaporate them to dryness (to remove mobile phase), redissolve them in a deuterated solvent and examine them by conventional NMR using microcells and microprobes if needed. When compounds are volatile, unstable or air sensitive this technique is no longer appropriate as is the case for many natural products. LC-NMR offers a means for immediate analysis after an on-line separation. Applications of LC-NMR to Natural Product Profiling In 1997 LC-NMR began to find wider use in natural products analysis. These early reports of the application of LC-NMR to natural products involved the characterisation of isomeric mixtures produced by exposing a pure natural product to light or heat. LCNMR was used to determine the structure of the photo-isomerisation product of the bioinsecticide azadirachtin [105] and to characterise the geometric isomers of vitamin A

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acetate produced upon exposure to heat [106]. The azadirachtin study employed stopflow LC-NMR measurements, while the vitamin A acetate study used on-flow measurements to detect the resonances of olefinic protons in order to determine cis or trans configurations of double bonds. LC-NMR studies of natural products have progressed to include the characterisation of individual components in crude or partially purified extracts and have demonstrated the full power of the hyphenated technique in eliminating the need to isolate individual components from a crude extract for subsequent NMR experiments. Spring et al. in 1995 published one of the first applications, the characterisation of the sesquiterpene lactones in Zaluzania grayana by on-flow and stop-flow LC-NMR experiments [107]. The characterisation of a wide range of plant natural products. including prenylated flavones from Monotes engleri [108], monoterpene dimers from Lisianthius seemannii [109] and napthoquinones from Cordia linnaei [110] have also been reported. In addition, napthylisoquinoline [111,112] and pyrrolizidine [93] alkaloids, sesquiterpene lactones [113-116], phenylphenalenones [117], taxanes [118], lignans [119], glycosides [120,121] and other compounds [122-127] have been identified from LC-NMR data. Most of these reports described the identification of known members of these structure classes by LC-NMR, but the technique has also been used to determine the structures of new analogues of known compounds [107-109]. In these examples, stop-flow measurements employing 2D NMR experiments such as COSY and TOCSY, HSQC and NOESY have been applied to determine the structure of novel compounds [8,72,128]. Wolfender and co-workers [55] have investigated various plant species in which they characterised, among other classes of compounds [125], prenylated flavonones [108], secoiridoids [109,124], naphthoquinones [110], pyrrolizidine alkaloids [93], benzophenones [129] and ‘quinone methide’ diterpenes [130]. Other groups have dealt with naphthylisoquinoline alkaloids [131-133], sesquiterpene lactones [113,135,136], triterpene saponins [137], taxanes [118], lignanes [119], phenylphenalenones [117], polyhydroxy steroids [138], fasciculol triterpenes [139], tocopherols and tocotrienols [126], carotenoid isomers [140], flavonoids [141,142], hop bitter acids [122,143] as well as betacyanin pigments [144]. Applications published so far deal with the characterisation of plant-derived mixtures, while applications to secondary metabolites of micro-organisms [145,146] or marine natural products [8, 147, 148] are still relatively uncommon [107]. Most frequently in natural products analysis, the stop-flow mode is selected to acquire 1H spectra of the compounds of interest or, if further structural information is required, to acquire 2D 1H NMR spectra. In many cases, an on-flow NMR chromatogram (usually at flow rates between 0.3 and 1 mL/min) is recorded beforehand, either to screen for the presence of particular groups of compounds or to gain a general overview of the sample composition. Heteronuclear LC-NMR experiments such as HSQC and HMBC of a natural product have been reported in the literature [108] for highly enriched fractions. ‘Time-sliced’ stop-flow and on-flow approaches at low flow rates have been applied to natural product extracts in order to combine the advantages of both on-flow (a ready overview on the entire sample) and stop-flow (sufficient acquisition time for minor compounds) modes [129,132,147,148]. The sensitivity of the NMR experiment depends on concentration and, so for a given amount of sample, molecules with a lower molecular weight give a more intensive

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signal. However, larger molecules usually possess shorter relaxation times, which allow faster spectral accumulation. Publications to date have focused mainly on the characterisation and identification of small molecules up to a molecular weight of about 700. Nevertheless, LC-NMR has been successfully applied to identify saponins of a molecular weight up to 1400 [147,148] and to characterise larger biomolecules such as glycosphingolipids [149]. LC-NMR has been applied to marine natural products and used to identify the marine alkaloid aaptamine in 2000 [37]. Aaptamine was found to be the active component in the crude dichloromethane extract of the sponge Aaptos sp. UV maxima obtained from HPLC profiles and mass data were used to search the marine natural products database, MarinLit, with four possible matching compounds identified. NMR data obtained from the LC-NMR run unequivocally identified the compound. An HPLC-NMR investigation of exchangeable protons in low molecular mass natural products has been reported [150]. Model alkaloids or crude plant extracts were dissolved in 2H2O-1H2O-MeCN (deuterium oxide-water-acetonitrile) or 2H2O-MeCN and after direct injection or chromatographic separation examined in a 60 µL NMR flow probe. Exchangeable amino protons initially detected by HPLC-MS(ESI) were subsequently identified and investigated by stop-flow 1H NMR, 2D TOCSY and NOESY. Another application of LC-NMR are biosynthetic studies employing feeding experiments with stable isotope-labelled compounds. 1H NMR spectra allow determination of the amount of isotopic label incorporated into metabolites by observing signals that arise from J-couplings of protons to 13C-labelled nuclei [151,152]. Extended Hyphenation (HP)LC-NMR Combined with (HP)LC/CD a) Relative Stereochemistry Elucidation of the relative configuration of purified compounds by on-line methods was reported in 1998 [131]. NMR signals and mass fragments do not intrinsically reveal chiral characteristics, so that information concerning the absolute configuration is not directly available. A method that allows the assignment of absolute configurations of compounds in an extract matrix would complete the structural elucidation without the necessity of isolation and purification. Circular Dichroism (CD) spectroscopy is a method that is widely used for the assignment of absolute configuration if experimental data from structurally related compounds is available or if structures fit into empirical CD rules [153]. In the past, detectors based on Optical Rotation Dispersion (ORD) have been used but limitations of this technique include low sensitivity and lack of compatibility with gradient elution. CD is based on the absorption difference between right and left circularly polarized light and shows up only in the presence of a chromophore, which gives CD a higher intrinsic stability and sensitivity compared to ORD. Bringmann et al. report RPLC on-line coupling to CD spectroscopy for the stereochemical analysis or crude plant extracts [133]. The method was applied to the tropical liana Habropetalum dawei (Dioncophyllaceae) in which the extract was initially investigated by HPLC-NMR and HPLC-ESI-MS-MS. From these combined

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investigations, two unknown natural products were detected for which the configuration remained unknown. Subsequent HPLC-CD experiments permitted the assignment of the absolute configuration of the two metabolites by empirical analysis of the CD data. The combination of NMR, MS and CD data permitted the complete structural elucidation of two new metabolites, phylline and 5’-O-methyldioncopeltine A, in the extract without any isolation and sample purification prior to the coupling experiments. A photometric screening method for dimeric naphthylisoquinoline alkaloids has also been reported whereby the complete structure, including relative configuration, was elucidated on-line by LC-MS, LC-NMR and LC-CD on the extract [134]. b) Absolute Stereochemistry Classically, chemical methods such as Mosher’s ester synthesis have been frequently used for the characterisation of various isolated natural products bearing secondary alcohol functions [154]. In this case, the 1H NMR spectra of (R)- and (S)-2-methoxy-2phenyl-(trifluoromethyl) acetic acid (MTPA) ester derivatives of the analytes are compared. The difference in the chemical shifts of the (S)-MTPA and (R)-MTPA diastereoisomers (∆δH = δS –δR) indicates whether the alcohol function is (R) or (S) based on established conformational models [155]. Until recently Mosher’s ester synthesis was only used in combination with standard NMR. A recent study of crude reaction mixtures by LC-UV-MS and LC-NMR has proven to be a rapid and sensitive method for absolute configuration determination. This on-line method can be applied to a restricted amount of sample or to a fraction difficult to obtain in a pure form. The absolute configuration was determined using only a few milligrams of natural products. This technique was successfully applied to the determination of the absolute configuration of two α-pyrones isolated from the root bark of Ravensara crassifolia (Lauraceae) [156]. Another example of the use of the Mosher esterification method in conjunction with LC-NMR analysis for the elucidation of absolute configurations of micro quantities of available pure substances was reported in 2003 [156]. The absolute configuration of a novel tetrahydrophenathrene from Heliotropium ovalifolium was determined by LCNMR of its Mosher esters [157]. LC-UV-NMR-ELSD The ELSD fulfils the requirements for a sensitive, universal, conventional detector and was investigated by Petritis et al. (2002) as a potential on-line monitoring detector for LC-NMR using un-derivatized amino acids as model compounds [158]. These compounds were selected because they contain either strong, weak or no chromophore groups (e.g. phenylalanine/serine/taurine) or even fluorophore groups (tryptophan). This is particularly important for natural products, as so often many bioactive compounds do not possess a UV chromophore. Indeed ELSD’s are frequently used together with UV or UV(DAD) detectors in the isolation of natural products. The ELSD, like a MS, is a destructive method and should be coupled in parallel and not in tandem with NMR. An important parameter that must be set up carefully in online stop-flow LC-NMR is the exact time difference between the arrival of the chromatographic peak at the monitoring detector and the LC-NMR flow-cell. In fact, the signal from the detector is used to trigger the automated NMR acquisition sequence, including the interruption of chromatographic elution. In addition, the quantity directed

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towards the parallel detector (MS or ELSD) should be minimised to increase NMR sensitivity. Petritis et al. pioneered the use of ELSD prior to NMR acquisition for the on-line monitoring of the chromatographic separation of compounds with weak or no UV chromophore. LC-NMR-CLND Another detector worthwhile investigating as an in-line monitoring detector for LCNMR experiments, especially for nitrogen containing compounds such as alkaloid natural products, is the Chemiluminescence Nitrogen Detector (CLND). This detector is well adapted for sensitive amino analysis detection [158]. Applications of LC-NMR Combined with LC-MS to Natural Product Profiling Application of both LC-NMR and LC-MS to a partially purified extract of Veronia fastigiate led to the direct identification of nine antibacterial sesquiterpene lactones without isolation of individual compounds [114]. The rapid structural analysis of both major and minor components of this class of compounds demonstrated the power of structure-guided screening as a complementary method to bioassay-guided screening. In LC-NMR significant segments of proton spectra are lost through solvent suppression (2.0 ± 0.125 ppm, acetonitrile signal, and ~4.5 ppm, water signal). A method was reported to obtain a complete set of proton resonances. In order to get information about the suppressed signals, the LC-NMR spectra were run again in a methanol/water gradient. Comparison of the resulting spectra with the spectra obtained in the acetonitrile/water allowed the assignment of all proton resonances of the corresponding compounds using just two LC-NMR runs. A review by Hostettmann and Wolfender (1999) described the application of LCNMR and LC-MS in the search for new bioactive compounds from plants of the Americas [159]; while Sanvoss (2002) provided an overview of the application of LCNMR and LC-NMR-MS hyphenation to natural products analysis [107]. LC-NMR together with LC-UV-MS was used to achieve on-line identification of unstable cinnamoyal catalpol glycoside esters from the plant Jamesbrittenia fodina (Scrophulariaceae) by the group of Hostettmann and Wolfender (2003) [160]. An on-line identification of the antifungal constituents of Erythrina vogelii was carried out using LC-NMR and LC-MS-MS [SU79]. The chemical screening strategy with integrated antifungal bioassays permitted on-line identification of numerous constituents and provided a useful and efficient peak-guided isolation procedure. On-line and off-line HPLC-NMR and HPLC-MS analyses of the extracts Jasminium subtriplinerve and Terminalia macroptera have been conducted [161]. The isolation of bioactive compounds via bioassay-guided separation techniques, such as online HPLC-bioassays, and the structure determination by MS and NMR of the bioactive principals from these extracts were carried out. Biologically active natural products were isolated by means of on-line LC-bioassay, LC-NMR and LC-MS from Cussonia barteri (Araliaceae), Terminalia macroptera (Combretaceae), Jasminum subtriplinerve (Oleaceae) and Petunia hybrida (Solanaceae) [162].

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The use of (HP)LC-NMR and other hyphenated techniques such as (HP)LC-MS-MS for identification of natural products from plant sources has been reviewed by Wolfender and Hostettmann [8,72]. Plant products, including polyphenols and bitter components from Gentianaceae species, have been characterised [127] including the assignment of stereochemistry at a double bond in a new secoiridoid glycoside, seemannodide [163]. Other studies include the identification of antifungal materials from the African plant Swertia calycina [127,163], compounds from the Leguminosae family [55], prenylated flavanones from dichloromethane extracts of Monotes engleri [108], naphthoquinones from Cordia linnaei [110], pyrrolizidine alkaloids from Senecio species [125] and antioxidant compounds from the leaves of Orophea enneandra [93]. New naphthylisoquinoline alkaloids from a root extract of Ancistrocladus likoko have also been identified using directly coupled (HP)LC-NMR spectroscopy [111]. Other natural product studies that have used (HP)LC-NMR, include the characterisation of vitamin derivatives [77], saponins from Bacopa monniera [137], antibacterial sesquiterpene lactones from an extract from Veronia fastigata [136], components from Hypericum perforatum L. [164] and ecdysteroids from Silene otites [138]. In the latter study, directly coupled (HP)LC-NMR-MS was also used to identify additional compounds. The metabolism of 2,3,10,11-oxygenated protoberberine alkaloids was studied in cell cultures of Corydalis species. The structures were determined by LC-NMR and LC-MS analyses [165]. LC-NMR has become an important technique for the investigation of natural products. The application of LC-NMR for screening plant constituents has been described in numerous publications [166]. LC-NMR is generally considered a very powerful (although not a fast) technique and exploited further by hyphenating it with MS to produce LC-NMR-MS. (HP)LC-NMR-MS It is seldom possible to solve the structure of a novel compound by NMR alone. Common functional groups such as carboxylic acids, phenols and amino groups are NMR-silent in many solvents because of proton-deuterium exchange. Nitro groups and sulfate conjugates do not contain protons and although these functional groups are not directly detectable in proton NMR spectra, they can be readily detected by MS. Conversely, MS data might give molecular formulae that are insufficient to unambiguously assign the molecular structure of an unknown compound. In the more difficult cases closely eluting isobars and isomers are indistinguishable by LC-MS. Therefore, NMR and MS data of the same analyte are crucial for structural information. When different isolates, such as metabolites, are analysed, one cannot always be certain that the NMR and the MS data apply to the same analyte. To avoid this ambiguity, LCMS and LC-NMR are combined. In practice, the use of either LC-MS or LC-NMR on their own can solve many analytical problems but there are occasions when they each fail and additional techniques are required. In these cases using both LC-MS and LC-NMR can provide further information and, usually, structural identity. A natural progression is to combine the two into one integrated LC-NMR-MS system. In addition MS, in scanning or MS-

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MS mode is also used to provide fragment ion data on selected peaks to coordinate with the NMR data. Apart from the gain in time and sample efficiency, the most important advantage of the doubly hyphenated LC-NMR-MS set-up over LC-MS and LC-NMR individual set ups is the unequivocal assignment of the MS data to the NMR peaks. LC-MS and LCNMR chromatograms of the sample are sometimes difficult to correlate because slightly different chromatograms are obtained in the two systems. This is due to the differences arising from the higher amounts of injected sample in LC-NMR compared to LC-MS, the different chromatographic behaviour of deuterium oxide compared to water or different gradient-forming units in the respective chromatographic systems. The double hyphenated technique involving the coupling of MS and NMR was first described in 1995 [167] and a fully integrated commercial LC-NMR-MS system launched in 1999 [100]. LC-UV-MS-NMR UV detection after the HPLC column is an advantage and thus, strictly speaking, the technique becomes LC-UV-NMR-MS. The steps involve acquisition of a HPLC chromatogram with the generation of a UV profile for the extract, followed by NMR detection and finally MS detection. Alternatively, the NMR and MS detections can be synchronised so that the peak of interest is delivered to the NMR and MS detectors simultaneously, Fig. (4). The UV detector can be either a variable wavelength instrument or a DAD capable of providing UV spectra to complement the NMR and MS data. Although not essential, the UV detector provides a very convenient means of monitoring the separation and aids the spectroscopist to accurately determine the delay times between the analyte exiting the chromatographic system and reaching the spectrometers. Solvent selection is a compromise between the ideal requirements of each instrument. For (HP)LC-NMR the use of inorganic buffers, like sodium phosphate, for pH modification is preferred because no additional signals are introduced into the NMR spectrum. However, this type of buffer system is currently incompatible with most (HP)LC-MS systems using an ESI interface. An alternative acidic modifier is trifluoroacetic acid (TFA), which has no protons to complicate the NMR spectrum but with acidic analytes ion suppression is observed even at high sample concentrations in the MS. Formic acid is a suitable compromise between the needs of MS and NMR. The single proton of formic acid has a sharp, readily suppressible NMR singlet at δ 8.5, and enables MS data to be acquired for acidic analytes. As previously discussed, insensitivity is the major disadvantage with NMR, with relatively large amounts of analyte required to give good signals compared with MS. For 1 H NMR, 1-5 µg on-column in flow mode will produce a good signal, whereas only ng amounts or less are needed for MS. Splitting the column flow unevenly, with 2-5% being directed to the MS and the remainder to the NMR spectrometer, overcomes this difference. Fig. (4) [100]. Recent studies have devoted attention to the use of superheated water (or D2O) as the eluant in LC-NMR-MS [87]. While the detection performance is increased, the approach

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is not suitable for all analytes due to the elevated temperatures causing degradation of thermolabile compounds, which is often the case for many natural products.

Fig. (4). Schematic of the hyphenated spectroscopic technique, LC-NMR-MS. In order to obtain sufficient accumulation time for NMR spectra, on-flow LC-NMRMS investigations can be performed as overnight experiments at eluant flow rates lower than usual (e.g. 0.05 mL/min). This allows a number of scans (~128), to be recorded per spectrum. Sanvoss et al. report that for both early and late eluting asterosaponins, such a low flow rate did not result in peak broadening [135]. Another instrumental conflict is the effect of the magnetic field (typically 400-600 MHz, up to 800 MHz) of the NMR instrument on the MS. Wilson indicated that the high stray magnetic field from the NMR magnet can have adverse effects on the MS and, in practice, means that the mass spectrometer is best sited outside the 5 Gauss line [167]. Modern superconducting NMR magnets are actively shielded so this problem should not occur for commercial systems, but for older NMR or lab-built systems positioning of the mass spectrometer away from the NMR magnet is critical. In the case of (HP)LC-NMR-MS experiments there are some additional considerations. The principal MS ionisation method has been ESI in either positive or negative ion mode (using either single quadrupole or ion-trap mass spectrometers), which puts further constraints on the chromatographic solvent systems. Running the instruments in series allows for the completion of all NMR experiments with either an on-flow or stop-flow procedure adopted before the beginning the sample destructive MS analysis. The possibility of peak dispersion before MS analysis is introduced for any peaks trapped between the NMR and MS when the flow is stopped. Series operation causes the NMR flow-cell and connections to be operated at pressures higher than

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designed with the consequence that leaks are more likely. Running in series also fails to take advantage of the ability for the mass spectroscopist to quickly flag up peaks of interest [168]. Operation of the instruments in parallel is advantageous. The delay between the appearance of the peak in the UV detector and detection by the NMR and MS can be manipulated such that the analyte enters both spectrometers simultaneously. Alternatively, the analyte can be detected first in the MS enabling an informed decision on obtaining a stop-flow NMR spectrum for a particular peak. Reviews by Wilson [167] and Elipe [85] suggested that MS data should be obtained using an off-line approach such as LC-MS, since with NMR data collection in the stopflow mode can take hours or days depending on the complexity of the structure and the amount of sample. As in the case of LC-NMR, the void volumes in a coupled system are high. The NMR flow-probe or the storage loop, which is located further downstream, is reached approximately 10-40 seconds after the peak first appears in the LC detector and needs to be calibrated. A problem with the use of deuterated solvents such as D2O with MS is that the deuterium can exchange with protons on ionisable groups. The practical consequence of this is that the wrong molecular mass may be determined unless the mass spectroscopist takes exchange into account. Sample Recovery in LC-NMR or LC-NMR-MS After separation of the sample and acquisition of spectroscopic data, the sample can be collected in a fraction collector. Further investigation, especially by different MS techniques can follow and fractions collected to be put through a bioassay. Automation To date the majority of LC-NMR-MS applications use stop-flow mode. In this mode, the sample, as in conventional NMR, is stationary. Once the analyte reaches the active NMR probe volume, the flow is stopped and the subsequent eluant is simply diverted either to waste or to on-line storage loops. Loop-storage, as discussed earlier, is a valuable advance whereby chromatographic peaks are trapped on-line in a 36-loop cassette (Bruker BioSpin) or in any array of loops (Varian Inc.) determined by a UV or MS detection threshold [169,170]. Automation directs peaks to the loops and controls the transfer of loop contents, one-at-a-time, to the NMR flow probe for stop-flow analysis. Loop-storage avoids peak diffusion on-column, which reduces NMR sensitivity when several analytes require long NMR acquisition. Less sample is required because all the analytes in a single injection are stored and acquired later under automation. With the Bruker-NMR-Mass spectrometry Interface (BNMI) integrated system, MS experiments can be obtained on the loop contents while the NMR acquires data. The loop-storage mode is a highly efficient mode of operation. Manual, semi-automated or fully automated operation is possible in both stop-flow and loop-storage modes. For flexibility, switch between modes is possible during a run. The goal of LC-NMR-MS is to target important analytes for efficient NMR analysis. In natural product drug discovery programs, where novel diverse molecules are present in complex mixtures, UV and MS provide insight for further NMR experiments. Routine acquisition of LC-NMR-MS can be significantly improved by optimisation of the chromatographic separation conditions. Typically, analytical scale reversed-phase

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HPLC uses columns of 2-4.6 mm i.d. × 5-250 mm length and flow rates of 0.2-1.5 mL/min. Mobile phase mixtures employing deuterated water and non-deuterated organic modifiers are routinely employed (acetonitrile/D2O or methanol/D2O) together with efficient solvent suppression routines. Occasionally a fully deuterated organic solvent is used to minimise solvent artefacts in the NMR spectrum. It is seldom possible by 1D 1H NMR to fully characterise co-eluting analytes when NMR signals from two or more compounds of similar concentration are overlapped. Online MS detection can be used to deconvolute co-eluting components, but only if they are not isobars or isomers. If sufficient material is available, 2D 1H-1H NMR is useful to determine correlations between the resonances within the co-eluting analytes but can be time consuming. Therefore, optimising the chromatographic resolution is frequently the best solution. Until recent years, interfacing LC with NMR and MS has been difficult, but many problems such as sitting the LC and MS physically close to the NMR magnet have now been resolved by the use of shielded magnets. A benchtop ion trap MS can now be placed <1 m from the centre of a 500 MHz NMR magnet without adverse performance. The short distance also limits LC peak broadening and results in enhanced NMR sensitivity. Practically, a simple hyphenation of LC to NMR and MS is achieved using a post-column splitter, which directs 90-95% of the flow to the NMR via a 1-2 m capillary and the remainder to the MS. An alternative is the valve-switching interface termed the BNMI, which is a computer-controlled splitter, and a double dilutor that provides an appropriate make-up flow for optimal ionisation in the MS. BNMI also permits protondeuterium exchange to simplify MS spectra otherwise obtained in LC-NMR-MS. The BNMI also plays an important role in LC-NMR-MS loop-storage mode in which a portion of the loop contents, on transfer to the NMR, can be stored in a delay loop. During NMR acquisition, the dilutor then slowly infuses analytes into the MS. These integrated LC-NMR-MS systems are highly versatile, operating as needs dictate. For instance, LC-MS can be used routinely during longer NMR experiments. In the area of natural products the hyphenated technique LC-NMR-MS has been applied as a rapid screening method of searching for unknown marine natural products in chromatographic fractions [171] and for the separation and characterisation of natural products from plant origin [172,173]. LC-NMR-MS and Natural Product Profiling In drug discovery from natural products it is crucial that duplicate isolation of known or undesirable compounds from complex extracts is avoided. An explosive growth in the use of LC-NMR and LC-NMR-MS for dereplication has taken place in the past few years [37,55]. While the majority of publications have identified known structural classes to evaluate the use of LC-NMR and LC-MS for dereplication, only a few have reported interesting novel bioactive analogues. The first application of LC-NMR-MS to natural products analysis was reported in 1999 [174]. The additional MS information allowed the identification of a further ecdysteroid in an extract of Silene otides, which could not be identified by LC-NMR alone [138]. Further applications of this double hyphenation technique dealt with the identification of napthodianthones [164] and flavone glycosides [164,175] in natural product extracts. In recent years a number of studies on the use of LC in combination

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with NMR and MS detection in a single setup have been reported [87,168,176]. In view of the demanding nature of the non-target approach that is generally prevalent in natural product analysis, LC-NMR-MS would be expected to be the method of choice. With regard to LC implementation with NMR and MS, there appear to be two “schools” of thought. Researchers such as Wolfender and Hostettmann prefer to use the two spectroscopic techniques separately. LC-NMR is generally the most demanding technique and may compromise the use of other hyphenated technique(s) [177,178]. Data from LC-UV(DAD) and LC-MS-MS are acquired at the same time while LC-NMR and LC-micro-fractionation are performed in a separate second analysis. Loading of the sample can now be optimised for each technique and D/H exchange problems during MS detection do not occur. In addition, 10% of each micro-fraction (used for a bioassay) is kept for post-run UV-MS analysis in case of doubt regarding the attribution of LC peaks. This latter precautionary measure indicates the limitation and weakness of this approach with respect to the problem of peak correlation between the two runs, especially if minor peaks are considered. At present, two stand alone LC-MS and LC-NMR setups seem preferred by workers over a single hyphenated system. A recent demonstration of the potential of having both NMR and MS available in one LC run was described in a study on the Baltic starfish, Asterias rubens [171]. Previously unreported asterosaponins were identified from sub-fractions after rapid sample preparation by matrix solid-phase dispersion. Despite the high complexity and close analogy of the structures, the targeted isolation and off-line structural elucidation of seven new compounds was achieved and up to 17 individual constituents could be characterised in a single chromatogram of an asterosaponin fraction. An application of LC-NMR-MS also was reported in the separation and characterisation of two secoisolariciresinol diglucoside isomers in flaxseed [172]. LC-NMR-MS hyphenation was applied to the screening of an asterosaponin subfraction from the starfish Asterias rubens for unknown compounds. This method was successful in indicating the presence of unidentified asterosaponins in the sample and subsequently resulted in the isolation of four new compounds, ruberosides A-D. The compounds were elucidated using 1D and 2D NMR techniques. In the case of asterosaponins, several complicating factors were indicated. Conventional screening methods, such as column chromatography-TLC or HPLC-PDA, are not sufficiently specific as asterosaponins are difficult to separate and show little UV absorbance [147]. (HP)LC-MS methods employing soft ionisation techniques such as ESI are well suited in principle but yield little or no information on the various structural isomers. Also, the response under ESI or APCI conditions strongly depends on the chemical nature of the compounds. 1H NMR spectra can be used to check the purities of isolated compounds but when applied to the analysis of mixtures even 2D NMR spectra are difficult to interpret because of their complexity. An LC-NMR-MS method was developed in 2000 to characterise subfractions of toxic glycosidic constituents of starfish (asterosaponins), which were not sufficiently separated by classical preparative column chromatography [147]. Asterosaponins are ∆9(11)-3β, 6α-dioxygenated steroids with a sulfate group attached at C3 and an oligosaccharide chain containing five or six sugar units at C6. Individual representatives of this homogeneous class differ in their steroidal sidechain or their sugar moiety while the steroidal nucleus is common to all asterosaponins. There are about 100 different

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combinations of sugar moiety and sidechain described in the literature. Dereplication by LC-NMR-MS allowed recognition of novel asterosaponins at an early stage of the dereplication process. Within 2 days, starting from the intact animal material, an overview of the composition of the asterosaponin fraction was obtained by Wolfender et al. [177]. In this study, LC-MS of asterosaponins did not permit identification as identical molecular masses and fragmentation patterns were observed. In such situations, however, LC-NMR-MS facilitates the identification of unknown compounds in the presence of known compounds and thereby prevents unnecessary re-isolation. Natural product isolations will also benefit from faster dereplication using automated loop-storage LC-NMR-MS and is illustrated by the identification of nine closely eluting and isomeric aporphine alkaloids in the Taiwanese plant Litsea genus using 50 times less material compared to conventional experiments using 5 mm tubes and the same field strength NMR spectrometer [170]. Automated loop-storage LC-NMR-MS also led to rapid identification of the main alkaloid classes from extracts of four medicinal plants from the Cape Peninsula region [176]. Natural product investigations using nonhyphenated approaches can take several months, in comparison these results were achieved in 36 hours using fully automated loop-storage mode on a 500 MHz spectrometer using only 150-300 mg of each extract. Microbial production of secondary metabolites is another facet of natural product isolation. Identification of novel warfarin metabolites from Streptomyces rimosus [169] and the identification of the antibiotic aristeromycin from Streptomyces citricolour [145] were achieved by LC-NMR studies. Similarly, LC-NMR and LC-MS were used to identify bioactive molecules from marine sources such as the sponge Aaptos sp. [37] and the starfish Asterias rubens [147]. Clearly the discovery of novel molecular diversity from such phytochemical, microbial and marine sources will be greatly facilitated by advances in LC-NMR-MS. The factors that hamper complete on-line identification of unknown natural products are mainly linked to the present limitations of LC-NMR. LC-UV or LC-MS provide comparable types of spectroscopic information to those recorded for pure constituents and sensitivity does not compromise the HPLC separation. LC-UV-MS and LC-NMR are very efficient for the recording of spectra in crude reaction mixtures at the microgram level. LC-NMR-MS cannot fully replace LC-MS, LC-NMR or even NMR techniques for the structural elucidation of compounds. Cases will always exist were purification of the analyte(s) is required, when the structural problem is too complex or the separation of the chromatographic peak is not suitable. All techniques need to be available to the analyst to choose that which is appropriate for each structural problem. LC-NMR-MS and Beyond LC-SPE-NMR-MS Solid-phase extraction (SPE) has been integrated inline in the LC-NMR-MS sequence. Unlike most SPE applications, which are carried out on crude sample extracts in order to obtain a mixture of analytes, the SPE cartridges are positioned after the HPLC column so that eluting components can be trapped on their own cartridges. Thus, SPE acts as a fraction collector where multiple injections can be undertaken in order to accumulate the target compounds. The individual components in the cartridges can then

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be washed before elution to the NMR and MS. The sensitivity advantages are significant where one trapping step has improved the signal-to-noise ratio for NMR by up to a factor of four. An approach of combining Matrix Solid-Phase Dispersion (MSPD) extraction with LC-NMR-MS hyphenation was first applied in 2001 for screening of the asterosaponin fraction of the starfish Asterias rubens [60]. The intention was to demonstrate that MSPD could be successfully used with on-line LC-NMR-MS to provide information about the compounds in the asterosaponin fraction. In particular, the on-flow LC-NMRMS approach was carried out to assess if adequate separation of closely related asterosaponins could be achieved with sufficient quality spectroscopic information to permit identification. Use of an on-line LC-UV-SPE-NMR-MS system with a cryogenic NMR flow probe was reported in 2003 for the automated analysis of a Greek oregano extract [166]. Combining the data provided by the UV, MS and NMR spectra, the flavanoids taxifolin, aromadendrin, eriodictyol, naringenin, and apigenin, the phenolic acid rosmarinic acid, and the monoterpene carvacrol were identified. The automated technique was found to be very useful for natural product analysis and the greater sensitivity enhancement due to the use of the cryogenic NMR flow probe led to significantly reduced NMR acquisition times. To further increase LC-NMR sensitivity, the SPE method for concentrating the compounds of interest was used for peak storage after the LC separation and prior to NMR analysis. The SPE unit allows the use of normal protonated solvents for the LC separation and fully deuterated solvents for flushing trapped compounds into the NMR probe. Therefore, solvent suppression was no longer required and multiple trappings of the same compound from repeated LC injections was utilised to solve the problem of low concentration and to obtain 2D heteronuclear NMR spectra. When compared to the classical uses of UV, MS and NMR spectroscopy applied to pure natural products, ideally the integration of all these techniques in their hyphenated forms (LC-UV, LC-MS and LC-NMR) in a single setup with centralised acquisition of the spectroscopic data should permit the complete spectroscopic characterisation of different metabolites in a mixture in a single analysis. Further, other existing hyphenated techniques, such as LC-IR and LC-CD, may also result in valuable additional information. The combination of all these techniques in a single setup is possible and the creation of a ‘total analysis device’ has been demonstrated in the case of on-line HPLCUV(DAD)-NMR-MS-FTIR analyses [178]. The coupling of all these different techniques (especially LC-NMR-MS) is not an easy task to perform since operation conditions that are compatible with all have to be found. The possibility of acquiring all data during a unique analysis gives an opportunity to efficiently associate the set of online spectroscopic data with a given peak and renders the processing easier to perform. Extended Hyphenation LC-UV(DAD)-NMR-FTIR-MS LC-UV(DAD)-NMR-MS with the parallel sequence is generally preferred to the serial NMR-plus-MS sequence and the next extension was to include FTIR by collecting the effluent from an NMR instrument on-line with associated solvent evaporation and

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subsequent off-line FTIR detection. The triple hyphenation of (HP)LC-NMR-IR-MS for collecting the eluant for subsequent FTIR measurements was described by Wilson et al. [42] in 1999. The suitability of an integrated LC-UV-NMR-FTIR-MS system for the analysis of natural products was assessed using ecdysteroids whereby two compounds, 20-hydroxyecdysone and polypodine B, were unequivocally identified [43]. A Time-Of-Flight (TOF) based LC-UV(DAD)-NMR-FTIR-TOF-MS system was designed with IR spectra obtained on-flow to study a reasonably concentrated mixture of four non-steroidal anti-inflammatory drugs including ibuprofen and naproxen [179]. This was undertaken as a “proof of concept” and was successful in that good quality spectroscopic data and accurate masses were obtained for all analytes. In these studies stop-flow 1H NMR was used. They showed that diagnostic UV, IR, MS and 1H NMR spectra could be obtained on-flow and in a single run for quantities of material on the order of 50-100 µg. Here the layout of the instrumentation was not fully optimised and further work [180] indicated that a five- to ten-fold improved performance could be achieved by paying attention to minimising band broadening. This ability to obtain four sets of correlated data is a very exciting development particularly to the field of natural products chemistry. Other Hyphenated Spectroscopic Techniques GC Hyphenation Among the separation-identification setups, GC-MS was the earliest and the first hyphenated technique to become useful for routine research and development purposes and has been used to profile metabolites for over forty years. Neither GC-FTIR nor GC coupled to an Atomic Emission Detector (GC-AED) has achieved the same popularity as GC-MS. FTIR is suitable for functional-group recognition, but much less so for true analyte identification. However, GC-FTIR-MS systems have shown utility in the analysis of natural products such as flavours, fragrances and essential oils. A number of reports discuss the application of GC hyphenated techniques [181,182]. For complex samples typically subjected to GC-FTIR-MS, a more sophisticated GC analysis was needed, and hence a GC-GC setup with a cryogenic trap between the two GC columns was used [183]. The recent introduction of GC × GC-TOF-MS has led to markedly successful separations. Recently there has also been renewed attention to the application of coupled-column techniques to enhance resolution with typical examples, including (normal phase) LC-GC and, increasingly, GC × GC (2D-GC) and LC × LC (2D-LC), also known as comprehensive techniques (see review by Wilson and Brinkmann) [87]. The use of GC-MS is restricted to compounds that are sufficiently volatile to pass through GC columns at temperatures of up to 400°C, the upper limit of ‘high temperature’ capillary columns. In natural product research, GC-MS is most frequently used to analyse essential oils. Applicability of GC-MS is limited to less polar compounds with molecular masses below 1 kDa. In many cases, natural products have to be derivatised prior to the chromatographic separation whereby the chromatographic separation, appearance of mass ions and fragmentations are all affected by the choice of derivatising agents used for substitution of polar groups.

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SFC-MS A short time after the development of commercial instruments for supercritical fluid capillary (SFC), normally using CO2 fluid equipped with usual gas chromatographic detectors, coupling with MS was achieved using direct introduction systems. The restrictions typical of capillary SFC, such as the low sample capacity which also reduces the efficiency of the mass detection, has limited applications of this technique. SFC-NMR The coupling of NMR with SFC was reported in 1994 [184] and an on-line SFCNMR system proposed in 1995 where SFC processes of roasted coffee and black pepper samples were monitored using 2D 1H NMR spectra [185]. The temperature and pressure conditions need to be maintained to have the mobile phase in supercritical form in the flow-cell but the problem with solvent signals is eliminated compared to LC-NMR. HILIC-MS(ESI) A technique known as Hydrophilic Interaction Chromatography coupled with ESI ionisation mass spectrometry (HILIC-MS(ESI)) was developed in 1999 to meet the need of evaluating highly polar natural products that cannot be retained on traditional reversed-phase stationary phases [56]. Specifically, amide, polyhydroxyethyl aspartamide and cyclodextrin based packings provided superior performance for the analysis of a set of polar natural product compounds where the properties of the mobilephase buffers also greatly impacted on the separations. LC-ICP-MS The hyphenation of (RP)LC and Inductively Coupled Mass Spectrometry (LC-ICPMS) has become a routine methodology in many laboratories. The technique is most popular for the study of metal-containing compounds but is also well suited for the analysis of halogen, P- and S-containing compounds. RECENT ADVANCES AND SPECTROSCOPIC TECHNIQUES

THE

FUTURE

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HYPHENATED

NMR Probe Developments Most recent major NMR probe developments include the “cryo-probe”, the use of small-scale micro-coils for data acquisition of very small samples, and the introduction of multiplex probes. The most significant recent advance has been the cryogenic cooling of the NMR radio frequency coils and electronics to give greatly enhanced sensitivity. The first cryogenic probe built in flow configuration and its application in an LCNMR-MS study of acetaminophen metabolites in urine was reported in 2003 [186]. Previously undetected metabolites of acetaminophen were directly observed in a 15minute on-flow experiment using 40% less material than formerly reported. The probe provides superior sensitivity over conventional non-cryogenic flow NMR probes, allowing analysis of lower concentrations of metabolites or natural products. The strategy is applicable to samples containing mass-limited analytes, such as natural product extracts. NMR detection limits have advanced significantly with the recent introduction of the so-called cryo-probes (Varian Inc. and Bruker Biospin) whereby the probe electronic

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components are cryogenetically cooled to approximately 20 K but the sample remains at ambient temperature. Recently, commercial LC-NMR-MS systems involving the use of this cryo-probe technology have become available and when used in an LC-SPE-NMRMS system, the enhancement is increased by about 20-fold and similar enhancements are achieved in 2D-LC systems. Most of these innovations were necessary to increase the sensitivity of NMR detection compared to MS. The importance of MS data in these combined experiments should not be underestimated as in many cases correlation of molecular ion masses with NMR data is sufficient for compound recognition. This can be achieved at low resolution using an ion trap or single quadrupole mass spectrometer or in high-resolution mode for accurate mass determination with a TOF mass detector. In other experiments, the NMR structural data is insufficient, so the full MS or MS-MS spectra are recorded to aid compound identification. The decision to record MS-MS spectra can be made automatically when a certain condition is met, such as the appearance of a particular molecular ion. Such data-dependent scanning is also available in NMR spectrometry in a different form. NMR data systems can be programmed to recognise a certain combination of peaks in an on-flow run and then initiate a stop-flow run in 2D NMR mode for improved sensitivity. IFC-Interchangeable-Flow-Cell Probes One common problem with flow NMR is that after the probe has been used for thousands of samples, the sample cell can become contaminated. One of the first symptoms of a contaminated sample cell is that the quality of solvent suppression becomes degraded and, as has been suggested in Keifer’s review [70], this occurs because the contaminants create a magnetic-susceptibility distortion that degrades the NMR line shape. Efforts to rigorously wash the cell are not always successful, and it is advantageous to allow the user to change the flow-cell. This capability became available with Varian’s Interchangeable Flow-Cell (IFC) probes. The IFC probe design allows users to change the flow-cell as well as to acquire NMR data without the flow-cell in place. In the latter situation, the probe behaves as a micro-probe. The dual-purpose nature of the IFC probes not only allows a user to service their own flow probe, but also allows the probe to be a fully functional high-resolution probe, even if a new clean flowcell is not available. A limitation of DI-NMR is that repetitive injections can eventually clog the NMR flow-cell. With the development of the user-changeable flow-cells this has been addressed and led to the interchangeable flow-cell probe. Larger Probes Probe and Hardware Developments A larger volume (120 µL) flow probe has been optimised for NMR screening applications using 15N-HSQC data and DI-NMR methods [187]. Smaller Probes Micro-coils Micro-coils are NMR receiver coils with diameters ≤ 1mm and wrapped directly onto the capillary that contains the sample. Although micro-coils have been employed for

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over 20 years, their direct application to capillary-scale analytical separations and to high resolution NMR spectroscopy did not occur until the mid-1990s [188-190]. A four-coil flow-through multiplex sample NMR probe was described in 1999, with potential to increase throughput [191]. Further probe development involving small-scale micro-coils has allowed NMR data to be acquired on samples ranging in size from roughly 1 µL down to 1 nL. The primary justification for this development was to enable applications in flow NMR, more specifically to allow NMR data to be acquired with capillary HPLC and capillary electrophoresis applications. Several reports have discussed the applications of smaller-volume ‘micro-coil’ flow probes that have active volumes of about 1-5 µL. One application is an analysis of a selected natural product library to identify known taxane compounds using 5-50 µg of compound dissolved in 3 µL of solvent [192]. A Triple-Resonance (TXI) (1H, 13C, 15N) high resolution capillary probe with 2.5 µL NMR-active sample volume was described in 2002 for applications to mass and volume limited samples and for coupling LC to NMR [193]. Miniaturised NMR applications have been reported with discrete capillary sample tubes using a 1 mm TXI microliter probe designed for a 600 MHz instrument. The limited sensitivity of the NMR detector often requires that on-line LC-NMR is performed in the stop-flow mode and, since NMR and HPLC operate on different time scales, so it could be preferable to collect HPLC peaks first and then analyse them one by one in the NMR probe. Off-line peak storage can be carried out using storage loops, solid-phase extraction cartridges or small LC columns. An alternative way is to use discrete sample tubes for the peak storage by using 1 mm capillary NMR tubes to store HPLC fractions. The NMR capillaries with micro-fractionated LC peaks can easily be collected and efficiently measured with a TXI probe using existing NMR automation and sample-changing routines. This off-line approach offers advantages such as the minimisation of potential dead volume effects caused by long transfer capillaries and by valve switching and fluidic problems. Also, LC peak dilution is kept to an absolute minimum, which is crucial for obtaining a good signal-to-noise ratio with mass-limited samples. LC peaks can be directly fractionated into 1 mm capillaries if fully deuterated eluants are used. Alternatively, if the separation is carried out using protonated solvents, the peaks can be temporarily “stored” in a well plate and the protonated eluant can be exchanged with deuterated solvent before transferring the LC peak into the 1 mm capillary. The fractionation system can be operated under inert conditions with a nitrogen or argon atmosphere to prevent sample decomposition. For some applications, such as extremely air and light sensitive samples, a closed on-line system is advantageous. The probe allows the measurement of 1D 1H NMR or 2D and 3D inverse heteronuclear NMR experiments with high sensitivity, speed and quality using only a few nanomoles (µg) of compound. Advances in Separations Capillary Separations Small scale hyphenated separation techniques, such as Capillary Liquid Chromatography (CLC), Capillary Electrophoresis (CE) and Capillary Electrochromatography (CEC), have revolutionised the ability to separate components in small samples. These techniques can provide faster analysis times, higher separation efficiencies and greater

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pre-concentration abilities starting from less material. Sample amounts as small as picomoles have been analysed using capillary-NMR (CNMR) techniques. Capillary Separations and Micro-coil NMR Probes Miniaturisation of separation techniques is potentially important in hyphenated NMR, particularly for mass-limited samples, such as natural products in drug discovery. Micro-coil probes have a high filling factor as the RF coil is wound directly onto the cell. Coupling capillary LC (C(HP)LC) and CEC or CE to these probes requires less sample and eluant and shorter analysis times [78,194]. A higher sample loading than CENMR is also achievable. Recently Bruker reported a commercial CLC-NMR system using a CNMR probe with a 1.5 µL active NMR volume in automated stop-flow mode to obtain 1H NMR spectra at 600 MHz with detection limits of 5-25 ng per drug metabolite in an extract of urine 4 hours after a 1 g dose of acetaminophen [195]. Undoubtedly, as the newer CNMR techniques become commercialised they will be used at the discovery stage for mass-limited samples. Capillary Isotachochophoresis (CITP) and CE have also been successfully coupled to NMR micro-coils for improved sample concentration and trace impurity analysis. In general, LC performed with columns of less than 0.5 mm diameter is considered CLC. Chromatographic peak volumes for CLC processes range from ~1 µL to ~100 µL [196]. CLC-NMR One of the requirements for CLC-NMR is that the sample needs to be soluble in a volume of approximately 5 µL or less, which is not always possible. Due to the small solvent volumes involved, most CLC-NMR experiments are performed with deuterated mobile phase, which eliminates the need for solvent suppression and allows access to the total chemical shift range. Another advantage of micro-column CLC techniques is an enhanced detection performance since there is a higher concentration of analytes for a given injected amount. To avoid any adverse effects of magnetic field on LC instrumentation, usually a long transfer line is required to couple the capillary column to the NMR probe but this is not a problem with shielded magnets. Miniaturisation of NMR Probes Hyphenated to Capillary Scale Separations The miniaturisation of NMR samples and hyphenation to a variety of capillary-scale analytical separation techniques including LC, CE and CITP has been described [197]. Capillary based LC and micro-coil NMR have compatible flow rates and sample volume requirements. A typical capillary LC on-column flow rate is 5 µL/min or less while the autosampler-injected analyte volume is 0.1 µL or more and accurate flow is achieved through a capillary of 50 µm i.d. The NMR flow-cell has a total volume of 5 µL and the micro-coil observe volume is 1 µL. A typical injected sample amount for CLC-NMR analysis of a small molecular weight compound is a few µg (nmol) or less. In addition CLC-NMR enables steep solvent gradients of water/organic mobile phases as high as 30% per min, to be used. Interfacing CE with nL volume NMR flow-probes has also been described. By electrophoretic concentration of dilute µL-volume samples into higher concentration nLvolume bands, CITP extends the range of feasibility for micro-coil NMR experiments. Apart from the concentration factor of up to two orders of magnitude that CITP offers, another is the ability to separate charged components in mixtures.

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The C(HP)LC-NMR separation of an extract of black beetles was carried out in which one hundred black beetles were extracted with methanol [198]. Continuous or onflow measurements showed the presence of two major compounds which were later assigned by stop-flow measurements to be 2-ethylbenzo-1,4-quinone and 2-ethyl-3methoxy-benzo-1,4-quinone. CE-MS CE is one of the most efficient separation techniques in liquid phase. The on-line coupling of CE-MS allows simultaneous exploitation of the high separation efficiency of CE and the identification capability of mass detection. The main drawback, which has limited the applications of CE-MS, is the use of very low sample volumes (nL range) and, as a consequence, the high detection limits in terms of concentration. Efforts to improve the sensitivity have included the use of different mass detectors such as TOF spectrometers and Matrix Assisted Laser Desorption Ionisation (MALDI) coupled to TOF (MALDI-TOF) and narrower capillaries or on-line preconcentration procedures. CE-MS has been used for the identification of a number of non-steroidal antiinflammatory drugs and their metabolites in SPE of human urine [199]. A variety of MS techniques were used including tandem mass spectrometry (MS-MS) to profile the extracts and negative ion ESI MS for their detection. Low cone voltages produced rapidly detectable [M-H]- ions while higher voltages allowed the production of a range of diagnostic fragments via in-source Collision Induced Dissociation (CID). A solvent compensation method based on FIA was used recently to obtain high quality NMR spectra with a solvent gradient. A binary solvent system containing D2O and CD 3OD with a 10% methanol per min solvent composition gradient was used with some observation of the NMR line broadening and chemical shift changes noted [81]. Creating a second equal but reverse gradient and combining the two solvent gradients before the NMR detector kept the composition of solvent reaching the NMR flow-cell constant. Using this approach, methods can be developed to generate high quality NMR spectra during on-flow gradient LC-NMR experiments. The ultimate applicability of this approach depends on the ability to compensate for the disturbance of the solvent gradient and reverse gradient by a pair of LC columns. Proposed Hyphenation The ultimate in multi-hyphenated spectroscopic techniques for natural product profiling would be LC-UV(DAD)-NMR-ELSD-MS-CD-FTIR coupled on-line to a bioassay, Fig. (5), using a cryogenic probe for increased sensitivity. The hyphenated operation begins after off-line LC optimisation of the separation with a consideration of suitable buffers in the mobile phase, which will not interfere with the individual spectroscopic techniques. The LC is coupled to a DAD to detect chromophores, but as an option a CLND can be used to selectively identify nitrogencontaining compounds. Separated peaks enter the cryogenic probe in the NMR using firstly the on-flow method for an initial profile run. In this initial run an overview of the analyte can be obtained as well as initial MS data. This also allows any necessary finetuning of the mobile phase. Here, the proportions need to be split to send approximately 90% to the NMR, 5% to the MS and the other 5% to an ELSD. The ELSD, being a

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Fig. (5). Schematic of proposed on-line hyphenated spectroscopic techniques coupled to on-line bioassay. Different options are available for the proposed hyphenation, such as: [1] Chemiluminescence Nitrogen Detector (CLND); [2] cryogenic probe; [3] Electrospray Ionisation (ESI) or Atmospheric Pressure Ionisation (APCI) mass spectrometry.

universal and quantitative detector, will be able to identify additional components not observed by the DAD or CLND. The second run would adopt the use of the stop-flow method using a multiple column-trapping method, followed by transfer to storage loops to obtain 1D and 2D NMR data. The separated compounds can be stored, if desired, in the loops until all analyses are completed. Again, a splitter is used in the stop-flow method but with a 95% to 5% split to the NMR and MS only or as previously mentioned, if using the ELSD. Once NMR acquisition is completed for a compound, then the sample is transferred out of the NMR flow-probe. At this point, the eluting compound enters another on-line splitting valve sending approximately 90% to the FTIR for functional group confirmation and 10% to the CD, enabling relative and/or

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stereochemical determinations. Finally, the compound is recovered from the FTIR via a fraction collector and, by robotic means, is transferred to a master microtitre plate. Once all the desired compounds are collected and transferred, the microtiter plate is evaporated to dryness in a vacuum chamber or by using a stream of nitrogen. From these, daughter plates are made and put through HTS or other bioassays for evaluation. While this may be efficient in terms of run time, sample size and data correction, an obvious disadvantage of such an extended hyphenated system is that it may be very inefficient in the utilisation of expensive spectrometers. It is not clear whether the benefits of such complex hyphenated systems outweigh the costs of assembling such an array of instruments. A single spectroscopic technique or any combination of hyphenated techniques will not always provide an unequivocal solution. This applies to both the dereplication and the characterisation of novel natural products. In addition, no single or multiple hyphenated spectroscopic approach will be able to completely study all constituents in a natural product extract, as this process is specific for the selectivity and sensitivity of the detector. In all dereplication strategies (hyphenated or non-hyphenated), a requirement is that specific databases need to be consulted. Other considerations, such as capillary separation methods, 2D-LC, SPE, 13C NMR and database extensions could be applied to hyphenated spectroscopic techniques to the dereplication process in the future. Future Hyphenations The possibilities for adding extra detectors to an LC-NMR-MS system include (HP)LC-UV-NMR-MS-FTIR, which has been successfully attempted [43]. LC-MS has been linked simultaneously to two MS detectors, such as ICP-MS and TOF-MS, to give an hyphenated system LC-UV(DAD)-ICP-MS-TOF-MS for the analysis of drug metabolites in rat urine [200]. Work is in progress to create LC-NMR-MS systems using ICP-MS alone and with the dual detectors ICP-MS-TOF-MS. ICP-MS is useful for the detection of specific atoms such as bromine, arsenic and selenium. Further additions that have been discussed include CD and fluorescence detectors as well as performing different separation technologies, such as SFC, CE or CEC, linked to multiple detectors. Capillary LC-NMR, CE-NMR and CEC-NMR will be increasingly employed since their operation at low flow rates will enable the use of fully deuterated solvents. High magnetic field strengths with cryogenically cooled NMR probes and preamplifiers provide unsurpassed NMR sensitivity. In 2003, the highest field used for LC-NMR-MS was 800 MHz [201] and LC-NMR has yet to be reported at 900 MHz. An alternative for increasing sensitivity on existing LC-NMR systems is the on-line SPE or 2D-LC add on, particularly for routine field strengths of 400-600 MHz. In the integrated LC-SPE-NMR or the 2D-LC-NMR systems the analytes are detected post-column by UV or MS and automatically trapped on the SPE cartridges in 96 well plate format or by trapping on a second miniature LC column in the case of 2D-LC-NMR. Multiple trapping of a given peak on a given SPE cartridge or a given second miniature LC column is possible. For LC-SPE-NMR the cartridge is dried under nitrogen and the contents are finally eluted from the cartridge into the NMR flow-probe. These are more

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economical procedures as non-deuterated solvents and a wider choice of HPLC buffers are now permissible for the chromatography with only the final transfer volume of 200500 µL using deuterated solvent. Exchangeable protons can be observed in the NMR spectrum, which can aid assignment, and, since the probe only receives the same deuterated solvent, shimming is trivial and solvent suppression is mostly not required. There is an automated wash and dry procedure so that cross-contamination is avoided. The signal-to-noise ratio is improved up to 6.8-fold on triple trapping compared with the conventional loop collection mode for a 60 µL probe at 500 MHz and the procedure is fully automated. As stated earlier, the cryogenic cooling of the RF coils and electronics to give greatly enhanced sensitivity is the most significant recent advance in NMR spectroscopy [186,202]. This is of critical importance in drug discovery from natural products with often mass-limited constituents present. A recent application of a cryogenic probe to the identification of acetaminophen metabolites in human urine using LC-NMR-MS, reported three metabolites previously undetected at 500 MHz in a 15-minute on-flow experiment [186]. MS data combined with stop-flow spectra for greater signal-to-noise ratios enabled unambiguous assignment of these compounds. LC-NMR-MS in automated loop-storage mode clearly provides a versatile analytical platform for complex mixture analysis such as natural product extracts. The most demanding structure determination problems require 2D and 13C NMR data and the continuing pace of SPE, 2D-LC and cryogenic probe developments will no doubt drive these applications forward. In the future, automated MS-directed LC-SPE-NMR-MS or 2D-LC-NMR-MS systems equipped with cryogenic probes should provide the state-ofthe-art in NMR sensitivity for natural product drug discovery. (HP)LC-13C NMR Two approaches under development in order to achieve LC- 13C NMR include the use of immobilised free radicals to reduce the apparent T 1 relaxation times and the other is to use the benefit of electron-13C magnetisation transfer by employing dynamic nuclear polarisation [90]. A modification of the design of the flow-cell could lead to a further increase in sensitivity wherein the addition of a proton RF coil for selective excitation of the protons before entering the 13C flow-cell enables the full build-up of the nuclear Overhauser effect (nOe) in a continuous or on-flow system. The combination of this NMR flow-cell design, together with the use of immobilised paramagnetic species, could lead to the realisation of continuous-flow 13C NMR spectra of separated species. Databases The chemical screening of extracts by various hyphenated spectroscopic techniques generates a large amount of information. In order to rationalise and use this approach efficiently with a high sample throughput, the challenge is to find a means to centralise all the data necessary for pattern recognition with reference to a library of standard compounds. In particular, LC-UV and LC-MS-MS or LC-MS n databases have to be built up and LC-NMR analysis should be used as a complement for studying, in more detail, compounds that are not found in these databases. Integration of high resolution on-line LC-bioassays is crucial in this strategy to permit an efficient localisation of the bioactive

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compounds in the crude extracts and allow their subsequent on-line, full or partial, identification. CONCLUSION Natural products will continue to be very important lead compounds. LC-hyphenated techniques play an increasingly important role as a strategic tool to support natural product investigations, while the last two decades have seen the development of sensitive hyphenated spectroscopic techniques for the analysis of natural product mixtures. Hyphenated techniques provide a great deal of preliminary information about the content and nature of the constituents of crude extracts, which is critical when large numbers of samples need to be processed and the isolation of known compounds is to be avoided. LC-MS analysis of crude extracts is not straightforward due to the great variety of constituents. No MS interface allows an optimum ionisation of all the metabolites within a single crude extract, since the response is compound dependent. Often different ionisation modes or different interfaces are necessary to obtain a complete understanding of the extract composition. Artefacts can also be formed within the LC-MS interface and may lead to incorrect molecular weight assignments. The combination of LC-UV and LC-MS information can be very helpful in the first step of dereplication, especially when this information is combined with taxonomic classifications for cross reference against natural product databases. LC-NMR allows for the recording of complementary on-line structure information, which is particularly important in situations when LC-UV-MS data are insufficient for unambiguous peak identification. Further hyphenation of other spectroscopic techniques, such as IR spectroscopy, for analyte identification has been demonstrated. In addition, other types of MS detection techniques will be increasingly used in (HP)LC-NMR-MS, such as TOF and ICR-MS, which allow accurate masses and, hence, empirical molecular formulae to be determined. Another development is the coupling of HPLC to inductively coupled plasma MS (ICP-MS) to provide a specific atom detector. The future trend to hyphenate multiple techniques, such as LC with NMR, MS and even IR, is expected to occur on the capillary scale. The ability to analyse additional nuclei, such as 13C, 31P and 15N, is expected to be implemented in the future to further increase the analytical utility of the hyphenated spectroscopic techniques currently available. The development of probes with multiple coils connected in parallel may result in the simultaneous acquisition of NMR data from several samples. With further improvement in sensitivity, on-line C(HP)LC-NMR in conjunction with C(HP)LC-MS and, further to this, the double hyphenation of C(HP)LC-NMR-MS are likely to be used as the major tools for the analysis of not only natural products but also to problems encountered in genomics, proteomics and drug metabolomics. ACKNOWLEDGEMENTS The authors gratefully acknowledge Dr R.A. Tinker for assistance in the preparation of this manuscript.

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ABBREVIATIONS NCI

=

National Cancer Institute

USA

=

United States of America

FDA

=

Food Drug Administration

AIDS

=

Acquired Immune Deficiency Syndrome

HIV

=

Human Immunodeficiency Virus

DNA

=

Deoxyribonucleic Acid

SAR

=

Structure-Activity Relationships

PKC

=

Protein Kinase C inhibitors

HTS

=

High-Throughput Screening

UV

=

Ultra Violet Spectroscopy

UV-Vis

=

Ultra Violet Spectroscopy and Visible spectroscopy

CD

=

Circular Dichroism

ORD

=

Optical Rotation Dispersion

NMR

=

Nuclear Magnetic Resonance spectroscopy

MS

=

Mass Spectrometry

IR

=

Infra-Red spectrometry

FT

=

Fourier Transformation

FTIR

=

Fourier-Transform Infra-Red

GC

=

Gas Chromatography

SFC

=

Supercritical Fluid Chromatography

SEC

=

Size-Exclusion Chromatography

HILIC

=

Hydrophilic Interaction Chromatography

IEC

=

Ion-Exchange Chromatography

TLC

=

Thin Layer Chromatography

MTT

=

Methyl Thiazoyl Tetrazolium chloride

HP(LC)

=

High Pressure Liquid Chromatography

RPLC

=

Reversed-Phase Liquid Chromatography

NPLC

=

Normal Phase Liquid Chromatography

ODS

=

Octa-Decyl Silane

HSCCC

=

High-Speed Counter Current Chromatography

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AED

=

Atomic Emission Detection

SPE

=

Solid-Phase-Extraction

SPME

=

Solid-Phase-Matrix-Extraction

MSPD

=

Matrix Solid-Phase Dispersion

PDA

=

Photo-Diode Array detection

DAD

=

Diode Array Detection

ELSD

=

Evaporative Light Scattering Detector

CLND

=

Chemiluminescence Nitrogen Detector

RI

=

Refractive Index

TSP

=

Thermospray

PB

=

Particle Beam

HN

=

Heated Nebulizer

APPI

=

Atmospheric Pressure Photo-Ionisation

ESI MS

=

Electrospray Ionisation Mass Spectrometry

API

=

Atmospheric-Pressure Ionisation

APCI

=

Atmospheric-Pressure Chemical Ionisation

TOF

=

Time-Of-Flight mass spectrometry

MALDI

=

Matrix-Assisted Laser Desorption Ionisation

CID

=

Collision Induced Dissociation

ESCI

=

Electrospray and Chemical Ionisation spectrometry

ICP

=

Inductively Coupled Plasma

ICR

=

Ion-Cyclotron Resonance

CITP

=

Capillary Isotachophoresis

FTMS

=

Fourier Transform ion cyclotron Mass Spectrometer

DI

=

Direct Injection

FIA

=

Flow Injection Analysis

ACD

=

Advanced Chemistry Development

WET

=

Water Suppression Enhanced through T1 effects

VAST

=

Versatile Automated Sample Transport sample changer

BEST

=

Bruker Efficient Sample Transfer

BNMI

=

Bruker-NMR-Mass spectrometry Interface

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nOe

=

nuclear Overhauser effect

COSY

=

Correlation Spectroscopy

DOSY

=

Diffusion-Ordered Spectroscopy

TOCSY

=

Total Correlation Spectroscopy

NOESY

=

nuclear Overhauser effect Spectroscopy

ROESY

=

Rotational nuclear Overhauser Effect Spectroscopy

HSQC

=

Heteronuclear Single Quantum Coherence Spectroscopy

HMBC

=

Heteronuclear Multiple Bond Coherence Spectroscopy

PFG

=

Pulsed-Field Gradient

SLP

=

Shifted Laminar Pulse

PEEK

=

Poly Ether Ketone

RF

=

Radio Frequency

MSPD

=

Matrix Solid-Phase Dispersion

TFA

=

Tri-Fluoro Acetic Acid

MTPA

=

Methoxy-(Trifluoromethyl)-2-Phenyl-Acetic acid

C(HP)LC

=

Capillary Liquid Chromatography

CNMR

=

Capillary NMR

CEC

=

Capillary Electro-Chromatography

CE

=

Capillary Electrophoresis

CITP

=

Capillary Isotachophoresis

TXI

=

Triple-resonance high resolution NMR capillary probe

IFC

=

Interchangeable Flow-Cell probes

H2O

=

Water

D2O

=

Deuterium oxide

CH3OH

=

Methanol

CD3OD

=

Deuterated methanol

CH3CN

=

Acetonitrile

H/D

=

Hydrogen/Deuterium exchange

2D

=

Two-dimensional

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The Role of Kinetics in High Throughput Screening for Drugs Agustina Gómez-Hens* and Mª Paz Aguilar-Caballos Department of Analytical Chemistry, Faculty of Sciences, “Marie Curie” Building Annex, Campus of Rabanales, University of Córdoba, 14071-Córdoba, Spain Abstract: A systematic study of the incidence of kinetics in high throughput screening for drug design and discovery is presented and discussed. This study includes dynamic aspects of the techniques and assays used in this complex research field, kinetic methods applied to the selection of drug candidates, and recent advances in the elucidation of drug-receptor interaction mechanisms and in high throughput pharmacokinetic screening.

INTRODUCTION Combinatorial technologies have given rise to the availability of large compound collections from which physiologically active drugs can be obtained. Also, there are an increasing number of new molecular targets emerged from advances in molecular biology and the development of genome and proteome programs. As a result of this situation, improvements in high throughput screening (HTS) capabilities are required to evaluate more compounds active against more targets and to attain the correct selection of drug candidates in the early step of the complex drug discovery process. Many of these HTS assays are based on the use of techniques or methodologies in which kinetic aspects play a significant role so that they require the control of time-dependent variables to obtain adequate results. Homogeneous formats are typically used in these assays, avoiding separation and washing steps and allowing the rapid analytical throughput for kinetic characterization. This characterization is required because kinetics and structure are interrelated as optimum kinetics are dependent on physicochemical properties. Absorption, distribution, metabolism and excretion (ADME) are essential kinetic processes in drug discovery. Thus, drug efficacy depends on the oral delivery rate and also, on first-pass metabolism rates and liver or renal clearance rates. Drug metabolism can give rise to clinically active or toxic metabolites as well as drug-drug interactions. The kinetics of formation and clearance of each metabolite are important parameters in the global profile of a drug. The understanding of metabolic rates is essential to explain the results obtained from in vivo experiments, and also to develop modeling strategies suitable for the prediction of preliminary lead selection and/or optimization [1]. All these studies are required because about 40% of drug candidates fails in clinical trials due to inadequate pharmacokinetic and metabolism properties [2]. A number of in vitro, in vivo *Corresponding author: E-mail: [email protected] Garry W. Caldwell / Atta-ur-Rahman / Barry A. Springer (Eds.) All rights reserved – © 2005 Bentham Science Publishers.

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and in silico approaches has been described to achieve a high throughput pharmacokinetic screening [3]. Many HTS assays for metabolic screening of small drugs are frequently based on the use of end-point measurements of enzymatically produced products because of the easier automation of steady-state assays whether compared to kinetic assays [4]. However, instruments that can perform kinetic assays for metabolite identification are now commercially available, which contribute to improve the selectivity of some traditional enzymatic assays. The aim of this article is to emphasize the kinetic aspects involved in the different techniques and methodologies applied in HTS, to present an overview of the most recent kinetic methods reported in this research area and to highlight the importance that kinetics have on the whole drug discovery. DYNAMIC ASPECTS OF TECHNIQUES AND ASSAYS USED IN HTS Many analytical techniques or approaches are perceived to be of kinetic nature or to involve key kinetic components. Thus, chromatography and electrophoresis are differential migration techniques in which thermodynamic and kinetic aspects are responsible of the final separation. The chromatographic separation occurs as a result of repeated sorption/desorption processes during the movement of the sample components along the column, so that the differences in the distribution constants of the individual components allow the separation. However, kinetics play a double function as it is necessary to take into account the time required to reach each distribution equilibrium and the differential displacement rate of the sample components, which would be the last responsible of the separation process. Several kinetic factors contribute to the band broadening, which determines the chromatographic efficiency. Thus, a major source of band broadening in chromatographic separations is the resistance to mass transfer in both the stationary and mobile phases, which prevents to reach an instantaneous equilibrium. Also, molecular diffusion, which is a time-dependent process of equalizing concentration and is an important physical kinetic process, contributes to band broadening, increasing its effect with the amount of time the solute spends in the column. Liquid chromatography (LC) and capillary electrophoresis (CE) are widely applied in HTS for drug discovery as they allow to obtain information about the biological activity of large series of compounds, including binding to selective targets such as enzymes, receptors or membrane proteins [5]. Both techniques have been also applied to the separation of drug enantiomers [6], which is of great interest in the pharmaceutical industry to have enantiomeric pure compounds available. One of the most useful detection systems in LC is mass spectrometry (MS) as it allows a large number of compounds to be rapidly screened. For instance, the usefulness of LC with tandem MS (LC/MS/MS) has been shown in HTS for the determination of selected estrogen receptor modulators in human plasma, reaching a sample throughput of 2000 samples/h [7]. The shape and quality of the analytical signal in flow systems, such as unsegmented continuous-flow systems, usually named flow injection analysis (FIA), are directly influenced by dispersion, which occurs as a result of mass transfer and mixing during sample-reagent(s) transport by the carrier stream to a detector. Axial and radial

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diffusion, which is the most significant mechanism of mass transport, greatly contributes to dispersion in these flow systems, together with convection, which is another timedependent process of equalizing density and temperature. Both diffusion and convection processes can be altered when chemical reactions occur during the transport. Measurements in flow systems are obtained when neither physical (homogenization) nor chemical equilibrium have been attained by the time that the sample zone reaches the continuous detector, so the corresponding determinations are doubly kinetic in nature. An example of the application of a FIA system in HTS is the flow probe proposed for the direct transfer of the sample from a reservoir into a NMR detector, obtaining a significant increase in the sample throughput, which is of interest for screening of candidate drug compounds [8]. All luminescent phenomena are processes of an intrinsically kinetic nature as they involve the emission of ultraviolet, visible or near-infrared radiation from a molecule or an atom resulting from the transition of an electronically excited state to a lower energy state, usually the ground state. For instance, in photoluminescence processes, which require the use of electromagnetic radiation as the exciting source and the transition from a singlet (fluorescence) or a triplet (phosphorescence) electronically excited state, measurements are carried out under conditions of dynamic change controlled by the rates of deactivation processes that follow the excitation. The excited states responsible for luminescence phenomena have finite lifetimes that can be measured by applying time-resolved methodologies and used as additional analytical parameters. The temporal information given by fluorescence lifetime can be usually employed in combination with other parameters to identify compounds. Also, if two or more luminescent compounds have similar absorption or emission spectra but different luminescence decay times, the compounds can be determined by differential kinetic analysis. The resolution of spectrally similar fluorophores based on differences in lifetime is suitable when other methods for simultaneous determination fail, when it may be difficult to separate the components in the sample or when the chemical treatment of the sample may increase analysis time or introduce contamination. It is very unlikely that two components will have the same lifetimes as well as the same excitation and emission spectra. Luminescence-based assays have gained widespread acceptance and growing incorporation into HTS programs [9-13]. They have emerged as an alternative to radiolabel-based assays as they approach the sensitivity of radioactive detection along with ease operation, which makes them amenable to miniaturization. Fluorescent and chemiluminescent techniques such as fluorescence polarization (FP), fluorescence correlation spectroscopy (FCS), time-resolved fluorescence resonance energy transfer (TR-FRET) and bioluminescence resonance energy transfer (BRET), offer the advantage of a homogeneous format, which is usually the format of choice for HTS and can be developed in microtiter plate readers. The advantages and limitations of several of these techniques for the establishment of miniaturized homogeneous screening assays have been widely discussed [9,11]. FP spectroscopy involves kinetic aspects as measurements are related with the timeaveraged rotational motion of molecules. When a molecule is excited by polarized light, the emitted light will also be polarized provided than the molecule does not rotate during the time elapsed between excitation and emission. The emission of polarized radiation from this molecule will mainly depend on the lifetime of the excited state compared with the time required for rotational motion, as well as on environmental variables such as

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viscosity and temperature. Small fluorescent molecules rotate rapidly, and normally exhibit no fluorescence polarization, while the rotation motion of macromolecules is slowed down and the fluorescence remains polarized. Thus, if small fluorescent molecules bind to larger molecules, their rotational diffusion is reduced and the retention of polarization is correspondingly increased, Fig. (1). For typical fluorescent molecules such as fluorescein, polarization is not observed if the molecule is rotating rapidly in solution under the conditions typically used in biological assays, such as aqueous buffers and room temperature. If the fluorescence polarization of a fluorescein-labeled ligand is measured, a low polarization will be observed when the ligand is free in solution, and a high polarization will be observed when the ligand is bound to a macromolecule such as a receptor or antibody, so that the extent of binding can be obtained.

Fig. (1). FP principle. (F: fluorescent label).

FP is usually expressed as the degree of polarization: mP = 1000 [(A-B)/(A+B)], in which A and B are the fluorescence intensities measured in the planes parallel and perpendicular to the plane of the incident polarized light. This radiometric measurement minimizes variations caused by fluctuations in lamp intensity or interferences caused by fluorescence quenching. No biological system can show polarization below 0 mP or greater than 500 mP. If a value outside this range occurs, it is a clear sign that there is an error, either in the instrument or, more likely, in the elements present in the assay sample, such as highly fluorescent or scattering compounds. FP technology has been used in basic research and commercial diagnostic assays for many decades, but has begun to be widely used in drug discovery only in the past few years. Originally, FP assays for drug discovery were developed for single-tube analytical instruments, but the technology was rapidly converted to HTS assays when commercial plate readers with equivalent sensitivity became available. Homogeneous FP has been implemented in instruments for HTS, using 96-, 384- or up to 1536-well plates, which enables a new range of FP assays to be carried out, showing that miniaturization is an

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inherent capability of FP. These instruments measure accurately the polarization of fluorescein at concentrations below 100 pM with a precision better than 7 mP [14]. The extent of interference in FP assays will vary depending on the nature of the compounds being screened. Thus, fluorescent compounds can cause interference, but the use of redshifted fluorophores instead of the commonly used fluorescein may be the best way to minimize fluorescent interferences as well as light scattering [15,16]. A number of FP assays for drug discovery research has been described, which include ligand-receptor binding and enzyme assays [17-23]. A multiplexing assay, which allows to monitor different parameters in a single assay volume, has been described using FP for screening steroid hormone receptors [24]. The assay relies on the displacement of spectrally distinct fluorescent ligands (tracers) from recombinant human estrogen receptor alpha and progesterone receptor ligand-binding domain. The binding of a test compound to its corresponding receptor can be established by a decrease in FP of the tracer that is specific to that receptor. Independent confirmation of binding to each of the receptors is possible because of the distinct spectral properties of the tracers. Kinetics are also present in time-resolved methods based on the use of chemical systems with relatively long luminescence lifetimes, in which measurements are obtained in the phosphorescence mode, using preset and gating times. Lanthanide chelates, mainly europium(III) and terbium(III) chelates, have been widely used in these methods because they exhibit a special behavior as a result of the intramolecular energy transfer from the excited triplet state of the ligand to the emitting level of the central ion. This process, named lanthanide-sensitized luminescence, gives rise to a large Stokes shift and narrow emission bands, affording the spectral discrimination of the analytical signal. Long-lived emissions are usually monitored at a fixed time after flash illumination, which enables the temporal discrimination of the analytical signal, avoiding scatter, Raman and any fluorescent background signals. Also, this timeresolved mode increases the analytical signal as it is integrated over a longer period than in the fluorescence mode, which results in improved detection limits [25,26]. Most applications of lanthanide-sensitized luminescence in HTS involves the use of fluorescence resonance energy transfer (FRET). FRET is a versatile approach in which a fluorescent donor transfers its electronic energy non-radiatively to an acceptor, which reemits light at another wavelength. As a result, the fluorescence intensity of the donor decreases, while the fluorescence of the acceptor increases. This process only takes place if the emission spectrum of the donor molecule and the absorption spectrum of the acceptor molecule overlap sufficiently. The efficiency of the process depends on the distance between the donor and the acceptor, which should range between 1 and 10 nm, and on their relative orientation. The direct coupling of the donor and the acceptor is unnecessary if the fluorescence lifetime of the donor is higher than the duration of the energy-transfer process. The energy transfer rate constant, ket, depends on the inverse sixth power of the distance between the fluorophores involved in the coupling: ket = (1/τD) (R 0/R)6, where τD is the donor fluorescence lifetime, R0 the characteristic transfer distance or Föster distance and R the actual distance between donor and acceptor. The FRET efficiency (E) can be deduced from the amplitude-averaged lifetimes of the donor in the presence (τDA) and absence (τD) of the acceptor: E = 1- (τDA/τD) [11]. One of the first homogeneous fluorescence assays applied in HTS was based on the use of FRET between two visible-

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wavelength dyes, such as fluorescein and tetramethylrhodamine, but the presence of autofluorescence interferences has restricted its use [11]. However, this limitation can be avoided using FRET in association with time-resolved fluorescence (TR-FRET), which has allowed the design of a homogeneous technology suitable for HTS applications. A lanthanide chelate, usually a europium cryptate chelate, characterized by a long lived fluorescence emission is used as donor and a cross-linked allophycocyanin, a 105 kDa phycobiliprotein, is used as acceptor, Fig. (2). The basics of this technology and their applications to the study of molecular interactions, including HTS, have been widely reviewed [27,28]. Several applications of FRET and TR-FRET in HTS have been described involving many of them enzymatic assays [9,10,29-31], which are commented below. Miniaturized homogeneous immunoassays have been described using TR-FRET, which can be suitable for HTS [32,33]. Human interleukin-13 (IL-13), which was secreted from NK3.3 cells stimulated with interleukin-2, was detected using biotinylated anti-IL-13 monoclonal antibody, europium cryptate-labeled different anti-IL-13 monoclonal antibody and crosslinked allophycocyanin-conjugated with streptavidin [32]. The assay was carried out using 384-well assay plate, in which both cell stimulation and FRET detection can be done, successively. The detection limit of IL-13 was estimated to be less than 600 pg/ml. The method can be suitable for screening IL-13 production inhibitors and discovering anti-allergic drugs. Interferon-γ (IFN-γ) has been also determined using a similar method [33] in which the reagents are added to microplate wells where NK3.3 cells are being cultured and the production of IFN-γ was stimulated with interleukin-12. This assay was applied in HTS for IFN-γ production inhibitors. A TR-FRET assay has been recently described for the identification of inhibitors of heatshock protein 90 (Hsp90), which is required for the stability and function of a number of proteins, many of which are involved in cancer development [34]. This assay allowed the identification of several potent and reversible inhibitors. Fluorescence correlation spectroscopy (FCS) is another fluorimetric technique suitable for miniaturized HTS using homogeneous assay formats [35]. FCS is based on the measurement of fluorescence fluctuations, which can be due to the diffusion of the fluorophore in the excitation volume or to a change of the fluorescence quantum yield because of a chemical reaction. The burst on fluorescent emission of a molecule passing through a small volume of space defined by a sharply focused laser beam, typically one femtoliter, is measured. The photons emitted in each burst are recorded in a timeresolved mode by a highly sensitive single-photon detection device. These measurements are carried out using confocal optics to provide the highly focused excitation light and background rejection required for single molecule detection. This technique can be used to measure kinetic properties of single molecules in drops of solutions or in cells and to measure diffusion coefficients and chemical reaction rates, taking advantage of the differences in the translational diffusion of small versus large molecules. Small molecules diffuse rapidly through the volume and thus yield short bursts of light. Binding of these small molecules to larger molecules reduces their translational diffusion and correspondingly increases the duration of the light bursts. Thus, molecules of different size, and hence different diffusion coefficient, remain in the detection volume for different periods of time. Deconvolution of the emission patterns in a sample by appropriate software can yield the relative amount of the bound and unbound states of a fluorescently tagged ligand. This technique is sensitive to

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fluorophore concentrations in the nanomolar to femtomolar range, requiring that the lifetime of the fluorophore is less than its diffusion time through the confocal volume. Some applications of FCS involve the measurement of receptor-ligand interactions, DNA-protein interactions, nucleic acid hybrid formation and various enzymatic reactions [35-37]. A better selectivity can be obtained using dual-color fluorescence cross-correlation spectroscopy [38,39]. Although the instrumentation required is more complex as two coaxial laser beams are required, it allows to detect molecules that bear two different fluorescent labels. These fluorophores should have excitation and emission spectra that do not overlap to avoid energy transfer as well as cross-talk between the two channels. This technique has been employed to analyze kinetics of nucleic acid and peptide modifications catalyzed by nucleases, polymerases and proteases [39]. Chemiluminescence (CL) is probably the most markedly kinetic process of the luminescent phenomena as the factors affecting the emission intensity are a combination of luminescence and chemical reaction rate aspects. Molecules in the electronically excited state are produced by a chemical, biochemical (bioluminescence, BL) or electrochemical (electroluminescence) reaction, so that the emission intensity, IL, is directly proportional to the rate of the reaction involved, dC/dt, in molecules reacting per second, according to the equation: IL = ΦL (dC/dt). The proportionality constant ΦL is the CL quantum yield or efficiency, in photons emitted per molecule reacting. This CL efficiency is the product of the excitation quantum yield, expressed as excited states produced per molecule reacting, and the emission quantum yield, expressed as photons emitted per excited state. Although the lifetimes of the excited singlet states that are responsible for CL and BL emissions have typical durations in the nanoseconds region, the emission of light persists for as long as the CL or BL reaction takes place. Thus, the photophysics of the electronically excited products of the reaction and the kinetics of the reaction are involved in the luminescence emission. Two important factors to be considered in developing a luminescent method are the efficiency of the luminescent reaction, which ultimately affects sensitivity and detection limits, and the reaction kinetics, which dictates precision and throughput. In practice, both parameters can be affected by experimental conditions such as solvents, concentrations, pH and reagent purity. A significant advantage of CL and BL assays is that light is emitted by a specific reaction involving the analyte, which avoids the background signal from the sample matrix usually present in fluorimetric techniques. Taking into account that luminescence measurements are dynamic in nature, because they are based on the detection of a transient light emission, all CL and BL methods might be classified as kinetic methods. The analytical parameters most frequently employed in these methods are the peak intensity and the integrated area under all or a part of the light emission-time curve, requiring in both instances the control of the interval between initiation of the reaction and acquisition data. The usefulness of CL and BL in HTS has been recently reviewed [40]. Several applications have been focused to the determination of inhibitors of various enzymatic systems [41-46], some of which will be commented below. Firefly luciferase is widely used as reporter for monitoring promoter activity in the control of gene expression. Luciferase catalyzes the ATP-dependent oxidation of luciferin generating a flash of

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green light, with maximal emission at 563 nm. This system has been used in HTS to screen for drug candidates affecting a specific aspect of cellular physiology. A BL assay suitable in HTS has been described using the luciferase/luciferin system for the determination of antimycobacterial drugs in vitro and in infected macrophages [47]. Other BL systems applied in HTS involve the use of aequorin and the green fluorescent protein (GFP) [48]. A special BL methodology is BRET, which is a Föster resonance energy transfer process occurring from a bioluminescent donor protein to a fluorescent acceptor protein. When the donor and the acceptor are brought into close proximity to one another (in the order of 1-10 nm) and are correctly oriented, the former transfers its energy directly to the latter in a nonradiative way. Since the acceptor emits light at a different wavelength than the donor, the energy transfer can be easily detected by measuring the ratio of the acceptor emission intensity to the donor emission intensity. BRET allows to monitor protein-protein interactions and intracellular signaling events in live cells. It is theoretically applicable to the study of the activation state of any receptor that undergoes polymerization or conformational change, as the process strictly depends on the molecular proximity between donor and acceptor. In a BRET system, the first protein partner is fused to Renilla luciferase (Rluc), whereas the second protein partner is fused to a fluorescent protein such as the yellow fluorescent protein (YFP)] [49], which is a yellow mutant of the GFP. If the two partners do not interact, only one signal can be detected after addition of the luciferase substrate coelenterazine which is oxidized, giving rise to a blue luminescence flash with emission at 485 nm. If the two partners interact, a resonance energy transfer occurs and an additional signal emitted by the YFP at 530 nm can be detected, Fig. (2).

Fig. (2). FRET and BRET principles. (EuCh: Eu-cryptate chelate; AL: allophycocyanin; Rluc: Renilla luciferase; Coe: Coelenterazine; Coeox: oxidized coelenterazine.

BRET and FRET are two analogous methodologies, but they show some differences [49]. BRET eliminates the need for an excitation light source and its associated problems such as high background caused by the autofluorescence emitted by endogenous sample

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components and photobleaching of the donor fluorophore, which results in the loss of signal with time [50,51]. Also, the overlapping absorption and emission spectra of the fluorescent donor used in FRET could give rise to the direct excitation of the acceptor fluorophore, which would complicate the interpretation of the results. However, FRET permits, under microscopic observation, visualization in a single living cell of proteinprotein interactions at the subcellular level [52], which is difficult to perform with BRET methodology. BRET has been used to monitor the activity of the insulin receptor [53,54], which is a glycoprotein composed of two α-subunits and two β-subunits linked by disulfide bonds. Binding of insulin to the α-subunits of the receptor induces the autophosphorylation of the β-subunits on tyrosine residues, which stimulates the tyrosine kinase activity of the receptor toward intracellular substrates, thereby allowing the transmission of the signal. In pathological states, such as diabetes and obesity, insulin effect on its target tissues is markedly reduced, which is often associated with a decrease in the tyrosine kinase activity of the receptor. The discovery of new molecules, capable of stimulating the tyrosine kinase activity of the receptor, may be of considerable importance for the treatment of insulin-resistant or insulin-deficient patients. Human insulin receptor of cDNA was fused to either Rluc or YFP coding sequences. The conformational change induced by insulin on its receptor could be detected as an energy transfer process, so that BRET signal parallels insulin-induced autophosphorylation of the fusion receptor [54]. Also, antibodies that activate or inhibit the autophosphorylation of the receptor have similar effects on BRET signal. The method can be applied in HTS tests for discovery of drugs with insulin-like properties as it allows to study the effects of agonists on insulin receptor activity. APPLICATION OF KINETIC METHODOLOGY IN HTS Kinetic methodology plays a significant role in HTS as about the half of all the marketed drugs act as inhibitors of enzymatic systems [55], in which kinetic parameters such as the apparent maximal rate (V max) and Michaelis-Menten constant (Km) values are important indicators of the interactions between a substrate and its corresponding enzyme. The inhibition effect of a drug is usually studied by measuring the decrease in the enzymatic activity, which is obtained by measuring the rate of the enzymatic reaction. The characterization of the type of inhibition (competitive, uncompetitive and noncompetitive), which is studied using kinetic measurements, is a step required in the design and development of new drugs [56]. A competitive inhibitor binds exclusively to the free enzyme, so that the inhibitor and substrate compete with each other for binding to the enzyme. Thus, for instance, enzyme kinetic measurements have recently identified to phenyl-thiazolylurea-sulfonamides as a new class of potent competitive inhibitors of bacterial phenylalanyl-tRNA synthetase [57], which is an essential enzyme that catalyzes the transfer of phenylalanine to the phenylalanyl-specific tRNA, a key step in protein biosynthesis. Also, the kinetic study of fluorogenic substrates for the protease activities of botulinum neurotoxins (BoNTs), which are zinc metalloproteases that cleavage neuronal proteins involved in neurotransmitter release and are among the most toxic natural products known, has allowed to characterize a new competitive inhibitor of BoNT B protease activity [58]. Taking into account that Km defines the substrate concentration at which the half Vmax under steady state conditions is obtained, the

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inhibition would be more easily detected at substrate concentrations below Km. When the inhibition is uncompetitive, the inhibitor binds exclusively to the enzyme-substrate (ES) complex or to some species that occurs along the reaction pathway subsequent to the ES complex formation. In this case the inhibitor is more easily detected at substrate concentrations above Km. Finally, a noncompetitive inhibitor binds to both the free enzyme and the ES complex, or later species in the reaction pathway. This type of inhibitor is less sensitive to substrate concentrations than competitive and uncompetitive inhibitors are. Generally, for screening purposes where the aim is to identify a wide group of potential inhibitors and, also, it is not clear which type of inhibitor will be most effective in vivo, the assays are usually carried out at a substrate concentration equal to Km. Inhibition is usually quantified for screening purposes in terms of the IC50, which represents the concentration of inhibitor that reduces the reaction rate by 50% under specific assay conditions. As the inhibition is higher in the initial phase of the reaction than in the later stages, the initial rate would be the parameter chosen to study the inhibition mechanism as a better sensitivity can be obtained. However, the fixed-time method is more often used in HTS than the initial-rate method, which is justified to reduce cost. In this instance, the time point must be chosen in the initial phase of the reaction. A model to choose an appropriate substrate conversion for enzymatic assays in HTS has been given [59] in which the relationship between the IC50 value for an inhibitor and the percentage of substrate conversion using a first-order kinetic model under conditions that obey Michaelis-Menten kinetics has been obtained. The 384-well microplate format is the dominant format of kinetic assays for HTS, although the use of 1536-well format continues to grow [60]. A microplate bioassay has been described for students to learn the principles and techniques used by drug discovery HTS researchers including enzyme inhibition, Michaelis-Menten kinetics and Lineweaver-Burk plots [61]. This drug discovery experiment involves the determination of the dissociation constant for inhibitor binding of the carboxypeptidase A inhibitor, 2benzylsuccinic acid, using kinetic methodology. Kinetic studies carried out in a microtiter plate have shown the usefulness of several 5,5’-dithiobis(2-nitrobenzamides) as alternative substrates for trypanothione reductases and thioredoxin reductases, which are enzymes central to cellular thiol metabolism and related to psoriasis, cancer, and autoimmune diseases [62]. The natural substrates of these enzymes are very expensive and difficult to obtain, while the proposed substrates can be easily synthesized. They are converted to their corresponding chromophoric thiolates, using colorimetric measurements to obtain enzyme activity values. The method is amenable to automation and suitable for inhibitor screening. Flow systems are also an alternative option useful for the determination of enzymatic inhibitors in HTS. Thus, a fluorescence flow injection assay has been described for determining the catalytic inhibition of DNA topoisomerase II [63], which is an ATPdependent nuclear and mitochondrial enzyme that alters DNA topology by catalyzing the passing of an intact DNA double helix through a transient double-stranded break made in the second helix. This enzyme is the target for a number of the most important anticancer drugs. The proposed method is faster and more sensitive than the agarose gel electrophoresis and radioactive centrifugation assays [64].

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Protein kinases are an important group of targets for drug design as they play crucial roles in the regulation of many signal transduction pathways and aberrant activities of these enzymes have been implicated in several diseases such as cancer, inflammation and immune disorder. However, the finding of selective and safe inhibitors is difficult as their active sites share a high level of similarity. A recent review summarizes the literature on chemical libraries towards protein kinase inhibitors [65]. The interest in the identification of new inhibitors of these enzymes can be shown through the numerous methods recently described [21,41,42,66-69]. For instance, a series of indenopyrazolebased cyclin-dependent kinase (CDK) inhibitors has been studied [67]. Kinetic data showed that these compounds are competitive with respect to ATP and bind in the kinase ATP pocket. A series of semicarbazide-based inhibitors are highly potent against CDK2 and CDK4 while maintaining selectivity against other relevant serine/threonine kinases. Also, there are several kinetic assays for screening drug candidates as potential inhibitors of cytochrome P450 (CYPs) isoenzymes [70-72]. These isoenzymes are involved in the oxidative metabolism of more than 50% of all clinically administered drugs as they play an important role in metabolizing and detoxifying endogenous and exogenous compounds. Polymorphic variants of these isoenzymes can affect the metabolism of some drugs, leading to toxic effects and adverse drug reactions. CYP2C9 is the principal human cytochrome P450 isoenzyme involved in the oxidant metabolism of many drugs, including nonsteroidal anti-inflamatory compounds. A kinetic method has been described for identifying compounds that are potential substrates for CYPs [73]. The method is based on the detection of the NAD(P)(H) consumption or generation in cells expressing a NAD(P)(H)-dependent target enzyme. Also, diverse fluorogenic substrates have been used as prototypic probes to obtain in vitro CYP2C9 metabolic rates and kinetic parameters, such as apparent Km, Vmax, and Vmax/Km ratios for allelic variants of CYP2C9 [72]. Measuring inhibition of the fluorescent signal in the presence of competitive drugs allows detection of isozyme-specific substrates and inhibitors. Several kinetic assays suitable for HTS have been recently described using fluorimetric techniques such as FP, TR-FRET and FCS [14,21,23,29-31,35]. For instance, FRET has been used for the assay of N-acyl hydrazone inhibitors of human immunodeficiency virus-1 (HIV-1) reverse transcriptase (RT)-associated ribonuclease H (RNase H) activity, which is an underexplored target for antiretroviral development [30]. The assay substrate was an 18-nucleotide-3’-fluorescein-labeled RNA annealed to a complementary 18-nucleotide 5’-Dabcyl-modified DNA. This RNA/DNA hybride substrate showed extremely low background fluorescence, but signal enhancements of approximately 50-fold were obtained upon complete hydrolysis by HIV-1 RT-RNase H. The fluorescein-labeled ribonucleotide fragment readily dissociated from the complementary DNA at room temperature with immediate generation of a fluorescent signal. A TR-FRET method has been described for the identification of diverse inhibitors of viral and bacterial helicases [29], which are an important class of targets for the development of novel anti-infective agents, as they are responsible for the unwinding of double-stranded DNA, facilitated by the binding and hydrolysis of 5’-nucleoside triphosphates. The usefulness of FP and TR-FRET in structure-activity relationship (SAR) studies has been shown using Src kinase as a model system [74]. Both techniques allow the detection of subnanomolar inhibitors of this enzyme.

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The determination of enzymatic inhibitors has been also proposed using CL and BL assays [40-46]. These methods are based either on the detection of the end products of the enzymatic reaction or the direct, real time evaluation of the rate of the enzymecatalyzed reaction through its coupling with a suitable luminescent system. The latter possibility allows not only enzyme inhibition measurements but also evaluation of the reaction kinetics, which is useful for the study of enzyme inhibition mechanisms. For instance, the fixed-time method has been used for the CL detection of protein kinase activity [41], which could be applied for identifying novel classes of protein kinase inhibitors. The assay involves the use of biotinylated enzyme substrate peptides captured on a streptavidin-coated microtiter plate and monoclonal antibodies to detect their phosphorylation. Another CL kinetic method has been described for the determination of acetylcholinesterase inhibitors using coupled enzymatic reactions involving acetylcholinesterase, choline oxidase and horseradish peroxidase, with luminol as the CL substrate [44]. Also, a gas phase CL analyzer has been used for the study of nitric oxide synthase activity and the estimation of the inhibition kinetics measuring the formation of nitric oxide [45]. The method is a suitable alternative to the use of radiolabeled materials. A BL method has been proposed for the screening of potential inhibitors of proteases using an aequorin fusion protein that incorporates an optimum natural cleavage site [46]. This protein was immobilized onto microtiter plate wells and used as the substrate for the HIV-1 protease, obtaining a decrease of the BL signal as a result of the proteolytic bond cleavage and the release of aequorin from the solid phase. The scintillation proximity assay (SPA) technology, which involves the use of microscopic beads impregnated with a scintillant and with receptor molecules immobilized on its surface, has been also applied in HTS involving enzymatic systems [69,71,75-77]. Thus, an assay has been developed for the HTS of large compound libraries to identify inhibitors of poly(ADP-ribose)polymerase-1 (PARP-1) [76], an important enzyme involved in DNA repair. The assay allows the determination of IC50 and is adaptable to kinetic evaluation of lead molecules. The mechanism of action of the assay requires the binding of PARP-1 to a double-stranded DNA oligonucleotide leading to the active enzyme. Using NAD(+) and (3)H-NAD(+) as substrate, activated PARP-1 synthesizes labelled poly(ADP-ribose) chains. Once the reaction is stopped, ADP-ribose polymers are brought into proximity with pretreated microplate wells, resulting in signal amplification, which is detected by a scintillation plate reader. Another SPA assay has been described for the identification of small-molecule inhibitors of STK15, a centrosome-associated serine/threonine kinase [77]. The signal to noise ratio obtained was three times better than the value obtained using a TR-FRET assay evaluated with the same reagents. Mass spectrometry (MS) is a useful technique to study enzyme kinetics and inhibition mode. Reaction products can be directly and quantitatively detected, eliminating the requirement of an intrinsic or extrinsic chromophore or fluorophore or a radioactive probe, or the use of secondary enzymatic reactions irrelevant to the target enzyme reaction. LC/MS/MS has been applied for routine screening of drug candidates as potential inhibitors of several human CYP isozymes [78,79]. A 96-well format was used to develop the enzymatic reaction, which was stopped after incubation, and the solution was analyzed by LC/MS/MS. The applicability of LC-MS to the study of enzyme kinetics and the evaluation of inhibitors has been also demonstrated using the

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enzyme uridine diphosphate N-acetyl-muramyl-L-alanine ligase (MurC), an essential enzyme in the bacterial peptidoglycan biosynthetic pathway [80]. Microchip CE is a recent alternative approach for the rapid screening of combinatorial compounds in enzyme inhibition formats [81-83] as the separations are faster than and comparable in efficiency to conventional CE. Microchannels with dimensions in the 10-100 micrometer range are fabricated in glass or fused-silica substrates using photolithography and etching techniques borrowed from the semiconductor industry. The pumping mechanism is electroosmotic, which provides accurate control of the small sample and reagent volumes required and eliminates the need for pump and valves. Microchip CE has been used with a model enzyme assay that involves the hydrolysis with β-glucuronidase (an acid hydrolase) of the fluorescein-β-Dglucuronide (FMG), which liberates fluorescein [82]. FMG and fluorescein are separated and fluorimetrically detected. Also, the inhibition of the enzyme by the competitive inhibitor D-saccharic acid-1,4-lactone was also determined. The usefulness of microchip CE for multiplexed screening has been shown by the electrophoretic separation of four cationic inhibitors of acetylcholinesterase [84]. The use of biosensors in HTS of drugs is a suitable option for monitoring real time interactions between biomolecules and drugs. Biosensors based on surface plasmon resonance (SPR) technology have been widely used to obtain kinetic parameters that may serve as useful indicators towards subtle differences in the binding strength [85]. SPR is a phenomenon occurring in a thin metal film when an incident light beam strikes the surface at a particular angle. Depending on the thickness of a molecular layer at the metal surface, the SPR phenomenon results in a graded reduction in intensity of the reflected light. This system uses polarized light and can detect slight changes in optical resonance that occur when molecules bind to or dissociate from an immobilized target molecule. Kinetic information on the binding interaction provides more information than equilibrium assays alone as it has been shown in the study of several enzyme-inhibitor interactions using these biosensors [86-88]. Thus, the performance of a commercial SPR biosensor has been evaluated analyzing the binding of a number of small-molecule inhibitors interacting with the enzyme carbonic anhydrase II [88]. The development of enantioselective enzymes is an interesting new approach that could have usefulness in HTS for the kinetic resolution of racemic mixtures [89-91]. The method involves the use of a wild-type enzyme that catalyzes a given reaction of interest but not enantioselectively. The gene that encodes the wild-type enzyme is first subjected to random mutagenesis using a molecular biological method. Upon inserting the library of mutant genes in an appropriate microorganism, mutant enzymes (variants) are expressed and individually screened for activity and enantioselectivity in the reaction of interest. The mutant gene of the optimal enzyme variant is then subjected once more to mutagenesis/expression/screening. This process identifies sensitive positions in the enzyme which are responsible for improved enantioselectivity. A lipase has been used as the catalyst in the hydrolytic kinetic resolution of a chiral ester. Also, electrochemical sensors based on potentiometry and amperometry have been used as detectors in enantioselective HTS of drugs using flow injection and sequential injection analysis techniques [92]. The usefulness of nuclear magnetic resonance (NMR) in the design of new pharmaceuticals, the characterization of drug-receptor interactions and metabolite

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identification has been described [93,94]. NMR has been used for characterizing the product or products of an enzymatic reaction and for gaining insight into the kinetics of the reaction [95,96]. Usually, these studies require high substrate concentrations owing to the low sensitivity of the NMR technique and only strong inhibitors could be detected. However, the NMR method called three fluorine atoms for biochemical screening (3FABS) has extended the capabilities of NMR enabling rapid, efficient and reliable highthroughput functional screening for the identification of enzymatic inhibitors [97]. The substrate is tagged with a CF3 moiety and 19F NMR spectroscopy is used for the detection of the substrate and product components. This approach has been applied to screen multiple enzymes at the same time using different CF3-containing substrates, which allows to study the selectivity of an inhibitor for one target enzyme in the presence of other enzymes of the same family. KINETIC ASPECTS OF DRUG-RECEPTOR INTERACTIONS Pharmacological role of receptor theory and its evolution has been reviewed recently [98]. G-protein coupled receptors (GPCRs) are seven transmembrane helical proteins that interact with molecules involved in the intercellular communication. Approximately 50% of clinical drugs and many abused drugs have GPCRs as their targets, which makes them specially interesting for drug discovery programs. Several models have been proposed to quantitatively simulate GPCRs behavior, such as the extended ternary model. This approach describes a receptor that can exist in both active and inactive states, depending on their ability to activate G proteins. Kinetic studies are used in pharmacology to know the dynamics of physical interactions between different parts of the signal transduction pathway. These studies are often carried out using membrane fragments and not whole cells even when there are two substantial differences: 1) membrane assays are more stable over the time; 2) they are not influenced by cellular processes such as receptor down-regulation, modification or desensitization. For these reasons, the results obtained in these studies can be biased [99]. Kinetic behavior of ligands is different for positive agonists, negative agonists or antagonists. Negative agonists bind more slowly than positive agonists because the receptor must release the G-protein and change to the inactive receptor conformation, which are two additional steps to the releasing of the tracer ligand and binding of the test ligand. Thus, the use of kinetic measurements can provide information about drug efficiency in GPCRs systems. There are receptors coupled to G protein prior to the binding of agonists. A kinetic model has been developed to study the effect of kinetics of receptor and G-protein association and dissociation on the predicted unoccupied sites [100]. It was observed that changes in the reaction kinetics can have effect on the dose-response curve, which cannot be observed using an equilibrium model [101]. There are two mechanisms of receptor actuation, as they can be degraded intracellularly or be recycled to the external surface in an active form. A mathematical approach based on the use of initial-rate equations for the recycling process can be derived from steady-state approaches to enzyme-substrate interactions and from a method for multi-step reactions [102]. This model has been validated using the endocytosis of trapped label (14C-sucrose-LDL) by the LDL receptor of cultured hepatic (Hep-G2) cells. The use of kinetic methodologies for investigating neurotransmitter rapid chemical reactions on cell surfaces in the microsecond-millisecond time region using laser has

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been reviewed [103]. Further literature on drug-receptor interactions can be found in some revision articles [104-106], and also some kinetic models encompassing receptormediated endocytosis have been developed [107-111]. There are many real time methodologies used in HT drug-receptor interaction studies. Receptor activity can be directly or indirectly measured after drug-receptor interactions as Table (1) shows. Table 1.

Real-Time Methodologies Used for the Study of Drug-Receptor Interactions Direct

SPR biosensors gene reporter assays

Indirect

First messengers Second messengers

GTP assays Intracellular calcium cAMP assays ion channels

Direct assays are based on biosensing systems using basically SPR measurements and on gene reporter assays using BL or fluorescent systems. Indirect measurements are based on systems involving the determination of first or second messengers, such as guanosine, 5’-triphosphate (GTP) [112,113] or cyclic adenosine monophosphate (cAMP) [112,114,115], intracellular calcium [116-118] or other ion channels [119-122], respectively. SPR biosensors have been widely reported for the kinetic analysis of ligand-receptor interactions [123-125]. The use of kinetics gives the opportunity to optimize lead compounds based on binding rates, which are likely to be important aspects of drug potency. Rate constants (ks) can be calculated using the following equation [126]: (dRU/dt) = Req (1 – exp (-ks)(t – to)), where RU is the arbitrary binding unit (resonance unit), t o is the time at the start of sample injection, and Req is the equilibrium response. Since k s = k ass C + kdiss, the value of the association rate constant, kass was then obtained from the slope of the ks versus concentration plot, where C is the concentration of injected protein, and kdiss is the dissociation rate constant. This technique is also useful for the analysis of structure/function relationships of target/inhibitor interactions, providing more information than equilibrium assays alone. This fact was checked by the analysis of small molecules, such as sulfonamides, which are carbonic anhydrase inhibitors, using a commercial biosensor [88]. Measurements can be obtained in less than 100 s. Another technique which is also used for the biosensor technology is Plasmon Waveguide Resonance (PWR) [127]. It can be used to study kinetics of conformational changes associated to drug-receptor and G protein-receptor interactions for GPCRs. It has been found using this technique that kinetics of drug binding are distinct among various drug classes. These kinetic differences have been attributed to the participation of lipid bilayer in the agonist activation process, including changes in both protein conformation and bilayer structure, as experiments with βadrenoceptors demonstrate. GPCRs are very hydrophobic and they need a lipid environment to maintain their native conformation. A SPR method, referred as capture and reconstitution method, has been developed to assemble GPCRs onto a biosensor

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chip surface [128]. Human chemokine receptors CXCR4 and CCR5 have been used as model systems and captured in the presence of alkane groups. Structure-sensitive antibodies were used to check out the efficiency of reconstitution process, which is carried out in a lipid environment to maintain the structural and functional activity. The time required for a whole cycle takes around two thousand seconds and these biosensor systems can perform 200 assays/day. The binding of a ligand to GPCRs catalyzes the exchange of GTP to guanosine, 5’diphosphate (GDP) and the dissociation of the G-protein heterotrimer, giving rise to the GTP-bound α-subunit and free βγ-complexes to signal to downstream targets. This receptor activation process has been studied by using two luminescent techniques whose kinetic fundamentals have been discussed above, such as FRET [112] and TR [113]. In the FRET assay two GFP variants were covalently bound to different protein G subunits. When heterotrimer is intact, FRET intensity is maximum and it decreases when a ligand is bound as a consequence of the G protein disassociation. TR-FRET has been also applied to study the activation of nuclear receptors (NRs) [129], which are important targets for drug discovery as they form a group of ligand-dependent transcription factors that mediate the effects of hormones and other endogenous ligands to regulate the expression of specific genes. Peroxisome proliferator-activated receptor has been used as a model system for characterizing the ligand-dependent interaction between nuclear receptors and nuclear receptor coactivators. A TR membrane assay containing a receptor, an agonist, GDP and Eu-GTP showed that the activity of the receptor could be studied and the results obtained were consistent with those obtained using scintillation counting [113]. The use of fluorescence or BL detection techniques has allowed the real-time determination of receptors or the visualization of receptor trafficking inside the cell. A microfluidic system has been built up to use the luciferase reporter gene activity in the reporter cell line HFF11, based on HeLa cells as a model system [130]. This microfluidic instrument is based on the cascade of intracellular reactions, which ends in the expression of Photinus luciferase. This system continuously supplies fresh cell medium, influencing thus the fast kinetics. It seems that only a short ligand stimulation time is necessary to obtain a strong activation of the reporter system and the microfluidic system could be useful for studies to follow intracellular kinetics in real time. GFP has been used for tagging GPCRs or as a reporter gene expression marker [112,131-134]. GFP acts as a reporter gene for in vivo and in vitro assays to measure cell death in setups involving relocalization of GFP fusion proteins. Single-cell analysis performed by flow cytometry allows direct evaluation of apoptosis [132]. Kinetic measurements of the decrease of enhanced Green Fluorescent Protein (EGFP) would allow a distinction between induction of cell death and cell growth arrest to be done. This assay may be more convenient for screening a large panel of drugs or genes on a limited number of cell lines. GFP has also been studied as a label for a fusion protein family (FPR) for exploration of kinetic disassembly mechanism on bead as sensors in flow cytometry [133]. The use of this technique for real-time HTS of G-protein coupled receptors has been extensively revisited [135-137]. Throughput of assays using conventional flow cytometry has been increased by using automated liquid handling systems. The sample throughput has changed from 2 to 1000 samples per minute in a commercial system recently developed [137]. These systems can be used for monitoring kinetics at the subsecond scale, to study drug-receptor kinetics or receptor solubilization. However,

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there is still some improvement to be made such as the minimization of liquid carryover and sample residual in these commercial systems [138], which could be achieved by reducing the size of the components of the system and by treating PVC tubing to modify the humidity degree of its surface. The use of second messenger assays is also useful for the real-time determination of GPCRs activity. The monitoring of cyclic nucleotides such as cAMP [112,114,115] or the determination of inorganic phosphate [139] has been reported for this purpose. A Gprotein FRET assay [112] allowed the examination of kinetics of transient loss of FRET on addition and removal of cAMP using adequate stopped-flow systems and sensitive fluorometers in the subsecond time order. Thus, a dose-response curve of cAMP and its analogues that bind to CAR1 receptor can be obtained. A scintillation proximity assay (SPA) has been proposed to determine the adenosine triphosphatase (ATPase) activity, and also substrate or product concentrations [139]. These assays are designed in such a way that only the substrate or the product bound to a bead can produce a significant scintillation signal so, a physical separation step is unnecessary. The utility of this SPA procedure for mechanistic studies was assessed by studying the initial rate of the system. The inorganic phosphate released by the action of ATPase is bound to molibdate to form phosphomolibdate anion, which is also bound to scintillation beads. The measurement of intracellular calcium ion concentration has been also used as an indicator of receptor activation. Although it has been widely described for end-point assays, some kinetic studies have been also developed in flow systems [116,117] or multi-well formats [115,118]. In all of them, fluorescent indicators of calcium were used, such as aequorin [118], fura-2 [117] or fluo4-acetoxymethylester [115]. Initial rates of calcium response can be used as a rapid analytical methodology for the discrimination of different drugs [117] using a flow-injection renewable surface technique cell-based assay. Also, the delay introduced in the Ca2+-aequorin interaction kinetics caused by a Ca 2+-chelator has been used to develop kinetic methodologies using multi-well format as the timing of sample handling and plate reading are in the same order of magnitude [118]. Other devices based on microfluidic systems have been described for potassium channels [121,122]. HIGH THROUGHPUT PHARMACOKINETIC SCREENING Kinetics are present in the whole process of absorption, distribution, metabolism, excretion and toxicity (ADMET) of a compound. There are three kinetic mechanisms involved in pharmacokinetic screening: first-order, zero-order and Michaelis-Menten kinetics. Most of absorption, diffusion, permeation and excretion processes can be described using first-order or linear kinetics. This means that the transformation rate of the drug is dependent on its concentration, following the equation: (dC/dt) = -kC, where C is drug concentration, k is the first-order rate constant and t is time. The negative sign indicates that concentration decreases with time. Excretion kinetics can be also given by zero-order kinetics, being the excreted drug concentration independent of initial drug concentration. The rate equation can be expressed as: (dC/dt) = -k0, where k 0 is the zero order rate constant. The well known Michaelis-Menten rate equation, under drug excess conditions, is very useful as most of bio-transformation processes are catalyzed by enzymatic systems. Fig. (3) shows the most relevant kinetic parameters involved in different stages of an ADMET process, which are commented below.

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Fig. (3). The role of kinetics at the different stages of absorption, metabolism, and excretion studies at early drug discovery. (kIAM, k ILC, retention factors for immobilized artificial membrane (IAM) chromatography and immobilized liposome chromatography (ILC)).

The determination of the absorption rate at early stages is important since it can be used to calculate the bioequivalence of a drug [140]. The study of solubility of potential pharmaceutical compounds is an important aspect in HTS as the rate-limiting step for the absorption of drugs from the gastrointestinal tract is frequently the dissolution of a solid dosage form. The rate in which a compound is dissolved is given by the modified Noyes-Whitney equation [141]: (dC/dt) = [(AD)/l](c 0-c1), where dC/dt is the variation of the concentration in time, c0 and c1 are concentrations at a distance 0 from the solid particle (saturated solubility) and at a distance l from the diffusion layer, respectively, A is the surface area available for dissolution, and D is the diffusion coefficient. Kinetics are present in these studies for any dosage form. Controlled release polymer dosage is specially indicated for rapidly metabolized drugs. Variables affecting the modulation rate are polymer composition, compression force and hydrodynamic conditions among others [142]. Automatic measurements of kinetic aqueous solubility can be done using an instrument with robotic sample handling, multiwell format and nephelometric detection [143], being analyzed more than 300 compounds/day. Immobilized Artificial Membrane (IAM) chromatography uses stationary phases constituted by phospholipids, covalently bound to silica supports. Thus, the polar head of phospholipids can reproduce hydrophobic, ion-pairing and hydrogen-bonding interactions that take place between analytes and biological membranes. The interest of IAM chromatography in the early drug discovery process as a powerful in vitro tool for high throughput screening and their applications have been reviewed [144]. This technique enables the study of non specific binding of biomolecules with cell membranes through hydrophobic interactions and for specific-binding establishing the bound between biomolecules and analytes. IAM has been widely applied to calculate the hydrophobicity parameters for a great variety of compounds [144-152]. The results obtained with this technique have been compared to those obtained by reversed-liquid chromatography [146,147], micellar liquid chromatography and micellar electrokinetic capillary chromatography (MEKC). MEKC and IAM chromatography correlated well,

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which would be probably due to similarities between the organized mediums provided by surfactants and phospholipids. Stationary phases with immobilized receptors have been developed [150-152] to show their usefulness for drug-receptor interactions. Immobilized liposome chromatography (ILC) has been also used for membrane partitioning studies and its uses have been recently reviewed [153]. The predictions made using ILC can be more realistic as liposomes constitute a hydrophobic region sandwiched between two interfacial hydrophilic layers, as it happens in biological membranes. Permeability studies are other important issue to be taken into account in drug absorption screening. Drug permeation often involves non-steady-state conditions. Solutes sometimes have different rates of adsorption to membranes and they can form aggregates in solution or within the membranes thus, affecting permeability. Surface changes of membranes can give rise to attraction or repulsion forces. Apparent permeability (Papp) has a kinetic component as it can be calculated according to the equation: P app = (1/AC0)(dQ/dt), where C0 is the initial concentration of drug, A is the surface area of the filter/cell, and dQ/dt is the permeability rate. Cell lines have been traditionally used for permeation assays and results from Caco-2 cell lines correlate well with in vivo procedures but the assays using these cells often feature a low throughput as three weeks are needed for they to be grown. Marby-Darby canine kidney (MDCK) cells constitute an alternative to Caco-2 cells for permeability assays [154-156], taking into account that only three days are needed to achieve an appropriate cell culture. The results correlate well with those provided by Caco-2 cells and also with those by in vivo assays, what demonstrate its practical usefulness at early drug discovery. A high-throughput assay used for permeation studies is the Parallel Artificial Membrane Permeation Assay (PAMPA). It is a membrane-based assay involving the use of two plates separated by a porous filter made from an inert material coated with a lipid solution to prepare the artificial membrane. Wells from both plates are filled with drug and buffer solutions, respectively, and incubated [157]. Afterwards, the drug concentration in both plates is examined using UV [158-161] or analyzed by LC/MS [160] to measure the rate of permeation, which is determined by the drug effective permeability. The use of LC/MS is very useful for compounds that lack absorbing chromophore groups and the influence of some drug solubilizers, which are commonly used as excipients can be checked out without any interference unlike the UV-vis method [160]. In most instances, the results obtained with this technique correlated well with those provided by Caco-2 cell monolayers for absorption processes based on passive drug transport, which is the most usual phenomenon. The features of this technique such as simplicity, low cost and high throughput have proven that it is a useful tool at early drug discovery process for the selection of potential lead candidates, compared to Caco-2 cell assays. However, the use of PAMPA assays cannot exclude the use of cell lines since some phenomena such as drug efflux, first-pass metabolism and protein transport have to be studied using cell lines. Additionally, new technical improvements, such as the individual stirring of the wells [162] have increased the intrinsic high throughput of this technique. This approach is particularly interesting in the case of lipophilic molecules for which the diffusion of the drug across the water layer on both sides of the membrane is the rate-limiting step. Thus, the incubation time for lipophilic compounds is reduced from 15 h to 15 min. PAMPA assays have been

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efficiently automated in the 96-well format and fully automated equipments are now commercially available. Membrane proteins such as P-glycoprotein can contribute as active transporters of drugs, giving rise to the drug efflux out of the cell. Substrates of this protein are highly hydrophobic and therefore, they have a high diffusion rate. There is balance between passive diffusion across membrane bilayer and active trasport. A continuous fluorescence assay using tetramethylrosamine was developed to quantify drug transport in proteoliposomes of defined phospholipids [163]. The transport rate was observed in real time at time intervals of 150 s. This method was more advantageous than fixed timepoint rapid filtration technique because the later needed multiple samples, one at each time-point. The elucidation of carrier mechanisms might help to develop theoretical models for predicting drug absorption when drug efflux occurs. Mathematical models have been developed to simulate oral drug absorption [140,164-166]. One model described the gastrointestinal transit and absorption processes to analyze and predict plasma concentration profiles after oral administration [164]. For this simulation, gastrointestinal tract was divided into eight segments, considering firstorder absorption kinetics and the absorbability measurements defined by the absorption rate constant. Plasma concentration-time profiles were predicted using a convolution method for four model drugs. The results obtained showed that this model can be applied in any instance, including drugs experimenting first-pass metabolism or absorption. Other model involves a physiologically based method, which considers the intestine as a continuous tube and the function chosen follows a Gausiann distribution [165]. Two input parameters are needed, intestinal permeability coefficient and solubility in intestinal fluids. Concentration-time curves obtained were very similar to the values obtained in the literature. A great number of drugs are eliminated from the body via metabolism and/or excretion. Lipophilic molecules may move from plasma to hepatic cytosol by simple or facilitated diffusion. Kinetics are related to metabolism by means of plasma concentration-time profiles. Areas under the curve (AUC) can be calculated using the trapezoidal rule, using the relationship [167]: [AUC]0∞ = [AUC] 0t + (Ct/k), where [AUC]0∞ is the total area under the curve, [AUC]0t is the area under the curve at the last measurable point, Ct is the plasma concentration at the last measurable point and k is the elimination rate constant for the terminal phase. Plasma clearance (C l) can be determined by dividing intravenous doses by [AUC]0∞. Plasma half-lives (t 1/2) can be determined by logarithmic-linear least squares regression of the terminal phase of plasma concentration-time profiles. Hepatic transport is important in drug screening because extensive hepatic uptake or enhanced biliary excretion may be desirable features for a potential drug candidate [168]. In-vitro models used for the study of hepatic metabolism are cultured hepatocytes and microsomes although sometimes the results can be affected by inter-individual variability. The use of rapid methods for the evaluation of drug metabolic processes has been reviewed [169,170]. One of the indicators used to predict drug metabolism are liver enzymes, mainly cytochrome P450s (CYP450s). However, it has been recently reported that these enzymes do not follow typical Michaelis-Menten kinetics as they are affected by allosteric effects [1] and the prediction of kinetics by using kinetic modeling is often very complicated as they do not correlate with in vivo measurements. Kinetic parameters

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were calculated and these assays were also used to predict adverse drug reactions. The study of enzyme kinetics is important at early stages of the drug discovery as the use of their sensitivity or selectivity towards a target can be used for the assessment of the utility of a compound. A high throughput method for measuring enzymatic kinetics has been fabricated for a commercial liquid handler platform [4]. It consists of a heating block for incubation of 96 samples at 37 ºC, which can measure inhibition rates under physiological conditions unlike to the conventionally used end-point assays at room temperature. The calculation of inhibition and Michaelis constants of known inhibitors and substrates, respectively, showed the validity of this method, as the results obtained were comparable to those reported in the literature. As it has been mentioned above, LC coupled to tandem MS is a valuable tool for planification activities in HTS as it allows the combination of quantitative and qualitative data to accelerate the determination of metabolites in a single analysis [171,172]. The use of tandem mass spectrometry provides useful information about metabolite formation using M, which is the parent molecule mass, and M+14, M + 16, M + 32 and M + 176, corresponding to ketoformation, hydroxylation, dihydroxilation and glucuronidation, respectively [171]. Metabolites can be resolved from parent molecules without any interference, due to multiple reaction monitoring, mainly in microsomes and hepatocytes. This information is useful for the study of metabolism to make the appropriate modifications in order to adequate their structure into another less susceptible of biotransformation. Procedures commonly used to enhance the throughput of metabolism studies are cassette-dosing and sample pooling [173]. Cassette dosing or N-in-one studies appeared some years ago as a mean to enhance the throughput for the in vivo screening of drugs. This approach consists of the simultaneous dosing of several drugs in order to reduce the number of assays. The advantages and shortcomings of this approach have been extensively reviewed [174]. The main limitation of these studies are drug-drug interactions, which are basically kinetic interactions, giving erroneous values for bioavailability, oral absorption or clearance of drugs. These errors can be false positive or negatives, depending on drug-plasma protein interactions or due to some drugs from cassettes which can be transport proteins or liver enzymes inhibitors. These interactions can be minimized or avoided by lowering the initial drug concentration, even to nM levels and by reducing the number of cassette components. LC/MS/MS has been extensively used to determine the compounds and their metabolites involved in these N-in-one approaches [167,171,172,175-184]. Some of them include automated solid phase extraction coupled on-line to the chromatographic system, which has also increased the throughput of these determinations [179,184]. The use of a commercial liquid handling sampler adapted to 96-well format to achieve automated sample preparation, which includes protein precipitation assay, has been reported [179]. This approach has been applied to individual compounds and to cassette dosing for the pharmacokinetic screening of VLA-4 antagonists in the range 1-5 ng/mL. Staggered parallel LC/MS/MS is an approach based on two LC systems coupled to the same mass spectrometric detector and are switched for the compounds to be detected [177,178,182]. This procedure enhances two-fold the throughput of the system. The analysis of 20 compounds can be done in an overnight assay [178]. Urinary excretion-time data together with serum concentration-time data and pharmacodynamics have been settled up by some institutions, such as United States Food and Drug Administration (FDA), as parameters indicating bioavailability [185].

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However, the lack of information about the relationship between serum concentration and renal clearance has given rise to a limited use of urinary excretion-time profiles, especially when renal clearance is not linear. To study the errors obtained in the assessment of renal clearance, a kinetic open one-compartmental model was used, which considered first-order absorption and linear/nonlinear clearance. This later was related to saturation but it may be also associated with other mechanisms of transport-mediated reabsorption. It is concluded that a prior knowledge of the relationship between serum concentration and renal clearance should be done. The kinetic information obtained through the assays involved in pharmacokinetic screening is a useful tool for the building up of mathematical and computational models. These approaches constitute the in silico screening, which can be very valuable at early stages if models can predict accurately in vivo results. Some models, which take into account reaction mechanisms in the ADMET processes and physicochemical properties of drug candidates have been developed in recent years [186-190]. These models have been named physiologically based pharmacokinetic (PBPK) models. A generic PBPK model based on conventional mass balance differential equations of drug disposition in the different compartments has been proposed [186]. Input parameters are in vitro data of metabolism, plasma-protein binding and lipophilicity, which are available at early drug discovery. In ultimate instances, this model takes into account a scaling approach from the translation of in vitro data to in vivo situations. The comparison of the simulated with experimental data on plasma and tissue concentration-time profiles can provide mechanistic information if key ADME processes are correctly described by the model. This PBPK model was evaluated in ten different tissues for three non-structurally related drugs, two lipophilic bases (diazepam, propanolol) and one neutral (ethoxybenzamide). Some discrepancies between predicted and in vivo data were found in specific tissues, which were ascribed to transport phenomena and to accumulation in tissue processes, respectively. Thus, a deeper study of ADME processes should be needed. An integral model based on the combination of in silico and in vitro prediction tools for the whole ADME process has been reported [187]. It is an iterative closed-loop model, which justify its assumptions in each stage through the comparison of the predicted values with in vivo data. The work is emphasized first on disposition and then, on oral absorption to predict both phenomena in humans. The development of these models has been extended to the prediction of the toxicity of some compounds [188]. It is assumed that the integration of in vitro data and quantitative structure activity relationship (QSAR) models is possible thanks to biokinetic and toxicodynamic modeling. The proposed scheme consists of four stages: a) evaluation based on physicochemical properties and chemical functionality, b) biokinetic modeling and basal toxicity testing, c) election of tests at high tissue concentrations and d) choice from a battery taking into account legislation requirements. The higher predictive ability of conceptual models based on subcellular pharmacokinetics whether compared to model-free QSAR methods has been discussed [189]. The lack of enough experimental data for the validation of a model can be solved using a cross-validation technique, which consists of iterative calculations of the predicted magnitude when a group of data points is not considered. The main limitation of this approach is that it cannot predict values outside of the parameter space. To overcome this shortcoming a leave-extremes-out cross validation technique is used and maximum and minimum values are omitted for calculations. The results obtained from

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this study show how better the predictions with this model are if compared to approaches based on empirical models (neural networks, polynomial regression) for magnitudes out of the space. This is of great interest for the prediction of the behavior of large sets of different compounds, situation in which model-free QSAR empirical approaches usually fail. FINAL REMARKS The extensive literature devoted to drug discovery emphasizes the recent developments and advances in HTS such as miniaturization, automation, homogeneous formats, microarray platforms, in silico screening, etc. However, the significant incidence of kinetics in this research field is frequently omitted or hidden, although the control of the time-dependent variables is essential in most of its different steps to obtain satisfactory results. This article has tried to give an overview of the dynamic aspects involved in many of the techniques, methodologies and assays applied in HTS, in the drug-receptor mechanisms and in the ADMET properties of drug candidates. ACKNOWLEDGEMENTS Authors gratefully acknowledge financial support from the Spanish Ministerio de Ciencia y Tecnología (MCyT) (Grant No. BQU2003-03027). ABBREVIATIONS HTS

=

High Throughput Screening

ADME

=

Absorption, Distribution, Metabolism, Excretion

LC

=

Liquid Chromatography

CE

=

Capillary Electrophoresis

MS

=

Mass Spectrometry

FIA

=

Flow Injection Analysis

FP

=

Fluorescence Polarization

FCS

=

Fluorescence Correlation Spectroscopy

TR-FRET

=

Time-Resolved Fluorescence Resonance Energy Transfer

IL-13

=

Human Interleukin-13

IFN-γ

=

Interferon-γ

BRET

=

Bioluminescence Resonance Energy Transfer

NRs

=

Nuclear Receptors

CL

=

Chemiluminescence

BL

=

Bioluminescence

GFP

=

Green Fluorescent Protein

Rluc

=

Renilla luciferase

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YFP

=

Yellow Fluorescence Protein

BoNTs

=

Botulinus Neurotoxins

ES

=

Enzyme-Substrate

CDK

=

Cyclin-dependent-kinase

CYP

=

Cytochrome P450

HIV-1-RT-Rnase H

=

Human Immuno Deficiency Virus-1-Reverse Transcriptaseassociated ribonuclease H

SAR

=

Structure-Activity Relationship

SPA

=

Scintillation Proximity Assay

PARP-1

=

poly (ADP-ribose) polymerase-1

STK

=

Serine/Threonine Kinase

MurC

=

N-acetyl-muramyl-L-alanine-ligase

FMG

=

Fluorescein β-D-Glucuronide

SPR

=

Surface Plasmon Resonance

NMR

=

Nuclear Magnetic Resonance

3-FABS

=

Three-Fluorine Atoms for Biochemical Screening

GPCRs

=

G-protein coupled receptors

LDL

=

Low-density lipoprotein

GTP

=

Guanosine, 5’-triphosphate

cAMP

=

Cyclic adenosine monophosphate

PWR

=

Plasmon Waveguide Resonance

GDP

=

Guanosine, 5’-diphosphate

EGFP

=

Enhanced Green Fluorescent Protein

FPR

=

Fusion protein

ADMET

=

Absorption, distribution, metabolism, excretion and toxicity

IAM

=

Immobilized Artificial Membrane

ILC

=

Immobilized Liposome Chromatography

MDCK

=

Marby-Darby Canine Kidney

PAMPA

=

Parallel Artificial Membrane Permeability Assay

AUC

=

Area under the Curve

CL

=

Plasma Clearance

FDA

=

United States Food and Drug Administration

QSAR

=

Quantitative Structure Activity Relationship

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Xinchun, T.; Ita, I.E.; Wang, J.; Pivnichny, J.V. J. Pharm. Biomed. Anal., 1999, 20, 773-784. Wu, J.T. Rapid Commun. Mass Spectrom., 2001, 15, 73-81. Korfmacher, W.A.; Veals, J.; Dunn-Meynell, K.; Zhan, X.; Tucker, G.; Cox, K.A.; Lin, C.C. Rapid Commun. Mass Spectrom., 1999, 13, 1991-1998. Tong, X.S.; Wang, J.; Zheng, S.; Pivnichny, J.V. J. Pharm. Biomed. Anal., 2004, 35, 867-877. Bryant, M.S.; Korfmacher, W.A.; Shiyong, N.; Nardo C.; Nomeir, A.A.; Lin C.C. J. Chromatogr. A, 1997, 777, 61-66. Colwell, L.F.; Tamrakopoulos, C.S.; Wang, P.R.; Pivnichny, F.V.; Shih, T.L. J. Chromatogr. B, 2002, 772, 89-98. Ohkawa, T.; Ishida, Y.; Kanaoka, E.; Takahashi, K.; Okabe, H.; Matsumoto, T.; Nakamoto, S.; Tamada, J.; Koike, M.; Yoshikawa, T. J. Pharm. Biomed. Anal., 2003, 31, 1089-1099. Raynaud, F.I.; Fischer, P.M.; Nutley, B.P.; Goddard, P.M.; Lane, D.P.; Workman, P. Mol. Cancer Ther., 2004, 3, 353-362. Beaudry, F.; Le Blanc, J.C.Y.; Coutu, M.; Brown, N.K. Rapid Commun. Mass Spectrom., 1998, 12, 1216-1222. Thompson, G.A.; Toothaker, R.D. Pharmaceut. Res., 2004, 21, 781-784. Poulin, P.; Theil, F.P. J. Pharm. Sci., 2002, 91, 1358-1370. Theil, F.P.; Guentert, T.W.; Haddad, S.; Poulin, P. Toxicol. Lett., 2003, 138, 29-49. Blaauboer, B.J. Toxicol. Lett., 2003, 138, 161-171. Balaz, S.; Lukacova V. J. Mol. Graph. Model., 2002, 20, 479-490. Poulin, P.; Theil, F.P. J. Pharm. Sci., 2000, 89, 16-35.

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Assessment of iDEA pkEXPRESSTM for The Prediction of Caco-2 Permeabilities Cheng-Pang (Matt) Hsu, Garry W. Caldwell*, John A. Masucci, Zhengyin Yan and David M. Ritchie Johnson & Johnson Pharmaceutical Research and Development, LLC, Welsh & McKean Roads, P.O. Box 776, Spring House, PA 19477, USA Abstract: The assessment of iDEA pkEXPRESSTM 1.1 for the in silico prediction of Caco-2 permeabilities was investigated. We found that when the software was used in a high/low classification scheme with a cutoff Caco-2 permeability value 5 nm/s, the prediction ability of the tool to evaluate large data sets was acceptable. Using a Caco-2 library of 666 compounds, approximately 78% of the predictions in a high/low classification scheme were correct. In addition, the average fold error of these correct predictions was approximately 3. After removing compounds contained in the training set (275 compounds), the prediction ability of the tool was still acceptable where overall predictions in a high/low classification scheme was 76% correct with an average fold error of approximately 3. The software could be useful for analyzing hits after high-throughput screening of large structurally diverse compound libraries. Unfortunately, the software was unable to provide a measure of confidence to the predictions. Without being able to identify poor predictions, it is difficult to evaluate small data sets using the software.

INTRODUCTION The strategy invoked by most pharmaceutical companies to identify high-risk pharmacokinetic drug candidates early in the drug discovery process involves using an array of in-vitro absorption, distribution, metabolism and excretion (ADME) assays [1 – 4]. The basic approach has been to terminate ADME deficient drug candidates in drug discovery before these compounds underwent prolonged and expensive preclinical and clinical drug development. In following this philosophy, it was anticipated that the success rates of drug candidates in preclinical and clinical phases of drug development should improve since time and resources were allocated to drug candidates with real potential. Since many ADME properties of drug candidates are interrelated to each other as well as to the drug’s pharmacodynamic (PD) properties, the usefulness of the strategy has suffered since drug discovery scientists are faced with understanding and assimilating large volumes of multivariate ADME data. While some successes have arisen from this approach, simultaneous optimization of these properties has proven to be a challenging process [5]. Typically, a compromise between ADME and PD is obtained rather than an optimal value for each property.

*Corresponding author: E-mail: [email protected] Garry W. Caldwell / Atta-ur-Rahman / Barry A. Springer (Eds.) All rights reserved – © 2005 Bentham Science Publishers.

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It has been suggested that physiologically based (PB) computational models could be used to integrate these multivariate ADME data into more manageable information for assessing the overall pharmacokinetic risk profile of drug candidates and thereby improving the ADME/PD optimization process [6]. Recently, the predictions of human in-vivo oral absorption for 28 known drugs using two commercial physiologically based software packages (iDEATM and GASTROPLUSTM) were investigated [7]. The input data into the PB absorption models were combinations of experimental solubility (thermodynamic) and permeability data (human colon carcinoma cell line; Caco-2) or insilico Caco-2 permeability data generated from two-dimensional (2D) molecular representations. Assessment of the predictions was obtained primarily by comparing the fraction-absorbed prediction to the experimental value according to the following absorption classification scheme: low < 33%, medium 33-66%, and high > 66%. Using experimental solubility data and in-silico Caco-2 permeability predictions as input, the iDEATM software package assigned 20 out of 28 drugs to the correct absorption class. Thus, the overall correct classification rate was approximately 71%. When experimental Caco-2 data was used as input, the iDEATM software package assigned 22 out of 28 drugs to the correct absorption class (79% correct). These results were extremely interesting since they implied in-silico generated Caco-2 data from only twodimensional (2D) molecular structures were comparable to Caco-2 experimental data for the prediction of human absorption. However, as pointed out by the authors, since the iDEATM software package did not disclose its internal drug training set and the 28 drugs used in the evaluation have been well studied in the literature, these 28 drugs might have been part of the internal training set. If the drugs were part of the internal training set, this situation could have biased the conclusions of the study. In the present study we more fully evaluate the in-silico predictions of Caco-2 permeabilities using the iDEATM software package. The experimentally determined Caco-2 results of over six hundred compounds are used to assess the predictiveness of the iDEATM software package. A discussion is presented that examines the usefulness of this in silico method for making decisions in a drug discovery environment. METHODS Permeability, Caco-2 All experimental Caco-2 permeability data were generated at Absorption Systems (Exton, PA, USA). The Caco-2 monolayers were grown to confluence on collagencoated micro-porous polycarbonate membranes in 12-well plates [8]. The inserts (1.13 cm2) were seeded with approximately 60,000 cells per well with the majority of the cells growth occurring between 3 and 8 days. Cells grown for 21 – 30 days (passage number 50 – 60) had a transepithelial electrical resistance (TEER) between 450-650 Ω cm2. The TEER measurements were used to check for monolayer integrity. Any cell monolayer less than 200 Ω cm2 was rejected. The permeability assay buffer was Hank’s Balanced Salt Solution containing 10 mM N-(2-hydroxyethyl)piperazine-N’-(2-ethanesulfonic acid (HEPES) and 15 mM glucose at a pH of 7.0-7.2. Dosing solution concentrations of compounds were 10 µM in assay buffer. Cells were dosed on the apical side (A-to-B) and incubated at 37°C with 5% CO2 and 90% relative humidity. At two time points, 1 and 2 hours, a 200-uL aliquot was taken from the receiver chamber and replaced with fresh assay buffer with each determination being performed in duplicate. All samples

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were assayed by standard liquid chromatography mass spectrometry (LC/MS) methods using electrospray ionization [9]. The apparent permeability (Papp) expressed in nm/s was calculated under sink conditions according to standard procedures [10]. Several controls were used to monitor the experimental data. Permeability through a cell-free (blank) membrane was studied to determine non-specific binding and free diffusion of the compound through the collagen-coated micro-porous polycarbonate membranes. Compounds with non-specific binding problems were removed from the database. Lucifer yellow flux (< 4 nm/s) was also measured for each monolayer after being subjected to the test compounds to ensure no damage was inflicted to the cell monolayers during the flux period. This test allowed the removal of false-positive data. Positive controls were used daily to monitor the day-to-day variability of the assay. For example, the measured permeability of atenolol was between 2 – 5 nm/s while propranolol was between 150 – 250 nm/s. The in-vivo absorption mechanisms of the compounds used in this study were unknown. That is, the compounds used could have an in-vivo absorption mechanism involving both passive and carrier mediated mechanisms. iDEA pkEXPRESSTM 1.1 Several companies produce software that simulates human physiology. The iDEA software (Lion Bioscience Inc., San Diego, CA) was investigated in this study. Two versions of the software were used (iDEATM 2.0 and iDEA pkEXPRESSTM 1.1) in the present evaluation. The absorption modules for each of these software packages assumed a passive absorption mechanism. Each was evaluated and found to produce the same results even though the training sets contained different numbers of compounds. Therefore, only the results from iDEA pkEXPRESSTM 1.1 will be discussed since it is the latest version on the market. Since much of the details of the algorithms used for iDEA pkEXPRESSTM 1.1 are kept proprietary, only information contained in brochures or reference manuals are available. However, the underlying principles for the software package are contained in the literature [6]. iDEA pkEXPRESSTM 1.1 contains a structure based model for the in silico prediction of Caco-2 permeabilities. It is assumed that this Caco-2 model uses a statistical pattern recognition technique trained by experimental Caco-2 permeability data from approximately 779 compounds. These Caco-2 permeability training data were produced within the Lion organization or from a consortium of pharmaceutical companies. Our company was part of this consortium and contributed 275 compounds to the training set of iDEA pkEXPRESSTM 1.1. The iDEATM Caco-2 assay protocol was similar to the assay used here except Lion’s studies were performed under stirring conditions using an orbital shaker at 50 oscillations per minute and 100 µl aliquots from the receiver side of the monolayer at 30, 50, 70 and 90 minutes post-dosing was used to calculate the apparent permeability. Since the interlaboratory variability of measuring Caco-2 permeabilities can be significant [8], a Caco-2 calibration procedure supplied in the iDEATM software package was used to compare data sets. The iDEATM manual recommended comparing Lion’s Caco-2 data, which had been measured using the iDEATM Caco-2 assay protocol, with Caco-2 values measured in other laboratories. This data set contained ten compounds including acyclovir (6.2 nm/s), amiloride (18.0 nm/s), atenolol (10.7 nm/s), foscamet

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(5.3 nm/s), hydrochlorothiazide (9.2 nm/s), ketoprofen (186 nm/s), bretylium (3.9 nm/s), metropolol (266 nm/s), naproxen (211 nm/s) and propranolol (287 nm/s). Our Caco-2 permeability data was within 2- to 3-fold of Lion’s data except for atenolol which had approximately a 5-fold difference. There was significantly more scatter between the data sets at the lower permeability range (i.e., below approximately 10 nm/s) as compared to data at the higher permeability range (i.e., greater than approximately 150 nm/s). The total least squares regression analysis of the log-log correlation of the data sets had a slope equal to 1.02 and an intercept of 0.12. Based on these results we felt that there was no real significant difference between the data sets. Therefore, our experimental Caco-2 data was compared unchanged to the iDEA pkEXPRESSTM 1.1 predicted values. Characteristics of Caco-2 Database Our Caco-2 database contained 666 compounds that were synthesized at Johnson & Johnson Pharmaceutical Research & Development, LLC. There were 25 distinct structural families of compounds covering five therapeutic areas. In Figs. (1-3), the molecular weight, in silico Log P and experimental Caco-2 apparent permeabilities of all 666 compounds are shown. The average molecular weight for the database was 480 Daltons with molecular weights ranging from 209 to 871 Daltons. Compounds contained C, H, N, O, S, F and Cl elements. Most of the compounds were lipophilic with an average Log P equal to 4.5. The Log P values ranged from –1.8 to 10. The distribution of the Caco-2 apparent permeabilities were as follows: 146 compounds with Papp < 5 nm/s, 125 compounds with Papp between 5 - 24 nm/s, 165 compounds with Papp between 25 - 100 nm/s and 230 compounds with Papp > 100 nm/s.

Fig. (1). The distribution of molecular weight for compounds used in this investigation.

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Fig. (2). The distribution of Log P for compounds used in this investigation.

Fig. (3). The distribution of Caco-2 permeabilities (nm/s) for compounds used in this investigation.

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Method for Calculating Success Criteria Using the structure based absorption model- iDEA pkEXPRESSTM 1.1 and only 2D molecular structure descriptors of the compounds (ISIS/Draw; Elsevier MDL, CA, USA), the in silico Caco-2 permeabilities were calculated and compared to experimental results. The evaluation of the predicted Caco-2 permeability values was accomplished by calculating the average-fold error (equation 1).

Average − fold error = 10

∑

log( predicted / actual ) N

(1)

If iDEA pkEXPRESSTM 1.1 predicted the actual Caco-2 value perfectly, the averagefold error would equal one. If iDEA pkEXPRESSTM 1.1 predicted values to be 100% above or 50% below the actual value, the average-fold error would equal two and so on. It is typically recommended that prediction methods with average-fold errors <2 can be considered successful [11]. To further facilitate the assessment of the predictions, the in silico Caco-2 permeabilities were categorized into a high/low scheme. The refinement of the predictions into more complicated categorization schemes, such as high, medium, and low were deemed not prudent since only two time points were used to measure the experimental apparent Caco-2 permeabilities and the day-to-day variability in the experimental permeabilities was on the average 2 to 3 fold. Due to the sigmoidal nature of the relationship between the in-vivo fraction absorbed and the in-vitro Caco-2 Papp values, the selection of a high/low cutoff value for our data has been typically between 5 – 10 nm/s [8]. In the present study, we are using a cutoff permeability value of 5 nm/s to sort the data into a high/low classification scheme. It should be noted that there was no significant difference in the results when a cutoff value of 10 nm/s was used. RESULTS AND DISCUSSION Experimental Caco-2 Data Set The log-log correlation of the predicted and experimental Caco-2 permeability values are shown in Figs. (4 and 5). As evident in Fig. (4), the correlations between these data sets are poor (r2 = 0.30; N = 666). For visualization purposes, a unity line was drawn in Fig. (4). The adjacent lines to the unity line in Fig. (4) are 0.5 log units away from the unity line. For these types of predictions, an error in the range of + 0.5 log units is acceptable. It is noted that a significant amount of data falls within this 0.5 log unit range. Therefore, the average fold error and its distribution were calculated for all 666 compounds. The average fold error between the predicted and experimental Caco-2 permeabilities was 4.82 with errors ranging from 1 to over 1000. The distribution of the fold error was: 203 compounds (30%) with a fold error < 2, 104 compounds (16%) with a fold error between 2.0-2.9, 61 compounds (9%) with a fold error between 3.0-3.9, 32 compounds (5%) with a fold error between 4.0-5.0, and 266 compounds (40%) with a fold error >5. Based on the criteria that the average fold error should be <2 to be considered successful, iDEA pkEXPRESSTM 1.1 cannot be used to predict absolute Caco-2 permeability values. However, a large fraction of the results (60%) had an average fold error of <5. This result implied that iDEA pkEXPRESSTM 1.1 should be able to sort compounds into a high/low classification scheme.

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Fig. (4). The log-log correlation of experimental and iDEA pkEXPRESSTM 1.1 predicted Caco-2 permeability values (nm/s). This graph contains a unity line and two adjacent lines that are 0.5 log units away from the unity line.

In Fig. (5), the log-log correlation of the predicted and experimental Caco-2 permeabilities were divided into four quadrants. A permeability cutoff value of 5 nm/s (0.5 X 10 -6 cm/sec) was used as the criteria to divide the data. The upper right quadrant represented a true positive result (TP, or high). In this quadrant the experimental Caco-2 permeability was greater than 5 nm/s and the predicted Caco-2 permeability was also greater than 5 nm/s. The lower left quadrant represented a true negative result (TN, or low). In this quadrant the experimental Caco-2 permeability was less than 5 nm/s and the predicted Caco-2 permeability was also less than 5 nm/s. The lower right quadrant represented a false negative result (FN). In this quadrant the experimental Caco-2 permeability was greater than 5 nm/s, however, the predicted Caco-2 permeability was less than 5 nm/s. Finally, the upper left quadrant represented a false positive result (FP). In this quadrant the experimental Caco-2 permeability was less than 5 nm/s, however, the predicted Caco-2 permeability was greater than 5 nm/s. The distribution and percentage of correct compounds classified based on the 5 nm/s cutoff value are summarized in Table (1). The experimental data set contained 666 compounds with 520 compounds classified > 5 nm/s and 146 compounds classified < 5 nm/s. The iDEA pkEXPRESSTM 1.1 software package predicted 491 compounds (FP

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Fig. (5). The log-log correlation of experimental and iDEA pkEXPRESSTM 1.1 predicted Caco-2 permeability values (nm/s). This graph is divided into four quadrants. The acronyms are TP (true positives), FN (false negatives), TN (true negatives) and FP (false positives). Table 1.

Predictions of Caco-2 Permeabilities Using iDEA pkEXPRESSTM 1.1

Method

Total Number of Compounds

True Positives (High)

Experimental

666

520

iDEA

666

433

% Correct

83%

Average fold error

3

False Negatives

True Negatives (Low)

False Positives

146 87

88

58

60% 31

3

19

plus TP) with Caco-2 values > 5 nm/s and 175 compounds (TN plus FN) classified as low < 5 nm/s. This percent distribution was similar to the experimental results. The fraction of these 491 predicted compounds that were true positives (TP or high) was 433 compounds. In other words, 83% of the compounds predicted to be > 5 nm/s were correct. The fraction of the 175 predicted compounds that were true negatives (TN or low) was 88 compounds or 60% correct. These results are very good considering that

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only 2D ISIS/Draw structural representations of the compounds were used as input into the model. In addition a false negative percentage of only 17% (87 out of 520 compounds) was a significant advantage of the model. In this type of classification scheme, a false negative designation would imply that a potentially reasonable compound was eliminated and would not be considered for further analysis. Thus, a low percentage false negative designation was necessary for these types of predictions. On the other hand, a false positive designation of 40% (58 out of 146 compounds) would imply that a compound with potentially poor absorption was retained. False positive designations are less of a problem since they could be eliminated later using additional preclinical assays. The overall percent correct was 78% (i.e., high plus low (521) out of 666 compounds). It was also noted that when the software package predicted the correct classification category (TP or TN) for the compound, the Caco-2 permeability values had an average fold error of approximately 3 with an error range from 1 to 30. When the predicted Caco-2 permeability was in the wrong classification category the average fold error was significantly larger (Table 1). These results were consistent with having a reasonable permeability cutoff value for the classification scheme. Removal of the Training Set from the Experimental Set Since some of our experimental data was used to train the iDEA pkEXPRESSTM 1.1 software, these data were removed to further examine the predictability of the software package. The log-log correlation of the predicted and experimental Caco-2 permeability values for this data set is shown in Fig. (6). As evident in Fig. (6), the correlations between these data sets are again poor (r2 = 0.25; N = 391). The average fold error and its distribution were calculated for all 391 compounds. The average fold error between the predicted and experimental Caco-2 permeabilities was 5.24 and the error ranged from 1 to over 900 fold. The distribution of the fold error was: 113 compounds (29%) with a fold error < 2, 59 compounds (15%) with a fold error between 2.0-2.9, 39 compounds (10%) with a fold error between 3.0-3.9, 20 compounds (5%) with a fold error between 4.0-5.0 and 160 compounds (41%) with a fold error >5. These results were similar to the full data set of 666 compounds. The distribution and percentage of correct compounds classified based on the 5 nm/s cutoff value are summarized in Table (2). A total of 275 compounds were removed from the original data set. Therefore, the experimental data contained a total of 391 compounds with 335 compounds > 5 nm/s (high) and 56 compounds classified < 5 nm/s (low). The fraction of these predicted results that were true positives (high) was 273 compounds (or 81% correct). The fraction of these predicted results that were true negatives (low) was 25 compounds (or 45%). A false negative percentage of 19% (62 out of 335 compounds) and a false positive percentage of 55% (31 out of 56 compounds) were observed. The overall percent correct was 76% (i.e., high plus low (298) out of 391). When the software package predicted the correct classification of the compound the Caco-2 permeability values had an average fold error of approximately 3. These results were again similar to the full data set. The log-log correlation of the predicted and experimental Caco-2 permeabilities values that were contained in the training set is shown in Fig. (7). As evident in Fig. (7),

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Fig. (6). The log-log correlation of experimental and iDEA pkEXPRESSTM 1.1 predicted Caco-2 permeability values (nm/s). The experimental data does not contain compounds used in the iDEA pkEXPRESSTM 1.1 training set. Table 2.

Predictions of Caco-2 Permeabilities Using iDEA pkEXPRESSTM 1.1 (Compounds not Contained in the Training Set)

Method

Total Number of Compounds

True Positives (High)

Experimental

391

335

iDEA

391

273

Correct

81%

Average fold error

3

False Negatives

True Negatives (Low)

False Positives

56 62

25

31

45% 33

3

20

the correlations between these data sets are again poor (r2 = 0.36; N = 275). The average fold error and its distribution were calculated for all 275 compounds. The average fold

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error between the predicted and experimental Caco-2 permeabilities was 4.28 and the error ranging from 1 to over 600. The distribution and percentage of correct compounds classified based on the 5 nm/s cutoff value are summarized in Table (3). The experimental data contained a total of 275 compounds with 185 compounds > 5 nm/s (high) and 90 compounds classified < 5 nm/s (low). The fraction of these predicted results that were true positives (high) was 160 compounds (or 86% correct). The fraction of these predicted results that were true negatives (low) was 63 compounds (or 63%). A false negative percentage of 14% (25 out of 185 compounds) and a false positive percentage of 30% (27 out of 90 compounds) were observed. The overall percent correct was 81% (i.e., high plus low (223) out of 275) with an average fold error of approximately 3. These results were somewhat better when compared to the full 666 compounds data set and the 391 compounds data set. These results demonstrate the completeness of the iDEA pkEXPRESSTM 1.1 training set.

Fig. (7). The log-log correlation of experimental and iDEA pkEXPRESSTM 1.1 predicted Caco-2 permeability values (nm/s). The experimental data contains only compounds used in the iDEA pkEXPRESSTM 1.1 training set.

Use of in Silico Caco-2 Models in Drug Discovery The iDEA pkEXPRESSTM 1.1 software package has several significant advantages in a drug discovery environment, however, it cannot be used to predict absolute Caco-2

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permeability values since it is not capable of flagging unreasonable predictions. The average fold error between the predicted and experimental Caco-2 permeabilities was approximately 5 with the error ranging over two orders of magnitude. The software contains a parameter called the measurement of uncertainty (MOU) that provides a measurement of confidence to the prediction. The MOU denotes good predictions as high or medium and poor predictions as low. The MOU was high for 661 out of 666 compounds with 4 compounds being medium and 1 compound being low. Based on our comparison between experimental and predicted data, we would have expected to see many more low confidence MOU predictions. We estimated that over 200 compounds out of 666 compounds had extremely poor Caco-2 predictions. Since this MOU method failed to identify poor predictions, we conclude that it is unreliable to sort the data. Furthermore, it must be concluded that the use of iDEA pkEXPRESSTM 1.1 for the in silico predictions of Caco-2 permeabilities is extremely risky for small data sets. Table 3.

Predictions of Caco-2 Permeabilities Using iDEA pkEXPRESSTM 1.1 (Compounds Contained in the Training Set)

Method

Total Number of Compounds

True Positives (High)

Experimental

275

185

iDEA

275

160

Correct

86%

Average fold error

3

False Negatives

True Negatives (Low)

False Positives

90 25

63

27

70% 16

3

29

CONCLUSION The results, from this study, have suggested that when iDEA pkEXPRESSTM 1.1 is used in the evaluation of larger test sets (>600 compounds) approximately 75% of the predictions in a high/low classification scheme are correct. In addition, the average fold error is approximately 3 or 4 with the error ranging over only one order of magnitude. The software could be useful in analyzing hits after high-throughput screening of large structurally diverse compound libraries. Therefore used in this regard, the in silico Caco2 model contained in the iDEA pkEXPRESSTM 1.1 software package could provide guidance in the selection of compounds with potentially good absorption. At the right stage in a drug discovery process, the ability to correctly categorize compounds into a high /low scheme can be as valuable as the absolute answer. There is a need within drug discovery for in silico screens to characterize the ADME characteristics of early drug candidates. The dream of many drug discovery scientists is to generate virtual compound libraries by using predicted ADME software to designed drug candidates that are potentially well behaved in humans. While the in silico Caco-2 model contained in the iDEA pkEXPRESSTM 1.1 physiologically based software package has made considerable advances, the accurate predictions (<2 fold error) of data and the flagging of unreasonable predictions is still problematic.

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ABBREVATIONS ADME

=

Absorption, distribution, metabolism, and excretion

PD

=

Pharmacodynamic

PB

=

Physiologically based

Caco-2

=

Human colon carcinoma cell line

2D

=

Two-dimensional

TEER

=

Transepithelial electrical resistance

LC/MS

=

Liquid chromatography mass spectrometry

Papp

=

Apparent permeability

TP

=

True positive result

TN

=

True negative result

FP

=

False positive result

FN

=

False negative result

MOU

=

Measurement of uncertainity

REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11]

Humphrey, M.J. Drug Metab. Rev. 1996, 28(3), 473-489 Caldwell, G. W. [Published erratum appears in Cur. Opin. Drug Dis. Dev . 2000, 3(2), 250]. Cur. Opin. Drug Dis. Dev.; 2000, 3(1), 30-41. Caldwell, G. W.; Ritchie, D. M.; Masucci, J. A.; Hageman, W.; Yan, Z. Cur. Top. Med. Chem. 2001, 1(5), 353-366. Caldwell, G. W.; Yan, Z.; Masucci, J. A.; Hageman, W.; Leo, G.; Ritchie, D. M. Pharm. Dev. Regul . 2003, 1(2), 117-132. Smith, D.; Schmid, E.; Jones, B. Clin. Pharm. 2002, 41(13), 1005-1019 Grass, G. M; Sinko, P. J. Adv. Drug Del. Rev. 2002, 54, 433-451. Parrott, N.; Lave’, T. Eur. J. Pharm. Sci. 2002, 17, 51-61. Hidalgo, I. J. Cur. Topic Med. Chem. 2001, 1(5), 385-401. Caldwell, G. W.; Easlick, S. M.; Gunnet, J.; Masucci, J. A.; Demarest, K. J. Mass Spectrum. 1998, 33, 607-614. Stenberg, P.; Norinder, U.; Luthman, K.; Artursson, P. J. Med. Chem. 2001, 44(12), 1927-1937 Obach, R. S.; Baxter, J. G.; Liston, T. E.; Silber, B. M.; Jones, B. C.; Macintyre, F.; Rance, D. J.; Wastall, P. J. Pharmacol. Exp. Ther. 1997, 283(1), 46-58.

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Exploring the Viability of Metabonomic Urinalysis as a Toxicity Screen Within a Pharmaceutical Drug Discovery Division Gregory C. Leo*, Gary W. Caldwell, William Hageman, Becky Hastings, Beata Starosciak, Kristin Snyder, Jaclyn Scowcroft, Aaron Krikava Johnson & Johnson Pharmaceutical Research and Development, LLC, Welsh and McKean Roads, P.O. Box 776, Springhouse, PA 19477-0776, USA Abstract: This study investigated the applicability of metabonomic urinalysis as a toxicological screen in a drug discovery setting as a means to reduce the attrition of new chemical entities in pre-clinical and clinical development. The model hepatotoxins, α-naphthylisothiocyanate (ANIT) and thioacetamide (TA) were dosed in rats to validate our methodologies. The toxins generated significant deviations from the normal metabolic profile of the rat urine, and principal component analysis (PCA) readily showed a separation of controls from animals given acute doses. Spectral changes observed upon ANIT dosing reflected previous literature results showing a large decrease in tricarboxylic acid cycle intermediates and the appearance of bile in the urine. The spectral changes observed for TA reflected glycosuria consistent with known toxicological observations. A test set of drug candidates that failed in preclinical testing, because of target organ toxicity, was then submitted to metabonomic urinalysis. Metabonomic urinalysis failed to classify 3 of the 5 compounds as having toxicological problems. This deficiency can be attributed to the acute dosing protocol and possibly the need to fine tune data collection times. Metabonomic urinalysis as a toxicological screening tool in our environment, a pharmaceutical drug discovery department, appears not to be useful due to a high rate of false positive results and the large amount of material required for a single acute dose in rats.

INTRODUCTION Pharmaceutical companies strive to discover and to develop drugs that are safe and efficacious, but the process is scientifically complex and financially risky [1, 2]. Much financial cost is incurred by high attrition of new compound entities in pre-clinical and clinical development. The reasons for failure of these compounds generally fall into one or more of the following categories: poor efficacy, safety deficiencies or economic reasons. Our group has been working on a new pre-clinical paradigm for drug development based on the premise that efficacy and safety issues reveal themselves in pharmacokinetics, toxicokinetics, drug-drug interactions and drug metabolism studies

*Corresponding author: E-mail: [email protected] Garry W. Caldwell / Atta-ur-Rahman / Barry A. Springer (Eds.) All rights reserved – © 2005 Bentham Science Publishers.

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[3]. Detecting defects in these areas at an early stage of drug discovery would be highly valuable. It is in this regard, that metabonomics was investigated to follow changes in the endogenous pattern of metabolites found in rat urine upon dosing rats with drug discovery compounds. Metabonomics is the marriage of NMR (nuclear magnetic resonance) methods with pattern recognition tools as promulgated by the team of investigators at Imperial College [4]. This report applies metabonomics early in the drug discovery process as a filter for highlighting those compounds that alter normal rat metabolism, thus, implying toxicological problems. There are previous reports that use metabonomics for the toxicity screening [5, 6] but the emphasis was more highly placed on known toxins and not small molecule drug candidates. The methodology for NMR data collection and data reduction by pattern recognition tools has been reported in detail and reviewed in the literature and will not be enumerated here [4, 7, 8]. Metabonomics has demonstrated utility with respect to toxins and this paper explores its limitations in a drug discovery setting. The much studied toxins, ANIT and TA were used to validate methodology and then the procedures were applied to several typical drug candidates. Five different drug candidates that had failed because of unfavorable toxic side effects were chosen plus two marketed compounds. It was felt necessary to do a dose response because these compounds would represent compounds coming through the drug discovery process and would not be as well characterized, as were the textbook examples of ANIT and TA. The dose range would be based on knowledge and experience gained from previous biological assays. This was important given the wide variability in activities. At the onset it became apparent that the quantity of material needed for studies involving single doses required a prohibitive amount of material, approximately one gram. Depending of the protocol chosen, chronic dosing could require 10-50 grams of material and was not considered in this report. This paper describes the application of metabonomics for the study of rat urine collected from rats challenged by compounds found in the literature and compounds generated internally. Two model toxins (ANIT and TA) were chosen as benchmarks to establish the methodology. Two marketed drugs (amiodarone and rosiglitazone) were used as representatives of typical pharmaceutical drugs. Amiodarone is known to cause phosphlipidosis upon chronic dosing [9]. Rosiglitazone is not one of the thiazolidinediones to cause hepatotoxicity and adverse effects were not anticipated with the doses administered [10]. The remaining five compounds were in-house compounds chosen as representative drug candidates but were rejected for development because of adverse toxicity in preclinical trials. Our results obtained from the ANIT and TA studies gave comparable spectra to those from other laboratories. Using a test group, two marketed compounds and five drug candidates, we show some limitations of metabonomics in the drug discovery environment when using an acute dosing protocol. MATERIALS AND METHODS All the procedures involving animals were consistent with the guidelines (Guide for the Care and Use of Laboratory Animals) published by the National Research Council August, 2001 and approved by the animal ethics committee (IACUC, Institutional Animal Care and Use Committee) at Johnson & Johnson Pharmaceutical Research & Development, LLC.

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Animal Handling and Urine Collection Twenty male Sprague-Dawley rats (Charles River, Wilmington, MA) were used for each study. Their tails were numbered with a permanent marker pen so that the urine spectra could be assigned to a given rat. They were group housed (5 rats/cage) under controlled conditions (20 - 22 °C; 50 – 65% relative humidity and 12 h (hour) light cycle) with free access to food, certified diet 5001 (LabDiet, Purina Mills, St. Louis, MO), and water during the times when urine was not being collected. To collect urine the rats were transferred to metabolism cages (Lab Products) for a period of seven hours in which the urine was collected at room temperature after 4 h and/or after 7 h. Graduated, 50 ml (milliliter) plastic Corning tubes were used to collect the urine and the volumes were recorded. The urine collection was done during the rats’ light (resting) cycle and no food was provided during this time period. Eliminating food at this time removed problems with food contamination of the urine. Bacterial growth was inhibited by adding 1.0 ml of a 1% sodium azide solution or 0.5 ml of 2% sodium azide to the collection tubes and by freezing the urine after collection. Metabolism cages were rinsed daily during the study. ANIT Dosing and Urine Collection Time Points Four groups of four rats were given 25, 50, 100, or 150 mg/kg (milligram/kilogram) doses of ANIT dissolved in corn oil by gavage. An additional group of four rats was only given vehicle. Urine was collected from the twenty rats prior to dosing for a six hour period and at the following time points after dosing: 0-7 h, 24-28 h, 28-31 h, 48-52 h, 52-55 h, 72-76 h and 240-244 h. The age of the rats at the initiation of this study was 72-77 days and the weights ranged from 310 – 371 grams. Thioacetamide Dosing and Urine Collection Time Points Three groups of five rats were dosed with 50, 100 or 200 mg/kg of TA dissolved in methylcellulose by gavage. A separate group of five rats was given only methylcellulose. Urine was collected from the twenty rats prior to dosing for a six hour period and at the following time points after dosing: 0-7 h, 24-30.5 h, 48-55 h, 72-79 h and 95-101 h. The age of the rats at the initiation of this study was 66-71 days and the weights ranged from 275 - 375 grams. Amiodarone Dosing and Urine Collection Time Points Three groups of five rats were dosed with 100, 300 or 600 mg/kg of amiodarone dissolved in methylcellulose by gavage. A separate group of five rats was given only methylcellulose. Urine was collected from the twenty rats prior to dosing for a six hour period and at the following time points after dosing: 0-7 h, 24-31 h, 48-55 h, 72-79 h and 96-102 h. The age of the rats at the initiation of this study was 72-77 days and the weights ranged from 306 – 369 grams. Rosiglitazone Dosing and Urine Collection Time Points Three groups of five rats were dosed with 30, 100 or 300 mg/kg of rosiglitazone dissolved in methylcellulose by gavage. A separate group of five rats was given only methylcellulose. Urine was collected from the twenty rats prior to dosing for a six hour period and at the following time points after dosing: 0-7 h, 24-31 h, 48-55 h, 72-79 h and

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96-102 h. The age of the rats at the initiation of this study was 60-65 days and the weights ranged from 253 – 318 grams. Compound 1 Dosing and Urine Collection Time Points Three groups of five rats were dosed with 50, 100 or 150 mg/kg of compound 1 dissolved in methylcellulose by gavage. A separate group of five rats was given only methylcellulose. Urine was collected from the twenty rats prior to dosing for a six hour period and at the following time points after dosing: 0-7 h, 24-31 h, 48-55 h, 72-79 h and 96-102 h. The age of the rats at the initiation of this study was 72-77 days and the weights ranged from 305 – 360 grams. Compound 2 Dosing and Urine Collection Time Points Three groups of five rats were dosed with 10, 30 or 100 mg/kg of compound 2 dissolved in sterile water by gavage. A separate group of five rats was given only sterile water. Urine was collected from the twenty rats prior to dosing for a six hour period and at the following time points after dosing: 0-7 h, 24-31 h, 48-55 h, 72-79 h and 96-102 h. The age of the rats at the initiation of this study was 72-77 days and the weights ranged from 314 – 383 grams. Compound 3 Dosing and Urine Collection Time Points Three groups of five rats were dosed with 30, 150 or 300 mg/kg of compound 3 dissolved in methylcellulose by gavage. A separate group of five rats was given only methylcellulose. Urine was collected from the twenty rats prior to dosing for a six hour period and at the following time points after dosing: 0-7 h, 24-31 h, 48-55 h, 72-79 h and 96-102 h. The age of the rats at the initiation of this study was 72-77 days and the weights ranged from 290 – 355 grams. Compound 4 Dosing and Urine Collection Time Points Three groups of five rats were dosed with 50, 100 or 300 mg/kg of compound 4 dissolved in sterile water (adjusted pH 8-10) by gavage. A separate group of five rats was given only sterile water. Urine was collected from the twenty rats prior to dosing for a six hour period and at the following time points after dosing: 0-7 h, 24-31 h, 48-55 h, 72-79 h and 96-102 h. The age of the rats at the initiation of this study was 72-77 days and the weights ranged from 309 –380 grams. Compound 5 Dosing and Urine Collection Time Points Three groups of five rats were dosed with 3, 30 or 300 mg/kg of compound 5 dissolved in methylcellulose by gavage. A separate group of five rats was given only methylcellulose. Urine was collected from the twenty rats prior to dosing for a six hour period and at the following time points after dosing: 0-7 h, 24-31 h, 48-55 h, 72-79 h and 96-102 h. The age of the rats at the initiation of this study was 72-77 days and the weights ranged from 305 – 369 grams. Proton NMR Analysis The preparation of the urine for NMR analysis was based upon a protocol reported in the literature [11]. To minimize chemical shift variation due to differences in the urine pH, 300 µl of 0.2 M (Molar), pH 7.4 phosphate buffer was added to 600 µl (microliter)

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aliquots of the rat urine. After 10 minutes the samples were centrifuged at 10,000 rpm (revolutions per minute) for 10 minutes and 800 µl of the supernatant was removed and placed in 1.5 ml sample vials. Before capping the vials with septum caps 50 µl of a 1 mg/ml solution of TSP (3-trimethylsilylpropionic-(2,2,3,3-d4)-acid) in D2O (deuterium oxide) was added to each sample. The NMR data were acquired on a Bruker DMX-400 spectrometer (400.03 MHz (megaHertz) 1H frequency) interfaced with Bruker’s BEST flow injection accessory (i.e., a Gilson 215 liquids sample handler). The 5 mm (millimeter) broadband flow probe used had a single cell inverse configuration. The injection volume was 600 ul. Sample information was input into Bruker’s ICONNMR automation software using a spreadsheet. The pulse sequence used was a 1D-NOESY (one dimensional nuclear Overhauser effect spectroscopy) using water pre-saturation (64 Hz field strength) during the re-cycle delay (3 s (seconds)) and the mixing delay (0.08 s) [12]. The acquisition time was 2 seconds using 32K complex points for a 20 ppm sweep width. The number of scans collected for each urine sample was 256. The data were processed using 0.3 Hz exponential line broadening. Residual water signal was eliminated using the method of Marion, Ikura and Bax [13]. Spectra were manually rephased and then baseline corrected before reducing the data using the AMIX software by Bruker. Data reduction involved dividing the spectra into 255 segments, each 0.04 ppm wide for the spectral window ranging from –0.2 to 10.0 ppm. The region from 4.5 to 6.2 ppm was excluded from the data analysis. The sum of the intensities for each segment was used to define each variable and each variable was scaled to the total intensity. Endogenous metabolites resonance assignments, when made, were based upon published literature chemical shift values [14]. Parent drug and/or related metabolites in the urine were identified by comparison with the spectrum of the parent drug; isolation was not carried out for further verification. Chemometric Analysis The reduced data described above were used for principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) using Pirouette software, version 3.10 by Infometrix, Inc. (Woodinville, WA). These methods use multivariate statistics as a means to visualize changes that occur in large quantities of data. These methods are well documented and have been applied in the areas of analytical science and specifically, metabonomics [15]. The computations were carried out on a desktop personal computer. For the PCA the preprocessing option chosen was mean-center with no rotations or transforms performed. SIMCA was performed using the pre-dose urine spectra as the model group. The SIMCA model group was limited to the rats used for a given study. The number of spectra used to define the SIMCA model ranged from 15 to 20. If n was less than 20 it was usually because of instrument problems (poor water suppression). The vehicle spectra monitored if there was a shift in the urine metabolite pattern due to circumstances not attributable to the drug substance. As seen in the results sections, this was observed to happen in some of the studies where the vehicle data did not fall within the region defined by the model. RESULTS Initial efforts to do these metabonomic studies indicated that the urine collected had to be free of contamination. Following published protocols there were problems with food contamination that were resolved by removing the food during urine collection

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periods as noted above in the methods section. Food contamination resulted in many peaks in the sugar region of the proton spectrum and lactate and acetate. An interesting observation was the variation of the metabolite patterns in the control urine. This variation often involved citrate, taurine, and 2-oxoglutarate in agreement with previous observations [16]. These variations could not be correlated with events in the lab, such as, lab cleaning. If the variation occurred, it usually was a group related event and would be seen in most of the rats used for the study (e.g., 18 of 20). A vehicle control group was always used and in this way if a group of rats should be startled or upset during the course of an experiment, drug effects could be separated from environmental effects. Large variation in the gut microflora, as noted by the loss of hippurate [17, 18], was not usually seen in the control spectra. As a benchmark, rats were dosed with ANIT at one sub-acute and three acute doses. Proton spectra following the time dependence of the urinary metabolite changes for one of the rats given the 200 mg/kg ANIT dose are shown in Fig. (1).

Fig. (1). Proton NMR spectra of rat urine from a rat dosed with 150 mg/kg of ANIT. Changes in the urine metabolite profile are presented as a function of time. Spectrum a is the pre-dose urine spectrum. Spectra b through f are the urine spectra 0-7 hr., 24-28 hr., 48-52 hr., 72-76 hr. and 240244 hr. after dosing, respectively. The spectra are scaled to the reference peak from TSP at 0.0 ppm.

The appearance and disappearance of peaks follows the original metabonomics study of ANIT. Some of the most notable spectral changes are the loss of citrate, 2oxoglutarate and succinate (resonances in the 3.1 to 2.4 ppm region) throughout the major portion of the study and the appearance of bile acids (1.9 to 0.7 ppm) at the point

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of maximum ANIT induced liver damage 24 hours after dosing. There were no resonances observed in the aromatic region of the proton spectra at 400 MHz that could be attributed to ANIT or to α-aminonaphthalene, its metabolite. The PCA trajectories of the dose responses are shown in Fig. (2) (top).

Fig. (2). The PCA plot (top) of the metabolic trajectory calculated from the 1H NMR spectra of urine for rats given different doses of ANIT. The bottom chart displays the same data using SIMCA to create a model based on the predose urine spectra. Both graphs use the same coding: open boxes for pre-dose samples, open circles for the 25 mg/kg samples, plus signs for the 50 mg/kg samples, x’s for the 100 mg/kg samples, filled triangles for the 150 mg/kg samples and filled boxes for the vehicle (corn oil) treated rats.

The spectra from the rats given the sub-acute dose, 25 mg/kg (open circles), showed all the data points remaining very close to the principal component space of the pre-dose

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spectra (open boxes). The pre-dose points are centered about 0 along factor 2 and between 0.01 and 0.03 along factor 1. At 50 mg/kg (plus signs) marked changes are seen for two of the rats after 24 and 28 hours. These are the four plus signs in the upper left branch of the data in the PCA chart. All the rats in this group showed a drop in the tricarboxylic acid cycle intermediates and the two rats most affected also had bile acids in their urine spectra. After two days the 50 mg/kg, rat urine profiles had returned mostly back to the pre-dose region. Trajectories from the groups dosed with 100 (x’s) and 150 mg/kg (filled triangles) ANIT exhibited points in the upper left region of the chart due to the appearance of bile in the urine and the absence of citric acid cycle intermediates. After 48 hours, the two high dose groups exhibited points in another region of the principal component space (the region less than zero along factor 2 and between –0.02 and –0.04 along factor 1). This reflected the partial recovery from ANIT toxicity at higher doses and the corresponding spectra were distinguished by the continued absence of citric acid cycle intermediates, an increase in creatine and the disappearance of the bile acids peaks. The loss of citric cycle acid metabolites was suggestive of damage to the acinar zone 1 of the liver that has been ascribed as predominantly responsible for citric acid cycle metabolism but no further experiments were performed to substantiate this. In the bottom part of Fig. (2) is the same data analyzed using SIMCA. The SIMCA model is generated from the predose urine spectra of 20 rats and represents normal rat metabolism. Those data used to generate the SIMCA model are in the lower left corner (open boxes). The horizontal line cutting through the data is the boundary line for samples that fit the model criteria (below the line) and those that do not fit the model criteria. The line represents the 95% confidence limit. For those samples that do not fit the model, the metabolism is viewed as being perturbed from its normal state since specific toxicity models were not generated. This approach highlights compounds that alter normal metabolism as potential problems. An advantage of this format is that the data are shown as a dose response. A dose response was observed and after ten days most of the rats were completely recovered. It is not clear why the vehicle data in the SIMCA plot are at the edge of the model limits. It may be a stress related phenomenon or with time it may be related to aging [16]. The other well-characterized toxin used was TA, which is known to damage specific regions of the liver and the kidney. Fig. (3) shows the rat urine spectra 55 hours after dosing with 200 mg/kg. This result is very consistent with previous published data illustrating the large metabolic disruption induced by TA, in particular glycosuria . The large increase in the urine sugar concentration was easily recognized by the presence of the α- and β- anomeric protons of glucose (5.3 and 4.7 ppm, respectively) in an uncluttered region proton spectrum. These are the large resonances on each side of 5 ppm. A less pronounced elevation of urinary amino acids was manifested by the increased intensity of amino acid methyl resonances (0.8 –1.5 ppm) as well as other signals. Our urine collection was terminated before full recovery of the rats was observed for those rats given the higher doses. From the SIMCA analysis a dose response was seen (Fig. 4) and the two highest doses elicited a similar response suggesting saturation. The offset in the data points for the dosed animals during the 0-7 hour period was in large part due to the presence of an intense methyl resonance from acetone. The change in the urine metabolite profile induced by the toxin builds to a maximum at the second and third day of the study. The rats given the lowest dose were not as affected and their associated points in the SIMCA plot are equivalent to vehicle by

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Fig. (3). Proton NMR spectra of rat urine from a rat dosed with 200 mg/kg of thioacetamide. The urine was collected for the period 48 – 55 hours after the rat was dosed.

Fig. (4). SIMCA display generated from the proton NMR spectra of rat urine from rats given thioacetamide. The open boxes are pre-dose urine samples and the open circles, plus signs and filled triangles are for the rats dosed with 50, 100 or 200 mg/kg of TA, respectively. The filled boxes are from rats given vehicle (methylcellulose).

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day three. The vehicle dosed animals at the 24-31 hour time period fell outside the model generated using the pre-dose urine. Vehicle data points, which did not fall within the model limits, were also observed in other studies. It possibly reflects stress felt by the vehicle treated animals with respect to the other animals or the group as a whole was affected by an event unrelated to the dosing. The list of test compounds that were tested reflected a typical range of compounds in a drug discovery environment: amiodarone, rosiglitazone, an α-2 adrenergic based analgesic (compound 1), a Ca receptor agonist (compound 2), a p-38 inhibitor (compound 3), an anti-epileptic (compound 4), and a vasopressin inhibitor (compound 5). Rosiglitazone and amiodarone are marketed drugs. Amiodarone, an antiarrythmia drug was found to induce hepatic phospholipidosis upon chronic administration [9, 19]. Rosiglitazone, an antidiabetic drug is a member of the thiazolidinedione class that does not express the hepatotoxicity as for the related troglitazone [10]. The last five compounds were in-house drug discovery candidates that were brought forward to development but were discontinued because of toxicological concerns. Compounds 1, 2 and 4 caused convulsions and compounds 3 and 5 generated liver toxicity (neutrophilic infiltrations – 3 and hepatobilary toxicity – 5). The amiodarone data is presented in Fig. (5) using SIMCA to predict outliers. The first time point, 0-7 hours, showed the data for the dosed as well as the vehicles falling outside the model limit. Inspection of the urine spectra from the vehicle treated rats showed that citrate and 2-oxoglutarate peak intensities dropped. This was not a result of the vehicle used, methylcellulose [20], but it was viewed as a change in the rats’

Fig. (5). SIMCA display generated from the proton NMR spectra of rat urine from rats given amiodarone. The open boxes are pre-dose urine samples and the open circles, plus signs and filled triangles are from rats dosed with 100, 300 or 600 mg/kg of amiodarone, respectively. The filled boxes are from rats given vehicle (methylcellulose).

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metabolism that occurred during that collection period unrelated to dosing. This sensitivity of the metabonomics method reflected the need to have a control group alongside the dosed group. The offset for the dosed animals reflects similar drops in citrate and 2-oxoglutarate but also included an increase in phenylacetylglycine and trimethylamine-N-oxide. The high dose point at 0.0015 (along the vertical axis) in the 0-7 hour time period was low relative to the other high doses because it did not contain an increase in phenylacetylglycine and all its metabolite concentrations appeared to be reduced with citrate and 2-oxoglutarate more than the others. The two and three day time periods for the rats given the highest dose moved away from the model suggesting a delayed onset of a toxicological response. The low dose point, marked by a 1, at the 96-103 hour time period was an outlier having a spectrum with several intensity differences relative to control spectra. Fig. ( 6) shows the SIMCA test set versus the dosed and vehicle treated rats for the rosiglitazone study. The urine samples used for generating the model had, in general, lower levels of citrate and elevated levels of phenylacetylglycine relative to the urine collected after dosing. The urine volume for the predose rats was about 2-3 times the volume that is normally collected (5-7 ml). After the dosing commenced, urine volumes returned to volumes normally observed. The urine from the dosed animals and the vehicle treated animals are not distinct from one another relative to the SIMCA model generated from the predose urine samples. No dose dependence is observed. If a SIMCA

Fig. (6). SIMCA display generated from the proton NMR spectra of rat urine from rats given rosiglitazone. The open boxes are for pre-dose urine samples and the open circles, plus signs and filled triangles are from rats dosed with 30, 100 or 300 mg/kg of rosiglitazone, respectively. The filled boxes are from rats given vehicle (methylcellulose).

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model is generated using the vehicle samples instead of the predose samples then there is some separation between dosed and vehicle data. This difference straddles the model cutoff line and again there is no dose dependent response observed. It was not expected for a single acute dose of rosiglitazone or amiodarone that a toxic situation would develop. Amiodarone requires chronic dosing for toxicological problems to develop although at the very high dose of 600 mg/kg a perturbation away from normal metabolism was observed after two days. These compounds (amiodarone and rosiglitazone) provide a measure of the metabonomic response that can be expected from marketed pharmaceutical drugs. The need for large amounts of sample (approximately one gram for acute dosing) affected the set of in-house compounds that we could chose to test metabonomics as a toxicity screen. Only compounds that had made it to preclinical evaluation could be tested. Compound 1 was a potent alpha-2 adrenoceptor agonist with activity in acute and neuropathic pain models. Fig. (7) shows the results from SIMCA. The vehicle data (filled boxes) fall within the model limit but with time (4 days) start to drift to the edge of the model confidence limits.

Fig. (7). SIMCA display generated from the proton NMR spectra of rat urine from rats given compound 1. The open boxes are for pre-dose urine samples and open circles, plus signs and filled triangles are from rats dosed with 50, 100 or 150 mg/kg of compound 1, respectively. The filled boxes are from rats given vehicle (methylcellulose).

The urine volumes for the 0-7 hour time point were 2-3 times the volume of the predose collection period and relative to the reference, TSP, the metabolite levels were lowered. The 0-7 hour time period also reflected the presence of drug substance (and/or metabolites) in the urine as well as blood in the some of the urine samples. At the doses

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administered to the rats, most of them suffered from chromadacoyrrea (bloody tears) during the first urine collection period. A dose response can be seen for days one, two and three. Day four shows the points drifting away from the model limit for the rats given the highest (filled triangles) and middle doses (plus signs). The main reason for this is the decrease in hippurate and citrate and an increase in taurine for those rats. Since the urine collection was halted after the 96-103 hour collection period it was not clear if the movement away from the model for the animals given the higher doses was due to the development of a toxicological response or simply to animal variation. The metabonomics results for compound 1 indicate a dose dependent disruption of normal metabolism. The level of analysis does not account for the mechanism, only that there is a deviation from normal metabolism upon administration of the drug substance. Warning signs were raised independent of the metabonomics results because of the chromadacoyrrea. The next compound presented was a calcium channel agonist (compound 2) and the SIMCA results are shown in Fig. (8). In general the points fall within the model cutoff. Small peaks attributable to the parent compound and/or metabolites are seen in the spectra at the 0-7 hour time period and at the 24-31 hour time period for the highest dose. In the 0-7 hour collection period the three points farthest outside the model limit have an elevated concentration of 2-oxoglutarate relative to the other samples in the group. These results do not indicate that compound 2 affects normal metabolic pathways.

Fig. (8). SIMCA display generated from the proton NMR spectra of rat urine from rats given compound 2. The open boxes are for pre-dose urine samples and the open circles, plus signs and filled triangles are from rats dosed with 10, 30 or 100 mg/kg of compound 2, respectively. The filled boxes are from rats given vehicle (sterile water).

A p-38 kinase inhibitor (compound 3) designed for possible use against inflammatory diseases was the next example and the SIMCA results are presented in Fig. (9). No clear trend is observed except that the points for the middle time periods are

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Fig. (9). SIMCA display generated from the proton NMR spectra of rat urine from rats given compound 3. The open boxes are for pre-dose urine samples and the open circles, plus signs and filled triangles are from rats dosed with 30, 150 or 300 mg/kg of compound 3, respectively. The filled boxes are from rats given vehicle (methylcellulose).

more removed from the model for both the dosed and vehicle treated animals. The urine volumes were higher for the two lower doses for the 24-31 and 48-55 hour collection periods. The volume increases ranged from one to three-fold. The urine volumes for the rats given the highest dose increased slightly (1 – 1.5 fold) during the first collection period (0-7 hours). The urine volumes alerted the researcher to a change but were not used as variables in the statistical analysis. An anti-convulsant (compound 4) was tested and the analysis of the data using SIMCA is shown in Fig. (10). The 0-7 hour time points were outside the model limits due to the presence of drug metabolites and the decrease of citrate and 2-oxoglutarate. An inverse relation between the dose and the concentrations of citrate and 2-oxoglutarate was seen for the 0-7 hour collection period. This decrease in citrate for compound 4 may be related to its inhibition of carbonic anhydrase. By the 24-31 hour time point the metabolite patterns returned to the edge of the model limit established by the pre-dose samples. The remaining time points for the dosed and vehicle treated rats reflected a slight drift away from the model. One metabolite change that contributed to this drift was the decrease in hippurate during the course of the study. In Fig. (11) the SIMCA analysis shows the data points for compound 5 fit the normal rat metabolism model. Compound 5 is a vasopressin inhibitor. The urine volumes collected for the first time period after dosing were very large – up to 63 ml for one of the rats given a high dose of the drug substance. For comparison, pre-dose urine volumes were in the 5-7 ml range. The spike for the points in the first collection period is not due to the presence of drug substance or drug metabolites but rather to an increase in

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Fig. (10). SIMCA display generated from the proton NMR spectra of rat urine from rats given compound 4. The open boxes are for pre-dose urine samples and the open circles, plus signs and filled triangles are from rats dosed with 50, 100 or 300 mg/kg of compound 4, respectively. The filled boxes are from rats given vehicle (sterile water, pH adjusted between 8 - 10).

Fig. (11). SIMCA display generated from the proton NMR spectra of rat urine from rats given compound 5. The open boxes are for pre-dose urine samples and the open circles, plus signs and filled triangles are from rats dosed with 3, 30 or 300 mg/kg of compound 5, respectively. The filled boxes are from rats given vehicle (methylcellulose).

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hippurate. This was most pronounced for the highest dose administered. Rat 11 was particularly sensitive to this compound and required 4 days before returning within the model limits. The distinguishing features for rat 11 at the 24-31 and 48-55 hour collection periods were the decrease in citric acid cycle metabolites and the increase in phenylacetylglycine. The results indicate that compound 5 causes a temporary perturbation (the initial time period, 0 – 7 hours) in metabolism. DISCUSSION Data have been presented showing the results obtained from metabonomic analysis of rat urine in a pharmaceutical drug discovery environment. We took a simplistic approach and attempted to use metabonomics to classify compounds as altering or leaving unchanged the normal metabolic profile of rat urine to detect compounds having undesired toxicity. The protocol that was chosen was limited by the necessity of having large quantities of drug substance to perform the tests. The in-house compounds that were tested had advanced out of drug discovery to pre-clinical testing and thus were available for testing metabonomics. Following a protocol using a single dose diminishes the chance to detect compounds that require chronic administration (e.g., amiodarone). Other companies have taken a different strategy employing a large metabonomics effort to generate toxicity models to then be able to rank compounds relative to those models. This was one of the goals of the Consortium On Metabonomics Technology (COMET). Well-defined handling of the animals was used to avoid contamination of the urine and undue stress of the animals. The protocol adopted for handling the rats incorporated group housing with free access to food and water until the urine collection periods and then the labeled rats were isolated in separate metabolism cages without access to food thus insuring that the urine was free of food contamination. The group housing prior to the administration of compounds should have allowed for common hydration and fed state of the animals. Even under such conditions, there was sufficient variation observed in the urine metabolite pattern so that the vehicle rats often fell outside the 95% confidence limit for the healthy animal model. Variation of metabolite patterns in rat urine has been documented previously [16]. Variation in the urine metabolite profile may appear unexpectedly as in the rosiglitazone example where the predose urine metabolite patterns displayed significant variation relative to the control group over the course of the study. What caused the alteration in the metabolite profile is not known and that underscores the need for continued research in this field [21]. Other “-omics” technologies are also information rich and a full understanding of all the information is not possible at the present time. Metabonomics can be used to differentiate toxic compounds from controls but most of the test compounds in this study did not cause dramatic changes in metabolism and were not differentiated from the control group. Of the five in-house drug discovery compounds tested only compound 1 produced a marked deviation from the pre-dose control urine and this compound also caused chromadacoyrrea. Three of the samples studied (amiodarone, and compounds 4 and 5) only gave changes at the 0-7 hour time point and these changes were increases or decreases in the concentrations of metabolites that normally show the most variation [16]. Of these three, compound 5 caused a pronounced increase in the urine output. Some compounds (TA and compounds 1,2 and 4) yielded drug metabolites in the urine at the initial, 0-7 hour, time point resulting in a separation in the pattern recognition results. For the amiodarone study there was a

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movement away from the control group that occurred two days after the rats were given the highest dose of amiodarone. The strength behind pattern recognition is its ability to reduce a large amount of data to something that can be readily visualized and we found it convenient to use SIMCA to visualize the dose response and to visualize samples that fell outside the limits of the model group. Other statistical tools, that can and have been effectively used for metabonomics, were not represented in this report [22 - 25]. As mentioned this application of metabonomics requires relatively large amounts of compound but if there was a willingness to use mice the amount of compound required would decrease approximately 10-fold. The reduced volumes of urine available from mice should not be a problem with the current generation of small volume probes available. Our application of metabonomics using an acute dosing protocol missed compounds that we knew to have target organ toxicity and a chronic dosing protocol would be expected to work better. This would add xenobiotic resonances in the urine spectra adding significant complexity to the interpretation of the pattern recognition results and might be circumvented by switching analytical methods to mass spectroscopy. With mass spectroscopy mass filters can be used to select compounds with the desired molecular weights and this type of metabonomic’s application is being commercially performed (e.g., Metabolon Inc., Research Triangle Park, NC). CONCLUSION Metabonomics as applied in this report was not found useful as a toxicological screen within our pharmaceutical drug discovery environment because of the false positives that were observed and the excess amount of compound needed for rat studies. This is not to discredit the technology for there have been commercial applications utilizing metabonomics in clinical areas (e.g., Liposcience in Raleigh, NC) and biomarker identification or in conjunction with genomics and proteomics (e.g., Beyond Genomics in Waltham, MA). The technology would be expected to play an expanded role in the toxicological profiling of new compound entities after compounds have been handed over from drug discovery to development. An application that would seem appropriate for metabonomics in a typical pharmaceutical drug discovery environment may be for the better classification of in vivo disease models. This is not unreasonable given that the technique has been shown to be able to differentiate genetic strain differences in mice [26] and to show the effect of different vehicles on metabolite patterns in rat urine [20]. ACKNOWLEDGEMENTS Carlos Cotto, Jeffrey Hall and Diane Gauthier are acknowledged for their assistance at various stages of this project. ABBREVIATIONS 1D-NOESY

=

One dimensional nuclear Overhauser effect spectroscopy

ANIT

=

α-naphthylisothiocyanate

D2O

=

Deuterium oxide

h

=

Hour

228 Frontiers in Drug Design & Discovery, 2005, Vol. 1

Hz

=

Hertz

IACUC

=

Institutional Animal Care and Use Committee

M

=

Molar

mg/kg

=

Milligram/kilogram

ml

=

Milliliter

mm

=

Millimeter

µl

=

Microliter

MHz

=

MegaHertz

NMR

=

Nuclear Magnetic Resonance

PCA

=

Principal Component Analysis

ppm

=

Parts per million

rpm

=

Revolutions per minute

s

=

Seconds

SIMCA

=

Soft Independent Modeling of Class Analogy

TA

=

Thioacetamide

TSP

=

3-trimethylsilylpropionic-(2,2,3,3-d4)-acid

Leo et al.

REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17]

Prentis, R. A.; Lis, Y.; Walker, S. R. British Journal of Clinical Pharmacoloogy, 1988, 25, 387-396. Caldwell, G. W. Current Opinion in Drug Discovery & Development, 2000, 3, 30-41. Caldwell, G. W.; Ritchie, D. M.; Masucci, J. A.; Hageman, W.; Yan, Z. Current Topics in Medicinal Chemistry (Hilversum, Netherlands), 2001, 1, 353-366. Nicholson, J. K.; Lindon, J. C.; Holmes, E. Xenobiotica, 1999, 29, 1181-1189. Shockcor, J. P.; Holmes, E. Current Topics in Medicinal Chemistry (Hilversum, Netherlands), 2002, 2, 35-51. Robertson, D. G.; Reily, M. D.; Lindon, J. C.; Holmes, E.; Nicholson, J. K. In Comprehensive Toxicology; Sipes, I.G., McQueen, C.A., Gandolfi, A.J., Eds.; Elsevier Science B.V.: Amsterdam, 2002, pp. 583-610. Holmes, E.; Nicholls, A. W.; Lindon, J. C.; Connor, S. C.; Connelly, J. C.; Haselden, J. N.; Damment, S. J. P.; Spraul, M.; Neidig, P.; Nicholson, J. K. Chem. Res. Toxicol., 2000, 13, 471-478. Lindon, J. C.; Nicholson, J. K.; Holmes, E.; Everett, J. R. Concepts Magn Reson, 2000, 12, 289-320. Goldman, I. S.; Winkler, M. L.; Raper, S. E.; Barker, M. E.; Keung, E.; Goldberg, H. I.; Boyer, T. D. American Journal of Roentgenology, 1985, 144, 541-546. Lebovitz, H. E. Diabetes/Metabolism Research and Reviews, 2002, 18, S23-S29. Waters, N. J.; Holmes, E.; Williams, A.; Waterfield, C. J.; Farrant, R. D.; Nicholson, J. K. Chem Res Toxicol, 2001, 14, 1401-1412. Spraul, M.; Hofmann, M.; Ackermann, M.; Nicholls, A. W.; Damment, S., J. P.; Haselden, J. N.; Shockcor, J. P.; Nicholson, J. K.; Lindon, J. C. Analyst (Cambridge, U K), 1997, 122, 339-341. Marion, D.; Ikura, M.; Bax, A. J. Magn. Reson, 1989, 84, 425-430. Lindon, J. C.; Nicholson, J. K.; Everett, J. R. Annual Reports on NMR Spectroscopy, 1999, 1-88. Holmes, E.; Shockcor, J. P. Current Opinion in Drug Discovery & Development, 2000, 3, 72-78. Bollard, M. E.; Holmes, E.; Lindon, J. C.; Mitchell, S. C.; Branstetter, D.; Zhang, W.; Nicholson, J. K. Analytical Biochemistry, 2001, 295, 194-202. Phipps, A. N.; Stewart, J.; Wright, B.; Wilson, I. D. Xenobiotica, 1998, 28, 527-537.

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Williams, R. E.; Eyton-Jones, H. W.; Farnworth, M. J.; Gallagher, R.; Provan, W. M. Xenobiotica, 2002, 32, 783-794. Poucell, S.; Ireton, J.; Valencia-Mayoral, P.; Downar, E.; Larratt, L.; Patterson, J.; Blendis, L.; Phillips, M. J. Gastroenterology, 1984, 86, 926-936. Beckwith-Hall, B. M.; Holmes, E.; Lindon, J. C.; Gounarides, J.; Vickers, A.; Shapiro, M. J.; Nicholson, J. K. Chem. Res. Toxicol., 2002, 15, 1136-1141. van der Greef, J.; Stroobant, P.; van der Heijden, R. Current Opinion in Chemical Biology, 2004, 8, 559-565. Holmes, E.; Foxall, P. J. D.; Nicholson, J. K.; Neild, G. H.; Brown, S. M.; Beddell, C. R.; Sweatman, B. C.; Rahr, E.; Lindon, J. C. Analytical Biochemistry, 1994, 220, 284-296. Azmi, J.; Griffin, J. L.; Antti, H.; Shore, R. F.; Johansson, E.; Nicholson, J. K.; Holmes, E. Analyst, 2002, 127, 271-276. Anthony, M. L.; Rose, V. S.; Nicholson, J. K.; Lindon, J. C. J. Pharm. Biomed. Anal. , 1995, 13, 205211. Brindle, J. T.; Antti, H.; Holmes, E.; Tranter, G.; Nicholson, J. K.; Bethell, H. W. L.; Clarke, S.; Schofield, P. M.; McKilligin, E.; Mosedale, D. E.; Grainger, D. J. Nature Medicine , 2002, 8, 14391444. Gavaghan, C. L.; Holmes, E.; Lenz, E.; Wilson, I. D.; Nicholson, J. K. FEBS Letters, 2000, 484, 169174.

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Partition of Solvents and Co-Solvents of Nanotubes: Proteins and Cyclopyranoses Francisco Torrens* Institut Universitari de Ciència Molecular, Universitat de València, Dr. Moliner 50, E-46100 Burjassot (València), Spain Abstract: The main contribution to the water-accessible surface area of lysozyme helices is the hydrophobic term, while the hydrophilic part dominates in the sheet, what is related to the 1-octanol–, cyclohexane– and chloroform–water partition coefficients Po–ch–cf of helices, which are greater than those of the sheet are. The analysis of atom–group partial contributions to logPo–ch–cf allows building local maps. The molecular lipophilicity pattern differentiates among helices, sheet and binding site. For a given atom, logP is sensitive to the presence of other atoms. The contributions of C70-a–c atoms to logP are slightly greater than that of d–e are, which correlate with the distances from the nearest pentagon. (10,10) is the favourite single-wall carbon nanotube (SWNT), presenting consistency between a relatively small aqueous solubility and great Po–ch–cf. Efforts to use fullerenes–SWNTs in therapeutic applications are re-evaluated. There is a strong possibility for hydrophobic interactions between proteins and fullerenes–SWNTs in biomilieu, when the latter is used for biomedical applications, unless the molecule is delivered effectively at the intended site of action.

INTRODUCTION Single-wall carbon nanotubes (SWNT) have not yet been fully integrated into biosystems, because of the difficulty in rendering them soluble in aqueous solutions. There were some attempts to disperse fullerenes stably in water without stabilizer [1,2]. To study colloidal fullerene–SWNT bioactivities, it is essential to know the dispersion fundamental properties (colloidal-particle structure and size distribution), and stabilization mechanism. Their colloid bioactivities might be different from those of water-soluble derivatives [3,4], or their aqueous solutions via complexation [5] or with surfactants. Fullerene–SWNT supramolecular structures, assemblies and arrays were applied in materials science and biosystems. While water-soluble polymers and surfactants can bring aqueous solubilities to SWNTs, they may not be biocompatible. Interest in C60 chemistry is due to its unique physical–chemical properties: (1) optical limiting property due to electronic absorption in the entire ultraviolet–visible (UV–VIS) range, (2) efficient singlet-oxygen ( 1O2) generating ability, (3) radical scavenging character and (4) *Corresponding author: E-mail: [email protected] Garry W. Caldwell / Atta-ur-Rahman / Barry A. Springer (Eds.) All rights reserved – © 2005 Bentham Science Publishers.

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superconduictivity on doping with alkali metals. New methods incorporated hydrophobic C 60 with low solubility in organic solvents. Host molecules form supramolecular structures with C60–70, including calixarenes [6–12], cyclotri-veratrylene [13], triptycenes [14], porphyrin [15], cyclodextrin8 (CD8) and CD7. Few are utilizable to solubilize water-insoluble molecules for drug-delivery systems [16]. Studies on deoxyribonucleic acid (DNA)–C60 interactions showed that C60 cleaves DNA, and is base specific [17]. C60–human immunodeficiency virus type 1 (HIV-1) protease (HIVP) interaction inhibited the activity of the latter [18]. C60 aqueous solubilization by nucleophilic addition of CD7-R-monoamines (R = iminoalkyl, iminoaryl) to C60, and studies involving host–guest characteristics, free-radical scavenging and DNA-cleaving properties indicated that C60 has potential for biomedical applications [19]. A watersoluble polyfullerene was synthesized by nucleophilic reaction of a diamine supramolecularly shielded in a CD7 cavity with C60 [20]. SWNT effects were investigated on the polymerase chain reaction [21]. Solubilizing SWNTs in starch aqueous solutions is interesting [22]. CD6–10 are cyclic molecules consisting of 6–10, α-(1→4)-linked D-glucopyranose (D-Glcp) residues, Fig. (1a–c). CDs are able to form

Fig. (1). Structures of (a) D-glucopyranose and (b) cyclodextrin6 (CD 6), (c) molecular dimensions of CD (h = 7.9Å): CD6 (D = 14.6Å, d = 4.9Å), CD7 (D = 15.4Å, d = 6.2Å) and CD8 (D = 17.5Å, d = 7.9Å), and (d) intramolecular H-bonds in CD.

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inclusion complexes with guest molecules ranging in character from purely hydrophobic to purely hydrophilic, provided that the guest be small enough to fit into CD annular aperture [23,24]; CDs were model compounds in the study of starch complexes, tyrosine-residues burying and enzyme action [25–27]. Jensen et al. reviewed fullerene bioapplications [28]. Beck et al. reconsidered fullerene solubility in various solvents [29]. Connors re-evaluated CD-complex stability [30]. D’Souza and Lipkowitz edited a special issue to review CDs [31]. Lipkowitz [32], and Castro and Barbiric [33] discussed computational chemistry studies of CDs and complexes. Bezmel’nitsyn et al. reviewed fullerenes in solutions [34]. Diederich and Gómez-López reconsidered C60–70 inclusion complexes by macrocycles [35]. Da Ros and Prato re-evaluated medicinal chemistry with fullerenes [36]. Bianco et al. discussed fullerene-based amino acids–peptides [37]. Guldi and Martín reviewed supramolecular fullerene architectures [38]. The Proceedings of the Lipophilicity Symposia covered drug action and toxicology [39,40]. Earlier works reconsidered structural–topological hypotheses [41], and fullerene–SWNT aqueous solubilization via CD–amylose (Amy)·iodine inclusion complexation [42], and reported calculated partitions of lysozyme [43] and C60–70 [44]. Fullerene [45,46] and SWNT [47,48] periodic tables were discussed. AQUAFAC model calculated SWNT aqueous coefficients [49]. A linear–cyclic-D-Glcpn comparative study provided overall conformations, contact surfaces and cavity proportions [50–56]. The aim of this review is to discuss SWNT solvation–partition in the hope of biopreparations. The following sections review racemic separations, partition of proteins, fullerenes and SWNTs via inclusion complexes, biomolecule immobilization, bioactivity, transport and remediation. RACEMIC-MIXTURE SEPARATIONS BY CYCLODEXTRINS One application of CDs, particularly of CD polymers, which seems to be of promise is the resolution of racemates by means of complex formation [57]. As CDs themselves are optically active molecules, they form a diastereomeric pair with each included racemate; the two components of the pair exhibit different physical properties:

D(+) - cyclodextrin⋅ (+)-antipode Diastereomers D(+)-cyclodextrin⋅ (–)-antipode  Enantiomeric selective separation is a sharp problem in pharmaceutical industry. Between two synthesized enantiomers, only one presents the required pharmacological properties; the other can be inactive or even toxic [58]. Notice that there are no precise rules allowing, for a given separation, to choose the good stationary phase. To evaluate theoretically the different interactions that can cause the enantiomeric-pair separation, several attempts were performed using molecular dynamics [59]. Considering the great size of the stationary phase–solute (PS–S) complexes, few studies were done using quantum chemistry methods [60]. It is interesting to determine the different structures of PS–S complexes and interactions that can be responsible for the enantioselective separation using theoretical models. CDs and their derivatives received much attention in the field of chromatographic separations. The wide interest in the use of CDs as a separation medium arises from the fact that CDs can offer a selective system for chromatographic separation. CD complexation is highly selective, moreover stereoselective. Inclusion complex formation

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is mainly affected by the hydrophobicity and shape of guest molecules. Steric factors are important for the formation and stability of CD inclusion complexes. The partitioning and binding of many hydrophobic and hydrophilic organic molecules to CD cavity can be more selective than the partitioning and binding to a single solvent or to a single traditional stationary phase. For this reason, CDs find their use in typically difficult separations of enantiomers, diastereomers, structural isomers and geometric isomers, in all current types of chromatography [61,62]. The particular properties of CDs can be employed for the chromatographic separation of complex mixtures of substances, even racemates, by molecular recognition [63]. The chirality inherent in cyclodextrins (CD) enables them to differentiate between stereoisomeric potential guest molecules [64], or vice versa, to induce conformational enantiomerism of encapsulated achiral molecules. Albeit some direct hints for these effects can be obtained from solid-state structural analysis [65,66], nuclear magnetic resonance (NMR) data [67,68] and chromatographic separations using CDs as asymmetric stationary phases [69], the chiral resolution of the unmodified CDs is generally poor [70–73]. It is the undirected nature of hydrophobic and van der Waals interactions that causes the significant lack of specificity during molecular recognition by CDs. Even the distinct directionality of hydrogen bond (H-bond) interactions is opposed by the pseudo n-fold symmetry of the various CDs, which provides n alternative, but equally potent H-bond donor and acceptor functions for stabilization of the molecular assembly. Chemically modified CDs [74,75] were considered as basic molecular models for enzymes [76–81] and transition-state binding [82], but the observed regio and stereospecificity, and thus, the differentiation between different substrates remain low [83]. Chemical modification can alter the physico-chemical properties of CDs in a pronounced fashion. An attractive stationary phase is CD7. The two CD 7 faces have different diameters according to experience [84]. The narrowest one (≈8Å) consists of the primary hydroxyl (OH) groups, each group forming an H-bond with the O atom of the neighbouring cycle. The widest opening (≈15Å) consists of two alternating families of secondary OH groups (C2OH and C3OH) bound, respectively, to the C2 and C3 atoms in each glucose unit, Fig. (1d). In view of complex sizes, two glucose units (diglucose, DG) were model compounds in the study of CD7 structure. DG–butanol pair was a model inclusion compound in the study of CD7–solute complex. ORGANIC SOLVENT–WATER PARTITION OF PROTEINS Fleming (1922) discovered lysozyme [85], which was studied by bacteriologists because of its lytic activity against bacteria. Following the successful crystallization of lysozyme from hen egg white by Abraham and Robinson, lysozyme began to attract the attention of protein chemists [86]. There was considerable difficulty attached to studying the structure–function relationship of lysozyme, due to the obscurity of its enzymatic activity. Berger and Weiser observed theβ-N-acetylglucosaminidase activity of lysozyme [87]. Salton and Ghuysen prepared soluble oligosaccharide substrates from a hydrolyzate of bacterial cell walls [88]. Jollès et al. [89] and Canfield [90] determined the aminoacid sequence of hen egg-white lysozyme; Phillips’ group (1965) reported its first X-ray crystallographic analysis [91–93]. Detailed information on the three-dimensional (3D) conformation of lysozyme, and substrate binding mode followed. Lysozyme is the first enzyme in which it is possible to understand the enzymatic activity on the basis of its 3D

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fine structure, Fig. (2). Progress has been made in physicochemical and enzymatic studies of lysozyme in solution (cf. Table 1) [94]. Table 1.

Some Physicochemical Properties of Lysozyme

Partial specific volume (cm3·g-1)

0.189 (546nm), 0.1955 (436nm), 0.195 (436nm), 0.188 (578nm)

Molecular weight

14307Da

Size

16Å, 15.3Å (radius) 32×30×28Å, 45×30×30Å

Fig. (2). Structures of (a) lysozyme with a number of water molecules from the hydration sphere, (b) ribbon image, (c) binding site and (d) Cα skeleton.

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Table 2.

Francisco Torrens

Parameters of Secondary Structure Regions in Lysozyme

Structure

Region

Type

Residue

Length Percentage

Helix

A

α

5–15

11

8.5

B

α

24–34

11

8.5

C

3.010

80–85

6

5

D

α

88–96

9

7

Total α-helix

–

α

5–15, 24–34, 88–96

31

24

Total helix

–

–

5–15, 24–34, 80–85, 88–96

37

29

β-Sheet

E

Antiparallel

41–54

14

11

Total helix+sheet

–

–

5–15, 24–34, 41–54, 80–85, 88–96

51

40

Active site

BS

Substrate binding site

34, 35, 37, 44, 57, 59, 62, 63, 101, 107, 114

11

8.5

Total

–

Protein

1–129

129

100

The regions of helices and sheet are given in Table 2. The Gibbs free energy of solvation ∆Gsolv results for lysozyme (cf. Table 3) show that – ∆Gsolv,water of the helices is Table 3.

a

Free Energy of Solvation, Partition Coefficient and Hydrophobic Moment Results for Lysozyme and Its Secondary Structures

Structure

∆Gsolv,wa

∆Gsolv,ob

∆Gsolv,chc

∆Gsolv,cfd

log Poe

log Pchf

log Pcfg

µHh

A

-174.1

-244.1

-140.7

-226.0

12.3

-5.87

9.11

4.53

B

-165.5

-234.4

-136.0

-218.9

12.1

-5.19

9.38

2.75

C

-90.93

-124.9

-73.57

-119.1

5.96

-3.05

4.96

4.01

D

-137.0

-181.1

-105.8

-171.4

7.73

-5.49

6.03

5.26

Mean of α-helices

-158.9

-219.9

-127.5

-205.4

10.7

-5.52

8.17

4.18

Mean of helices

-141.9

-196.1

-114.0

-183.9

9.52

-4.90

7.37

4.14

Antiparallel β-sheet

-360.8

-299.7

-172.1

-275.5

-10.7

-33.1

-15.0

5.12

Binding site

-401.6

-372.2

-215.7

-343.9

-5.16

-32.7

-10.1

6.50

All molecule

-2189

-2133

-1290

-2124

-9.85

-158

-11.5

25.9

Gibbs free energy of solvation in water (kJ·mol-1). b Gibbs free energy of solvation in 1-octanol (kJ·mol-1). c Gibbs free energy of solvation in cyclohexane (kJ·mol-1). d Gibbs free energy of solvation in chloroform (kJ·mol-1). e Po is the 1-octanol–water partition coefficient. f Pch is the cyclohexane–water partition coefficient. g Pcf is the chloroform–water partition coefficient. h µH is the hydrophobic moment.

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smaller than that of the sheet is. However, this trend is damped in the organic solvents 1-octanol, cyclohexane and chloroform (o, ch and cf = CHCl3). The logarithm of the partition coefficients logPo–ch–cf of the helices are strongly greater than those of the sheet are. The greater logPo–ch–cf for the helices are related to their large hydrophobic solventaccessible surface area (SASA), and the lower logPo–ch–cf for the sheet, to its large hydrophilic SASA. Phelix – Psheet differences result 20, 28 and 22 log units for Po, Pch and Pcf, respectively. For logP > 3 more than 99.9% of the solute is in the organic phase, and for logP < –3 more than 99.9% of the solute is in the aqueous phase, predicting a negligible quantity of solute in each corresponding alternate phase. Three –logP values are greater than the Avogadro number exponent is, P < 10–23, meaning that no solute molecules would be present in the organic phase to allow experiments for validation. However, all logP figures are kept for the purpose of comparison between helices and sheet. The molecular lipophilicity pattern (MLP) is the normalized logPo map of lysozyme, Fig. ( 3). Lipophilicity is positive for the four helices, and negative for the binding site and, especially, β-sheet. The hydrophobic moment µH (Table 3) cannot differentiate properly between helices and sheet. µH for the whole molecule is greater than those for the fragments are: µH,helix ≈ µH,sheet < µH,binding site << µH,all. The ∆Gsolv, logP and µH for Fe4S4Cysn (0 ≤n ≤4) models of high-potential iron–sulphur proteins [95] (cf. Table 4) show that Po, Pch and Pcf decrease monotonically 4.41, 6.22 and 4.60 log units per Cys ligand, respectively. One value of –logPch is greater than the Avogadro number exponent is. Po results are of the same order of magnitude as CDHI computations, which are based on a method developed by Kantola et al. [96].

Fig. (3). Molecular lipophilicity pattern of lysozyme.

238 Frontiers in Drug Design & Discovery, 2005, Vol. 1

Table 4.

Francisco Torrens

Free Energy of Solvation, Partition Coefficient and Hydrophobic Moment Results for High-Potential Iron–Sulphur Protein Models

Clust.

∆Gs,wa

∆Gsol,ob

∆Gso,chc

∆Gso,cfd

Fe4S4

-2.56

-2.76

-1.39

-2.01

0.04

0.28

-0.21

-0.70

-0.10

0.22

0.25

Fe4S4 Cys

-61.74

-36.64

-24.86

-34.73

-4.41

-3.66

-6.48

-5.42

-4.74

-5.46

4.42

Fe4S4 Cys2

-216.4

-166.8

-144.6

-163.6

-8.72

-7.21

-12.6

-10.0

-9.28

-11.0

3.49

Fe4S4 Cys3

-454.9

-380.5

-348.0

-376.1

-13.1

-11.2

-18.8

-14.6

-13.8

-16.5

0.77

Fe4S4 Cys4

-648.4

-548.1

-505.5

-542.9

-17.6

-16.2

-25.1

-19.5

-18.5

-22.3

2.62

Cys

-50.31

-26.25

-15.55

-25.02

-4.23

-0.87

-6.11

-5.23

-4.44

-5.22

5.97

log Poe log Po Ref.f

log Pchg

log Pch log Pcfi log Pcf Rf.h Rf.h

µHj

a

Gibbs free energy of solvation in water (kJ·mol-1). b Gibbs free energy of solvation in 1-octanol (kJ·mol-1). c Gibbs free energy of solvation in cyclohexane (kJ·mol-1). d Gibbs free energy of solvation in chloroform (kJ·mol-1). e Po is the 1-octanol–water partition coefficient. f CDHI: calculations carried out with a method developed by Kantola et al. g Pch is the cyclohexane–water partition coefficient. h Calculations carried out with a method developed by Leo et al. i Pcf is the chloroform–water partition coefficient. j µH is the hydrophobic moment.

Pch–cf results are of the same order of magnitude as calculations performed with a method by Leo and Hansch [97]. With these reference methods, Po, Pch and Pcf decrease monotonically 4.12, 4.70 and 5.63 log units per Cys ligand, in that order. LogPo, logPch and logPcf mean relative errors (MRE) are 17%, 26% and -16%, correspondingly. These represent globally a MRE of 9%. However, this result should be taken with care because the mean unsigned relative error (URE) is 19%. The error of CHCl3 is rather smaller than that of cyclohexane is, due to the greatest similarity in relative dielectric permittivity between CHCl3 and 1-octanol. In particular for Fe4S4 Po–ch–cl are close to 0 log unit. Fe4S4Cys4 MLP, Fig. (4) shows that lipophilicity is near zero for the Fe4S4 cluster and negative close to Cys ligands. µH quantitatively differentiates Fe4S4Cysn structures. On varying the number of Cys units, the structures show µH indicative of particularly amphipathic structures as Fe4S4Cys. ORGANIC SOLVENT–WATER PARTITION OF FULLERENES The existing methods for production and purification of fullerenes in macroscopic quantities are based on the use of solvents [98]. The most generally employed technology of further separation of fullerenes of different sorts, and their subsequent

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Frontiers in Drug Design & Discovery, 2005, Vol. 1 239

Fig. (4). Molecular lipophilicity pattern of Fe4S4Cys4 iron–sulphur protein models.

purification is based on the concept of liquid chromatography [99,100]. Another generally employed method for separation and purification of fullerenes is based on the phenomenon of fullerene crystallization in solutions [101,102]. C60–70 and higher can be isolated by extraction in an organic solvent [103-105]. It was not possible to extract C60–70 from a solution in toluene to water. It was not possible to extract C60–70 from an aqueous dispersion (nC60–70) to toluene. Similar results were reported for other nC60–70 aqueous dispersions [106]. C60 dissolved in water via complexation with CD8 was extracted to toluene. C60 incorporated into artificial lipid membranes was not extracted to toluene, but extraction became possible after vesicle destruction adding KCl [107]. Extraction of poly(N-vinylpyrrolidone) (PVP)-solubilized C60 to toluene required KCl addition. Deguchi et al. prepared stable aqueous nC60–70 injecting into water a C60–70 saturated solution in tetrahydrofuran (THF), followed by THF removal purging N2(g) [108]. When they added NaCl to nC60–70, C60–70 were extracted into toulene and the toluene phase exhibited faint magenta–orange, characteristic colours for a solution of C60–70 in toluene, what permits measuring nC60–70 concentration in water by spectrophotometry. As they prepared aqueous nC60–70 with a saturated solution in THF, it is impossible to prepare more concentrated nC60–70. Injecting a saturated solution in THF into nC60–70 prepared beforehand, it is possible to concentrate aqueous nC60–70. When they concentrated aqueous nC60 twice, particle size remained the same by dynamic light scattering (DLS) and transmission electron microscopy (TEM). nC60 does not grow by further C 60 feed but new nC60 is formed. They concentrated nC60 four times and formed polycrystalline aqueous nC60 [109,110]. Aqueous-nC60 stability is achieved by the

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negatively charged cluster surface, which is one reason why nC60–70 cannot be extracted from aqueous dispersions to toluene, and nC60 does not grow by further C60 addition. The negative-charge origin on nC60–70 surfaces is not clear. Possible mechanisms are hydroxyl ion adsorption, clathrate formation and charge transfer. In order to test the formation of anionic endohedral metallofullerenes (EMF, M@C2n) during their extraction from EMF-containing soot [111], Kareev et al. studied different EMF extracts applying electrospray-ionization mass spectrometry (ESI–MS) [112]. The aqueous solubility of C60–70–82, van der Waals dimer (C 60)2 and C60H60 was calculated with a program based on AQUAFAC model [113–118]. C60-Ih is especially symmetric, with all atoms occupying equivalent sites in a truncated icosahedron [119]. The molecular structure contains 12 pentagons and 20 hexagons, constituting a roughly spherical molecule. The pentagons sit as far as possible from each other at the vertices of an icosahedron; they may be viewed as defects compared to the un-strained hexagons. All atoms are equivalent and occur at the vertex joining one pentagon and two hexagons [120]. C 70-D5h is similar, with the 10 extra atoms inserted in a hexagons band around the truncated-icosahedron middle, producing a prolate ellipsoid. A substructure [121], where the five non-equivalent atoms are labelled a–e, Fig. (5a), shows that atoms a–d join one pentagon with two hexagons, while atom e joins three hexagons. On going from a to e the distance from the nearest pentagon increases. H atoms introduced by C60 chemical reduction would lay in the cluster outside [122,123]. The symmetric exohedral structure was predicted highly strained. Endo-C60H60 isomers with C–H bonds pointing inside the cavity resulted more stable than their all-out counterparts did. The calculations refer to AM1 optimum number of inside H atoms and geometry, which has 10 endo-H [124]. The solvation descriptors (cf. Table 5) show that –∆Gsolv,water,C60–82 increase from 16–21kJ·mol-1. –∆Gsolv,1-octanol increases from 129–172kJ·mol-1. Po–ch–cf increase by seven orders of magnitude with the number of atoms. (C60)2-C5h results show logPo ≈ 39 indicating that a negligible quantity remains in water. When the calculation was repeated imposing the condition that the aqueous phase be entirely assigned to the monomer, the organic phase is additionally favoured by 2.7 log units. The other organic solvents show a similar effect. C60H60 results show that no important effect on logP is expected related to the all-exo (Ih) or partially endo (C1) H-atom position. Both SCAP logP indicate that all C60H60 would remain in the organic phase. A sharp discrepancy in the orders of magnitude is predicted by CDHI for logPo (≈3–4). CDHI results indicate a preferential solubility in 1-octanol of only 103 times that in water, a prediction that seems unlikely for a system that can be thought as fully saturated of cyclic tertiary C atoms. CDHI spurious results illustrate the danger of using parameter-fitted methods out of the range of molecules that were used in the fitting. LogPch–cf results are of the same order of magnitude as reference calculations performed with a method by Leo and Hansch. SCAP analysis shows that C 70-a–c normalized-logPo–ch–cf contributions are slightly greater than those of d–e are, what can be explained because the distances from the nearest pentagon D vary gradually from a to e. CDHI cannot differentiate atoms a–e. SCAP C70 MLP (10×normalized logPo), Fig. (5b), shows that lipophilicity decreases as D increases, and logPo vs. D, Fig. (6) correlates as: Log Po = 23.7 – 0.153 D – 0.0643D2 r = 0.997 s = 0.068 F = 190.2 (1)

Partition of Solvents and Co-Solvents

Frontiers in Drug Design & Discovery, 2005, Vol. 1 241

Fig. (5). Flat projection of ca. 3/10 of the structure of C70-D5h: (a) the five non-equivalent atom types (C5 axis is through the centre of the top and bottom pentagons), and (b) molecular lipophilicity pattern.

ORGANIC SOLVENT–WATER PARTITION OF NANOTUBES SWNT chromatographic purifications relied on size-exclusion chromatography of surfactant-stabilized dispersions with water as the mobile phase [125,126]. Poly(phenylacethylene)-wrapped multiple-wall carbon nanotubes (MWNT) were analyzed by gel permeation chromatography [127]. Functionalized SWNTs were purified by chromatography [128]. AQUAFAC SWNT aqueous solubility Sw (cf. Table 6) shows that Sw monotonically decreases with n and m. All the values of logSw < –3 meaning that less than 0.1% of SWNT is in solution. Even all –logSw values are greater than the Avogadro exponent is. The results are consistent with the fact that SWNTs are completely insoluble in water. SWNT solubility is hindered because SWNTs aggregate in bundles due to large van der Waals interactions. Although individual van der Waals forces are weak, the total force is large

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because of the great number of atoms interacting between the surfaces of aligned SWNTs. Ways of increasing SWNT solubility include the use of anionic–non-ionic surfactants. Table 5.

Solubility, Free Energy of Solvation, Partition and Atom-to-Atom Normalized Partition Coefficient Results for Fullerene Systems

logSwa ∆Gsolv,wb ∆Gsolv,oc

∆Gchd ∆Gsol,cfe logPof

logPo logPch logPcf logPchh logPcfj Ref.g Rf.i Rf.i

-23.9

-15.60

-128.7

-78.48

-103.2

19.9

13.8

11.1

11.6

15.4

21.0

C60 dimer (C5h) -43.8

-30.82

-250.0

-153.1

-202.4

38.5

27.6

21.5

24.2

30.1

42.0

Fullerene

C60 (Ih)

C60 dimer (C5h)k

–

-15.60

-250.0

-153.1

-202.4

41.2

–

24.2

26.0

32.8

45.0

C60H60 (10 H inside, C1)

-25.4

35.43

-122.3

-72.09

-91.44

27.7

2.76

18.9

16.9

22.3

29.8

C60H60 all-out (Ih)

-24.0

38.04

-124.5

-75.04

-97.67

28.6

4.07

19.9

17.4

23.8

30.8

C70 (D5h)

-27.0

-18.09

-148.4

-91.20

-119.9

22.9

15.8

12.8

13.6

17.9

24.4

C82 (C2)

-31.7

-20.86

-172.4

-106.2

-139.2

26.6

17.6

15.0

16.1

20.8

28.6

Fullerene

Atom type

logPof

logPo Ref.g

logPchh

logPch Ref.i

logPcfj

logPcf Ref.i

C60 (Ih)

a

20.0

13.8

11.0

11.7

15.3

21.2

C70 (D5h)

a

23.7

15.8

13.3

14.2

18.2

25.3

b

23.5

15.9

13.2

14.0

18.2

25.1

c

23.2

15.8

12.9

13.8

17.9

24.8

d

22.6

15.9

12.6

13.4

17.8

24.1

e

22.1

15.9

12.5

13.1

17.4

23.5

average

39.6

27.6

22.0

24.9

30.7

43.2

C60 dimer (C5h) a

Sw is the solubility in water (mol·L–1). b Gibbs free energy of solvation in water (kJ·mol–1). c Gibbs free energy of solvation in 1-octanol (kJ·mol–1). d Gibbs free energy of solvation in cyclohexane (kJ·mol–1). e Gibbs free energy of solvation in chloroform (kJ·mol–1). f Po is the 1-octanol–water partition coefficient. g Calculations carried out with a method developed by Kantola et al. h Pch is the cyclohexane–water partition coefficient. i Calculations carried out with a method developed by Leo and Hansch. j Pcf is the chloroform–water partition coefficient. k Here, C60 is calculated as monomer in water and van der Waals dimer in the organic phase.

Partition of Solvents and Co-Solvents

Frontiers in Drug Design & Discovery, 2005, Vol. 1 243

Fig. (6). Normalized logPo vs. distance from the nearest pentagon for C70-D5h.

LogSw(n,0)–(n,n) correlate well with (n2+nm+m2)1/2. LogSw(n,0) variation with (n2+nm+m2)1/2 turns out to be

log Sw( n,0 ) = −4.76 − 3.53(n2 + nm + m 2 ) N = 10

r = −0.999994 2

2 1/2

LogSw(n,n) variation with (n +nm+m )

r = −0.999998

(2)

s = 0.038

F = 707859.2

turns out to be

log Sw( n,n ) = −5.31− 4.09( n2 + nm + m2 ) N =6

12

12

s = 0.032

(3)

F = 836663.0

The absolute slope of (n,0) is smaller than that of (n,n) is. LogSw(n,0) results greater than logSw(n,n) does, especially for thicker SWNTs. LogSw(10,10) is the smallest for all SWNTs. SCAP partition coefficients (cf. Table 6) show that Po increases with n and m. All logPo > 3, meaning that more than 99.9% of the solute is in the organic phase. Even all logPo are greater than the Avogadro exponent is. LogPo results are of the same order of

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Table 6.

Solubility, Free Energy of Solvation, Partition and Atom-to-Atom Normalized Partition Coefficient Results for Carbon Nanotubes

Nanot.

log Swa ∆Gs,wb ∆Gsolv,oc ∆Gsol,chd ∆Gsolv,cfe log Pof

log Po log Pch log Pcf log Pchh log Pcfj Ref.g Ref.i Ref.i

90 (9,0)

-36.6

-25.3

-195.1

-105.2

-160.2

29.8

23.7

14.1

18.3

23.7

32.3

100 (10,0)

-40.1

-28.3

-222.0

-118.2

-179.8

34.0

28.0

15.8

21.1

26.6

37.0

110 (11,0)

-43.6

-31.3

-247.3

-131.3

-199.1

37.9

29.1

17.6

23.8

29.5

41.4

120 (12,0)

-47.1

-34.3

-271.7

-144.0

-218.0

41.7

33.0

19.3

26.3

32.3

45.6

130 (13,0)

-50.7

-37.3

-295.7

-156.7

-237.0

45.4

34.4

21.0

28.8

35.1

49.8

140 (14,0)

-54.2

-40.3

-319.5

-169.1

-256.2

49.1

38.1

22.6

31.3

37.9

53.9

150 (15,0)

-57.7

-43.2

-343.2

-181.6

-274.8

52.7

39.7

24.3

33.7

40.7

58.0

160 (16,0)

-61.3

-46.1

-366.8

-194.1

-293.6

56.3

43.3

26.0

36.2

43.5

62.1

170 (17,0)

-64.8

-48.9

-389.3

-207.0

-312.2

59.8

45.0

27.8

38.5

46.2

66.0

180 (18,0)

-68.4

-52.0

-413.8

-218.7

-330.6

63.6

48.5

29.3

41.1

48.9

70.2

100 (5,5)

-40.7

-27.5

-211.3

-114.8

-174.4

32.3

25.8

15.3

20.0

25.8

35.0

120 (6,6)

-47.8

-33.5

-264.0

-140.8

-212.6

40.5

31.0

18.8

25.5

31.5

44.2

140 (7,7)

-54.8

-39.5

-313.1

-165.7

-251.1

48.1

36.2

22.2

30.6

37.2

52.8

160 (8,8)

-61.9

-45.2

-359.8

-190.4

-288.2

55.3

41.6

25.5

35.5

42.7

60.9

180 (9,9)

-69.0

-51.0

-406.9

-215.0

-325.2

62.5

46.7

28.8

40.4

48.2

69.1

200 (10,10) -76.1

-56.8

-453.3

-239.5

-362.1

69.6

51.9

32.1

45.2

53.6

77.1

Nanotube

Atom type

logPof

logPo Ref.g

logPchh

logPch Ref.i

logPcfj

logPcf Ref.i

170 (17,0)

a (trivalent)

62.0

45.0

29.0

40.0

49.7

68.5

b (divalent)

63.1

45.0

29.5

40.8

50.7

69.7

a (trivalent)

72.2

51.9

33.6

46.9

56.3

80.0

b (divalent)

74.4

51.9

34.5

48.4

60.0

82.4

200 (10,10)

a

Francisco Torrens

Sw is solubilty in water (mol·L-1). b Gibbs free energy of solvation in water (kJ·mol-1). c Gibbs free energy of solvation in 1-octanol (kJ·mol-1). d Gibbs free energy of solvation in cyclohexane (kJ·mol-1). e Gibbs free energy of solvation in chloroform (kJ·mol-1). f Po is the 1-octanol–water partition coefficient. g Calculations carried out with a method by Kantola et al. h Pch is the cyclohexane–water partition coefficient. i Calculations carried out with a method by Leo and Hansch. j Pcf is the chloroform–water partition coefficient.

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Frontiers in Drug Design & Discovery, 2005, Vol. 1 245

magnitude as reference calculations performed with CDHI. LogPo error is 30%. SCAP logPo(n,0)–(n,n) correlate well with (n2+nm+m2)1/2. LogPo(n,0) variation with (n2+nm+m2)1/2 turns out to be

log Po (n,0 ) = −3.17 + 3.72( n2 + nm + m2 ) N = 10

r = 0.9998 2

(4)

s = 0.257 2 1/2

LogPo(n,n) variation with (n +nm+m )

F = 17257.3

turns out to be

log Po (n,n ) = −4.27 + 4.28( n2 + nm + m2 ) N =6

12

r = 0.9996

12

(5)

s = 0.413

F = 5656.5

The slope of the (n,0) curve is smaller than that of the (n,n) curve is. LogPo(n,0) results smaller than logPo(n,n) does, especially for thicker SWNTs. Pch–cf increase with n and m. Most logP values are greater than the Avogadro exponent is. LogPch–cf results are of the same order of magnitude as reference calculations performed with the method by Leo and Hansch. LogPch–cf error is –28%. LogPch(n,0) variation vs. (n2+nm+m2)1/2 turns out to be

log Pch ( n, 0) = −1.08 + 1.69(n2 + nm + m2 ) N = 10

r = 0.99992 2

r = 0.99993

12

LogPcf(n,0) variation with (n +nm+m )

r = 0.99995 2

12

(8)

s = 0.089 2 1/2

LogPcf(n,n) variation with (n +nm+m )

F = 29068.9

turns out to be

log Pcf ( n,0 ) = −1.36 + 2.80( n2 + nm + m2 ) N = 10

(7)

s = 0.082 2 1/2

F = 50691.1

turns out to be

log Pch ( n, n ) = −1.35 + 1.93(n 2 + nm + m2 ) 2

(6)

s = 0.068 2 1/2

LogPch(n,n) variation with (n +nm+m )

N =6

12

F = 80850.0

turns out to be

log Pcf ( n,n ) = −1.87 + 3.21(n 2 + nm + m2 )

1 2

N = 6 r = 0.99994

s = 0.128

(9)

F = 33121.7

LogPo–ch–cf(10,10) are the greatest for all SWNTs. The partition of SCAP logP for (17,0)–(10,10) shows that the contribution of the trivalent atoms a is smaller that that of the divalent atoms b is. However, CDHI does not differentiate atoms a–b. (17,0)–(10,10) MLPs, Fig. (7), show that divalent atoms b present the greatest lipophilicity.

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Partition of Solvents and Co-Solvents

Frontiers in Drug Design & Discovery, 2005, Vol. 1 247 (Fig. 7) contd….

Fig. (7). (17,0) Nanotube: (a) projection (fragment) showing non-equivalent atoms, and (b) molecular lipophilicity pattern (MLP); (10,10): (c) projection and (d) MLP.

ORGANIC SOLVENT–WATER PARTITION INCLUSION COMPLEX FORMATION

OF

FULLERENES

VIA

Wennerström’s group studied by molecular modelling [129], photophysics [130] and spectroscopy [131,132] a water-soluble (CD8)2·C60 inclusion complex, in which hydrophobic interactions are responsible, Fig. (8) [133–143]. One problem with highly symmetric C60 is that ring currents in hexagons are offset by those in neighbouring pentagons, giving rise to unpredictable NMR chemical shifts. The recognition of CDs binding to these systems is difficult to study, because of multiple association states where 2–1:1 complexes are in equilibrium with uncomplexed states, and the equilibria are affected by subtle changes in environmental conditions. Molecular modelling gained insight into equilibrium nature and complex structures. Charge-transfer complex C60δ––CD8δ+ was reported, with ether and alcoholic O atoms being electron donors [144]. AMBER force-field calculations performed to understand inclusion kinetics for the 2:1 C60 complex showed that dispersion forces dominated the associations [145]. Kadish’s group solubilized C60 in water and some polar organic solvents by CD6–8 inclusion chemistry [146]. Electrochemical [147] and photochemically reduced CD 8–C60– complex was studied [148]. C70 binding to CD8 was computed [149]. Cycloisomaltoheptaose and octaose (CI 7–8) water-soluble inclusion (2:1) complexes were formed with C60–70 [150]. C60–70 were solubilized by CD8 complexation, and C60 and dimer, with sulfocalix[8]arene [151]. The accessible C60 surface in CD7 complex is increased 8-fold compared to CD8 complex, which is important for bioapplications [152]. CD6 does not form an inclusion complex. C 60 incorporated into artificial lipid membranes. Natural and substituted CDs, and calixarenes were investigated for C60 aqueous solubilization [153], and proved that underivatized CD8 has unique solubilizing power, as it produces stable solutions and solids containing real 1:2 complexes, explained the differences in solution appearance

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(magenta–brown colour) by C60 hydration within the supramolecule, and proved complex composition and structure by chemical analyses, X-ray diffraction, AFM and solid-state NMR.

Fig. (8). Schematic description of cyclodextrin8–C60 complexes derived from molecular modelling: (a) 1:1 and (b) 2:1.

Co