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
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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
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enz
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