微生物基因组上药物作用靶位的识别

在基因组时代 ,开发抗微生物的新药离不开基因组研究 ,基因组测序和生物信息学的迅猛发展使得微生物基因组上药物作用靶位的识别成为可能 ,并将使得细菌、真菌和寄生虫等对抗生素的耐药性成为过去。本文综述了应用基因组信息技术识别微生物基因组上药物作用靶位的方法和进展     

Novel antibacterials: a genomics approach to drug discovery

The appearance of antibiotic resistant pathogens, including vancomycin resistant Staphylococcus aureus, in the clinic has necessitated the development of new antibiotics. The golden age of antibiotic discovery, in which potent selective compounds were readily extracted from natural product extracts is over and novel approaches need to be implemented to cover the therapeutic shortfall. The generation of huge quantities of bacterial sequence data has allowed the identification of all the possible targets for therapeutic intervention and allowed the development of screens to identify inhibitors. Here, we described a number of target classes in which genomics has contributed to its identification. As a result of analyzing sequence data, all of the tRNA synthetases and all of the two-component signal transduction systems were readily isolated; which would not have been easily identified if whole genome sequences were not available. Fatty acid biosynthesis is a known antibacterial target, but genomics showed which genes in that pathway had the appropriate spectrum to be considered as therapeutic targets. Genes of unknown function may seem untractable targets, but if those that are broad spectrum and essential are identified, it becomes valuable to invest time and effort to determine their cellular role. In addition, we discuss the role of genomics in developing technologies that assist in the discovery of new antibiotics including microarray gridding technology. Genomics can also increase the chemical diversity against which the novel targets can be screened.     

Genomics strategies for antifungal drug discovery--from gene discovery to compound screening

The use of genomics tools to discover new genes, to decipher pathways or to assign a function to a gene is just beginning to have an impact. Genomics approaches have been applied to both antibacterial and antifungal target discovery in order to identify a new generation of antibiotics. This review discusses genomics approaches for antifungal drug discovery, focusing on the areas of gene discovery, target validation, and compound screening. A variety of methods to identify fungal genes of interest are discussed, as well as methods for obtaining full-length sequences of these genes. One approach is well-suited to organisms having few introns (Candida albicans), and another for organisms with many introns (Aspergillus fumigatus). To validate broad spectrum fungal targets, the yeast Saccharomyces cerevisiae was used as a model system to rapidly identify genes essential for growth and viability of the organism. Validated targets were then exploited for high-throughput compound screening.     

The role of genomics in antibacterial target discovery

Complete DNA sequence information has now been obtained for several prokaryotic genomes, defining the entire genetic complement of these organisms. The collection of genomic data has provided new insights into the molecular architecture of bacterial cells, revealing the basic genetic and metabolic structures that support viability of the organisms. Genomic information has also revealed new avenues for inhibition of bacterial growth and viability, expanding the number of possible drug targets for antibiotic discovery. This review examines how genomic sciences and experimental tools are applied to antibacterial target discovery, the necessary first step in the development of new antibiotic classes. Significant advances have been realized in the development of functional genomic, comparative genomic, and proteomic methods for the analysis of completed genomes. The combination of these methods can be used to systematically parse the genome and identify targets worthy of inhibitor screens. Two basic categories of targets emerge from this exercise, comprising in vitro essential targets required for bacterial viability on synthetic media and in vivo essential targets required to establish and maintain infection within a host organism. Current use of genomic information is focused primarily on a definition of all in vitro essential targets that satisfy criteria of selectivity, spectrum, and novelty. As the genomes of additional bacterial pathogens are solved, it will be possible to select in vivo essential targets common to groups of select pathogens (e.g., bacterial agents of community acquired pneumonia) or even pathogen-specific targets. Consideration of host-pathogen interactions, defined at the level of gene expression for each organism, might provide novel therapeutic options in the future.     

Genomics and the prospects for the discovery of new targets for antibacterial and antifungal agents

The current increase in the number of microbes resistant to antibacterial or antifungal agents represents a potential crisis in human and veterinary medicine. Some believe that we are entering a post-antibiotic era where most antibiotics no longer will be efficacious. Therefore, it is important that new antibiotics be developed. However, because of the potential for cross-resistance, new targets for the discovery of antibiotics are needed particularly where resistance does not currently exist. The results obtained from the sequencing of genomes from pathogenic bacterial and fungal microbes provide an opportunity to ameliorate this problem. Genomic sequence data can be used to identify new genes that could be used as targets for new antibiotic discoveries. Viable new target genes might represent those that are widely distributed among pathogens or that have homologs and are essential for the viability of the organism. Chemical compounds that attack such targets would be expected to have classical antibiotic activities. Less widely distributed genes still could be valuable targets for narrow spectrum antibiotics. While many of these genes will have known or putative functions based on DNA sequence homology, the most interesting genes are the newly discovered genes with unknown functions. In this paper, it is suggested that novel, non-traditional targets also will be found through the analysis of genome sequences: those that are involved in disease pathogenesis and those that are involved in adaptation and growth in infection sites. The advantage of the non-classical targets is that targeting these sites may not result in the same degree of selective pressure that encourages resistance, and these could have a longer therapeutic life time.     

In silico research in drug discovery

Target and lead discovery constitute the main components of today's early pharmaceutical research. The aim of target discovery is the identification and validation of suitable drug targets for therapeutic intervention, whereas lead discovery identifies novel chemical molecules that act on those targets. With the near completion of the human genome sequencing, bioinformatics has established itself as an essential tool in target discovery and the in silico analysis of gene expression and gene function are now an integral part of it, facilitating the selection of the most relevant targets for a disease under study. In lead discovery, advances in chemoinformatics have led to the design of compound libraries in silico that can be screened virtually. Moreover, computational methods are being developed to predict the drug-likeness of compounds. Thus, drug discovery is already on the road towards electronic R&D.     

The role of genomics in the discovery of novel targets for antibiotic therapy

The emergence of antibiotic resistance and multi-drug resistance in bacterial pathogens underscores the need for the development of novel classes of antibiotics. The availability of complete genome sequence data from many important human pathogens provides a wealth of fundamental information. This allows us to define each gene and thus to better understand molecular pathogenesis. New techniques have enabled the identification and characterization of genes that are critical for bacterial growth and survival during infection. The combination of genome sequence data and new technologies make it possible to systematically explore the function of each open reading frame in a genome and identify any potential molecular targets for drug discovery. With particular emphasis on antibacterial therapy, this review discusses genome-based technologies and their important applications to anti-infective drug discovery.     

Delivering novel targets and antibiotics from genomics

Recent advances in DNA sequencing technology have made it possible to elucidate the sequences of the entire genomes of pathogenic bacteria and concomitant advancements in bioinformatic tools have driven comparative studies of these genome sequences. These evaluations are significantly increasing our ability to make valid considerations of the limitations and advantages of particular targets based on their predicted spectrum and selectivity. In addition, developments in gene-essentiality technologies amenable to pathogenic organisms liave enabled new genes and gene products critical to bacterial growth and pathogenicity to be uncovered at an unprecedented rate. This review will describe how aspects of the above capabilities are impacting the discovery and characterization of known and novel antibacterial targets using specific examples taken from a variety of important, diverse bacterial processes.     

Screening the receptorome: an efficient approach for drug discovery and target validation

The receptorome, comprising at least 5% of the human genome, encodes receptors that mediate the physiological, pathological and therapeutic responses to a vast number of exogenous and endogenous ligands. Not surprisingly, the majority of approved medications target members of the receptorome. Several in silico and physical screening approaches have been devised to mine the receptorome efficiently for the discovery and validation of molecular targets for therapeutic drug discovery. Receptorome screening has also been used to discover, and thereby avoid, the molecular targets responsible for serious and unforeseen drug side effects.     

Peptide ligands in antibacterial drug discovery: use as inhibitors in target validation and target-based screening

There is an urgent need to develop novel classes of antibiotics to counter the inexorable rise of resistant bacterial pathogens. Modern antibacterial drug discovery is focused on the identification and validation of novel protein targets that may have a suitable therapeutic index. In combination with assays for function, the advent of microbial genomics has been invaluable in identifying novel antibacterial drug targets. The major challenge in this field is the implementation of methods that validate protein targets leading to the discovery of new chemical entities. Ligand-directed drug discovery has the distinct advantage of having a concurrent analysis of both the importance of a target in the disease process and its amenability to functional modulation by small molecules. VITA is a process that enables a target-based paradigm by using peptide ligands for direct in vitro and in vivo validation of antibacterial targets and the implementation of high-throughput assays to identify novel inhibitory molecules. This process can establish sufficient levels of confidence indicating that the target is relevant to the disease process and inhibition of the target will lead to effective disease treatment.     

The promise of genomics to identify novel therapeutic targets

The cataloguing of the human genome has provided an unprecedented prospectus for target identification and drug discovery. A current analysis indicates that slightly more than 3000 unique protein encoding loci are potentially amenable to pharmacological intervention (the 'druggable genome', which can be queried at http://function.gnf.org/druggable). However, the assessment of genome sequence data has not resulted in the anticipated acceleration of novel therapeutic developments. The basis for this shortfall lies in the significant attrition rates endemic to preclinical/clinical development, as well as the often underestimated complexity of gene function in higher order biological systems. To address the latter issue, a number of strategies have emerged to facilitate genomics-driven target identification and validation, including cellular profiling of gene function, in silico modelling of gene networks, and systematic analyses of protein complexes. The expectation is that the integration of these and other systems-based technologies may enable the conversion of potential genomic targets into functionally validated molecules, and result in practicable gene-based drug discovery pipelines.     

Transgenic gene knock-outs: functional genomics and therapeutic target selection

The completion of the first draft of the human genome presents both a tremendous opportunity and enormous challenge to the pharmaceutical industry since the whole community, with few exceptions, will soon have access to the same pool of candidate gene sequences from which to select future therapeutic targets. The commercial imperative to select and pursue therapeutically relevant genes from within the overall content of the genome will be particularly intense for those gene families that currently represent the chemically tractable or 'drugable' gene targets. As a consequence the emphasis within exploratory research has shifted towards the evaluation and adoption of technology platforms that can add additional value to the gene selection process, either through functional studies or direct/indirect measures of disease alignment e.g., genetics, differential gene expression, proteomics, tissue distribution, comparative species data etc. The selection of biological targets for the development of potential new medicines relies, in part, on the quality of the in vivo biological data that correlates a particular molecular target with the underlying pathophysiology of a disease. Within the pharmaceutical industry, studies employing transgenic animals and, in particular, animals with specific gene deletions are playing an increasingly important role in the therapeutic target gene selection, drug candidate selection and product development phases of the overall drug discovery process. The potential of phenotypic information from gene knock-outs to contribute to a high-throughput target selection/validation strategy has hitherto been limited by the resources required to rapidly generate and characterise a large number of knock-out transgenics in a timely fashion. The offerings of several companies that provide an opportunity to overcome these hurdles, albeit at a cost, are assessed with respect to the strategic business needs of the pharmaceutical industry.     

Target validation

With the publication of draft maps of the human genome and an interim agreement that the human genome comprises approximately 21000 genes, there has been considerable anticipation that many novel disease-specific molecular targets will be rapidly identified and that these will form the basis of many new drug discovery programs. Genes associated with a given disease can thus be identified using genotyping and microarray approaches. However, transitioning from the identification to the subsequent validation and prioritization of their cognate proteins as bona fide drug targets using proteomic techniques--a process that could appropriately be termed targetomics--is still very much in its infancy, with expectations far exceeding present capabilities. The criteria for target validation have yet to be determined and the timing to success has been underestimated. Integrated pharmacological approaches that involve the use of the traditional null hypothesis approach and statistically validated replication have been largely overlooked in the enthusiasm to be the first to find new targets. Inevitably, the only useful measure of target validation occurs when a drug-like molecule, selective for the identified target, is advanced to the clinic where it can be shown to be efficacious in the appropriate human disease state.     

Fulfilling the promise: drug discovery in the post-genomic era

The genomic era has brought with it a basic change in experimentation, enabling researchers to look more comprehensively at biological systems. The sequencing of the human genome coupled with advances in automation and parallelization technologies have afforded a fundamental transformation in the drug target discovery paradigm, towards systematic whole genome and proteome analyses. In conjunction with novel proteomic techniques, genome-wide annotation of function in cellular models is possible. Overlaying data derived from whole genome sequence, expression and functional analysis will facilitate the identification of causal genes in disease and significantly streamline the target validation process. Moreover, several parallel technological advances in small molecule screening have resulted in the development of expeditious and powerful platforms for elucidating inhibitors of protein or pathway function. Conversely, high-throughput and automated systems are currently being used to identify targets of orphan small molecules. The consolidation of these emerging functional genomics and drug discovery technologies promises to reap the fruits of the genomic revolution.     

Structural bioinformatic approaches to the discovery of new antimycobacterial drugs

Integrated bioinformatic approaches to drug discovery exploit computational techniques to examine the flow of information from genome to structure to function. Informatics is being be used to accelerate and rationalize the process of antimycobacterial drug discovery and design, with the immediate goals to identify viable drug targets and produce a set of critically evaluated protein target models and corresponding set of probable lead compounds. Bioinformatic approaches are being successfully applied in the selection and prioritization of putative mycobacterial drug target genes; computational modelling and x-ray structure validation of protein targets with drug lead compounds; simulated docking and virtual screening of potential lead compounds; and lead validation and optimization using structure-activity and structure-function relationships. By identifying active sites, characterizing patterns of conserved residues and, where relevant, predicting catalytic residues, bioinformatics provides information to aid the design of selective and efficacious pharmacophores. In this review, we describe selected recent progress in antimycobacterial drug design, illustrating the strengths and limitations of current structural bioinformatic approaches as tools in the fight against tuberculosis.     

Support vector machines approach for predicting druggable proteins: recent progress in its exploration and investigation of its usefulness

Identification and validation of viable targets is an important first step in drug discovery and new methods, and integrated approaches are continuously explored to improve the discovery rate and exploration of new drug targets. An in silico machine learning method, support vector machines, has been explored as a new method for predicting druggable proteins from amino acid sequence independent of sequence similarity, thereby facilitating the prediction of druggable proteins that exhibit no or low homology to known targets.     

Functional Genomics Conference: From Identifying Proteins to Faster Drug Discovery. March 10-11, 1998, Washington DC, USA

The massive effort to sequence the human, mouse, rat, nematode (Caenorhabditis elegans), fruit fly (Drosophila), zebra fish, yeast (Saccharomyces cerevisiae), fungal (Candida albicans and Aspergillus fumigatus) and several bacterial genomes has produced a flood of sequence data. Of the more than 100,000 human genes and thousands from other organisms, many partial sequences and several completed microbial genomes are available in both public and private databases. However, elucidation of function has been achieved for only a very small portion and an even smaller percentage have been validated as drug targets. Many companies interested in identifying new drug targets also see this bounty of opportunity as a major challenge. The raw sequence data say little about the importance of the gene and nothing about its potential as a target for drug discovery. Since 1994, a new term, 'functional genomics', has entered our lexicon. Functional genomics, which in effect is 'high-throughput biology', was originally focused on understanding gene function by studying the genes of simpler organisms, such as the nematode, C. elegans. As the genes from a number of organisms are highly conserved across species, it is believed that studying these basic systems can yield valuable insights for drug companies interested in targeting therapeutics for the higher organisms. More recently, the approach to functional genomics has expanded to include study of gene function in organisms to be targeted for therapeutic intervention. This new approach was the theme of the Functional Genomics Conference: From Identifying Proteins to Faster Drug Discovery held in Washington DC on March 10 and 11, 1998. The organisers (NMHCC) hoped that the breadth of the conference topics would reflect the complexities of the modern drug discovery process and covered technologies from gene chips, bioinformatics, disease models, protein discovery and expression, target validation, high-throughput screening for genes of unknown function, to integration of the drug discovery process. The two day conference placed emphasis on cutting edge technology solutions and the development of high-throughput tools to address the emerging opportunities in genome-based drug discovery.     

Functional Genomics Conference: From Identifying Proteins to Faster Drug Discovery

The massive effort to sequence the human, mouse, rat, nematode (Caenorhabditis elegans), fruit fly (Drosophila), zebra fish, yeast (Saccharomyces cerevisiae), fungal (Candida albicans and Aspergillus fumigatus) and several bacterial genomes has produced a flood of sequence data. Of the more than 100,000 human genes and thousands from other organisms, many partial sequences and several completed microbial genomes are available in both public and private databases. However, elucidation of function has been achieved for only a very small portion and an even smaller percentage have been validated as drug targets. Many companies interested in identifying new drug targets also see this bounty of opportunity as a major challenge. The raw sequence data say little about the importance of the gene and nothing about its potential as a target for drug discovery. Since 1994, a new term, ‘functional genomics’, has entered our lexicon. Functional genomics, which in effect is ‘high-throughput biology’, was originally focused on understanding gene function by studying the genes of simpler organisms, such as the nematode, C. elegans. As the genes from a number of organisms are highly conserved across species, it is believed that studying these basic systems can yield valuable insights for drug companies interested in targeting therapeutics for the higher organisms. More recently, the approach to functional genomics has expanded to include study of gene function in organisms to be targeted for therapeutic intervention. This new approach was the theme of the Functional Genomics Conference: From Identifying Proteins to Faster Drug Discovery held in Washington DC on March 10 and 11, 1998. The organisers (NMHCC) hoped that the breadth of the conference topics would reflect the complexities of the modern drug discovery process and covered technologies from gene chips, bioinformatics, disease models, protein discovery and expression, target validation, high-throughput screening for genes of unknown function, to integration of the drug discovery process. The two day conference placed emphasis on cutting edge technology solutions and the development of high-throughput tools to address the emerging opportunities in genome-based drug discovery.     

From drug target to leads--sketching a physicochemical pathway for lead molecule design in silico

The discovery of new pharmaceuticals via computer modeling is one of the key challenges in modern medicine. The advent of global networks of genomic, proteomic and metabolomic endeavors is ushering in an increasing number of novel and clinically important targets for screening. Computational methods are anticipated to play a pivotal role in exploiting the structural and functional information to understand specific molecular recognition events of the target macromolecule with candidate hits leading ultimately to the design of improved leads for the target. In this review, we sketch a system independent, comprehensive physicochemical pathway for lead molecule design focusing on the emerging in silico trends and techniques. We survey strategies for the generation of candidate molecules, docking them with the target and ranking them based on binding affinities. We present a molecular level treatment for distinguishing affinity from specificity of a ligand for a given target. We also discuss the significant aspects of drug absorption, distribution, metabolism, excretion and toxicity (ADMET) and highlight improved protocols required for higher quality and throughput of in silico methods employed at early stages of discovery. We present a realization of the various stages in the pathway proposed with select examples from the literature and from our own research to demonstrate the way in which an iterative process of computer design and validation can aid in developing potent leads. The review thus summarizes recent advances and presents a viewpoint on improvements envisioned in the years to come for automated computer aided lead molecule discovery.