Current Pharmaceutical Design - Volume 8, Issue 13, 2002

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 postantibiotic 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.

Whole chromosome sequence of prokaryotes has provided the availability of multiple bacterial pathogen sequence data and it has become a widely used tool in the drug discovery process. However the sequence data in itself is merely a starting point for drug discovery of novel antibacterial targets and, eventually, drugs. In order to leverage this large amount of data it is necessary to match an understanding of the microbial physiology of pathogenic bacteria to disease processes and identifying the gene products for which intervention may reduce or eliminate the infectious state. However, to date, the application of genomics to anti-infective drug discovery has not, since 1995 with the first complete sequence of a pathogenic bacterium, led to identification of a novel antibacterial agent. Here we review the field of bacterial genomics and how it is enabling the drug discovery process. Many new molecular-based technologies (proteomics, transcriptional profiling, studies of gene expression in vivo) have originated or have expanded into wider use, and have been made possible by the availability of complete bacterial genome sequence information and subsequent bioinformatic analytic tools. Taken together, these technologies, overlaid within an established drug discovery program, now affords the opportunity for the identification, validation, and process design for high-throughput target mining at unprecedented volumes and timeframes.

The process of prokaryotic drug discovery has been a model of success for over fifty years, yet the number of exploited bacterial targets is a mere fraction, less than 0.1% of the potential targets (based on total number of bacterial genes identified by gene sequence projects). To better understand the potential for drug intervention, multiple paradigms have been established in the pharmaceutical industry, all with some semblance of commonality and uniqueness to provide proprietary positioning, yet no company has been successful to date in taking a ‘genomics approach’ to the finish line of having a genomics-based drug on the market. Within this overview, we provide a strategic overview of a sample process for the identification, validation and exploitation of novel antibacterial targets ascertained through a bioinformatics-based genomics drug discovery program.

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.

In large part, antimicrobial drug discovery is driven by the breadth and quality of both potential drug targets and available chemical libraries to screen. Traditionally, targets have been few in number and have been limited to those with known function, from which biochemical assays could be implemented into drug screens. Iterations of this same basic approach, applied to a few biochemically-defined targets have identified a limited set of novel antibiotics and even fewer antifungal agents. Indeed, in the last 50 years less than 30 antimicrobial targets have been exploited commercially. Within infectious disease, the industry was driven largely by chemistry-based approaches, simply making new analogs to existing drugs to overcome the growing problem of drug resistance. Elitra Pharmaceutical's approach has been to enable true functional genomics on a genome-wide scale. Elitra's vision has been to identify all of the essential genes directly in the key pathogenic organisms. Having moved rapidly towards the completion of this goal, we are now faced with the enviable challenge of prioritizing enormous target sets and developing novel sensitive screens for those best suited as definitive drug targets. These highly sensitive, cell-based screening paradigms enable re-screening of even well screened chemical libraries to reveal new chemical entities displaying novel modes of action against new targets. In parallel, we have also begun to shift the paradigm from screening targets singly, towards genome-wide approaches to drug screening.

Structural Genomics stands out among the emerging fields of proteomics since it influences the drug discovery process at so many points. Recent developments in protein expression technologies, x-ray crystallography and NMR spectroscopy provide the essential elements for high-throughput structure determination platforms. Bioinformatics methods to interrogate the resulting data will provide comprehensive, genome-wide databases of protein structure. Genomic sequencing and methods for high-throughput expression and protein purification are furthest advanced for microbial genes and so these have been the early targets for structural genomics initiatives. The information will be invaluable in understanding gene function, designing broad-spectrum small molecule inhibitors and in better understanding drug-host interactions.

Despite considerable progress in the analysis of microbial genomes, the number of validated targets suitable for the development of drugs acting on agents causing infectious diseases remains modest. The diversity of new chemical entities specific for such targets has almost not increased over the last years, while resistance to antiinfectious drugs has, in contrast, become a real threat in certain surroundings. New strategies are thus needed for selecting novel validated targets. We discuss here a combined approach which uses protein interaction mapping as the basic strategy to identify interacting domains which then serve to validate newly identified targets. The interactome of Helicobacter pylori is used as model to successively describe high-throughput protein interaction mapping, use of the H. pylori data to predict the interactome from other bacteria, analysis of interacting domains, and evaluation of the capacity of one such domain to block synthesis of flagella. The general applicability of this approach to target identification and validation, and to development of novel compounds is also discussed.