Prioritizing Genomic Drug Targets in Pathogens: Application to Mycobacterium tuberculosis

Citation: Hasan S, Daugelat S, Rao PSS, Schreiber M ( Prioritizing Genomic Drug Targets in Pathogens: Application to Mycobacterium tuberculosis Samiul Hasan 0 1 Sabine Daugelat 0 1 P. S. Srinivasa Rao 0 1 Mark Schreiber mark.schreiber@novartis 0 1 0 Novartis Institute for Tropical Diseases (NITD) , Chromos , Singapore 1 PLoS Computational Biology 2 www.ploscompbiol.org We have developed a software program that weights and integrates specific properties on the genes in a pathogen so that they may be ranked as drug targets. We applied this software to produce three prioritized drug target lists for Mycobacterium tuberculosis, the causative agent of tuberculosis, a disease for which a new drug is desperately needed. Each list is based on an individual criterion. The first list prioritizes metabolic drug targets by the uniqueness of their roles in the M. tuberculosis metabolome (''metabolic chokepoints'') and their similarity to known ''druggable'' protein classes (i.e., classes whose activity has previously been shown to be modulated by binding a small molecule). The second list prioritizes targets that would specifically impair M. tuberculosis, by weighting heavily those that are closely conserved within the Actinobacteria class but lack close homology to the host and gut flora. M. tuberculosis can survive asymptomatically in its host for many years by adapting to a dormant state referred to as ''persistence.'' The final list aims to prioritize potential targets involved in maintaining persistence in M. tuberculosis. The rankings of current, candidate, and proposed drug targets are highlighted with respect to these lists. Some features were found to be more accurate than others in prioritizing studied targets. It can also be shown that targets can be prioritized by using evolutionary programming to optimize the weights of each desired property. We demonstrate this approach in prioritizing persistence targets. - The Need for Tools to Rapidly Identify Drug Targets The cost of research and development in the pharmaceutical industry has been rising steeply and steadily in the last decade, but the amount of time required to bring a new product to market remains around ten to fifteen years [1]. This problem has been labeled an innovation gap, and it necessitates investment in inexpensive technologies that shorten the length of time spent in drug discovery. The target identification stage is the first step in the drug discovery process [2] and as such can provide the foundation for years of dedicated research in the pharmaceutical industry. As with all the other steps in drug discovery, this stage is complicated by the fact that the identified drug target must satisfy a variety of criteria to permit progression to the next stage. Important factors in this context include homology between target and host (to prevent host toxicity such homology must be low or nonexistent [3]); activity of the target in the diseased state [4,5]; and the essentiality of the target to the pathogens growth and survival [68]. The values of some of these selection criteria can be found easily by querying publicly available bioinformatics resources, including metabolic pathway databases such as KEGG (Kyoto encyclopedia of genes and genomes) [9], protein classification sets such as COGs (clusters of orthologous groups) [10], and databases of druggable (potentially useful as drug targets) proteins [5,11,12]. Traditional prioritization approaches such as literature searches and mental integration of multiple criteria can quickly become overwhelming for the researcher. A more effective alternative is computational integration over different criteria to create a ranking function. In this article, we describe such an applicationAssessDrugTargetthat ranks the genes in a genome according to a given set of weighted criteria. The Need for New Drugs for Tuberculosis Tuberculosis (TB) is one of the most serious infectious diseases worldwide. The World Health Organization predicts that between 2002 and 2020, 36 million people will have died from TB [13]. Infection occurs via aerosol, and inhalation of only a few droplets containing M. tuberculosis bacilli is sufficient for the pathogen to infect the lungs. Subsequently, the pathogenesis of M. tuberculosis infection occurs in two stages. The first stage, latent TB, is an asymptomatic state that can persist for many years in the host, requiring only a Editor: Gennady Verkhivker, Pfizer, United States of America The search for drugs to prevent or treat infections remains an urgent focus in infectious disease research. A new software program has been developed by the authors of this article that can be used to rank genes as potential drug targets in pathogens. Traditional prioritization approaches to drug target identification, such as searching the literature and trying to mentally integrate varied criteria, can quickly become overwhelming for the drug discovery researcher. Alternatively, one can computationally integrate different criteria to create a ranking function that can help to identify targets. The authors demonstrate the applicability of this approach on the genome of Mycobacterium tuberculosis, the organism that causes tuberculosis (TB), a disease for which new drug treatments are especially needed because of emerging drug-resistant strains. The experiences gained from this work will be useful for both wetlab and informatics scientists working in infectious disease research; first, it demonstrates that ample public data already exist on the M. tuberculosis genome that can be tuned effectively for prioritizing drug targets. Second, the output from numerous freely available bioinformatics tools can be pushed to achieve these goals. Third, the methodology can easily be extended to other pathogens of interest. Currently studied TB targets are also highlighted in terms of the authors ranking system, which should be useful for researchers focusing on TB drug discovery. weakened immune response to become activated [14]. In the second stage, active TB, the bacteria begins replicating and causing cough, chest pain, fatigue, and unexplained weight loss. If untreated, the disease eventually culminates in the death of the patient. The currently available treatment for TB, DOTS (directly observed treatment, short course), lasts for an exhausting 6 mo. The first 2 mo involve a strictly scheduled and monitored intake of four drugs: isoniazid (INH), rifampicin (RIF), pyrazinamide (PZA) and ethambutol (EMB) [1517]. This phase is followed by a continuation phase of 4 mo of INH and RIF. The problem of persistence. Only RIF and PZA show activity against persisters, organisms that are in the dormant phase. These drugs have helped to substantially shorten the length of DOTS therapy from between 12 and 18 mo to between 9 and 6 mo [16]. However, they do not eliminate all dormant populations, and PZA is likely to affect only those persisters that reside in acidic pH (...truncated)