title: The Mycobacterium tuberculosis drugome and its polypharmacological implications.
abstract: We report a computational approach that integrates structural bioinformatics, molecular modelling and systems biology to construct a drug-target network on a structural proteome-wide scale. The approach has been applied to the genome of Mycobacterium tuberculosis (M.tb), the causative agent of one of today's most widely spread infectious diseases. The resulting drug-target interaction network for all structurally characterized approved drugs bound to putative M.tb receptors, we refer to as the 'TB-drugome'. The TB-drugome reveals that approximately one-third of the drugs examined have the potential to be repositioned to treat tuberculosis and that many currently unexploited M.tb receptors may be chemically druggable and could serve as novel anti-tubercular targets. Furthermore, a detailed analysis of the TB-drugome has shed new light on the controversial issues surrounding drug-target networks [1]-[3]. Indeed, our results support the idea that drug-target networks are inherently modular, and further that any observed randomness is mainly caused by biased target coverage. The TB-drugome (http://funsite.sdsc.edu/drugome/TB) has the potential to be a valuable resource in the development of safe and efficient anti-tubercular drugs. More generally the methodology may be applied to other pathogens of interest with results improving as more of their structural proteomes are determined through the continued efforts of structural biology/genomics.
authors.affiliation: Institute of Molecular and Cellular Biology and Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom.
authors.forename: Sarah L
authors.initials: SL
authors.lastname: Kinnings
authors.forename: Li
authors.initials: L
authors.lastname: Xie
authors.forename: Kingston H
authors.initials: KH
authors.lastname: Fung
authors.forename: Richard M
authors.initials: RM
authors.lastname: Jackson
authors.forename: Lei
authors.initials: L
authors.lastname: Xie
authors.forename: Philip E
authors.initials: PE
authors.lastname: Bourne
mesh_terms: D000995:Antitubercular Agents / Q000737:chemistry / Q000494:pharmacology*; D001426:Bacterial Proteins / Q000378:metabolism*; D001665:Binding Sites; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D016208:Databases, Factual; D006801:Humans; D008954:Models, Biological; D058990:Molecular Targeted Therapy / Q000379:methods*; D009169:Mycobacterium tuberculosis / Q000378:metabolism*; D015203:Reproducibility of Results; D014376:Tuberculosis / Q000188:drug therapy / Q000382:microbiology
chemical_list: D000995:Antitubercular Agents; D001426:Bacterial Proteins