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.

Drug Repurposing: Far Beyond New Targets for Old Drugs

“…Recent academic enthusiasm in this field has resulted in the publication of relatively long lists of drugs that could potentially be repurposed for a variety of indications, including tuberculosis [41], breast and prostate cancer, and myelogenous leukemia [42]. This academic trend has two (unfortunate) consequences.…”

Potential non homologous protein targets of mycobacterium tuberculosis H37Rv identified from protein–protein interaction network

“…We have used TDR posted drug targets of MTB from http://tdrtargets.org which contains validated drug targets by manual curation from literatures. We also identified a high confidence drug targets from UniProt annotation for M. tuberculosis H37Rv and looked at a handful of genes reported to be predicted drug targets by Kinnings et al (2010) andUniProt (2008). Additionally, we have used the top 10 candidates by Mazandu and Nulder (2011).…”

“…From 3999 proteins in the Mtb proteome, only 284 unique proteins have solved structure in the RCSB Protein Data Bank (PDB) (Berman et al, 2000) (as November 5, 2009). This is approximated to only 7.2% structural coverage of the MTB proteome but by taking reliable homology models into consideration, it is possible to increase the structural coverage of the MTB proteome to approximately 43% (Kinnings et al, 2010). Hence out of 390 proteins from our proposed target list, only 33 have solved structure which is approximated to 8.46%.…”

Bioinformatics and Drug Discovery

“…The software CHARMM [227] and its derivatives facilitate the characterization of such dynamic interactions of proteins with their binding partners. Such studies are facilitated by general databases of drug-target interactions [180] and special databases documenting protein interactions in cancer cells [179] or in membranes involving GPCR-ligand associations [178] or organism-specific databases such as that for Mycobacterium tuberculosis [228].…”