Computational databases, pathway and cheminformatics tools for tuberculosis drug discovery

Abstract

We are witnessing the growing menace of both increasing cases of drug-sensitive and drug-resistant Mycobacterium tuberculosis strains and the challenge to produce the first new tuberculosis (TB) drug in well over 40 years. The TB community, having invested in extensive high-throughput screening efforts, is faced with the question of how to optimally leverage this data in order to move from a hit to a lead to a clinical candidate and potentially a new drug. Complementing this approach, yet conducted on a much smaller scale, cheminformatic techniques have been leveraged and are herein reviewed. We suggest these computational approaches should be more optimally integrated in a workflow with experimental approaches to accelerate TB drug discovery.

Validating New Tuberculosis Computational Models with Public Whole Cell Screening Aerobic Activity Datasets

“…Efforts to develop useful chemical probes of Mtb with the potential to inspire novel lead compounds have seen relatively limited application of cheminformatics methods that have been utilized in other therapeutic areas (5,19,31).…”

“…Antituberculosis drug discovery could use these Bayesian models (or other computational methods reviewed elsewhere (19)) and SMARTS alerts to assist in selecting compounds for in vitro screening that may have a higher probability of activity against Mtb while at the same time a lower probability of undesirable off-target effects due to chemical reactivity. In the words of Yogi Berra, "Life is a learning experience, only if you learn."…”

“…The contributions of this study are 1) further validation of Bayesian models of Mtb whole cell efficacy to deliver actives with a high degree of enrichment over random sampling and 2) demonstration of the utility of SMARTS filters to suggest potential liabilities and for refinement of either the chemical library input or hit set output for a screen. These along with similar cheminformatics methods (18,19) could help to identify new molecules that could become useful probes of Mtb essential biology or inspire novel antitubercular leads or drugs.…”

A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus

“…If this is the case it could provide a means to follow up with other small molecule analogs and/or additional FDA approved drugs that could target this protein-protein interaction. As with our other tuberculosis-focused research 32, 33 , and computational approaches to repositioning compounds 34 we embrace the essentiality for computational predictions to be interrogated through rigorous experimental studies. For example at least two in silico docking studies screened commercially available compounds 14, 15 .…”

Genetic Strategies for Identifying New Drug Targets

“…In a recent screen for antimycobacterial compounds (65), testing in excess of 100,000 compounds led to the identification of 1,549 hits. The prioritization of these for further development is currently based almost entirely on chemoinformatic approaches (66,67). However, knowledge of a compound's specific target accelerates the medicinal chemistry required to improve lead compounds.…”