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Cell Press, Trends in Microbiology, 2(19), p. 65-74

DOI: 10.1016/j.tim.2010.10.005

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Computational databases, pathway and cheminformatics tools for tuberculosis drug discovery

Journal article published in 2010 by Sean Ekins ORCID, Joel S. Freundlich, Inhee Choi, Malabika Sarker, Carolyn Talcott
This paper is available in a repository.
This paper is available in a repository.

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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 these data 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 examined in this review. We suggest that these computational approaches should be optimally integrated within a workflow with experimental approaches to accelerate TB drug discovery.