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Computational databases, pathway and cheminformatics tools for tuberculosis drug discovery

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TRENDS IN MICROBIOLOGY
卷 19, 期 2, 页码 65-74

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ELSEVIER SCI LTD
DOI: 10.1016/j.tim.2010.10.005

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  1. Bill and Melinda Gates Foundation [49852]
  2. National Institute of Allergy and Infectious Diseases [R41AI088893]

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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.

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