@inbook{270c8fcf79304a81b6b7bc8872b6ea33,
title = "Computational models for tuberculosis drug discovery",
abstract = "The search for small molecules with activity against Mycobacterium tuberculosis increasingly uses high-throughput screening and computational methods. Previously, we have analyzed recent studies in which computational tools were used for cheminformatics. We have now updated this analysis to illustrate how they may assist in finding desirable leads for tuberculosis drug discovery. We provide our thoughts on strategies for drug discovery efforts for neglected diseases.",
keywords = "Bayesian models, Collaborative Drug Discovery Tuberculosis database, Docking, Mycobacterium tuberculosis, Quantitative structure-activity relationship, Tuberculosis",
author = "Sean Ekins and Freundlich, {Joel S.}",
year = "2013",
doi = "10.1007/978-1-62703-342-8_16",
language = "English (US)",
isbn = "9781627033411",
series = "Methods in Molecular Biology",
publisher = "Humana Press Inc.",
pages = "245--262",
booktitle = "In Silico Models for Drug Discovery",
}