Computational models for tuberculosis drug discovery

Sean Ekins, Joel S. Freundlich

Research output: Chapter in Book/Report/Conference proceedingChapter

17 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationIn Silico Models for Drug Discovery
PublisherHumana Press Inc.
Number of pages18
ISBN (Print)9781627033411
StatePublished - 2013

Publication series

NameMethods in Molecular Biology
ISSN (Print)1064-3745

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Genetics


  • Bayesian models
  • Collaborative Drug Discovery Tuberculosis database
  • Docking
  • Mycobacterium tuberculosis
  • Quantitative structure-activity relationship
  • Tuberculosis


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