In silico analyses for the discovery of tuberculosis drug targets

Bevan Kai Sheng Chung, Thomas Dick, Dong Yup Lee

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Antibacterial drug discovery ismoving fromlargely unproductive high-throughput screening of isolated targets in the past decade to revisiting old, clinically validated targets and drugs, and to classical black-box whole-cell screens. At the same time, due to the application of existingmethods and the emergence of newhigh-throughput biology methods, we observe the generation of unprecedented qualities and quantities of genomic and otheromics data on bacteria and their physiology. Tuberculosis (TB) drug discovery and biology follow the same pattern. There is a clear need to reconnect antibacterial drug discovery with modern, genome-based biology to enable the identification of new targets with high confidence for the rational discovery of new drugs. To exploit the increasing amount of bacterial biology information, a variety of in silico methods have been developed and applied to large-scale biologicalmodels to identify candidate antibacterial targets. Here, we review key concepts in network analysis for target discovery in tuberculosis and provide a summary of potential TB drug targets iden-tified by the individualmethods.We also discuss current developments and future prospects for the application of systems biology in the field of TB target discovery.

Original languageEnglish (US)
Article numberdkt273
Pages (from-to)2701-2709
Number of pages9
JournalJournal of Antimicrobial Chemotherapy
Issue number12
StatePublished - Dec 2013
Externally publishedYes

ASJC Scopus subject areas

  • Pharmacology
  • Microbiology (medical)
  • Infectious Diseases
  • Pharmacology (medical)


  • Antimycobacterials
  • Bioinformatics
  • In silico methods
  • Systems biology
  • Target identification


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