Blueprint for antimicrobial hit discovery targeting metabolic networks

Y. Shen, J. Liu, G. Estiua, B. Isin, Y. Y. Ahn, D. S. Lee, A. L. Barabási, V. Kapatral, O. Wiest, Z. N. Oltvai

Research output: Contribution to journalArticlepeer-review

80 Scopus citations

Abstract

Advances in genome analysis, network biology, and computational chemistry have the potential to revolutionize drug discovery by combining system-level identification of drug targets with the atomistic modeling of small molecules capable of modulating their activity. To demonstrate the effectiveness of such a discovery pipeline, we deduced common antibiotic targets in Escherichia coli and Staphylococcus aureus by identifying shared tissue-specific or uniformly essential metabolic reactions in their metabolic networks. We then predicted through virtual screening dozens of potential inhibitors for several enzymes of these reactions and showed experimentally that a subset of these inhibited both enzyme activities in vitro and bacterial cell viability. This blueprint is applicable for any sequenced organism with high-quality metabolic reconstruction and suggests a general strategy for strain-specific antiinfective therapy.

Original languageEnglish (US)
Pages (from-to)1082-1087
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume107
Issue number3
DOIs
StatePublished - Jan 19 2010

Keywords

  • Antibiotics
  • Flux balance analysis
  • Virtual screening

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