Identification of novel bacterial histidine biosynthesis inhibitors using docking, ensemble rescoring, and whole-cell assays

S. T. Henriksen, J. Liu, G. Estiu, Z. N. Oltvai, O. Wiest

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


The rapid spread on multidrug-resistant strains of Staphylococcus aureus requires not just novel treatment options, but the development of faster methods for the identification of new hits for drug development. The exponentially increasing speed of computational methods makes a more extensive use in the early stages of drug discovery attractive if sufficient accuracy can be achieved. Computational target identification using systems-level methods suggested the histidine biosynthesis pathway as an attractive target against S. aureus. Potential inhibitors for the pathway were identified through docking, followed by ensemble rescoring, that is sufficiently accurate to justify immediate testing of the identified compounds by whole-cell assays, avoiding the need for time-consuming and often difficult intermediary enzyme assays. This novel strategy is demonstrated for three key enzymes of the S. aureus histidine biosynthesis pathway, which is predicted to be essential for bacterial biomass productions. Virtual screening of a library of ∼10 6 compounds identified 49 potential inhibitors of three enzymes of this pathway. Eighteen representative compounds were directly tested on three S. aureus- and two Escherichia coli strains in standard disk inhibition assays. Thirteen compounds are inhibitors of some or all of the S. aureus strains, while 14 compounds weakly inhibit growth in one or both E. coli strains. The high hit rate obtained from a fast virtual screen demonstrates the applicability of this novel strategy to the histidine biosynthesis pathway.

Original languageEnglish (US)
Pages (from-to)5148-5156
Number of pages9
JournalBioorganic and Medicinal Chemistry
Issue number14
StatePublished - Jul 15 2010
Externally publishedYes

Bibliographical note

Funding Information:
We gratefully acknowledge support of this research by The National Institutes of Health ( NIAID U01-0700499 to Z.N.O. and O. W.) and by travel grants from The American-Scandinavian Foundation , The Danish Chemical Society , The Otto Mønsted Foundation , The Knud Højgaard Foundation , The Augustinus Foundation , and The Oticon Foundation to S.T.H. The computations were performed on Kraken (a Cray XT5) at the National Institute for Computational Sciences ( ) and in Queen Bee at the Louisiana Optical Network Initiative. Generous allocation of computing resources by the Center for Research Computing at the University of Notre Dame is also acknowledged.


  • Antibiotics
  • Histidine biosynthesis
  • Systems biology
  • Virtual screening


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