In silico prediction of SARS protease inhibitors by virtual high throughput screening

Chem Biol Drug Des. 2007 Apr;69(4):269-79. doi: 10.1111/j.1747-0285.2007.00475.x.

Abstract

A structure-based in silico virtual drug discovery procedure was assessed with severe acute respiratory syndrome coronavirus main protease serving as a case study. First, potential compounds were extracted from protein-ligand complexes selected from Protein Data Bank database based on structural similarity to the target protein. Later, the set of compounds was ranked by docking scores using a Electronic High-Throughput Screening flexible docking procedure to select the most promising molecules. The set of best performing compounds was then used for similarity search over the 1 million entries in the Ligand.Info Meta-Database. Selected molecules having close structural relationship to a 2-methyl-2,4-pentanediol may provide candidate lead compounds toward the development of novel allosteric severe acute respiratory syndrome protease inhibitors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods*
  • Computer Simulation*
  • Databases, Protein
  • Drug Design
  • Drug Evaluation, Preclinical / methods*
  • Endopeptidases / metabolism*
  • Ligands
  • Models, Molecular
  • Molecular Conformation
  • Protease Inhibitors / chemistry
  • Protease Inhibitors / pharmacology*
  • Severe acute respiratory syndrome-related coronavirus / drug effects*
  • Severe acute respiratory syndrome-related coronavirus / enzymology*
  • Structure-Activity Relationship

Substances

  • Ligands
  • Protease Inhibitors
  • Endopeptidases