EUDOC: A computer program for identification of drug interaction sites in macromolecules and drug leads from chemical databases

Yuan Ping Pang, Emanuele Perola, Run Xu, Franklyn G. Prendergast

Research output: Contribution to journalArticle

89 Scopus citations

Abstract

The completion of the Human Genome Project, the growing effort on proteomics, and the Structural Genomics Initiative have recently intensified the attention being paid to reliable computer docking programs able to identify molecules that can affect the function of a macromolecule through molecular complexation. We report herein an automated computer docking program, EUDOC, for prediction of ligand-receptor complexes from 3D receptor structures, including metalloproteins, and for identification of a subset enriched in drug leads from chemical databases. This program was evaluated from the standpoints of force field and sampling issues using 154 experimentally determined ligand-receptor complexes and four "real-life" applications of the EUDOC program. The results provide evidence for the reliability and accuracy of the EUDOC program. In addition, key principles underlying molecular recognition, and the effects of structural water molecules in the active site and different atomic charge models on docking results are discussed.

Original languageEnglish (US)
Pages (from-to)1750-1771
Number of pages22
JournalJournal of Computational Chemistry
Volume22
Issue number15
DOIs
StatePublished - Nov 30 2001

Keywords

  • In silico screening
  • Molecular complexation
  • Molecular docking
  • Molecular recognition
  • Virtual screening

ASJC Scopus subject areas

  • Chemistry(all)
  • Computational Mathematics

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