Development and evaluation of a new statistical model for structure-based high-throughput virtual screening

Int J Bioinform Res Appl. 2009;5(3):269-79. doi: 10.1504/IJBRA.2009.026419.

Abstract

We have developed a High-Performance Computing (HPC)-based molecular docking scheme, termed HiPCDock, for drug discovery and development. To improve the statistical significance of our screening results, a bioinformatics approach, motivated by a sequence alignment package BLAST, was implemented. The statistical model was validated with ten known Thymidine Kinase (TK) binders and the real inhibitors showed significant statistics, in terms of low probabilities and expectation values. Our HiPCDock has been implemented to be used by both computational experts and experimental scientists. Thus it is an automated, easy-to-use, and efficient package for molecular docking-based high-throughput virtual screening in drug discovery.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods
  • Drug Design
  • Drug Discovery / methods*
  • Models, Statistical*
  • Protein Kinase Inhibitors / chemistry
  • Structure-Activity Relationship
  • Thymidine Kinase / antagonists & inhibitors

Substances

  • Protein Kinase Inhibitors
  • Thymidine Kinase