Structure based activity prediction of HIV-1 reverse transcriptase inhibitors

J Med Chem. 2005 Mar 24;48(6):2176-83. doi: 10.1021/jm049534r.

Abstract

We have developed a fast and robust computational method for prediction of antiviral activity in automated de novo design of HIV-1 reverse transcriptase inhibitors. This is a structure-based approach that uses a linear relation between activity and interaction energy with discrete orientation sampling and with localized interaction energy terms. The localization allows for the analysis of mutations of the protein target and for the separation of inhibition and a specific binding to the enzyme. We apply the method to the prediction of pIC(50) of HIV-1 reverse transcriptase inhibitors. The model predicts the activity of an arbitrary compound with a q(2) of 0.681 and an average absolute error of 0.66 log value, and it is fast enough to be used in high-throughput computational applications.

MeSH terms

  • Anti-HIV Agents / chemistry*
  • Binding Sites
  • Databases, Protein
  • HIV Reverse Transcriptase / chemistry*
  • Models, Molecular
  • Molecular Conformation
  • Molecular Structure
  • Quantitative Structure-Activity Relationship
  • Reverse Transcriptase Inhibitors / chemistry*

Substances

  • Anti-HIV Agents
  • Reverse Transcriptase Inhibitors
  • HIV Reverse Transcriptase