Performance of radial distribution function-based descriptors in the chemoinformatic studies of HIV-1 protease

Future Med Chem. 2020 Feb;12(4):299-309. doi: 10.4155/fmc-2019-0241. Epub 2020 Jan 27.

Abstract

Aim: This letter investigates the role of radial distribution function-based descriptors for in silico design of new drugs. Methodology: The multiple linear regression models for HIV-1 protease and its complexes with a series of inhibitors were constructed. A detailed analysis of major atomic contributions to the radial distribution function descriptor weighted by the number of valence shell electrons identified residues Arg8, Asp29 and residues of the catalytic triad as crucial for the correlation with the inhibition constant, together with residues Asp30 and Ile50, whose mutations are known to cause an emergence of drug resistant variants. Conclusion: This study demonstrates an easy and fast assessment of the activity of potential drugs and the derivation of structural information of their complexes with the receptor or enzyme.

Keywords: HIV protease; QSAR; RDF; drug design; inhibitors; radial distribution function.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cheminformatics*
  • HIV Protease / chemistry*
  • HIV Protease / metabolism
  • HIV Protease Inhibitors / chemistry*
  • HIV Protease Inhibitors / pharmacology
  • Humans
  • Ligands
  • Models, Molecular
  • Molecular Conformation
  • Quantitative Structure-Activity Relationship

Substances

  • HIV Protease Inhibitors
  • Ligands
  • HIV Protease
  • p16 protease, Human immunodeficiency virus 1