Quantitative structure-activity relationship modeling of dopamine D(1) antagonists using comparative molecular field analysis, genetic algorithms-partial least-squares, and K nearest neighbor methods

J Med Chem. 1999 Aug 26;42(17):3217-26. doi: 10.1021/jm980415j.

Abstract

Several quantitative structure-activity relationship (QSAR) methods were applied to 29 chemically diverse D(1) dopamine antagonists. In addition to conventional 3D comparative molecular field analysis (CoMFA), cross-validated R(2) guided region selection (q(2)-GRS) CoMFA (see ref 1) was employed, as were two novel variable selection QSAR methods recently developed in one of our laboratories. These latter methods included genetic algorithm-partial least squares (GA-PLS) and K nearest neighbor (KNN) procedures (see refs 2-4), which utilize 2D topological descriptors of chemical structures. Each QSAR approach resulted in a highly predictive model, with cross-validated R(2) (q(2)) values of 0.57 for CoMFA, 0.54 for q(2)-GRS, 0.73 for GA-PLS, and 0.79 for KNN. The success of all of the QSAR methods indicates the presence of an intrinsic structure-activity relationship in this group of compounds and affords more robust design and prediction of biological activities of novel D(1) ligands.

Publication types

  • Comparative Study

MeSH terms

  • Algorithms
  • Animals
  • Corpus Striatum / drug effects
  • Corpus Striatum / metabolism
  • Dopamine Antagonists / chemistry*
  • Dopamine Antagonists / pharmacology
  • In Vitro Techniques
  • Least-Squares Analysis
  • Ligands
  • Models, Molecular
  • Rats
  • Receptors, Dopamine D1 / chemistry*
  • Receptors, Dopamine D1 / drug effects
  • Structure-Activity Relationship

Substances

  • Dopamine Antagonists
  • Ligands
  • Receptors, Dopamine D1