Quantitative structure-activity relationship modeling of dopamine D₁ antagonists using comparative molecular field analysis, genetic algorithms- partial least-squares, and K nearest neighbor methods

Several quantitative structure-activity relationship (QSAR) methods were applied to 29 chemically diverse D₁ dopamine antagonists. In addition to conventional 3D comparative molecular field analysis (CoMFA), cross-validated R² guided region selection (q²-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 R² (q²) values of 0.57 for CoMFA, 0.54 for q²-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 D₁ ligands.