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

Several quantitative structure-activity relationship (QSAR) methods were ap plied to 29 chemically diverse D-1 dopamine antagonists. In addition to con ventional 3D comparative molecular field analysis (CoMFA), cross-validated R-2 guided region selection (q(2)-GRS) CoMFA (see ref 1) was employed, as w ere two novel variable selection QSAR methods recently developed in one of our laboratories. These latter methods included genetic algorithm-partial l east squares (GA-PLS) and K nearest neighbor (KNN) procedures (see refs 2-4 ), which utilize 2D topological descriptors of chemical structures. Each QS AR 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 n ovel D1 ligands.