Abstract
Statistically acceptable 3D-QSAR models were effortlessly obtained, by application of automatic template CoMFA, for the vast majority, arguably more than 95%, of 116 biological targets. Among these targets, 76 were structure-based, pooling multiple templates (as protein-bound conformation of ligands) and training sets into a single model, and the other 40 were ligand-based, with a low-energy conformation of an exemplar training set structure becoming the single template. Criteria proposed for statistical acceptability are a leave-one-out q(2) > 0.4, or a standard error of leave-one-out prediction <1.0, or a ratio of best-fit r(2) to count of PLS components >0.2. The structure-based 3D-QSAR models provide direct visual comparisons of SAR-derived 3D-QSAR contours with cavity surfaces.
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