Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark

Abstract

We describe a new method, Compass, for predicting the biological activities of molecules based on the activities and three-dimensional structures of other molecules. The method improves on previous techniques by representing only the surface of molecules, by incorporating a nonlinear statistical method, and by automatically choosing conformations and alignments of molecules. We use a benchmark problem of steroid binding affinity prediction to compare the performance of the method with that of two previous systems: CoMFA and a molecular similarity method. Compass predicts steroid affinities substantially more accurately than the others, which represent the state of the art. We present experiments showing that the improved performance depends on each of the technical innovations.