Compass: predicting biological activities from molecular surface properties. Performance comparisons on a steroid benchmark.
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.
Jain
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AN
Arris Pharmaceutical Corporation, South San Francisco, California 94080.
Koile
K
K
Chapman
D
D
D000465:Algorithms; D008958:Models, Molecular; D015233:Models, Statistical; D008968:Molecular Conformation; D012738:Sex Hormone-Binding Globulin / Q000378:metabolism; D013256:Steroids / Q000378:metabolism*; D013329:Structure-Activity Relationship; D013499:Surface Properties; D014156:Transcortin / Q000378:metabolism
D012738:Sex Hormone-Binding Globulin; D013256:Steroids; D014156:Transcortin