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Application of MM-GB/SA and WaterMap to SRC Kinase Inhibitor Potency Prediction
Anna Kohlmann1, Xiaotian Zhu1, David Dalgarno1
1Research Technologies, ARIAD Pharmaceuticals, Inc., Cambridge, Massachusetts, United States.
Abstract:
WaterMap and MM-GB/SA scoring methods were applied to an extensive congeneric series of small-molecule SRC inhibitors with high-quality enzyme data and well characterized binding modes to compare the performance of these scoring methods in this data set and to provide insight into the relative strengths of each method. Only minor conformational changes in SRC bound with representative DFG-in class of inhibitors were demonstrated in previous studies; thus, the protein flexibility that normally presents a challenge to pose and potency predictions was minimized in this model system. While WaterMap correctly recognized major trends in the SAR of this series, MM-GB/SA performed better in ranking the relative ligand affinities. The different scoring methods were further analyzed to determine which aspects of series SAR were more amenable to MM-GB/SA than WaterMap scoring.

