In fragment-based drug discovery, intelligent sampling and assembly of fragments facilitates an effective path to identifying hits for therapeutic targets. To enhance the capability of our growth algorithm, CONTOURTM, we developed a context sensitive in silico fragment sampling algorithm called dynamic fragment selection (DFS) for designing molecules de novo. A method designed to complement the characteristics of the binding site of protein target was developed to select molecular fragments that best fit the binding pockets during the growth process.  This approach significantly improves the growth efficiency over an exhaustive search by reducing the vast chemical and configurational space of the 10K fragment library. Only a subset of the fragment library is chosen that best matches the shape and features of a given pocket in the binding site. The results will demonstrate that DFS selects a greater number of fragments that are complementary than random sampling, thus enriching the top scoring molecules more efficiently. In addition the DFS calculations are 10 fold faster compared to the stochastic sampling method. Applications exemplifying the performance of DFS will be presented.

Growing molecules in protein binding pockets with a context sensitive dynamic fragment selection method: Selecting fragments based on binding site complementarity with CONTOUR™

243rd National Meeting (2012)

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