We have developed an empirical scoring function for predicting protein-ligand binding affinities that incorporates explicit waters and their free energies of displacement (obtained from a WaterMap molecular dynamics calculation) as well as many other terms which assess strain energy, interactions of various important chemical functional groups, etc.   The performance of the scoring function in rank ordering known active compounds, and in enrichment using data sets derived from the Protein Data Bank (PDB) will be presented.  In combination with ensemble docking, the scoring function shows promise in greatly reducing the number of false positives while retaining the ability to identify and approximately rank order active compounds. Particular focus is on the low micromolar activity range where most novel hits in drug discovery projects are located.

Development of an empirical scoring function for calculating protein-ligand binding affinities

243rd National Meeting (2012)

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