We present a novel scoring function for docking of small molecules to protein binding sites. The scoring function is based on a combination of two main approaches used in the field, the empirical and knowledge-based approaches. To calibrate the scoring function we used an iterative procedure in which a ligand's position and its score were determined self-consistently at each iteration. The scoring function demonstrated superiority in prediction of ligand positions in docking tests against the commonly used Dock, FlexX and Gold docking programs. It also demonstrated good accuracy of binding affinity prediction for the docked ligands.
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To estimate how sophisticated should an empirical scoring function be to ensure successful docking, scoring and virtual screening a new scoring function NScore (naive score) has been developed and tested. NScore is an extremely simple function and has the minimum possible number of parameters; nevertheless, it allows all the main effects determining the ligand-protein interaction to be taken into account. The fundamental difference of NScore from the currently used empirical functions is that all its parameters are selected on the basis of general physical considerations, without any adjustment or training with the use of experimental data on ligand-protein interaction. The results of docking and scoring with the use of NScore in an independent test sets of proteins and ligands have proved to be as good as those yielded by the ICM, GOLD, and Glide software packages, which use sophisticated empirical scoring functions. With respect to some parameters, the results of docking with the use of NScore are even better than those obtained using other functions. Since no training set is used in the development of NScore, this scoring function is indeed versatile in that it does not depend on the specific goal or target. We have performed virtual screening for ten targets and obtained results almost as good as those yielded by the Glide and better than GOLD and DOCK software.
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