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J Chem Inf Model. 2011 Sep 26;51(9):2097-106. doi: 10.1021/ci2000727. Epub 2011 Aug 31.

Scoring and lessons learned with the CSAR benchmark using an improved iterative knowledge-based scoring function.

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  • 1Department of Physics and Astronomy, University of Missouri, Columbia, Missouri 65211, United States.


Based on a statistical mechanics-based iterative method, we have extracted a set of distance-dependent, all-atom pairwise potentials for protein-ligand interactions from the crystal structures of 1300 protein-ligand complexes. The iterative method circumvents the long-standing reference state problem in knowledge-based scoring functions. The resulted scoring function, referred to as ITScore 2.0, has been tested with the CSAR (Community Structure-Activity Resource, 2009 release) benchmark of 345 diverse protein-ligand complexes. ITScore 2.0 achieved a Pearson correlation of R(2) = 0.54 in binding affinity prediction. A comparative analysis has been done on the scoring performances of ITScore 2.0, the van der Waals (VDW) scoring function, the VDW with heavy atoms only, and the force field (FF) scoring function of DOCK which consists of a VDW term and an electrostatic term. The results reveal several important factors that affect the scoring performances, which could be helpful for the improvement of scoring functions.

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