Motivation: The limited success rate of protein-protein docking procedures is generally attributed to structure differences between the bound and unbound states of the molecules. Herein we analyze a large dataset of protein-protein docking results and identify additional parameters that affect the performance of docking procedures. Results: We find that the distinction between nearly correct models (NCMs) and decoys depends on the size of the interface to be predicted thus setting a limit to the prediction ability of docking procedures, particularly those in which the geometric complementarity descriptor is dominant. The geometric complementarity score in grid-based docking carries a large statistical error which further reduces the distinction between NCMs and decoys. We propose a method for correcting the statistical error and show that the distinction is improved when the docking models are ranked by statistically equivalent scores. Availability: MolFit can be downloaded from our website http://www.weizmann.ac.il/Chemical_Research_Support/molfit Contact: miriam.eisenstein@weizmann.ac.il Supplementary information: Supplementary data are available at Bioinformatics online.
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