Refining near-native protein–protein docking decoys by local resampling and energy minimization
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How to refine a near-native structure to make it closer to its native conformation is an unsolved problem in protein-structure and protein-protein complex-structure prediction. In this article, we first test several scoring functions for selecting locally resampled near-native protein-protein docking conformations and then propose a computationally efficient protocol for structure refinement via local resampling and energy minimization. The proposed method employs a statistical energy function based on a Distance-scaled Ideal-gas REference state (DFIRE) as an initial filter and an empirical energy function EMPIRE (EMpirical Protein-InteRaction Energy) for optimization and re-ranking. Significant improvement of final top-1 ranked structures over initial near-native structures is observed in the ZDOCK 2.3 decoy set for Benchmark 1.0 (74% whose global rmsd reduced by 0.5 A r more and only 7% increased by 0.5 A r more). Less significant improvement is observed for Benchmark 2.0 (38% versus 33%). Possible reasons are discussed.
Proteins: Structure, Function and Bioinformatics
© 2009 Wiley Periodicals, Inc. This is the accepted version of the following article: Refining near-native protein–protein docking decoys by local resampling and energy minimization, Proteins: Structure, Function, and Bioinformatics, Vol. 76(2), 2009, pp. 309-316, which has been published in final form at dx.doi.org/10.1002/prot.22343 .