Refining near-native protein-protein docking decoys by local resampling and energy minimization
Data(s) |
01/08/2009
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Resumo |
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 angstrom or more and only 7% increased by 0.5 angstrom or more). Less significant improvement is observed for Benchmark 2.0 (38% versus 33%). Possible reasons are discussed. 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 angstrom or more and only 7% increased by 0.5 angstrom or more). Less significant improvement is observed for Benchmark 2.0 (38% versus 33%). Possible reasons are discussed. |
Identificador | |
Idioma(s) |
英语 |
Fonte |
Liang, Shide; Wang, Guangce; Zhou, Yaoqi.Refining near-native protein-protein docking decoys by local resampling and energy minimization,PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS,2009,76(2):309-316 |
Palavras-Chave | #Biochemistry & Molecular Biology; Biophysics #docking structure refinement #local resampling #energy score |
Tipo |
期刊论文 |