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Proteins. 2014 Feb;82(2):250-67. doi: 10.1002/prot.24370. Epub 2013 Oct 17.

DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction.

Author information

1
Bioinformatics and Computational Biology program, Iowa State University, Ames, Iowa.

Abstract

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. DockRank uses interface residues predicted by partner-specific sequence homology-based protein-protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/.

KEYWORDS:

docking scoring functions; homo-interologs; partner-specific protein-protein interface residue prediction; protein complex structure prediction; protein-protein docking; sequence homologs

PMID:
23873600
PMCID:
PMC4417613
DOI:
10.1002/prot.24370
[Indexed for MEDLINE]
Free PMC Article
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