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J Comput Chem. 2016 Jul;37(20):1861-5. doi: 10.1002/jcc.24412. Epub 2016 May 27.

Ranking protein-protein docking results using steered molecular dynamics and potential of mean force calculations.

Author information

1
Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, 575 Stadium Mall Drivem, West Lafayette, Indiana, 47907.
2
Department of Computer Science, Purdue University, 305 North University Street, West Lafayette, Indiana, 47907.
3
Department of Biological Sciences, Purdue University, 249 South Martin Jischke Drive, West Lafayette, Indiana, 47907.

Abstract

Crystallization of protein-protein complexes can often be problematic and therefore computational structural models are often relied on. Such models are often generated using protein-protein docking algorithms, where one of the main challenges is selecting which of several thousand potential predictions represents the most near-native complex. We have developed a novel technique that involves the use of steered molecular dynamics (sMD) and umbrella sampling to identify near-native complexes among protein-protein docking predictions. Using this technique, we have found a strong correlation between our predictions and the interface RMSD (iRMSD) in ten diverse test systems. On two of the systems, we investigated if the prediction results could be further improved using potential of mean force calculations. We demonstrated that a near-native (<2.0 Å iRMSD) structure could be identified in the top-1 ranked position for both systems.

KEYWORDS:

ZDOCK; potential of mean force; protein-protein interaction; steered molecular dynamics; umbrella sampling

PMID:
27232548
PMCID:
PMC5015890
DOI:
10.1002/jcc.24412
[Indexed for MEDLINE]
Free PMC Article

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