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Evaluation of the coarse-grained OPEP force field for protein-protein docking

Overview of attention for article published in BMC Biophysics, April 2016
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Title
Evaluation of the coarse-grained OPEP force field for protein-protein docking
Published in
BMC Biophysics, April 2016
DOI 10.1186/s13628-016-0029-y
Pubmed ID
Authors

Philipp Kynast, Philippe Derreumaux, Birgit Strodel

Abstract

Knowing the binding site of protein-protein complexes helps understand their function and shows possible regulation sites. The ultimate goal of protein-protein docking is the prediction of the three-dimensional structure of a protein-protein complex. Docking itself only produces plausible candidate structures, which must be ranked using scoring functions to identify the structures that are most likely to occur in nature. In this work, we rescore rigid body protein-protein predictions using the optimized potential for efficient structure prediction (OPEP), which is a coarse-grained force field. Using a force field based on continuous functions rather than a grid-based scoring function allows the introduction of protein flexibility during the docking procedure. First, we produce protein-protein predictions using ZDOCK, and after energy minimization via OPEP we rank them using an OPEP-based soft rescoring function. We also train the rescoring function for different complex classes and demonstrate its improved performance for an independent dataset. The trained rescoring function produces a better ranking than ZDOCK for more than 50 % of targets, rising to over 70 % when considering only enzyme/inhibitor complexes. This study demonstrates for the first time that energy functions derived from the coarse-grained OPEP force field can be employed to rescore predictions for protein-protein complexes.

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Mendeley readers

Mendeley readers

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Geographical breakdown

Country Count As %
Canada 1 6%
Unknown 17 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 33%
Professor > Associate Professor 3 17%
Student > Ph. D. Student 3 17%
Student > Bachelor 2 11%
Professor 1 6%
Other 2 11%
Unknown 1 6%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 28%
Chemistry 3 17%
Agricultural and Biological Sciences 2 11%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Chemical Engineering 1 6%
Other 5 28%
Unknown 1 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 April 2016.
All research outputs
#21,264,673
of 23,881,329 outputs
Outputs from BMC Biophysics
#52
of 57 outputs
Outputs of similar age
#259,869
of 301,840 outputs
Outputs of similar age from BMC Biophysics
#1
of 1 outputs
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