CLUB-MARTINI: Selecting Favourable Interactions amongst Available Candidates, a Coarse-Grained Simulation Approach to Scoring Docking Decoys.

Large-scale identification of native binding orientations is crucial for understanding the role of protein-protein interactions in their biological context. Measuring binding free energy is the method of choice to estimate binding strength and reveal the relevance of particular conformations in whic...

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Main Authors: Qingzhen Hou, Marc F Lensink, Jaap Heringa, K Anton Feenstra
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4864233?pdf=render
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author Qingzhen Hou
Marc F Lensink
Jaap Heringa
K Anton Feenstra
author_facet Qingzhen Hou
Marc F Lensink
Jaap Heringa
K Anton Feenstra
author_sort Qingzhen Hou
collection DOAJ
description Large-scale identification of native binding orientations is crucial for understanding the role of protein-protein interactions in their biological context. Measuring binding free energy is the method of choice to estimate binding strength and reveal the relevance of particular conformations in which proteins interact. In a recent study, we successfully applied coarse-grained molecular dynamics simulations to measure binding free energy for two protein complexes with similar accuracy to full-atomistic simulation, but 500-fold less time consuming. Here, we investigate the efficacy of this approach as a scoring method to identify stable binding conformations from thousands of docking decoys produced by protein docking programs. To test our method, we first applied it to calculate binding free energies of all protein conformations in a CAPRI (Critical Assessment of PRedicted Interactions) benchmark dataset, which included over 19000 protein docking solutions for 15 benchmark targets. Based on the binding free energies, we ranked all docking solutions to select the near-native binding modes under the assumption that the native-solutions have lowest binding free energies. In our top 100 ranked structures, for the 'easy' targets that have many near-native conformations, we obtain a strong enrichment of acceptable or better quality structures; for the 'hard' targets without near-native decoys, our method is still able to retain structures which have native binding contacts. Moreover, in our top 10 selections, CLUB-MARTINI shows a comparable performance when compared with other state-of-the-art docking scoring functions. As a proof of concept, CLUB-MARTINI performs remarkably well for many targets and is able to pinpoint near-native binding modes in the top selections. To the best of our knowledge, this is the first time interaction free energy calculated from MD simulations have been used to rank docking solutions at a large scale.
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spelling doaj.art-1a8f7fc999634e9f8440c1a83b4f9be52022-12-21T19:29:58ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01115e015525110.1371/journal.pone.0155251CLUB-MARTINI: Selecting Favourable Interactions amongst Available Candidates, a Coarse-Grained Simulation Approach to Scoring Docking Decoys.Qingzhen HouMarc F LensinkJaap HeringaK Anton FeenstraLarge-scale identification of native binding orientations is crucial for understanding the role of protein-protein interactions in their biological context. Measuring binding free energy is the method of choice to estimate binding strength and reveal the relevance of particular conformations in which proteins interact. In a recent study, we successfully applied coarse-grained molecular dynamics simulations to measure binding free energy for two protein complexes with similar accuracy to full-atomistic simulation, but 500-fold less time consuming. Here, we investigate the efficacy of this approach as a scoring method to identify stable binding conformations from thousands of docking decoys produced by protein docking programs. To test our method, we first applied it to calculate binding free energies of all protein conformations in a CAPRI (Critical Assessment of PRedicted Interactions) benchmark dataset, which included over 19000 protein docking solutions for 15 benchmark targets. Based on the binding free energies, we ranked all docking solutions to select the near-native binding modes under the assumption that the native-solutions have lowest binding free energies. In our top 100 ranked structures, for the 'easy' targets that have many near-native conformations, we obtain a strong enrichment of acceptable or better quality structures; for the 'hard' targets without near-native decoys, our method is still able to retain structures which have native binding contacts. Moreover, in our top 10 selections, CLUB-MARTINI shows a comparable performance when compared with other state-of-the-art docking scoring functions. As a proof of concept, CLUB-MARTINI performs remarkably well for many targets and is able to pinpoint near-native binding modes in the top selections. To the best of our knowledge, this is the first time interaction free energy calculated from MD simulations have been used to rank docking solutions at a large scale.http://europepmc.org/articles/PMC4864233?pdf=render
spellingShingle Qingzhen Hou
Marc F Lensink
Jaap Heringa
K Anton Feenstra
CLUB-MARTINI: Selecting Favourable Interactions amongst Available Candidates, a Coarse-Grained Simulation Approach to Scoring Docking Decoys.
PLoS ONE
title CLUB-MARTINI: Selecting Favourable Interactions amongst Available Candidates, a Coarse-Grained Simulation Approach to Scoring Docking Decoys.
title_full CLUB-MARTINI: Selecting Favourable Interactions amongst Available Candidates, a Coarse-Grained Simulation Approach to Scoring Docking Decoys.
title_fullStr CLUB-MARTINI: Selecting Favourable Interactions amongst Available Candidates, a Coarse-Grained Simulation Approach to Scoring Docking Decoys.
title_full_unstemmed CLUB-MARTINI: Selecting Favourable Interactions amongst Available Candidates, a Coarse-Grained Simulation Approach to Scoring Docking Decoys.
title_short CLUB-MARTINI: Selecting Favourable Interactions amongst Available Candidates, a Coarse-Grained Simulation Approach to Scoring Docking Decoys.
title_sort club martini selecting favourable interactions amongst available candidates a coarse grained simulation approach to scoring docking decoys
url http://europepmc.org/articles/PMC4864233?pdf=render
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