Collective variable driven molecular dynamics to improve protein–protein docking scoring

•Protein–protein interactions are fundamental in most cellular processes.•Hydrogen bond networks play a key role in molecular recognition.•MD is the tool by excellence to explore the protein potential energy landscape.•Collective variable driven MD have been able to accelerate rare events. In biophy...

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Veröffentlicht in:Computational biology and chemistry 2014-04, Vol.49, p.1-6
Hauptverfasser: Masone, Diego, Grosdidier, Solène
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container_title Computational biology and chemistry
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creator Masone, Diego
Grosdidier, Solène
description •Protein–protein interactions are fundamental in most cellular processes.•Hydrogen bond networks play a key role in molecular recognition.•MD is the tool by excellence to explore the protein potential energy landscape.•Collective variable driven MD have been able to accelerate rare events. In biophysics, the structural prediction of protein–protein complexes starting from the unbound form of the two interacting monomers is a major difficulty. Although current computational docking protocols are able to generate near-native solutions in a reasonable time, the problem of identifying near-native conformations from a pool of solutions remains very challenging. In this study, we use molecular dynamics simulations driven by a collective reaction coordinate to optimize full hydrogen bond networks in a set of protein–protein docking solutions. The collective coordinate biases the system to maximize the formation of hydrogen bonds at the protein–protein interface as well as all over the structure. The reaction coordinate is therefore a measure for docking poses affinity and hence is used as scoring function to identify near-native conformations.
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subjects Biology
Collective variable
Computation
Docking
Dynamical systems
Hydrogen Bonding
Hydrogen bonds
Mathematical models
Molecular dynamics
Molecular Dynamics Simulation
Proteins - chemistry
Proteins - metabolism
Protein–protein
Scoring
title Collective variable driven molecular dynamics to improve protein–protein docking scoring
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