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Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation

[Image: see text] A Gaussian accelerated molecular dynamics (GaMD) approach for simultaneous enhanced sampling and free energy calculation of biomolecules is presented. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved usin...

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Autores principales: Miao, Yinglong, Feher, Victoria A., McCammon, J. Andrew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2015
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4535365/
https://www.ncbi.nlm.nih.gov/pubmed/26300708
http://dx.doi.org/10.1021/acs.jctc.5b00436
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author Miao, Yinglong
Feher, Victoria A.
McCammon, J. Andrew
author_facet Miao, Yinglong
Feher, Victoria A.
McCammon, J. Andrew
author_sort Miao, Yinglong
collection PubMed
description [Image: see text] A Gaussian accelerated molecular dynamics (GaMD) approach for simultaneous enhanced sampling and free energy calculation of biomolecules is presented. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved using cumulant expansion to the second order. Here, GaMD is demonstrated on three biomolecular model systems: alanine dipeptide, chignolin folding, and ligand binding to the T4-lysozyme. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of these biomolecules. Furthermore, the free energy profiles obtained from reweighting of the GaMD simulations allow us to identify distinct low-energy states of the biomolecules and characterize the protein-folding and ligand-binding pathways quantitatively.
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spelling pubmed-45353652016-07-14 Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation Miao, Yinglong Feher, Victoria A. McCammon, J. Andrew J Chem Theory Comput [Image: see text] A Gaussian accelerated molecular dynamics (GaMD) approach for simultaneous enhanced sampling and free energy calculation of biomolecules is presented. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved using cumulant expansion to the second order. Here, GaMD is demonstrated on three biomolecular model systems: alanine dipeptide, chignolin folding, and ligand binding to the T4-lysozyme. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of these biomolecules. Furthermore, the free energy profiles obtained from reweighting of the GaMD simulations allow us to identify distinct low-energy states of the biomolecules and characterize the protein-folding and ligand-binding pathways quantitatively. American Chemical Society 2015-07-14 2015-08-11 /pmc/articles/PMC4535365/ /pubmed/26300708 http://dx.doi.org/10.1021/acs.jctc.5b00436 Text en Copyright © 2015 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes.
spellingShingle Miao, Yinglong
Feher, Victoria A.
McCammon, J. Andrew
Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation
title Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation
title_full Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation
title_fullStr Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation
title_full_unstemmed Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation
title_short Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation
title_sort gaussian accelerated molecular dynamics: unconstrained enhanced sampling and free energy calculation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4535365/
https://www.ncbi.nlm.nih.gov/pubmed/26300708
http://dx.doi.org/10.1021/acs.jctc.5b00436
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