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Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation
Author(s) -
Yinglong Miao,
Victoria A. Feher,
J. Andrew McCammon
Publication year - 2015
Publication title -
journal of chemical theory and computation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.001
H-Index - 185
eISSN - 1549-9626
pISSN - 1549-9618
DOI - 10.1021/acs.jctc.5b00436
Subject(s) - biomolecule , molecular dynamics , gaussian , folding (dsp implementation) , biological system , sampling (signal processing) , computer science , energy landscape , statistical physics , umbrella sampling , energy (signal processing) , chemistry , computational chemistry , physics , nanotechnology , materials science , biology , biochemistry , engineering , filter (signal processing) , quantum mechanics , electrical engineering , computer vision
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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