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Title: Exploring Valleys without Climbing Every Peak: More Efficient and Forgiving Metabasin Metadynamics via Robust On-the-Fly Bias Domain Restriction

Abstract

Metadynamics is an enhanced sampling method designed to flatten free energy surfaces uniformly. However, the highest-energy regions are often irrelevant to study and dangerous to explore because systems often respond irreversibly in unforeseen ways in response to driving forces in these regions, spoiling the sampling. Introducing an on-the-fly domain restriction allows metadynamics to flatten only up to a specified energy level and no further, improving efficiency and safety while decreasing the pressure on practitioners to design collective variables that are robust to otherwise irrelevant high energy driving. Here this paper describes a new method that achieves this using sequential on-the-fly estimation of energy wells and redefinition of the metadynamics hill shape, termed metabasin metadynamics. The energy level may be defined a priori or relative to unknown barrier energies estimated on the fly. Altering only the hill ensures that the method is compatible with many other advances in metadynamics methodology. The hill shape has a natural interpretation in terms of multiscale dynamics and the computational overhead in simulation is minimal when studying systems of any reasonable size, for instance proteins or other macromolecules. Ultimately, three example applications show that the formula is accurate and robust to complex dynamics, making metadynamics significantlymore » more forgiving with respect to CV quality and thus more feasible to apply to the most challenging biomolecular systems.« less

Authors:
 [1];  [2];  [2];  [1]
  1. Department of Chemistry, James Franck Institute, Institute for Biophysical Dynamics, and Computation Institute, The University of Chicago, Chicago, Illinois 60637, United States, Center for Nonlinear Studies, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
  2. Department of Chemistry, James Franck Institute, Institute for Biophysical Dynamics, and Computation Institute, The University of Chicago, Chicago, Illinois 60637, United States
Publication Date:
Research Org.:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
National Science Foundation (NSF); National Institutes of Health (NIH); USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1226572
Alternate Identifier(s):
OSTI ID: 1282054; OSTI ID: 1418757
Report Number(s):
LA-UR-15-27322
Journal ID: ISSN 1549-9618
Grant/Contract Number:  
AC52-06NA25396; CHE-1136709; CHE-1465248; R01-GM053148; ACI-1053575
Resource Type:
Journal Article: Published Article
Journal Name:
Journal of Chemical Theory and Computation
Additional Journal Information:
Journal Name: Journal of Chemical Theory and Computation Journal Volume: 11 Journal Issue: 12; Journal ID: ISSN 1549-9618
Publisher:
American Chemical Society
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; 59 BASIC BIOLOGICAL SCIENCES; Biological Science

Citation Formats

Dama, James F., Hocky, Glen M., Sun, Rui, and Voth, Gregory A. Exploring Valleys without Climbing Every Peak: More Efficient and Forgiving Metabasin Metadynamics via Robust On-the-Fly Bias Domain Restriction. United States: N. p., 2015. Web. doi:10.1021/acs.jctc.5b00907.
Dama, James F., Hocky, Glen M., Sun, Rui, & Voth, Gregory A. Exploring Valleys without Climbing Every Peak: More Efficient and Forgiving Metabasin Metadynamics via Robust On-the-Fly Bias Domain Restriction. United States. https://doi.org/10.1021/acs.jctc.5b00907
Dama, James F., Hocky, Glen M., Sun, Rui, and Voth, Gregory A. 2015. "Exploring Valleys without Climbing Every Peak: More Efficient and Forgiving Metabasin Metadynamics via Robust On-the-Fly Bias Domain Restriction". United States. https://doi.org/10.1021/acs.jctc.5b00907.
@article{osti_1226572,
title = {Exploring Valleys without Climbing Every Peak: More Efficient and Forgiving Metabasin Metadynamics via Robust On-the-Fly Bias Domain Restriction},
author = {Dama, James F. and Hocky, Glen M. and Sun, Rui and Voth, Gregory A.},
abstractNote = {Metadynamics is an enhanced sampling method designed to flatten free energy surfaces uniformly. However, the highest-energy regions are often irrelevant to study and dangerous to explore because systems often respond irreversibly in unforeseen ways in response to driving forces in these regions, spoiling the sampling. Introducing an on-the-fly domain restriction allows metadynamics to flatten only up to a specified energy level and no further, improving efficiency and safety while decreasing the pressure on practitioners to design collective variables that are robust to otherwise irrelevant high energy driving. Here this paper describes a new method that achieves this using sequential on-the-fly estimation of energy wells and redefinition of the metadynamics hill shape, termed metabasin metadynamics. The energy level may be defined a priori or relative to unknown barrier energies estimated on the fly. Altering only the hill ensures that the method is compatible with many other advances in metadynamics methodology. The hill shape has a natural interpretation in terms of multiscale dynamics and the computational overhead in simulation is minimal when studying systems of any reasonable size, for instance proteins or other macromolecules. Ultimately, three example applications show that the formula is accurate and robust to complex dynamics, making metadynamics significantly more forgiving with respect to CV quality and thus more feasible to apply to the most challenging biomolecular systems.},
doi = {10.1021/acs.jctc.5b00907},
url = {https://www.osti.gov/biblio/1226572}, journal = {Journal of Chemical Theory and Computation},
issn = {1549-9618},
number = 12,
volume = 11,
place = {United States},
year = {Fri Nov 20 00:00:00 EST 2015},
month = {Fri Nov 20 00:00:00 EST 2015}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at https://doi.org/10.1021/acs.jctc.5b00907

Citation Metrics:
Cited by: 25 works
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