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Exploring Valleys without Climbing Every Peak: More Efficient and Forgiving Metabasin Metadynamics via Robust On-the-Fly Bias Domain Restriction
[Image: see text] 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 change irreversibly in unforeseen ways in response to driving forces in t...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American
Chemical Society
2015
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4675329/ https://www.ncbi.nlm.nih.gov/pubmed/26587809 http://dx.doi.org/10.1021/acs.jctc.5b00907 |
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author | Dama, James F. Hocky, Glen M. Sun, Rui Voth, Gregory A. |
author_facet | Dama, James F. Hocky, Glen M. Sun, Rui Voth, Gregory A. |
author_sort | Dama, James F. |
collection | PubMed |
description | [Image: see text] 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 change 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. 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. 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. |
format | Online Article Text |
id | pubmed-4675329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | American
Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-46753292015-12-16 Exploring Valleys without Climbing Every Peak: More Efficient and Forgiving Metabasin Metadynamics via Robust On-the-Fly Bias Domain Restriction Dama, James F. Hocky, Glen M. Sun, Rui Voth, Gregory A. J Chem Theory Comput [Image: see text] 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 change 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. 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. 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. American Chemical Society 2015-11-03 2015-12-08 /pmc/articles/PMC4675329/ /pubmed/26587809 http://dx.doi.org/10.1021/acs.jctc.5b00907 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 | 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 |
title | Exploring Valleys without Climbing Every Peak: More
Efficient and Forgiving Metabasin Metadynamics via Robust On-the-Fly
Bias Domain Restriction |
title_full | Exploring Valleys without Climbing Every Peak: More
Efficient and Forgiving Metabasin Metadynamics via Robust On-the-Fly
Bias Domain Restriction |
title_fullStr | Exploring Valleys without Climbing Every Peak: More
Efficient and Forgiving Metabasin Metadynamics via Robust On-the-Fly
Bias Domain Restriction |
title_full_unstemmed | Exploring Valleys without Climbing Every Peak: More
Efficient and Forgiving Metabasin Metadynamics via Robust On-the-Fly
Bias Domain Restriction |
title_short | Exploring Valleys without Climbing Every Peak: More
Efficient and Forgiving Metabasin Metadynamics via Robust On-the-Fly
Bias Domain Restriction |
title_sort | exploring valleys without climbing every peak: more
efficient and forgiving metabasin metadynamics via robust on-the-fly
bias domain restriction |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4675329/ https://www.ncbi.nlm.nih.gov/pubmed/26587809 http://dx.doi.org/10.1021/acs.jctc.5b00907 |
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