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OneOPES, a Combined Enhanced Sampling Method to Rule Them All

[Image: see text] Enhanced sampling techniques have revolutionized molecular dynamics (MD) simulations, enabling the study of rare events and the calculation of free energy differences in complex systems. One of the main families of enhanced sampling techniques uses physical degrees of freedom calle...

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Autores principales: Rizzi, Valerio, Aureli, Simone, Ansari, Narjes, Gervasio, Francesco Luigi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10500989/
https://www.ncbi.nlm.nih.gov/pubmed/37603295
http://dx.doi.org/10.1021/acs.jctc.3c00254
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author Rizzi, Valerio
Aureli, Simone
Ansari, Narjes
Gervasio, Francesco Luigi
author_facet Rizzi, Valerio
Aureli, Simone
Ansari, Narjes
Gervasio, Francesco Luigi
author_sort Rizzi, Valerio
collection PubMed
description [Image: see text] Enhanced sampling techniques have revolutionized molecular dynamics (MD) simulations, enabling the study of rare events and the calculation of free energy differences in complex systems. One of the main families of enhanced sampling techniques uses physical degrees of freedom called collective variables (CVs) to accelerate a system’s dynamics and recover the original system’s statistics. However, encoding all the relevant degrees of freedom in a limited number of CVs is challenging, particularly in large biophysical systems. Another category of techniques, such as parallel tempering, simulates multiple replicas of the system in parallel, without requiring CVs. However, these methods may explore less relevant high-energy portions of the phase space and become computationally expensive for large systems. To overcome the limitations of both approaches, we propose a replica exchange method called OneOPES that combines the power of multireplica simulations and CV-based enhanced sampling. This method efficiently accelerates the phase space sampling without the need for ideal CVs, extensive parameters fine tuning nor the use of a large number of replicas, as demonstrated by its successful applications to protein–ligand binding and protein folding benchmark systems. Our approach shows promise as a new direction in the development of enhanced sampling techniques for molecular dynamics simulations, providing an efficient and robust framework for the study of complex and unexplored problems.
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spelling pubmed-105009892023-09-15 OneOPES, a Combined Enhanced Sampling Method to Rule Them All Rizzi, Valerio Aureli, Simone Ansari, Narjes Gervasio, Francesco Luigi J Chem Theory Comput [Image: see text] Enhanced sampling techniques have revolutionized molecular dynamics (MD) simulations, enabling the study of rare events and the calculation of free energy differences in complex systems. One of the main families of enhanced sampling techniques uses physical degrees of freedom called collective variables (CVs) to accelerate a system’s dynamics and recover the original system’s statistics. However, encoding all the relevant degrees of freedom in a limited number of CVs is challenging, particularly in large biophysical systems. Another category of techniques, such as parallel tempering, simulates multiple replicas of the system in parallel, without requiring CVs. However, these methods may explore less relevant high-energy portions of the phase space and become computationally expensive for large systems. To overcome the limitations of both approaches, we propose a replica exchange method called OneOPES that combines the power of multireplica simulations and CV-based enhanced sampling. This method efficiently accelerates the phase space sampling without the need for ideal CVs, extensive parameters fine tuning nor the use of a large number of replicas, as demonstrated by its successful applications to protein–ligand binding and protein folding benchmark systems. Our approach shows promise as a new direction in the development of enhanced sampling techniques for molecular dynamics simulations, providing an efficient and robust framework for the study of complex and unexplored problems. American Chemical Society 2023-08-21 /pmc/articles/PMC10500989/ /pubmed/37603295 http://dx.doi.org/10.1021/acs.jctc.3c00254 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Rizzi, Valerio
Aureli, Simone
Ansari, Narjes
Gervasio, Francesco Luigi
OneOPES, a Combined Enhanced Sampling Method to Rule Them All
title OneOPES, a Combined Enhanced Sampling Method to Rule Them All
title_full OneOPES, a Combined Enhanced Sampling Method to Rule Them All
title_fullStr OneOPES, a Combined Enhanced Sampling Method to Rule Them All
title_full_unstemmed OneOPES, a Combined Enhanced Sampling Method to Rule Them All
title_short OneOPES, a Combined Enhanced Sampling Method to Rule Them All
title_sort oneopes, a combined enhanced sampling method to rule them all
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10500989/
https://www.ncbi.nlm.nih.gov/pubmed/37603295
http://dx.doi.org/10.1021/acs.jctc.3c00254
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