Lessons learned about steered molecular dynamics simulations and free energy calculations

The calculation of free energy profiles is central in understanding differential enzymatic activity, for instance, involving chemical reactions that require QM-MM tools, ligand migration, and conformational rearrangements that can be modeled using classical potentials. The use of steered molecular d...

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Detalles Bibliográficos
Autores principales:	Boubeta, F.M., Contestín García, R.M., Lorenzo, E.N., Boechi, L., Estrin, D., Sued, M., Arrar, M.
Formato:	JOUR
Materias:	free energy Jarzynski maximum likelihood steered molecular dynamics
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_17470277_v_n_p_Boubeta
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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spelling	todo:paper_17470277_v_n_p_Boubeta2023-10-03T16:32:04Z Lessons learned about steered molecular dynamics simulations and free energy calculations Boubeta, F.M. Contestín García, R.M. Lorenzo, E.N. Boechi, L. Estrin, D. Sued, M. Arrar, M. free energy Jarzynski maximum likelihood steered molecular dynamics The calculation of free energy profiles is central in understanding differential enzymatic activity, for instance, involving chemical reactions that require QM-MM tools, ligand migration, and conformational rearrangements that can be modeled using classical potentials. The use of steered molecular dynamics (sMD) together with the Jarzynski equality is a popular approach in calculating free energy profiles. Here, we first briefly review the application of the Jarzynski equality to sMD simulations, then revisit the so-called stiff-spring approximation and the consequent expectation of Gaussian work distributions and, finally, reiterate the practical utility of the second-order cumulant expansion, as it coincides with the parametric maximum-likelihood estimator in this scenario. We illustrate this procedure using simulations of CO, both in aqueous solution and in a carbon nanotube as a model system for biologically relevant nanoheterogeneous environments. We conclude the use of the second-order cumulant expansion permits the use of faster pulling velocities in sMD simulations, without introducing bias due to large dispersion in the non-equilibrium work distribution. © 2019 John Wiley & Sons A/S JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_17470277_v_n_p_Boubeta
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	free energy Jarzynski maximum likelihood steered molecular dynamics
spellingShingle	free energy Jarzynski maximum likelihood steered molecular dynamics Boubeta, F.M. Contestín García, R.M. Lorenzo, E.N. Boechi, L. Estrin, D. Sued, M. Arrar, M. Lessons learned about steered molecular dynamics simulations and free energy calculations
topic_facet	free energy Jarzynski maximum likelihood steered molecular dynamics
description	The calculation of free energy profiles is central in understanding differential enzymatic activity, for instance, involving chemical reactions that require QM-MM tools, ligand migration, and conformational rearrangements that can be modeled using classical potentials. The use of steered molecular dynamics (sMD) together with the Jarzynski equality is a popular approach in calculating free energy profiles. Here, we first briefly review the application of the Jarzynski equality to sMD simulations, then revisit the so-called stiff-spring approximation and the consequent expectation of Gaussian work distributions and, finally, reiterate the practical utility of the second-order cumulant expansion, as it coincides with the parametric maximum-likelihood estimator in this scenario. We illustrate this procedure using simulations of CO, both in aqueous solution and in a carbon nanotube as a model system for biologically relevant nanoheterogeneous environments. We conclude the use of the second-order cumulant expansion permits the use of faster pulling velocities in sMD simulations, without introducing bias due to large dispersion in the non-equilibrium work distribution. © 2019 John Wiley & Sons A/S
format	JOUR
author	Boubeta, F.M. Contestín García, R.M. Lorenzo, E.N. Boechi, L. Estrin, D. Sued, M. Arrar, M.
author_facet	Boubeta, F.M. Contestín García, R.M. Lorenzo, E.N. Boechi, L. Estrin, D. Sued, M. Arrar, M.
author_sort	Boubeta, F.M.
title	Lessons learned about steered molecular dynamics simulations and free energy calculations
title_short	Lessons learned about steered molecular dynamics simulations and free energy calculations
title_full	Lessons learned about steered molecular dynamics simulations and free energy calculations
title_fullStr	Lessons learned about steered molecular dynamics simulations and free energy calculations
title_full_unstemmed	Lessons learned about steered molecular dynamics simulations and free energy calculations
title_sort	lessons learned about steered molecular dynamics simulations and free energy calculations
url	http://hdl.handle.net/20.500.12110/paper_17470277_v_n_p_Boubeta
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Lessons learned about steered molecular dynamics simulations and free energy calculations

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