Using the Maximum Entropy Principle to Combine Simulations and Solution Experiments

Molecular dynamics (MD) simulations allow the investigation of the structural dynamics of biomolecular systems with unrivaled time and space resolution. However, in order to compensate for the inaccuracies of the utilized empirical force fields, it is becoming common to integrate MD simulations with...

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Main Authors: Andrea Cesari, Sabine Reißer, Giovanni Bussi
Format: Article
Language:English
Published: MDPI AG 2018-02-01
Series:Computation
Subjects:
Online Access:http://www.mdpi.com/2079-3197/6/1/15
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spelling doaj-ba7a7ad761d04f2195c6abaa2cbeeea02020-11-24T23:44:20ZengMDPI AGComputation2079-31972018-02-01611510.3390/computation6010015computation6010015Using the Maximum Entropy Principle to Combine Simulations and Solution ExperimentsAndrea Cesari0Sabine Reißer1Giovanni Bussi2Scuola Internazionale Superiore di Studi Avanzati (SISSA), via Bonomea 265, 34136 Trieste, ItalyScuola Internazionale Superiore di Studi Avanzati (SISSA), via Bonomea 265, 34136 Trieste, ItalyScuola Internazionale Superiore di Studi Avanzati (SISSA), via Bonomea 265, 34136 Trieste, ItalyMolecular dynamics (MD) simulations allow the investigation of the structural dynamics of biomolecular systems with unrivaled time and space resolution. However, in order to compensate for the inaccuracies of the utilized empirical force fields, it is becoming common to integrate MD simulations with experimental data obtained from ensemble measurements. We review here the approaches that can be used to combine MD and experiment under the guidance of the maximum entropy principle. We mostly focus on methods based on Lagrangian multipliers, either implemented as reweighting of existing simulations or through an on-the-fly optimization. We discuss how errors in the experimental data can be modeled and accounted for. Finally, we use simple model systems to illustrate the typical difficulties arising when applying these methods.http://www.mdpi.com/2079-3197/6/1/15molecular dynamicsmaximum entropy principleensemble averagesexperimental constraints
collection DOAJ
language English
format Article
sources DOAJ
author Andrea Cesari
Sabine Reißer
Giovanni Bussi
spellingShingle Andrea Cesari
Sabine Reißer
Giovanni Bussi
Using the Maximum Entropy Principle to Combine Simulations and Solution Experiments
Computation
molecular dynamics
maximum entropy principle
ensemble averages
experimental constraints
author_facet Andrea Cesari
Sabine Reißer
Giovanni Bussi
author_sort Andrea Cesari
title Using the Maximum Entropy Principle to Combine Simulations and Solution Experiments
title_short Using the Maximum Entropy Principle to Combine Simulations and Solution Experiments
title_full Using the Maximum Entropy Principle to Combine Simulations and Solution Experiments
title_fullStr Using the Maximum Entropy Principle to Combine Simulations and Solution Experiments
title_full_unstemmed Using the Maximum Entropy Principle to Combine Simulations and Solution Experiments
title_sort using the maximum entropy principle to combine simulations and solution experiments
publisher MDPI AG
series Computation
issn 2079-3197
publishDate 2018-02-01
description Molecular dynamics (MD) simulations allow the investigation of the structural dynamics of biomolecular systems with unrivaled time and space resolution. However, in order to compensate for the inaccuracies of the utilized empirical force fields, it is becoming common to integrate MD simulations with experimental data obtained from ensemble measurements. We review here the approaches that can be used to combine MD and experiment under the guidance of the maximum entropy principle. We mostly focus on methods based on Lagrangian multipliers, either implemented as reweighting of existing simulations or through an on-the-fly optimization. We discuss how errors in the experimental data can be modeled and accounted for. Finally, we use simple model systems to illustrate the typical difficulties arising when applying these methods.
topic molecular dynamics
maximum entropy principle
ensemble averages
experimental constraints
url http://www.mdpi.com/2079-3197/6/1/15
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