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Entropy 2017, 19(12), 646; https://doi.org/10.3390/e19120646

Statistical Measures to Quantify Similarity between Molecular Dynamics Simulation Trajectories

1
Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
2
Department of Physics and Optical Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
3
Center for Biomedical Engineering and Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
*
Author to whom correspondence should be addressed.
Received: 10 October 2017 / Revised: 20 November 2017 / Accepted: 23 November 2017 / Published: 29 November 2017
(This article belongs to the Special Issue Understanding Molecular Dynamics via Stochastic Processes)
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Abstract

Molecular dynamics simulation is commonly employed to explore protein dynamics. Despite the disparate timescales between functional mechanisms and molecular dynamics (MD) trajectories, functional differences are often inferred from differences in conformational ensembles between two proteins in structure-function studies that investigate the effect of mutations. A common measure to quantify differences in dynamics is the root mean square fluctuation (RMSF) about the average position of residues defined by C α -atoms. Using six MD trajectories describing three native/mutant pairs of beta-lactamase, we make comparisons with additional measures that include Jensen-Shannon, modifications of Kullback-Leibler divergence, and local p-values from 1-sample Kolmogorov-Smirnov tests. These additional measures require knowing a probability density function, which we estimate by using a nonparametric maximum entropy method that quantifies rare events well. The same measures are applied to distance fluctuations between C α -atom pairs. Results from several implementations for quantitative comparison of a pair of MD trajectories are made based on fluctuations for on-residue and residue-residue local dynamics. We conclude that there is almost always a statistically significant difference between pairs of 100 ns all-atom simulations on moderate-sized proteins as evident from extraordinarily low p-values. View Full-Text
Keywords: molecular dynamics; conformational fluctuations; conformational similarity measures; p-values; statistical significance; beta-lactamase; site directed mutations molecular dynamics; conformational fluctuations; conformational similarity measures; p-values; statistical significance; beta-lactamase; site directed mutations
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Farmer, J.; Kanwal, F.; Nikulsin, N.; Tsilimigras, M.C.B.; Jacobs, D.J. Statistical Measures to Quantify Similarity between Molecular Dynamics Simulation Trajectories. Entropy 2017, 19, 646.

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