Campus Units

Biochemistry, Biophysics and Molecular Biology, Roy J. Carver Department of, Bioinformatics and Computational Biology

Document Type

Article

Publication Version

Published Version

Publication Date

6-20-2018

Journal or Book Title

PloS ONE

Volume

13

Issue

6

First Page

e0199225

DOI

10.1371/journal.pone.0199225

Abstract

Dynamic communities in proteins comprise the cohesive structural units that individually exhibit rigid body motions. These can correspond to structural domains, but are usually smaller parts that move with respect to one another in a protein’s internal motions, key to its functional dynamics. Previous studies emphasized their importance to understand the nature of ligand-induced allosteric regulation. These studies reported that mutations to key community residues can hinder transmission of allosteric signals among the communities. Usually molecular dynamic (MD) simulations (~ 100 ns or longer) have been used to identify the communities—a demanding task for larger proteins. In the present study, we propose that dynamic communities obtained from MD simulations can also be obtained alternatively with simpler models–the elastic network models (ENMs). To verify this premise, we compare the specific communities obtained from MD and ENMs for 44 proteins. We evaluate the correspondence in communities from the two methods and compute the extent of agreement in the dynamic cross-correlation data used for community detection. Our study reveals a strong correspondence between the communities from MD and ENM and also good agreement for the residue cross-correlations. Importantly, we observe that the dynamic communities from MD can be closely reproduced with ENMs. With ENMs, we also compare the community structures of stable and unstable mutant forms of T4 Lysozyme with its wild-type. We find that communities for unstable mutants show substantially poorer agreement with the wild-type communities than do stable mutants, suggesting such ENM-based community structures can serve as a means to rapidly identify deleterious mutants.

Comments

This article is published as Mishra SK, Jernigan RL (2018) Protein dynamic communities from elastic network models align closely to the communities defined by molecular dynamics. PLoS ONE 13(6): e0199225. doi: 10.1371/journal.pone.0199225.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Copyright Owner

Mishra, Jernigan

Language

en

File Format

application/pdf

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