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Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication

Allostery is one of the pervasive mechanisms through which proteins in living systems carry out enzymatic activity, cell signaling, and metabolism control. Effective modeling of the protein function regulation requires a synthesis of the thermodynamic and structural views of allostery. We present he...

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Detalles Bibliográficos
Autores principales: Guarnera, Enrico, Berezovsky, Igor N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4777440/
https://www.ncbi.nlm.nih.gov/pubmed/26939022
http://dx.doi.org/10.1371/journal.pcbi.1004678
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author Guarnera, Enrico
Berezovsky, Igor N.
author_facet Guarnera, Enrico
Berezovsky, Igor N.
author_sort Guarnera, Enrico
collection PubMed
description Allostery is one of the pervasive mechanisms through which proteins in living systems carry out enzymatic activity, cell signaling, and metabolism control. Effective modeling of the protein function regulation requires a synthesis of the thermodynamic and structural views of allostery. We present here a structure-based statistical mechanical model of allostery, allowing one to observe causality of communication between regulatory and functional sites, and to estimate per residue free energy changes. Based on the consideration of ligand free and ligand bound systems in the context of a harmonic model, corresponding sets of characteristic normal modes are obtained and used as inputs for an allosteric potential. This potential quantifies the mean work exerted on a residue due to the local motion of its neighbors. Subsequently, in a statistical mechanical framework the entropic contribution to allosteric free energy of a residue is directly calculated from the comparison of conformational ensembles in the ligand free and ligand bound systems. As a result, this method provides a systematic approach for analyzing the energetics of allosteric communication based on a single structure. The feasibility of the approach was tested on a variety of allosteric proteins, heterogeneous in terms of size, topology and degree of oligomerization. The allosteric free energy calculations show the diversity of ways and complexity of scenarios existing in the phenomenology of allosteric causality and communication. The presented model is a step forward in developing the computational techniques aimed at detecting allosteric sites and obtaining the discriminative power between agonistic and antagonistic effectors, which are among the major goals in allosteric drug design.
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spelling pubmed-47774402016-03-10 Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication Guarnera, Enrico Berezovsky, Igor N. PLoS Comput Biol Research Article Allostery is one of the pervasive mechanisms through which proteins in living systems carry out enzymatic activity, cell signaling, and metabolism control. Effective modeling of the protein function regulation requires a synthesis of the thermodynamic and structural views of allostery. We present here a structure-based statistical mechanical model of allostery, allowing one to observe causality of communication between regulatory and functional sites, and to estimate per residue free energy changes. Based on the consideration of ligand free and ligand bound systems in the context of a harmonic model, corresponding sets of characteristic normal modes are obtained and used as inputs for an allosteric potential. This potential quantifies the mean work exerted on a residue due to the local motion of its neighbors. Subsequently, in a statistical mechanical framework the entropic contribution to allosteric free energy of a residue is directly calculated from the comparison of conformational ensembles in the ligand free and ligand bound systems. As a result, this method provides a systematic approach for analyzing the energetics of allosteric communication based on a single structure. The feasibility of the approach was tested on a variety of allosteric proteins, heterogeneous in terms of size, topology and degree of oligomerization. The allosteric free energy calculations show the diversity of ways and complexity of scenarios existing in the phenomenology of allosteric causality and communication. The presented model is a step forward in developing the computational techniques aimed at detecting allosteric sites and obtaining the discriminative power between agonistic and antagonistic effectors, which are among the major goals in allosteric drug design. Public Library of Science 2016-03-03 /pmc/articles/PMC4777440/ /pubmed/26939022 http://dx.doi.org/10.1371/journal.pcbi.1004678 Text en © 2016 Guarnera, Berezovsky http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Guarnera, Enrico
Berezovsky, Igor N.
Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication
title Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication
title_full Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication
title_fullStr Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication
title_full_unstemmed Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication
title_short Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication
title_sort structure-based statistical mechanical model accounts for the causality and energetics of allosteric communication
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4777440/
https://www.ncbi.nlm.nih.gov/pubmed/26939022
http://dx.doi.org/10.1371/journal.pcbi.1004678
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