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A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility

BACKGROUND: Protein sites evolve at different rates due to functional and biophysical constraints. It is usually considered that the main structural determinant of a site’s rate of evolution is its Relative Solvent Accessibility (RSA). However, a recent comparative study has shown that the main stru...

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Autores principales: Huang, Tsun-Tsao, del Valle Marcos, María Laura, Hwang, Jenn-Kang, Echave, Julian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4101840/
https://www.ncbi.nlm.nih.gov/pubmed/24716445
http://dx.doi.org/10.1186/1471-2148-14-78
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author Huang, Tsun-Tsao
del Valle Marcos, María Laura
Hwang, Jenn-Kang
Echave, Julian
author_facet Huang, Tsun-Tsao
del Valle Marcos, María Laura
Hwang, Jenn-Kang
Echave, Julian
author_sort Huang, Tsun-Tsao
collection PubMed
description BACKGROUND: Protein sites evolve at different rates due to functional and biophysical constraints. It is usually considered that the main structural determinant of a site’s rate of evolution is its Relative Solvent Accessibility (RSA). However, a recent comparative study has shown that the main structural determinant is the site’s Local Packing Density (LPD). LPD is related with dynamical flexibility, which has also been shown to correlate with sequence variability. Our purpose is to investigate the mechanism that connects a site’s LPD with its rate of evolution. RESULTS: We consider two models: an empirical Flexibility Model and a mechanistic Stress Model. The Flexibility Model postulates a linear increase of site-specific rate of evolution with dynamical flexibility. The Stress Model, introduced here, models mutations as random perturbations of the protein’s potential energy landscape, for which we use simple Elastic Network Models (ENMs). To account for natural selection we assume a single active conformation and use basic statistical physics to derive a linear relationship between site-specific evolutionary rates and the local stress of the mutant’s active conformation. We compare both models on a large and diverse dataset of enzymes. In a protein-by-protein study we found that the Stress Model outperforms the Flexibility Model for most proteins. Pooling all proteins together we show that the Stress Model is strongly supported by the total weight of evidence. Moreover, it accounts for the observed nonlinear dependence of sequence variability on flexibility. Finally, when mutational stress is controlled for, there is very little remaining correlation between sequence variability and dynamical flexibility. CONCLUSIONS: We developed a mechanistic Stress Model of evolution according to which the rate of evolution of a site is predicted to depend linearly on the local mutational stress of the active conformation. Such local stress is proportional to LPD, so that this model explains the relationship between LPD and evolutionary rate. Moreover, the model also accounts for the nonlinear dependence between evolutionary rate and dynamical flexibility.
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spelling pubmed-41018402014-07-18 A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility Huang, Tsun-Tsao del Valle Marcos, María Laura Hwang, Jenn-Kang Echave, Julian BMC Evol Biol Research Article BACKGROUND: Protein sites evolve at different rates due to functional and biophysical constraints. It is usually considered that the main structural determinant of a site’s rate of evolution is its Relative Solvent Accessibility (RSA). However, a recent comparative study has shown that the main structural determinant is the site’s Local Packing Density (LPD). LPD is related with dynamical flexibility, which has also been shown to correlate with sequence variability. Our purpose is to investigate the mechanism that connects a site’s LPD with its rate of evolution. RESULTS: We consider two models: an empirical Flexibility Model and a mechanistic Stress Model. The Flexibility Model postulates a linear increase of site-specific rate of evolution with dynamical flexibility. The Stress Model, introduced here, models mutations as random perturbations of the protein’s potential energy landscape, for which we use simple Elastic Network Models (ENMs). To account for natural selection we assume a single active conformation and use basic statistical physics to derive a linear relationship between site-specific evolutionary rates and the local stress of the mutant’s active conformation. We compare both models on a large and diverse dataset of enzymes. In a protein-by-protein study we found that the Stress Model outperforms the Flexibility Model for most proteins. Pooling all proteins together we show that the Stress Model is strongly supported by the total weight of evidence. Moreover, it accounts for the observed nonlinear dependence of sequence variability on flexibility. Finally, when mutational stress is controlled for, there is very little remaining correlation between sequence variability and dynamical flexibility. CONCLUSIONS: We developed a mechanistic Stress Model of evolution according to which the rate of evolution of a site is predicted to depend linearly on the local mutational stress of the active conformation. Such local stress is proportional to LPD, so that this model explains the relationship between LPD and evolutionary rate. Moreover, the model also accounts for the nonlinear dependence between evolutionary rate and dynamical flexibility. BioMed Central 2014-04-09 /pmc/articles/PMC4101840/ /pubmed/24716445 http://dx.doi.org/10.1186/1471-2148-14-78 Text en Copyright © 2014 Huang et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Huang, Tsun-Tsao
del Valle Marcos, María Laura
Hwang, Jenn-Kang
Echave, Julian
A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility
title A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility
title_full A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility
title_fullStr A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility
title_full_unstemmed A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility
title_short A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility
title_sort mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4101840/
https://www.ncbi.nlm.nih.gov/pubmed/24716445
http://dx.doi.org/10.1186/1471-2148-14-78
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