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

Autores
Huang, Tsun Tsao; Marcos, María Laura; Hwang, Jenn Kang; Echave, Julián
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: Huang, Tsun Tsao. National Chiao Tung University; República de China
Fil: Marcos, María Laura. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Hwang, Jenn Kang. National Chiao Tung University; República de China
Fil: Echave, Julián. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
PROTEIN EVOLUTION
SITE-SPECIFIC SUBSTITUTION RATE
LOCAL PACKING DENSITY
ELASTIC NETWORK MODEL
FLEXIBILITY
STRESS
MEAN SQUARE FLUCTUATION
MEAN LOCAL MUTATIONAL STRESS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/33774

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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibilityHuang, Tsun TsaoMarcos, María LauraHwang, Jenn KangEchave, JuliánPROTEIN EVOLUTIONSITE-SPECIFIC SUBSTITUTION RATELOCAL PACKING DENSITYELASTIC NETWORK MODELFLEXIBILITYSTRESSMEAN SQUARE FLUCTUATIONMEAN LOCAL MUTATIONAL STRESShttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1BACKGROUND: 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.Fil: Huang, Tsun Tsao. National Chiao Tung University; República de ChinaFil: Marcos, María Laura. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Hwang, Jenn Kang. National Chiao Tung University; República de ChinaFil: Echave, Julián. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaBioMed Central2014-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/33774Huang, Tsun Tsao; Marcos, María Laura; Hwang, Jenn Kang; Echave, Julián; A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility; BioMed Central; BMC Evolutionary Biology; 14; 78; 4-2014; 1-91471-2148CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://bmcevolbiol.biomedcentral.com/articles/10.1186/1471-2148-14-78info:eu-repo/semantics/altIdentifier/doi/10.1186/1471-2148-14-78info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:39:23Zoai:ri.conicet.gov.ar:11336/33774instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:39:23.561CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv 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
spellingShingle A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility
Huang, Tsun Tsao
PROTEIN EVOLUTION
SITE-SPECIFIC SUBSTITUTION RATE
LOCAL PACKING DENSITY
ELASTIC NETWORK MODEL
FLEXIBILITY
STRESS
MEAN SQUARE FLUCTUATION
MEAN LOCAL MUTATIONAL STRESS
title_short 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_sort A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility
dc.creator.none.fl_str_mv Huang, Tsun Tsao
Marcos, María Laura
Hwang, Jenn Kang
Echave, Julián
author Huang, Tsun Tsao
author_facet Huang, Tsun Tsao
Marcos, María Laura
Hwang, Jenn Kang
Echave, Julián
author_role author
author2 Marcos, María Laura
Hwang, Jenn Kang
Echave, Julián
author2_role author
author
author
dc.subject.none.fl_str_mv PROTEIN EVOLUTION
SITE-SPECIFIC SUBSTITUTION RATE
LOCAL PACKING DENSITY
ELASTIC NETWORK MODEL
FLEXIBILITY
STRESS
MEAN SQUARE FLUCTUATION
MEAN LOCAL MUTATIONAL STRESS
topic PROTEIN EVOLUTION
SITE-SPECIFIC SUBSTITUTION RATE
LOCAL PACKING DENSITY
ELASTIC NETWORK MODEL
FLEXIBILITY
STRESS
MEAN SQUARE FLUCTUATION
MEAN LOCAL MUTATIONAL STRESS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv 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.
Fil: Huang, Tsun Tsao. National Chiao Tung University; República de China
Fil: Marcos, María Laura. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Hwang, Jenn Kang. National Chiao Tung University; República de China
Fil: Echave, Julián. Universidad Nacional de San Martín. Escuela de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
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.
publishDate 2014
dc.date.none.fl_str_mv 2014-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/33774
Huang, Tsun Tsao; Marcos, María Laura; Hwang, Jenn Kang; Echave, Julián; A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility; BioMed Central; BMC Evolutionary Biology; 14; 78; 4-2014; 1-9
1471-2148
CONICET Digital
CONICET
url http://hdl.handle.net/11336/33774
identifier_str_mv Huang, Tsun Tsao; Marcos, María Laura; Hwang, Jenn Kang; Echave, Julián; A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility; BioMed Central; BMC Evolutionary Biology; 14; 78; 4-2014; 1-9
1471-2148
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://bmcevolbiol.biomedcentral.com/articles/10.1186/1471-2148-14-78
info:eu-repo/semantics/altIdentifier/doi/10.1186/1471-2148-14-78
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv BioMed Central
publisher.none.fl_str_mv BioMed Central
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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