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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/33774
Ver los metadatos del registro completo
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CONICETDig_8466201087146a9e3c038ad2f7119cc3 |
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oai_identifier_str |
oai:ri.conicet.gov.ar:11336/33774 |
network_acronym_str |
CONICETDig |
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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1844614419054592000 |
score |
13.070432 |