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Modeling Structural Constraints on Protein Evolution via Side-Chain Conformational States

Few models of sequence evolution incorporate parameters describing protein structure, despite its high conservation, essential functional role and increasing availability. We present a structurally aware empirical substitution model for amino acid sequence evolution in which proteins are expressed u...

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Detalles Bibliográficos
Autores principales: Perron, Umberto, Kozlov, Alexey M, Stamatakis, Alexandros, Goldman, Nick, Moal, Iain H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736381/
https://www.ncbi.nlm.nih.gov/pubmed/31114882
http://dx.doi.org/10.1093/molbev/msz122
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author Perron, Umberto
Kozlov, Alexey M
Stamatakis, Alexandros
Goldman, Nick
Moal, Iain H
author_facet Perron, Umberto
Kozlov, Alexey M
Stamatakis, Alexandros
Goldman, Nick
Moal, Iain H
author_sort Perron, Umberto
collection PubMed
description Few models of sequence evolution incorporate parameters describing protein structure, despite its high conservation, essential functional role and increasing availability. We present a structurally aware empirical substitution model for amino acid sequence evolution in which proteins are expressed using an expanded alphabet that relays both amino acid identity and structural information. Each character specifies an amino acid as well as information about the rotamer configuration of its side-chain: the discrete geometric pattern of permitted side-chain atomic positions, as defined by the dihedral angles between covalently linked atoms. By assigning rotamer states in 251,194 protein structures and identifying 4,508,390 substitutions between closely related sequences, we generate a 55-state “Dayhoff-like” model that shows that the evolutionary properties of amino acids depend strongly upon side-chain geometry. The model performs as well as or better than traditional 20-state models for divergence time estimation, tree inference, and ancestral state reconstruction. We conclude that not only is rotamer configuration a valuable source of information for phylogenetic studies, but that modeling the concomitant evolution of sequence and structure may have important implications for understanding protein folding and function.
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spelling pubmed-67363812019-09-16 Modeling Structural Constraints on Protein Evolution via Side-Chain Conformational States Perron, Umberto Kozlov, Alexey M Stamatakis, Alexandros Goldman, Nick Moal, Iain H Mol Biol Evol Methods Few models of sequence evolution incorporate parameters describing protein structure, despite its high conservation, essential functional role and increasing availability. We present a structurally aware empirical substitution model for amino acid sequence evolution in which proteins are expressed using an expanded alphabet that relays both amino acid identity and structural information. Each character specifies an amino acid as well as information about the rotamer configuration of its side-chain: the discrete geometric pattern of permitted side-chain atomic positions, as defined by the dihedral angles between covalently linked atoms. By assigning rotamer states in 251,194 protein structures and identifying 4,508,390 substitutions between closely related sequences, we generate a 55-state “Dayhoff-like” model that shows that the evolutionary properties of amino acids depend strongly upon side-chain geometry. The model performs as well as or better than traditional 20-state models for divergence time estimation, tree inference, and ancestral state reconstruction. We conclude that not only is rotamer configuration a valuable source of information for phylogenetic studies, but that modeling the concomitant evolution of sequence and structure may have important implications for understanding protein folding and function. Oxford University Press 2019-09 2019-05-22 /pmc/articles/PMC6736381/ /pubmed/31114882 http://dx.doi.org/10.1093/molbev/msz122 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods
Perron, Umberto
Kozlov, Alexey M
Stamatakis, Alexandros
Goldman, Nick
Moal, Iain H
Modeling Structural Constraints on Protein Evolution via Side-Chain Conformational States
title Modeling Structural Constraints on Protein Evolution via Side-Chain Conformational States
title_full Modeling Structural Constraints on Protein Evolution via Side-Chain Conformational States
title_fullStr Modeling Structural Constraints on Protein Evolution via Side-Chain Conformational States
title_full_unstemmed Modeling Structural Constraints on Protein Evolution via Side-Chain Conformational States
title_short Modeling Structural Constraints on Protein Evolution via Side-Chain Conformational States
title_sort modeling structural constraints on protein evolution via side-chain conformational states
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736381/
https://www.ncbi.nlm.nih.gov/pubmed/31114882
http://dx.doi.org/10.1093/molbev/msz122
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