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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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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. |
format | Online Article Text |
id | pubmed-6736381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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