Computational protein design quantifies structural constraints on amino acid covariation.

Amino acid covariation, where the identities of amino acids at different sequence positions are correlated, is a hallmark of naturally occurring proteins. This covariation can arise from multiple factors, including selective pressures for maintaining protein structure, requirements imposed by a spec...

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Autores principales:	Noah Ollikainen, Tanja Kortemme
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/25c6e0753bb14072b6fa8d7f87178cc2
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spelling	oai:doaj.org-article:25c6e0753bb14072b6fa8d7f87178cc22021-11-18T05:53:24ZComputational protein design quantifies structural constraints on amino acid covariation.1553-734X1553-735810.1371/journal.pcbi.1003313https://doaj.org/article/25c6e0753bb14072b6fa8d7f87178cc22013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24244128/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Amino acid covariation, where the identities of amino acids at different sequence positions are correlated, is a hallmark of naturally occurring proteins. This covariation can arise from multiple factors, including selective pressures for maintaining protein structure, requirements imposed by a specific function, or from phylogenetic sampling bias. Here we employed flexible backbone computational protein design to quantify the extent to which protein structure has constrained amino acid covariation for 40 diverse protein domains. We find significant similarities between the amino acid covariation in alignments of natural protein sequences and sequences optimized for their structures by computational protein design methods. These results indicate that the structural constraints imposed by protein architecture play a dominant role in shaping amino acid covariation and that computational protein design methods can capture these effects. We also find that the similarity between natural and designed covariation is sensitive to the magnitude and mechanism of backbone flexibility used in computational protein design. Our results thus highlight the necessity of including backbone flexibility to correctly model precise details of correlated amino acid changes and give insights into the pressures underlying these correlations.Noah OllikainenTanja KortemmePublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 9, Iss 11, p e1003313 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Noah Ollikainen Tanja Kortemme Computational protein design quantifies structural constraints on amino acid covariation.
description	Amino acid covariation, where the identities of amino acids at different sequence positions are correlated, is a hallmark of naturally occurring proteins. This covariation can arise from multiple factors, including selective pressures for maintaining protein structure, requirements imposed by a specific function, or from phylogenetic sampling bias. Here we employed flexible backbone computational protein design to quantify the extent to which protein structure has constrained amino acid covariation for 40 diverse protein domains. We find significant similarities between the amino acid covariation in alignments of natural protein sequences and sequences optimized for their structures by computational protein design methods. These results indicate that the structural constraints imposed by protein architecture play a dominant role in shaping amino acid covariation and that computational protein design methods can capture these effects. We also find that the similarity between natural and designed covariation is sensitive to the magnitude and mechanism of backbone flexibility used in computational protein design. Our results thus highlight the necessity of including backbone flexibility to correctly model precise details of correlated amino acid changes and give insights into the pressures underlying these correlations.
format	article
author	Noah Ollikainen Tanja Kortemme
author_facet	Noah Ollikainen Tanja Kortemme
author_sort	Noah Ollikainen
title	Computational protein design quantifies structural constraints on amino acid covariation.
title_short	Computational protein design quantifies structural constraints on amino acid covariation.
title_full	Computational protein design quantifies structural constraints on amino acid covariation.
title_fullStr	Computational protein design quantifies structural constraints on amino acid covariation.
title_full_unstemmed	Computational protein design quantifies structural constraints on amino acid covariation.
title_sort	computational protein design quantifies structural constraints on amino acid covariation.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/25c6e0753bb14072b6fa8d7f87178cc2
work_keys_str_mv	AT noahollikainen computationalproteindesignquantifiesstructuralconstraintsonaminoacidcovariation AT tanjakortemme computationalproteindesignquantifiesstructuralconstraintsonaminoacidcovariation
_version_	1718424654968782848

Computational protein design quantifies structural constraints on amino acid covariation.

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