Evolutionary dynamics on protein bi-stability landscapes can potentially resolve adaptive conflicts.

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the tw...

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Autores principales:	Tobias Sikosek, Erich Bornberg-Bauer, Hue Sun Chan
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/7804b5e0bc924cbc96dff707ea25db22
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spelling	oai:doaj.org-article:7804b5e0bc924cbc96dff707ea25db222021-11-18T05:51:00ZEvolutionary dynamics on protein bi-stability landscapes can potentially resolve adaptive conflicts.1553-734X1553-735810.1371/journal.pcbi.1002659https://doaj.org/article/7804b5e0bc924cbc96dff707ea25db222012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23028272/pdf/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149-21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed.Tobias SikosekErich Bornberg-BauerHue Sun ChanPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 8, Iss 9, p e1002659 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Tobias Sikosek Erich Bornberg-Bauer Hue Sun Chan Evolutionary dynamics on protein bi-stability landscapes can potentially resolve adaptive conflicts.
description	Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149-21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed.
format	article
author	Tobias Sikosek Erich Bornberg-Bauer Hue Sun Chan
author_facet	Tobias Sikosek Erich Bornberg-Bauer Hue Sun Chan
author_sort	Tobias Sikosek
title	Evolutionary dynamics on protein bi-stability landscapes can potentially resolve adaptive conflicts.
title_short	Evolutionary dynamics on protein bi-stability landscapes can potentially resolve adaptive conflicts.
title_full	Evolutionary dynamics on protein bi-stability landscapes can potentially resolve adaptive conflicts.
title_fullStr	Evolutionary dynamics on protein bi-stability landscapes can potentially resolve adaptive conflicts.
title_full_unstemmed	Evolutionary dynamics on protein bi-stability landscapes can potentially resolve adaptive conflicts.
title_sort	evolutionary dynamics on protein bi-stability landscapes can potentially resolve adaptive conflicts.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/7804b5e0bc924cbc96dff707ea25db22
work_keys_str_mv	AT tobiassikosek evolutionarydynamicsonproteinbistabilitylandscapescanpotentiallyresolveadaptiveconflicts AT erichbornbergbauer evolutionarydynamicsonproteinbistabilitylandscapescanpotentiallyresolveadaptiveconflicts AT huesunchan evolutionarydynamicsonproteinbistabilitylandscapescanpotentiallyresolveadaptiveconflicts
_version_	1718424794830995456

Evolutionary dynamics on protein bi-stability landscapes can potentially resolve adaptive conflicts.

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