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Quantifying the Intrinsic Conformation Energy Landscape Topography of Proteins with Large-Scale Open–Closed Transition
[Image: see text] Large-scale conformational changes of proteins, including the open–closed transitions, are crucial for a variety of protein functions. These open–closed transitions are often associated with ligand binding. However, the understandings of the underlying mechanisms of the conformatio...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6107866/ https://www.ncbi.nlm.nih.gov/pubmed/30159398 http://dx.doi.org/10.1021/acscentsci.8b00274 |
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author | Chu, Wen-Ting Wang, Jin |
author_facet | Chu, Wen-Ting Wang, Jin |
author_sort | Chu, Wen-Ting |
collection | PubMed |
description | [Image: see text] Large-scale conformational changes of proteins, including the open–closed transitions, are crucial for a variety of protein functions. These open–closed transitions are often associated with ligand binding. However, the understandings of the underlying mechanisms of the conformational changes within proteins during the open–closed transitions are still challenging at present. In this study, we quantified the intrinsic underlying conformational energy landscapes of five different proteins with large-scale open–closed transitions. This is realized by exploring the underlying density of states and the intrinsic conformational energy landscape topography measure Λ. Λ is a dimensionless ratio of conformational energy gap δE versus conformational energy roughness δE and configurational entropy S or size of the intrinsic conformational energy landscape. By quantifying the Λ of intrinsic open–closed conformational (Λ(oc)) and intrinsic global folding (Λ(global)) energy landscapes, we show that both intrinsic open–closed conformation energy and entropy landscapes are funneled toward the closed state. Furthermore, our results indicate the strong correlations between Λ and thermodynamics (conformational state transition temperature against trapping temperature) as well as between Λ and kinetics (open–closed kinetic time) of these proteins. This shows that the intrinsic conformational landscape topography determines both the conformational thermodynamic stability and kinetic speed of the conformational dynamics. Our investigations provide important insights for understanding the fundamental mechanisms of the protein conformational dynamics in a physical and global way. |
format | Online Article Text |
id | pubmed-6107866 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-61078662018-08-29 Quantifying the Intrinsic Conformation Energy Landscape Topography of Proteins with Large-Scale Open–Closed Transition Chu, Wen-Ting Wang, Jin ACS Cent Sci [Image: see text] Large-scale conformational changes of proteins, including the open–closed transitions, are crucial for a variety of protein functions. These open–closed transitions are often associated with ligand binding. However, the understandings of the underlying mechanisms of the conformational changes within proteins during the open–closed transitions are still challenging at present. In this study, we quantified the intrinsic underlying conformational energy landscapes of five different proteins with large-scale open–closed transitions. This is realized by exploring the underlying density of states and the intrinsic conformational energy landscape topography measure Λ. Λ is a dimensionless ratio of conformational energy gap δE versus conformational energy roughness δE and configurational entropy S or size of the intrinsic conformational energy landscape. By quantifying the Λ of intrinsic open–closed conformational (Λ(oc)) and intrinsic global folding (Λ(global)) energy landscapes, we show that both intrinsic open–closed conformation energy and entropy landscapes are funneled toward the closed state. Furthermore, our results indicate the strong correlations between Λ and thermodynamics (conformational state transition temperature against trapping temperature) as well as between Λ and kinetics (open–closed kinetic time) of these proteins. This shows that the intrinsic conformational landscape topography determines both the conformational thermodynamic stability and kinetic speed of the conformational dynamics. Our investigations provide important insights for understanding the fundamental mechanisms of the protein conformational dynamics in a physical and global way. American Chemical Society 2018-08-01 2018-08-22 /pmc/articles/PMC6107866/ /pubmed/30159398 http://dx.doi.org/10.1021/acscentsci.8b00274 Text en Copyright © 2018 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Chu, Wen-Ting Wang, Jin Quantifying the Intrinsic Conformation Energy Landscape Topography of Proteins with Large-Scale Open–Closed Transition |
title | Quantifying the Intrinsic Conformation Energy Landscape
Topography of Proteins with Large-Scale Open–Closed Transition |
title_full | Quantifying the Intrinsic Conformation Energy Landscape
Topography of Proteins with Large-Scale Open–Closed Transition |
title_fullStr | Quantifying the Intrinsic Conformation Energy Landscape
Topography of Proteins with Large-Scale Open–Closed Transition |
title_full_unstemmed | Quantifying the Intrinsic Conformation Energy Landscape
Topography of Proteins with Large-Scale Open–Closed Transition |
title_short | Quantifying the Intrinsic Conformation Energy Landscape
Topography of Proteins with Large-Scale Open–Closed Transition |
title_sort | quantifying the intrinsic conformation energy landscape
topography of proteins with large-scale open–closed transition |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6107866/ https://www.ncbi.nlm.nih.gov/pubmed/30159398 http://dx.doi.org/10.1021/acscentsci.8b00274 |
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