Quantitative Analysis of Protein Unfolded State Energetics: Experimental and Computational Studies Demonstrate That Non-Native Side-Chain Interactions Stabilize Local Native Backbone Structure.


Journal

The journal of physical chemistry. B
ISSN: 1520-5207
Titre abrégé: J Phys Chem B
Pays: United States
ID NLM: 101157530

Informations de publication

Date de publication:
08 04 2021
Historique:
pubmed: 30 3 2021
medline: 15 5 2021
entrez: 29 3 2021
Statut: ppublish

Résumé

Proteins fold on relatively smooth free energy landscapes which are biased toward the native state, but even simple topologies which fold rapidly can experience roughness on their free energy landscape. The details of these interactions are difficult to elucidate experimentally. Closely related to the problem of deciphering the details of the free energy landscape is the problem of defining the interactions in the denatured state ensemble (DSE) which is populated under native conditions, that is, under conditions where the native state is stable. The DSE of many proteins deviates from random coil models, but quantifying and defining the energetics of the transiently populated interactions in this ensemble is extremely challenging. Characterization of the DSE of proteins which fold to compact structures is also relevant to studies of intrinsically disordered proteins (IDPs) since interactions in the dynamic ensemble populated by IDPs can modulate their behavior. Here we show how experimental thermodynamic and p

Identifiants

pubmed: 33779182
doi: 10.1021/acs.jpcb.0c08922
pmc: PMC8197028
mid: NIHMS1705730
doi:

Substances chimiques

Proteins 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3269-3277

Subventions

Organisme : NIGMS NIH HHS
ID : R01 GM078114
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM107104
Pays : United States

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Auteurs

Junjie Zou (J)

Department of Chemistry, Stony Brook University, Stony Brook, New York 11794-3400, United States.
Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794-3400, United States.

Shifeng Xiao (S)

Shenzhen Key Laboratory of Marine Biotechnology and Ecology, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen 518060, China.

Carlos Simmerling (C)

Department of Chemistry, Stony Brook University, Stony Brook, New York 11794-3400, United States.
Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794-3400, United States.

Daniel P Raleigh (DP)

Department of Chemistry, Stony Brook University, Stony Brook, New York 11794-3400, United States.
Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794-3400, United States.

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Classifications MeSH