Rotational dynamics and transition mechanisms of surface-adsorbed proteins.

Levy-flight transition high-speed atomic force microscopy machine learning orientational energy landscapes rotational dynamics of protein

Journal

Proceedings of the National Academy of Sciences of the United States of America
ISSN: 1091-6490
Titre abrégé: Proc Natl Acad Sci U S A
Pays: United States
ID NLM: 7505876

Informations de publication

Date de publication:
19 04 2022
Historique:
entrez: 12 4 2022
pubmed: 13 4 2022
medline: 15 4 2022
Statut: ppublish

Résumé

Assembly of biomolecules at solid–water interfaces requires molecules to traverse complex orientation-dependent energy landscapes through processes that are poorly understood, largely due to the dearth of in situ single-molecule measurements and statistical analyses of the rotational dynamics that define directional selection. Emerging capabilities in high-speed atomic force microscopy and machine learning have allowed us to directly determine the orientational energy landscape and observe and quantify the rotational dynamics for protein nanorods on the surface of muscovite mica under a variety of conditions. Comparisons with kinetic Monte Carlo simulations show that the transition rates between adjacent orientation-specific energetic minima can largely be understood through traditional models of in-plane Brownian rotation across a biased energy landscape, with resulting transition rates that are exponential in the energy barriers between states. However, transitions between more distant angular states are decoupled from barrier height, with jump-size distributions showing a power law decay that is characteristic of a nonclassical Levy-flight random walk, indicating that large jumps are enabled by alternative modes of motion via activated states. The findings provide insights into the dynamics of biomolecules at solid–liquid interfaces that lead to self-assembly, epitaxial matching, and other orientationally anisotropic outcomes and define a general procedure for exploring such dynamics with implications for hybrid biomolecular–inorganic materials design.

Identifiants

pubmed: 35412902
doi: 10.1073/pnas.2020242119
pmc: PMC9169768
doi:

Substances chimiques

Aluminum Silicates 0
Proteins 0
Solutions 0
muscovite 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e2020242119

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Auteurs

Shuai Zhang (S)

Department of Materials Science and Engineering, University of Washington, Seattle, WA 98195.
Physical Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352.

Robbie Sadre (R)

Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720.

Benjamin A Legg (BA)

Department of Materials Science and Engineering, University of Washington, Seattle, WA 98195.
Physical Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352.

Harley Pyles (H)

Department of Biochemistry, University of Washington, Seattle, WA 98195.
Institute for Protein Design, University of Washington, Seattle, WA 98195.

Talita Perciano (T)

Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720.

E Wes Bethel (EW)

Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720.
Department of Computer Science, San Francisco State University, San Francisco, CA 94132.

David Baker (D)

Department of Biochemistry, University of Washington, Seattle, WA 98195.
Institute for Protein Design, University of Washington, Seattle, WA 98195.
HHMI, University of Washington, Seattle, WA, 98195.

Oliver Rübel (O)

Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720.

James J De Yoreo (JJ)

Department of Materials Science and Engineering, University of Washington, Seattle, WA 98195.
Physical Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352.

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Classifications MeSH