Retrieving functional pathways of biomolecules from single-particle snapshots
Ali Dashti,
Ghoncheh Mashayekhi,
Mrinal Shekhar,
Danya Ben Hail,
Salah Salah,
Peter Schwander,
Amedee des Georges (),
Abhishek Singharoy (),
Joachim Frank () and
Abbas Ourmazd ()
Additional contact information
Ali Dashti: University of Wisconsin Milwaukee
Ghoncheh Mashayekhi: University of Wisconsin Milwaukee
Mrinal Shekhar: University of Illinois at Urbana-Champaign 405 N. Mathews Ave.
Danya Ben Hail: City University of New York
Salah Salah: City University of New York
Peter Schwander: University of Wisconsin Milwaukee
Amedee des Georges: City University of New York
Abhishek Singharoy: Arizona State University
Joachim Frank: Columbia University
Abbas Ourmazd: University of Wisconsin Milwaukee
Nature Communications, 2020, vol. 11, issue 1, 1-14
Abstract:
Abstract A primary reason for the intense interest in structural biology is the fact that knowledge of structure can elucidate macromolecular functions in living organisms. Sustained effort has resulted in an impressive arsenal of tools for determining the static structures. But under physiological conditions, macromolecules undergo continuous conformational changes, a subset of which are functionally important. Techniques for capturing the continuous conformational changes underlying function are essential for further progress. Here, we present chemically-detailed conformational movies of biological function, extracted data-analytically from experimental single-particle cryo-electron microscopy (cryo-EM) snapshots of ryanodine receptor type 1 (RyR1), a calcium-activated calcium channel engaged in the binding of ligands. The functional motions differ substantially from those inferred from static structures in the nature of conformationally active structural domains, the sequence and extent of conformational motions, and the way allosteric signals are transduced within and between domains. Our approach highlights the importance of combining experiment, advanced data analysis, and molecular simulations.
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://www.nature.com/articles/s41467-020-18403-x Abstract (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18403-x
Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/
DOI: 10.1038/s41467-020-18403-x
Access Statistics for this article
Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie
More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().