Automated and optimally FRET-assisted structural modeling

Mykola Dimura, Thomas-Otavio Peulen, Hugo Sanabria, Dmitro Rodnin, Katherina Hemmen, Christian A. Hanke, Claus A. M. Seidel () and Holger Gohlke ()
Additional contact information
Mykola Dimura: Heinrich Heine University Düsseldorf
Thomas-Otavio Peulen: Heinrich Heine University Düsseldorf
Hugo Sanabria: Heinrich Heine University Düsseldorf
Dmitro Rodnin: Heinrich Heine University Düsseldorf
Katherina Hemmen: Heinrich Heine University Düsseldorf
Christian A. Hanke: Heinrich Heine University Düsseldorf
Claus A. M. Seidel: Heinrich Heine University Düsseldorf
Holger Gohlke: Heinrich Heine University Düsseldorf

Nature Communications, 2020, vol. 11, issue 1, 1-14

Abstract: Abstract FRET experiments can provide state-specific structural information of complex dynamic biomolecular assemblies. However, to overcome the sparsity of FRET experiments, they need to be combined with computer simulations. We introduce a program suite with (i) an automated design tool for FRET experiments, which determines how many and which FRET pairs should be used to minimize the uncertainty and maximize the accuracy of an integrative structure, (ii) an efficient approach for FRET-assisted coarse-grained structural modeling, and all-atom molecular dynamics simulations-based refinement, and (iii) a quantitative quality estimate for judging the accuracy of FRET-derived structures as opposed to precision. We benchmark our tools against simulated and experimental data of proteins with multiple conformational states and demonstrate an accuracy of ~3 Å RMSDCα against X-ray structures for sets of 15 to 23 FRET pairs. Free and open-source software for the introduced workflow is available at https://github.com/Fluorescence-Tools . A web server for FRET-assisted structural modeling of proteins is available at http://nmsim.de .

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-020-19023-1 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_s41467-020-19023-1

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-020-19023-1

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 ().