EconPapers    
Economics at your fingertips  
 

EPR-aided approach for solution structure determination of large RNAs or protein–RNA complexes

Olivier Duss (), Maxim Yulikov, Gunnar Jeschke and Frédéric H.-T. Allain ()
Additional contact information
Olivier Duss: Institute for Molecular Biology and Biophysics, ETH Zürich
Maxim Yulikov: Institute for Physical Chemistry, ETH Zürich
Gunnar Jeschke: Institute for Physical Chemistry, ETH Zürich
Frédéric H.-T. Allain: Institute for Molecular Biology and Biophysics, ETH Zürich

Nature Communications, 2014, vol. 5, issue 1, 1-9

Abstract: Abstract High-resolution structural information on RNA and its functionally important complexes with proteins is dramatically underrepresented compared with proteins but is urgently needed for understanding cellular processes at the molecular and atomic level. Here we present an EPR-based protocol to help solving large RNA and protein–RNA complex structures in solution by providing long-range distance constraints between rigid fragments. Using enzymatic ligation of smaller RNA fragments, large doubly spin-labelled RNAs can be obtained permitting the acquisition of long distance distributions (>80 Å) within a large protein–RNA complex. Using a simple and fast calculation in torsion angle space of the spin-label distributions with the program CYANA, we can derive simple distance constraints between the spin labels and use them together with short-range distance restraints derived from NMR to determine the structure of a 70 kDa protein–RNA complex composed of three subcomplexes.

Date: 2014
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/ncomms4669 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:5:y:2014:i:1:d:10.1038_ncomms4669

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

DOI: 10.1038/ncomms4669

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 ().

 
Page updated 2025-03-19
Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4669