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Probabilistic validation of protein NMR chemical shift assignments.

Authors :
Dashti H
Tonelli M
Lee W
Westler WM
Cornilescu G
Ulrich EL
Markley JL
Source :
Journal of biomolecular NMR [J Biomol NMR] 2016 Jan; Vol. 64 (1), pp. 17-25. Date of Electronic Publication: 2016 Jan 02.
Publication Year :
2016

Abstract

Data validation plays an important role in ensuring the reliability and reproducibility of studies. NMR investigations of the functional properties, dynamics, chemical kinetics, and structures of proteins depend critically on the correctness of chemical shift assignments. We present a novel probabilistic method named ARECA for validating chemical shift assignments that relies on the nuclear Overhauser effect data . ARECA has been evaluated through its application to 26 case studies and has been shown to be complementary to, and usually more reliable than, approaches based on chemical shift databases. ARECA is available online at http://areca.nmrfam.wisc.edu/.

Details

Language :
English
ISSN :
1573-5001
Volume :
64
Issue :
1
Database :
MEDLINE
Journal :
Journal of biomolecular NMR
Publication Type :
Academic Journal
Accession number :
26724815
Full Text :
https://doi.org/10.1007/s10858-015-0007-8