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J Biomol NMR. 2016 Jan;64(1):17-25. doi: 10.1007/s10858-015-0007-8. Epub 2016 Jan 2.

Probabilistic validation of protein NMR chemical shift assignments.

Author information

1
Graduate Program in Biophysics, Biochemistry Department, University of Wisconsin-Madison, Madison, WI, USA.
2
Biochemistry Department, National Magnetic Resonance Facility at Madison, University of Wisconsin-Madison, Madison, WI, USA.
3
BioMagResBank, Biochemistry Department, University of Wisconsin-Madison, Madison, WI, USA.
4
Biochemistry Department, National Magnetic Resonance Facility at Madison, University of Wisconsin-Madison, Madison, WI, USA. markley@nmrfam.wisc.edu.
5
BioMagResBank, Biochemistry Department, University of Wisconsin-Madison, Madison, WI, USA. markley@nmrfam.wisc.edu.

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/.

KEYWORDS:

NMR chemical shift assignments; NOESY experiment; Probabilistic method; Validation

PMID:
26724815
PMCID:
PMC4744101
DOI:
10.1007/s10858-015-0007-8
[Indexed for MEDLINE]
Free PMC Article

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