Probabilistic validation of protein NMR chemical shift assignments

Hesam Dashti; Marco Tonelli; Woonghee Lee; William M Westler; Gabriel Cornilescu; Eldon L Ulrich; John L Markley

doi:10.1007/s10858-015-0007-8

Probabilistic validation of protein NMR chemical shift assignments

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

Authors

Hesam Dashti^{1

2}, Marco Tonelli², Woonghee Lee², William M Westler², Gabriel Cornilescu², Eldon L Ulrich³, John L Markley^{4

5}

Affiliations

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.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Nuclear Magnetic Resonance, Biomolecular / methods*
Proteins / chemistry*
Reproducibility of Results

Substances

Proteins

Abstract

Publication types

MeSH terms

Substances

Grants and funding