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Probabilistic validation of protein NMR chemical shift assignments.

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/.

SUBMITTER: Dashti H

PROVIDER: S-EPMC4744101 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Probabilistic validation of protein NMR chemical shift assignments.

Dashti Hesam H Tonelli Marco M Lee Woonghee W Westler William M WM Cornilescu Gabriel G Ulrich Eldon L EL Markley John L JL

Journal of biomolecular NMR 20160102 1

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 ...[more]

PMID: 26724815

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