Protein structure prediction using sparse NOE and RDC restraints with Rosetta in CASP13

Research output: Contribution to journalArticle

Authors

External Institution(s)

  • Vanderbilt University

Details

Original languageEnglish (US)
Pages (from-to)1341-1350
Number of pages10
JournalProteins: Structure, Function and Bioinformatics
Volume87
Issue number12
StatusPublished - Dec 1 2019
Peer-reviewedYes

Abstract

Computational methods that produce accurate protein structure models from limited experimental data, for example, from nuclear magnetic resonance (NMR) spectroscopy, hold great potential for biomedical research. The NMR-assisted modeling challenge in CASP13 provided a blind test to explore the capabilities and limitations of current modeling techniques in leveraging NMR data which had high sparsity, ambiguity, and error rate for protein structure prediction. We describe our approach to predict the structure of these proteins leveraging the Rosetta software suite. Protein structure models were predicted de novo using a two-stage protocol. First, low-resolution models were generated with the Rosetta de novo method guided by nonambiguous nuclear Overhauser effect (NOE) contacts and residual dipolar coupling (RDC) restraints. Second, iterative model hybridization and fragment insertion with the Rosetta comparative modeling method was used to refine and regularize models guided by all ambiguous and nonambiguous NOE contacts and RDCs. Nine out of 16 of the Rosetta de novo models had the correct fold (global distance test total score > 45) and in three cases high-resolution models were achieved (root-mean-square deviation < 3.5 å). We also show that a meta-approach applying iterative Rosetta + NMR refinement on server-predicted models which employed non-NMR-contacts and structural templates leads to substantial improvement in model quality. Integrating these data-assisted refinement strategies with innovative non-data-assisted approaches which became possible in CASP13 such as high precision contact prediction will in the near future enable structure determination for large proteins that are outside of the realm of conventional NMR.

    Research areas

  • CASP13, NMR spectroscopy, Rosetta, distance restraints, protein structure prediction

Citation formats

APA

Kuenze, G., & Meiler, J. (2019). Protein structure prediction using sparse NOE and RDC restraints with Rosetta in CASP13. Proteins: Structure, Function and Bioinformatics, 87(12), 1341-1350. https://doi.org/10.1002/prot.25769

Harvard

Kuenze, G & Meiler, J 2019, 'Protein structure prediction using sparse NOE and RDC restraints with Rosetta in CASP13', Proteins: Structure, Function and Bioinformatics, vol. 87, no. 12, pp. 1341-1350. https://doi.org/10.1002/prot.25769