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

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 d

SUBMITTER: Kuenze G 

PROVIDER: S-EPMC6851423 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature