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Open Access Green as soon as Postprint is submitted to ZB.
Prediction of protein structure using surface accessibility data.
Angew. Chem.-Int. Edit. 55, 11970-11974 (2016)
An approach to the de novo structure prediction of proteins is described that relies on surface accessibility data from NMR paramagnetic relaxation enhancements by a soluble paramagnetic compound (sPRE). This method exploits the distance-to-surface information encoded in the sPRE data in the chemical shift-based CS-Rosetta de novo structure prediction framework to generate reliable structural models. For several proteins, it is demonstrated that surface accessibility data is an excellent measure of the correct protein fold in the early stages of the computational folding algorithm and significantly improves accuracy and convergence of the standard Rosetta structure prediction approach.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Cs-rosetta ; Nmr Spectroscopy ; Paramagnetic Relaxation ; Protein Structure Prediction ; Structural Biology; Paramagnetic Relaxation Enhancements; Nmr Chemical-shifts; Structure Generation; Complexes; Rosetta
ISSN (print) / ISBN
1433-7851
e-ISSN
1521-3773
Quellenangaben
Volume: 55,
Issue: 39,
Pages: 11970-11974
Publisher
Wiley
Publishing Place
Weinheim
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Structural Biology (STB)