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Prediction of protein structure using surface accessibility data.

Angew. Chem.-Int. Edit. 55, 11970-11974 (2016)
Verlagsversion DOI
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
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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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter 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 Band: 55, Heft: 39, Seiten: 11970-11974 Artikelnummer: , Supplement: ,
Verlag Wiley
Verlagsort Weinheim
Begutachtungsstatus Peer reviewed