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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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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
Zeitschrift
Angewandte Chemie - Internationale Edition
Quellenangaben
Band: 55,
Heft: 39,
Seiten: 11970-11974
Verlag
Wiley
Verlagsort
Weinheim
Nichtpatentliteratur
Publikationen
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of Structural Biology (STB)