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van der Schot, G.* ; Zhang, Z.* ; Vernon, R.* ; Shen, Y.* ; Vranken, W.F.* ; Baker, D.* ; Bonvin, A.M.* ; Lange, O.F.

Improving 3D structure prediction from chemical shift data.

J. Biomol. NMR 57, 27-35 (2013)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
We report advances in the calculation of protein structures from chemical shift nuclear magnetic resonance data alone. Our previously developed method, CS-Rosetta, assembles structures from a library of short protein fragments picked from a large library of protein structures using chemical shifts and sequence information. Here we demonstrate that combination of a new and improved fragment picker and the iterative sampling algorithm RASREC yield significant improvements in convergence and accuracy. Moreover, we introduce improved criteria for assessing the accuracy of the models produced by the method. The method was tested on 39 proteins in the 50-100 residue size range and yields reliable structures in 70 % of the cases. All structures that passed the reliability filter were accurate (<2 Å RMSD from the reference).
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Nuclear magnetic resonance; Protein structure calculation; CS-ROSETTA; Sparse data; Protein-structure Determination ; Nmr Structure Determination ; Structure Generation ; Rosetta ; Plus
Sprache englisch
Veröffentlichungsjahr 2013
HGF-Berichtsjahr 2013
ISSN (print) / ISBN 0925-2738
e-ISSN 1573-5001
Zeitschrift Journal of Biomolecular NMR
Quellenangaben Band: 57, Heft: 1, Seiten: 27-35 Artikelnummer: , Supplement: ,
Verlag Springer
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Structural Biology (STB)
POF Topic(s) 30203 - Molecular Targets and Therapies
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-503000-001
PubMed ID 23912841
DOI 10.1007/s10858-013-9762-6
WOS ID WOS:000323673800004
Scopus ID 84883558585
Erfassungsdatum 2013-08-08
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