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PMID: 18326625 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, N.I.H., Intramural Research Support, Non-U.S. Gov't

Consistent blind protein structure generation from NMR chemical shift data.

Shen Y, Lange O, Delaglio F, Rossi P, Aramini JM, Liu G, Eletsky A, Wu Y, Singarapu KK, Lemak A, Ignatchenko A, Arrowsmith CH, Szyperski T, Montelione GT, Baker D, Bax A

Abstract

Protein NMR chemical shifts are highly sensitive to local structure. A robust protocol is described that exploits this relation for de novo protein structure generation, using as input experimental parameters the (13)C(alpha), (13)C(beta), (13)C', (15)N, (1)H(alpha) and (1)H(N) NMR chemical shifts. These shifts are generally available at the early stage of the traditional NMR structure determination process, before the collection and analysis of structural restraints. The chemical shift based structure determination protocol uses an empirically optimized procedure to select protein fragments from the Protein Data Bank, in conjunction with the standard ROSETTA Monte Carlo assembly and relaxation methods. Evaluation of 16 proteins, varying in size from 56 to 129 residues, yielded full-atom models that have 0.7-1.8 A root mean square deviations for the backbone atoms relative to the experimentally determined x-ray or NMR structures. The strategy also has been successfully applied in a blind manner to nine protein targets with molecular masses up to 15.4 kDa, whose conventional NMR structure determination was conducted in parallel by the Northeast Structural Genomics Consortium. This protocol potentially provides a new direction for high-throughput NMR structure determination.

MeSH Terms
Genomics Magnetic Resonance Spectroscopy Models, Molecular Protein Structure, Secondary Proteins/chemistry Software Thermodynamics Ubiquitin/chemistry
Chemicals
Proteins Ubiquitin
Authors & Affiliations
16 authors, click to expand affiliations / ORCID
Shen Yang
Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
Lange Oliver
Delaglio Frank
Rossi Paolo
Aramini James M
Liu Gaohua
Eletsky Alexander
Wu Yibing
Singarapu Kiran K
Lemak Alexander
Ignatchenko Alexandr
Arrowsmith Cheryl H
Szyperski Thomas
Montelione Gaetano T
Baker David
Bax Ad
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Article Info
Journal
Proceedings of the National Academy of Sciences of the United States of America
Abbr.
Proc Natl Acad Sci U S A
ISSN
1091-6490
Published
2008-03-25
Epub
2008-00-07
Pages
4685-90
Language
English
Region
United States
NLM ID
7505876
PMCID
PMC2290745
Subset
IM
Grants
NIGMS NIH HHS · U54 GM074958 · United States
Howard Hughes Medical Institute · United States
Intramural NIH HHS · United States
NIGMS NIH HHS · U54-GM074958 · United States
Corrections
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