Blind testing of routine, fully automated determination of protein structures from nmr data

Antonio Rosato, James M. Aramini, Cheryl Arrowsmith, Anurag Bagaria, David Baker, Andrea Cavalli, Jurgen F. Doreleijers, Alexander Eletsky, Andrea Giachetti, Paul Guerry, Aleksandras Gutmanas, Peter Güntert, Yunfen He, Torsten Herrmann, Yuanpeng J. Huang, Victor Jaravine, Hendrik R.A. Jonker, Michael A. Kennedy, Oliver F. Lange, Gaohua LiuThérse E. Malliavin, Rajeswari Mani, Binchen Mao, Gaetano T. Montelione, Michael Nilges, Paolo Rossi, Gijs Van Der Schot, Harald Schwalbe, Thomas A. Szyperski, Michele Vendruscolo, Robert Vernon, Wim F. Vranken, Sjoerd De Vries, Geerten W. Vuister, Bin Wu, Yunhuang Yang, Alexandre M.J.J. Bonvin

Research output: Contribution to journalArticlepeer-review

67 Scopus citations


The protocols currently used for protein structure determination by nuclear magnetic resonance (NMR) depend on the determination of a large number of upper distance limits for proton-proton pairs. Typically, this task is performed manually by an experienced researcher rather than automatically by using a specific computer program. To assess whether it is indeed possible to generate in a fully automated manner NMR structures adequate for deposition in the Protein Data Bank, we gathered 10 experimental data sets with unassigned nuclear Overhauser effect spectroscopy (NOESY) peak lists for various proteins of unknown structure, computed structures for each of them using different, fully automatic programs, and compared the results to each other and to the manually solved reference structures that were not available at the time the data were provided. This constitutes a stringent "blind" assessment similar to the CASP and CAPRI initiatives. This study demonstrates the feasibility of routine, fully automated protein structure determination by NMR.

Original languageEnglish (US)
Pages (from-to)227-236
Number of pages10
Issue number2
StatePublished - Feb 8 2012
Externally publishedYes

Bibliographical note

Funding Information:
Financial support to CASD-NMR was provided by the European Community FP7 e-Infrastructure “e-NMR” and “WeNMR” projects (Grants 213010 and 261572). We acknowledge financial support from the Centre National de la Recherche Scientifique and the Institut Pasteur (M.N. and T.E.M.); from the Lichtenberg Program of the Volkswagen Foundation, the Deutsche Forschungsgemeinschaft, and the Japan Society for the Promotion of Science (P.G.); from the National Institute of General Medical Science's Protein Structure Initiative (Grants U54 GM074958 and U54 GM094597 to G.T.M., C.A., M.A.K., and T.A.S.); and from the Brussels Institute for Research and Innovation (Innoviris, Grant BB2B 2010-1-12 to W.F.V.). The support of the national GRID Initiatives of Belgium, Italy, Germany, the Netherlands (via the Dutch BIG GRID project), Portugal, United Kingdom, South Africa, Taiwan, and the Latin America GRID infrastructure via the Gisela Project is acknowledged for the use of web portals and for computing and storage facilities.


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