| Literature DB >> 22325772 |
Antonio Rosato1, 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 Liu, Thérèse 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.
Abstract
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.Entities:
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Year: 2012 PMID： 22325772 PMCID： PMC3609704 DOI： 10.1016/j.str.2012.01.002
Source DB: PubMed Journal: Structure ISSN： 0969-2126 Impact factor: 5.006