Rapid prediction of multi-dimensional NMR data sets
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We present a computational environment for Fast Analysis of multidimensional NMR DAta Sets (FANDAS) that allows assembling multidimensional data sets from a variety of input parameters and facilitates comparing and modifying such “in silico” data sets during the various stages of the NMR data analysis. The input parameters can vary from (partial) NMR assignments directly obtained from experiments to values retrieved from in silico prediction programs. The resulting predicted data sets enable a rapid evaluation of sample labeling in light of spectral resolution and structural content, using standard NMR software such as Sparky. In addition, direct comparison to experimental data sets can be used to validate NMR assignments, distinguish different molecular components, refine structural models or other parameters derived from NMR data. The method is demonstrated in the context of solid-state NMR data obtained for the cyclic nucleotide binding domain of a bacterial cyclic nucleotide-gated channel and on membrane-embedded sensory rhodopsin II. FANDAS is freely available as web portal under WeNMR (http://www.wenmr.eu/services/FANDAS).
KeywordsNMR Software Chemical shift Membrane Protein Solid-state NMR
This work was supported by the Netherlands Organization for Scientific Research (NWO) (grants 700.26.121 and 700.10.443 to M.B.) and by the European Community’s Seventh Framework Program, BioNMR project, contract number 211800, and the FP7 e-Infrastructure project WeNMR (contract no. 261572, www.wenmr.eu). We would like to thank Dieter Oesterhelt (Martinsried) for informing us that N. pharaonis can grow with acetate as sole carbon source. Initial work of J. Sauermann on the extraction of N. pharaonis lipids is gratefully acknowledged.
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