Non‐Uniform Sampling and J‐UNIO Automation for Efficient Protein NMR Structure Determination |
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| Authors: | Dr Tatiana Didenko Dr Andrew Proudfoot Dr Samit Kumar Dutta Dr Pedro Serrano Prof?Dr Kurt Wüthrich |
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| Institution: | 1. Department of Integrative Structural and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037 (USA) http://www.jcsg.org;2. Joint Center for Structural Genomics, La Jolla, CA 92037 (USA), Fax: (+1)?858‐784‐8014;3. GPCR‐Network, 3430 S. Vermont Ave., TRF 105, Los Angeles, CA 90089‐3301 (USA), Fax: (+1)?858‐784‐8014 http://gpcr.usc.edu;4. Skaggs Institute for Chemical Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037 (USA), Fax: (+1)?858‐784‐8014 |
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| Abstract: | High‐resolution structure determination of small proteins in solution is one of the big assets of NMR spectroscopy in structural biology. Improvements in the efficiency of NMR structure determination by advances in NMR experiments and automation of data handling therefore attracts continued interest. Here, non‐uniform sampling (NUS) of 3D heteronuclear‐resolved 1H,1H]‐NOESY data yielded two‐ to three‐fold savings of instrument time for structure determinations of soluble proteins. With the 152‐residue protein NP_372339.1 from Staphylococcus aureus and the 71‐residue protein NP_346341.1 from Streptococcus pneumonia we show that high‐quality structures can be obtained with NUS NMR data, which are equally well amenable to robust automated analysis as the corresponding uniformly sampled data. |
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| Keywords: | automated data analysis compressed sensing J‐UNIO structure determination protocol NMR spectroscopy proteins |
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