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Application of anisotropic NMR parameters to the confirmation of molecular structure.

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Griesinger,  C.
Department of NMR Based Structural Biology, MPI for biophysical chemistry, Max Planck Society;

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Citation

Liu, Y., Navarro-Vázquez, A., Gil, R. R., Griesinger, C., Martin, G. E., & Williamson, R. T. (2019). Application of anisotropic NMR parameters to the confirmation of molecular structure. Nature Protocols, 14(1), 217-247. doi:10.1038/s41596-018-0091-9.


Cite as: http://hdl.handle.net/21.11116/0000-0002-AFF4-6
Abstract
The use of anisotropic NMR data, such as residual dipolar couplings (RDCs) and residual chemical shift anisotropies (RCSAs), has emerged as a powerful technique for structural characterization of organic small molecules. RDCs typically report the relative orientations of different 1H-13C bonds; RCSAs report the relative orientations of different carbon chemical shielding tensors and hence are more useful for proton-deficient molecules. This information is complementary to that obtained from conventional NMR data such as J couplings, isotropic chemical shifts, and nuclear Overhauser effects (NOEs)/rotational frame nuclear Overhauser effects (ROEs). Obtaining anisotropic NMR data requires the creation of an anisotropic sample environment through an alignment medium. Here, we focus on the use of compressed or stretched polymeric gels as two different but fundamentally equivalent methods for introducing sample anisotropy. Protocols are provided for the synthesis of the chloroform-compatible poly(methyl methacrylate) and dimethyl sulfoxide (DMSO)-compatible poly(2-hydroxyethyl methacrylate) gels and sample setup with a preparation time of 2-3 d. The bond-specific RDC data and the atom-specific RCSA data are extracted as changes in 1H-13C couplings and 13C chemical shifts, respectively, between two measurements under different alignment conditions, with a total experimental time of 0.5-4 d. NMR data acquisition and important considerations are described in detail. We also provide step-by-step procedures for the density functional theory (DFT) calculations involved and data analysis using the commercial software MSpin. We use three example compounds, namely cryptospirolepine (505 Da), retrorsine (351 Da), and estrone (270 Da), to demonstrate some important aspects of the workflow, such as input data preparation, handling of structural flexibility, and RCSA data correction when necessary.