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Magnetically Induced Alignment of Natural Products for Stereochemical Structure Determination via NMR.

ABSTRACT: Anisotropic NMR has gained increasing popularity to determine the structure and specifically the configuration of small, flexible, non-crystallizable molecules. However, it suffers from the necessity to dissolve the analyte in special media such as liquid crystals or polymer gels. Generally, small degrees of alignment are also caused by an anisotropic magnetic susceptibility of the molecule, for example, induced by aromatic moieties. For this mechanism, the alignment can be predicted via density functional theory. Here we show that both residual dipolar couplings and residual chemical shift anisotropies can be acquired from natural products without special sample preparation using magnetically induced alignment. On the two examples of the novel natural product gymnochrome?G and the alkaloid strychnine, these data, together with the predicted alignment, yield the correct configuration with high certainty.

SUBMITTER: Karschin N

PROVIDER: S-EPMC7540557 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Magnetically Induced Alignment of Natural Products for Stereochemical Structure Determination via NMR.

Karschin Niels N Wolkenstein Klaus K Griesinger Christian C

Angewandte Chemie (International ed. in English) 20200603 37

Anisotropic NMR has gained increasing popularity to determine the structure and specifically the configuration of small, flexible, non-crystallizable molecules. However, it suffers from the necessity to dissolve the analyte in special media such as liquid crystals or polymer gels. Generally, small degrees of alignment are also caused by an anisotropic magnetic susceptibility of the molecule, for example, induced by aromatic moieties. For this mechanism, the alignment can be predicted via density ...[more]

PMID: 32364661

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Project description:Diffusion-ordered NMR spectroscopy (DOSY) can be used to analyze mixtures of compounds since resonances deriving from different compounds are distinguished by their diffusion coefficients (D). Previously, DOSY has mostly been used for organometallic and polymer analysis, we have now applied DOSY to investigate diffusion coefficients of structurally diverse organic compounds such as natural products (NP). The experimental Ds derived from 55 diverse NPs has allowed us to establish a power law relationship between D and molecular weight (MW) and therefore predict MW from experimental D. We have shown that D is also affected by factors such as hydrogen bonding, molar density and molecular shape of the compound and we have generated new models that incorporate experimentally derived variables for these factors so that more accurate predictions of MW can be calculated from experimental D. The recognition that multiple physicochemical properties affect D has allowed us to generate a polynomial equation based on multiple linear regression analysis of eight calculated physicochemical properties from 63 compounds to accurately correlate predicted D with experimental D for any known organic compound. This equation has been used to calculate predicted D for 217 043 compounds present in a publicly available natural product database (DEREP-NP) and to dereplicate known NPs in a mixture based on matching of experimental D and structural features derived from NMR analysis with predicted D and calculated structural features in the database. These models have been validated by the dereplication of a mixture of two known sesquiterpenes obtained from Tasmannia xerophila and the identification of new alkaloids from the bryozoan Amathia lamourouxi. These new methodologies allow the MW of compounds in mixtures to be predicted without the need for MS analysis, the dereplication of known compounds and identification of new compounds based solely on parameters derived by DOSY NMR.

Dataset Information

Magnetically Induced Alignment of Natural Products for Stereochemical Structure Determination via NMR.

Publications

Magnetically Induced Alignment of Natural Products for Stereochemical Structure Determination via NMR.

Similar Datasets

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