A fractionation methodology aimed at the metabolomic mining of new phytoconstituents for the widely used botanical, wild yam (Dioscorea villosa), makes use of 1D qHNMR and 2D NMR profiles along the preparative fractionation pathway. This quantifiable and structural guidance led to the isolation of 14 diarylheptanoids (1-14), including five new compounds (1-5) with a tetrahydropyrano core skeleton. The structures, including the absolute configurations of both new and previously known diarylheptanoids, were assigned by a combination of HRESIMS, 1D and 2D NMR, (1)H iterative full spin analysis (HiFSA), and Mosher's ester method. The isolation yields were consistent with yields predicted by qHNMR, which confirms the (semi)quantifiable capabilities of NMR-based preparative metabolomic mining. The qHNMR-aided approach enabled the identification of new and potentially significant chemical entities from a small fraction of the plant extract and, thereby, facilitated the characterization of the residual complexity of the D. villosa secondary metabolome. LC-MS profiling of different D. villosa accessions further confirmed that the diarylheptanoids represent genuine secondary metabolites, which can serve as a new class of markers for botanical integrity analysis of D. villosa.
A fractionation methodology aimed at the metabolomic mining of new phytoconstituents for the widely used botanical, wild yam (Dioscorea villosa), makes use of n class="Chemical">1D qHNMR and 2DNMR profiles along the preparative fractionation pathway. This quantifiable and structural guidance led to the isolation of 14 diarylheptanoids (1-14), including five new compounds (1-5) with a tetrahydropyrano core skeleton. The structures, including the absolute configurations of both new and previously known diarylheptanoids, were assigned by a combination of HRESIMS, 1D and 2DNMR, (1)H iterative full spin analysis (HiFSA), and Mosher's ester method. The isolation yields were consistent with yields predicted by qHNMR, which confirms the (semi)quantifiable capabilities of NMR-based preparative metabolomic mining. The qHNMR-aided approach enabled the identification of new and potentially significant chemical entities from a small fraction of the plant extract and, thereby, facilitated the characterization of the residual complexity of the D. villosa secondary metabolome. LC-MS profiling of different D. villosa accessions further confirmed that the diarylheptanoids represent genuine secondary metabolites, which can serve as a new class of markers for botanical integrity analysis of D. villosa.
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