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Classification of Flavonoid Metabolomes via Data Mining and Quantification of Hydroxyl NMR Signals.

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Utilizing the distinct HMBC crossed-peak patterns of lower-field range (LFR; 11.80‒14.20 ppm) hydroxyl singlets, presented NMR methodology characterizes flavonoid metabolomes both qualitatively and quantitatively. It enables simultaneous classification of the… Click to show full abstract

Utilizing the distinct HMBC crossed-peak patterns of lower-field range (LFR; 11.80‒14.20 ppm) hydroxyl singlets, presented NMR methodology characterizes flavonoid metabolomes both qualitatively and quantitatively. It enables simultaneous classification of the structural types of 5-OH flavonoids and biogenetically related 2'-OH chalcones, as well as quantifica-tion of individual metabolites from 1H NMR spectra, even in complex mixtures. Initially, metabolite-specific LFR 1D 1H and 2D HMBC patterns were established via literature mining and experimental data interpretation, demonstrating that LFR HMBC patterns encode the different structural types of 5-OH flavonoids/2'-OH chalcones. Taking advantage of the sim-plistic multiplicity of the H,H-uncoupled LFR 5-/2'-OH singlets, individual metabolites could subsequently be quantified by peak fitting quantitative 1H NMR (PF-qHNMR). Metabolomic analysis of enriched fractions from three medicinal licorice (Glycyrrhiza) species established proof-of-concept for distinguishing three major structural types and eight subtypes in bio-medical applications. The method identified fifteen G. uralensis (GU) phenols from the six possible subtypes of 5,7-diOH (iso)flav(an)ones with 6-, 8-, and non-prenyl substitution, including the new 6-prenyl-licoisoflavanone (1) and two previously unknown cpds (4 and 7). Relative (100%) qNMR established quantitative metabolome patterns suitable for species discrim-ination and plant metabolite studies. Absolute qNMR with combined external and internal (solvent) calibration (ECIC) iden-tified and quantified 158 GU metabolites. HMBC-supported qHNMR analysis of flavonoid metabolomes ("flavonomics") empowers the exploration of structure-abundance-activity relationships of designated bioactives. Its ability to identify and quantify numerous metabolites simultaneously and without identical reference materials opens new avenues for natural product discovery and botanical quality control.

Keywords: metabolomes via; flavonoid metabolomes; structural types; hydroxyl; classification flavonoid

Journal Title: Analytical chemistry
Year Published: 2020

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