Anticipate, Target and Characterize: MS²-anticipated C-glycosylflavones from Erythrococca anomala

Abstract

We herein report on the first chemical assessment of Erythrococca anomala (Juss. ex Poir.) Prain (Euphorbiaceae), a genus that was – to the best of our knowledge – not studied yet from a phytochemical perspective. A molecular networking strategy was implemented to rapidly identify the known specialized metabolites from untargeted MS/MS analyses of E. anomala leaves ethanolic extract. This strategy allowed for the identification of diverse C-glycosyl flavones and a cursory examination of MS/MS spectra could extend the GNPS-provided annotation to pinpoint the structural novelty of further derivatives. The isolation of the sought-after structures could be streamlined based on MS-guidance and their structures, determined through extensive NMR analyses, displayed structural features in line with MS²-based predictions. Anticipating sharp structural features at an early stage of the dereplication process through a critical assessment of the tandem mass spectrometric landmarks was essential to embark on the isolation of the newly reported structures owing to the elevated number of flavonoid glycosides isomers thereof formerly known, which would have deterred us from isolating them without the support of additional tandem mass spectrometric information. The isolation of the main components of the ethanolic extract completed the currently provided chemical report on E. anomala, also resulting in the description of a new phenylethanoid derivative (3) and of a new orcinol-based dimer (4). Anomaloflavone (1) exhibit significant activities with minimal inhibitory concentration values of 25 µg/mL against Staphylococcus aureus and Mycobacterium smegmatis while failing to exert an antibacterial activity against Pseudomonas aeruginosa, while being devoid of cytotoxicity against SiHa cells.

Characterization of Corn Silk Extract Using HPLC/HRMS/MS Analyses and Bioinformatic Data Processing

“…Pilon et al (2019) showed that the O -glycosylated flavonoid compounds can be well characterized with molecular networking [ 42 ]. Kouamé et al (2021) used a molecular network approach to cluster C -glycosylated flavones and annotate them [ 43 ].…”