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Informed Feature-Based Molecular Networking as a Complementary Approach to Identify Bioactive Phyllobilins in Senescent Plant Extracts

Christian A. Elvert, Johanna K. S. Lückenbach, Simone Moser, Fabian Hammerle, Cornelia A. Karg

原始摘要(英文原文)· Original abstract
High Resolution Image Download MS PowerPoint Slide Phyllobilins are chlorophyll-derived metabolites that represent a distinct class of bioactive natural products. Although widespread in nature, they remain largely underexplored in phytochemical research. In this study, we present a workflow for the dereplication and identification of phyllobilins in complex plant extracts. The approach combines RP-MPLC fractionation, UHPLC-VWD-HRMS 2 analysis, antioxidant activity testing, and data analysis using feature-based molecular networking. Methanolic extracts of senescent Echinacea purpurea leaves, known to be rich in structurally diverse chlorophyll metabolites, were used to generate experimental MS 2 spectra for a set of phylloxanthobilins, which were subsequently uploaded to the GNPS community database. The workflow was then applied to senescent Salvia officinalis leaves, a pharmaceutically important plant with an unknown phyllobilin profile, leading to the annotation of several phylloxanthobilins. One metabolite featuring a malonic acid ester moiety was isolated and structurally confirmed using 1D- and 2D-NMR spectroscopy. Future applications of this workflow may enable the systematic annotation and prioritization of previously overlooked phyllobilins across diverse plant species, addressing a critical gap in the analytical profiling of bioactive plant extracts. By leveraging public MS 2 spectral libraries and network-based data analysis, it offers a scalable tool to address a long-standing blind spot of natural product research.
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Informed Feature-Based Molecular Networking as a Complementary Approach to Identify Bioactive Phyllobilins in Senescent Plant Extracts — 科研速览 Science Skim