Targeted Isolation of Prenylated Flavonoids from Paulownia tomentosa Fruit Extracts via AI-Guided Workflow Integrating LC-UV-HRMS/MS
This study highlights the combination of machine learning with analytical techniques to streamline natural product discovery via MS/MS and AI-guided pre-selection, efficient prioritization, and characterization of prenylated flavonoids, paving the way for a broader application in metabolomics and further exploration of prenylated constituents across diverse plant species.
Authors
- Barbora Valkova
- Lenka Molčanová (ORCID: https://orcid.org/0000-0002-6005-5033)
- Tomáš Rýpar (ORCID: https://orcid.org/0000-0003-4817-2250)
- Bernhard Seidl (ORCID: https://orcid.org/0000-0003-1022-5388)
- Karel Šmejkal (ORCID: https://orcid.org/0000-0002-4336-7924)
- Rainer Schuhmacher (ORCID: https://orcid.org/0000-0002-7520-4943)
- Christoph Bueschl (ORCID: https://orcid.org/0000-0003-1729-9785)
- Ema Hromadkova
Institutions
- Konrad Lorenz Institute for Evolution and Cognition Research (AT)
- Masaryk University (CZ)
- Mendel University in Brno (CZ)
Publication Details
- Journal
- Metabolites
- Published
- 2025-09-17
- DOI
- https://doi.org/10.3390/metabo15090616
- Primary Topic
- Bioactive natural compounds
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universität für Bodenkultur Wien