Targeted Isolation of Prenylated Flavonoids from <i>Paulownia tomentosa</i> Fruit Extracts via AI-Guided Workflow Integrating LC-UV-HRMS/MS.

ABSTRACT:

Objectives

This study presents a versatile, AI-guided workflow for the targeted isolation and characterization of prenylated flavonoids from Paulownia tomentosa (Thunb.) Steud. (Paulowniaceae).

Methods

The approach integrates established extraction and chromatography-based fractionation protocols with LC-UV-HRMS/MS analysis and supervised machine-learning (ML) custom-trained classification models, which predict prenylated flavonoids from LC-HRMS/MS spectra based on the recently developed Python package AnnoMe (v1.0).

Results

The workflow effectively reduced the chemical complexity of plant extracts and enabled efficient prioritization of fractions and compounds for targeted isolation. From the pre-fractionated plant extracts, 2687 features were detected, 42 wer

SUBMITTER: Rypar T 

PROVIDER: S-EPMC12471768 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature