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Integrated molecular networking and AI modeling reveal xanthine oxidase-inhibitory flavonoids from the edible plant Gnaphalium affine D. Don.

Created on 13 Jul 2026

Authors

Sen Mei, Xinchao He, Jin Qian, Lijuan Rao, Jiajing Liao, Chen Wang, Tao Wu, Haowei Fan, Guiming Fu, Yin Wan

Published in

Food & function. Jul 13, 2026. Epub Jul 13, 2026.

Abstract

Hyperuricemia, a diet-related metabolic disorder, is primarily managed by targeting xanthine oxidase (XOD), the central enzyme responsible for uric acid production. Conventional screening of natural XOD inhibitors often struggles to deconvolute complex food-derived metabolomes. Here, we establish an integrated framework coupling data-driven feature-based molecular networking (FBMN) with AI-assisted ColabFold structural modeling for the rapid discovery of XOD-inhibitory flavonoids. Applied to the edible plant Gnaphalium affine D. Don, this approach enabled the high-resolution annotation of 65 flavonoids, including 56 previously unreported in this species. Kaempferol 3,4'-diglucoside emerged as the most potent candidate, exhibiting strong structural complementarity to the XOD catalytic center (docking interaction energy = -68.1 kcal mol-1) and potent in vitro inhibitory activity (IC50 = 14.1 ± 0.8 μM). Structural analysis further revealed a multimodal binding mechanism, in which di-glycosylation enhances binding stability and affinity, providing new insights into the structure-activity relationships of flavonoids. Beyond validating G. affine as a functional dietary source, this study offers a scalable, data-driven strategy for the prioritization of potential candidates that may inform the future development of mechanism-oriented functional food ingredients from complex food matrices.

PMID:
42439056
Bibliographic data and abstract were imported from PubMed on 13 Jul 2026.

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