Profiling Class-Wide Bioactivities of Flavonoids While Minimizing Compound-Specific Effects Using an Equimolar Mixture Strategy
Flavonoids share a C<sub>6</sub>-C<sub>3</sub>-C<sub>6</sub> core yet vary in side-chain decorations. Here, we tested whether an equimolar cross-subclass mixture could serve as a "class reference" by capturing class-wide bioactivities and diluting outlier effects. Twenty flavonoids across five subclasses were blended and tested alongside five single-flavonoid representatives─luteolin, quercetin, naringenin, EGCG, and genistein. In rat PC12 pheochromocytoma cells, the flavonoid mixture enhanced NGF-induced neuronal differentiation and activated reporters of neurofilament, cAMP, NF-κB, and antioxidant response elements, paralleling the effects of the representatives and indicating conserved neurotrophic activity. All flavonoidic samples were nontoxic at 5 μM but became toxic at 50 μM, except naringenin. Notably, luteolin-induced mitochondrial depolarization and cytotoxicity were buffered as the proportion of other flavonoids increased. The mixture bound amyloid-β<sub>1-42</sub> ∼10× more weakly than EGCG, evidencing dilution of a specific interaction. This proof-of-concept study offers tools and a framework to map flavonoids' functions in nutritional and pharmacological contexts.
Authors
- Meixia Yang (ORCID: https://orcid.org/0009-0001-9910-6133)
- Aibing Wang (ORCID: https://orcid.org/0000-0002-0470-8220)
- Karl Wah Keung Tsim (ORCID: https://orcid.org/0000-0003-4808-1674)
- Alex Xiong Gao
- Jin Gao (ORCID: https://orcid.org/0000-0003-3199-6632)
- Manman Sun (ORCID: https://orcid.org/0000-0003-2168-7473)
- Farkhod Eshboev (ORCID: https://orcid.org/0000-0003-3054-6111)
- Zhengqi Wang
- Tina Ting‐Xia Dong
Institutions
- Chinese Academy of Sciences (CN)
- Hong Kong University of Science and Technology (HK)
- Hefei Institutes of Physical Science (CN)
- HKUST Shenzhen Research Institute (CN)
- High Magnetic Field Laboratory (CN)
Publication Details
- Journal
- Journal of Agricultural and Food Chemistry
- Published
- 2025-10-23
- DOI
- https://doi.org/10.1021/acs.jafc.5c09562
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00