Mechanisms of Resveratrol in Osteoarthritis Treatment and Potential Nephrotoxicity Risks
To investigate the potential mechanism of action of resveratrol in the treatment of osteoarthritis using a network pharmacology and molecular docking approach. The primary active components and associated targets of resveratrol were collected from PubChem, and potential targets were predicted using the Swiss Target Prediction database. Osteoarthritis-related target genes were retrieved from GeneCards, the Online Mendelian Inheritance in Man (OMIM) database, and the Therapeutic Target Database (TTD). Core components and targets were identified using Venny 2.1.0 and Cytoscape 3.10.1 to obtain intersecting targets of resveratrol and osteoarthritis. Enrichment analysis was conducted using the DAVID database, and molecular docking was employed to validate the interactions between key components and targets. A total of 69 active components of resveratrol and 52 intersecting targets were analyzed, leading to the identification of PTGS2, EGFR, MMP9, SRC, RELA, ESR1, IGF1R, and AR as key targets for osteoarthritis. Enrichment analysis indicated that the mechanism of action may involve cAMP, MAPK, and microRNA signaling pathways. Molecular docking results confirmed strong binding interactions between the main components and these targets. Resveratrol may exert therapeutic effects in osteoarthritis by modulating cellular stress, adhesion, and phosphorylation processes through multiple signaling pathways, including cAMP, MAPK, and microRNA-related pathways.
Authors
- Yu Sun (ORCID: https://orcid.org/0000-0002-4407-9123)
- Haiyang Kou
- Yunling Xu
- Shili Yang (ORCID: https://orcid.org/0009-0009-4125-3323)
- Huaiquan Liu (ORCID: https://orcid.org/0000-0002-2394-1554)
- Li Lai (ORCID: https://orcid.org/0000-0002-5731-2705)
- Xinyan Zhang (ORCID: https://orcid.org/0000-0001-6269-3138)
- Bo Chen
Institutions
- Guiyang College of Traditional Chinese Medicine (CN)
- Guizhou University (CN)
Publication Details
- Journal
- Journal of Biochemical and Molecular Toxicology
- Published
- 2025-10-16
- DOI
- https://doi.org/10.1002/jbt.70562
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00