ArticleTzu chi medical journal
Exploration of the mechanism of tetramethoxyflavone in treating osteoarthritis based on network pharmacology and molecular docking.
Article in Tzu chi medical journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- A tri-target in silico analysis of Testolift: a nutraceutical formulation targeting aromatase, myostatin, and prolyl hydroxylase-2 in testosterone regulation and muscle performance.Scientific reports · 2026Article
- Network pharmacology analysis and cellular experiment validation of puerarin in attenuating TBI through suppression of ferroptosis.Scientific reports · 2026Article
- Melatonin Exerts Chondroprotective Effects Against Osteoarthritis by Promoting PI3K/AKT/FoxO3-Mediated Mitophagy.The Kaohsiung journal of medical sciences · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: This study aimed to explore the potential mechanisms of TMF (5,7,3',4'-tetramethoxyflavone) in treating osteoarthritis (OA) using network pharmacology and molecular docking. Materials and Methods: Databases including SwissTargetPrediction, BATMAN-TCM, PharmMapper, TargetNet, SuperPred, and SEA were utilized to screen the targets of TMF. "OA" was used as the disease keyword to predict OA-related genes through GeneCards, Therapeutic Target Database, PharmGKB, Online Mendelian Inheritance in Man, and Comparative Toxicogenomics Database. The Venn diagram was employed to identify the intersection of predicted targets between TMF and OA as potential targets for TMF in treating OA. The intersection targets were input into the STRING 12.0 online database to construct a protein-protein interaction (PPI) network and identify core targets. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Metascape V3.5 online database platform. Finally, molecular docking between TMF and core targets was conducted using AutoDockTools 1.5.6. Results: A total of 228 intersection targets for TMF treating OA were obtained, and PPI network analysis identified 5 core targets: STAT3, SRC, CTNNB1, EGFR, and AKT1. GO enrichment analysis yielded 2736 results, while KEGG analysis identified 203 pathways. Most elated GO and KEGG items of TMF in treating OA may include hormonal responses, antiviral and anticancer effects, anti-inflammation, phosphorus metabolism, phosphate metabolism, nitrogen compound responses, cancer-related pathways, PI3K-Akt signaling pathway, and MAPK signaling pathway. Molecular docking revealed good binding affinities between TMF and all core targets except STAT3. Conclusion: TMF might act on multiple targets and activate diverse pathways to intervene in OA, revealing the molecular processes involved in TMF treatment of OA.
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