Based on network pharmacology methods and molecular docking technology, the targets of action of tauroursooxycholic acid (TUDCA) were predicted using the Swiss Target Prediction database. In addition, the potential TUDCA anti-inflammatory targets were obtained via mapping with antiinflammatory targets in the Genecards database. Protein-protein interactions (PPI) and ingredient-targetpathway (ITP) networks were constructed using the STRING database and Cytoscape software. The GO and KEGG enrichment analysis of potential targets were carried out via the David database, and the combination of TUDCA with the key targets were verified via molecular docking. The network showed that 81 targets were involved in the positive regulation of transcription by RNA polymerase II promoter, signal transduction, protein phosphorylation and another 259 biological processes. This highlighted the adjustment of 61 signaling pathways, such as cancer-related pathways, PI3K-Akt, and cAMP. Three key anti-inflammatory targets, MAPK3, SRC and EGFR, were screened using network analysis. The results from the molecular docking analysis showed that the TUDCA molecule had good binding activities with the three key targets. The study also found that TUDCA exhibited multi-target and multi-pathway characteristics, and preliminary explorations indicated anti-inflammatory mechanisms.
Background: Non-steroidal anti-inflammatory drugs, such as aspirin, have achieved good results in relation to treating inflammation, but these drugs are often accompanied by side effects. Tauroursodeoxycholic acid (TUDCA) has achieved good inflammation treatment results, with its unique ingredients, natural, safe and effective characteristics, and has therefore become a widely used anti-inflammatory drug.
Objective: To explore the anti-inflammatory mechanism of TUDCA and lay a foundation for the further development of TUDCA anti-inflammatory drugs.
Methods: Based on network pharmacology methods and molecular docking technology, the targets of action of tauroursooxycholic acid (TUDCA) were predicted using the Swiss Target Prediction database. In addition, the potential TUDCA anti-inflammatory targets were obtained via mapping with antiinflammatory targets in the Genecards database. Protein-protein interactions (PPI) and ingredient-targetpathway (ITP) networks were constructed using the STRING database and Cytoscape software. The GO and KEGG enrichment analysis of potential targets was carried out via the David database, and the combination of TUDCA with the key targets was verified via molecular docking.
Results: The network showed that 81 targets were involved in the positive regulation of transcription by RNA polymerase II promoter, signal transduction, protein phosphorylation and another 259 biological processes. This highlighted the adjustment of 61 signaling pathways, such as cancer-related pathways, PI3K-Akt, and cAMP. Three key anti-inflammatory targets, MAPK3, SRC and EGFR, were screened using network analysis. The results from the molecular docking analysis showed that the TUDCA molecule had good binding activities with the three key targets.
Conclusion: The study also found that TUDCA exhibited multi-target and multi-pathway characteristics, and preliminary explorations indicated anti-inflammatory mechanisms.
Keywords: TUDCA, Anti-inflammatory, Network pharmacology, Molecular docking, Mechanism of action, Biological process.