Network pharmacology-based research on the effect of Scutellaria baicalensis on osteosarcoma and the underlying mechanism.
Lijuan ZhangYushi TianJingbo WangShuangjiao DengHeng FanPublished in: Medicine (2023)
To explore the anti-tumor effects of Scutellaria baicalensis on osteosarcoma and its mechanism. Network pharmacology and molecular docking techniques were applied to investigate the effect and mechanism of Scutellaria baicalensis on osteosarcoma (OS). We analyzed the protein-protein interaction (PPI) network for potential targets of Scutellaria baicalensis for treating osteosarcoma and identified hub targets. We used KM curves to screen for hub targets that could effectively prolong the survival time of OS patients. We systematically performed gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis of the Scutellaria baicalensis potential targets and predicted the Scutellaria baicalensis molecular mechanism and function in treating osteosarcoma. Through molecular docking, the binding process between the hub targets, which could prolong the survival time of sarcoma patients, and Scutellaria baicalensis was simulated. PPI network analysis of potential therapeutic targets discriminated 12 hub targets. The KM curves of the hub targets showed that upregulation of RXRA, RELA, ESR1, TNF, IL6, IL1B, and RB1 expression, and downregulation of MAPK1, VEGFA, MAPK14, CDK1, and PPARG expression were effective in improving the 5-year survival rate of OS patients. GO and KEGG enrichment demonstrated that Scutellaria baicalensis regulated multiple signaling pathways of OS. Molecular docking results indicated that Scutellaria baicalensis could bind freely to the above hub target, which could prolong the survival time of sarcoma patients. Scutellaria baicalensis acted on osteosarcoma by regulating a signaling network formed by hub targets connecting multiple signaling pathways. Scutellaria baicalensis appears to have the potential to serve as a therapeutic drug for osteosarcoma and to prolong the survival of OS patients.
Keyphrases
- molecular docking
- end stage renal disease
- newly diagnosed
- signaling pathway
- ejection fraction
- chronic kidney disease
- network analysis
- prognostic factors
- poor prognosis
- emergency department
- protein protein
- molecular dynamics simulations
- oxidative stress
- climate change
- cell proliferation
- pi k akt
- patient reported outcomes
- estrogen receptor
- patient reported
- genome wide analysis