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Network Pharmacology and Molecular Docking Analysis on Molecular Targets and Mechanisms of Fei Jin Sheng Formula in the Treatment of Lung Cancer

[ Vol. 29 , Issue. 14 ]


Yun-Chao Zhang, Wen-Cang Gao, Wei-Jian Chen, De-Xiang Pang, Da-Yu Mo* and Min Yang*   Pages 1121 - 1134 ( 14 )


Background: Fei Jin Sheng Formula (FJSF) is widely used in clinical treatment of lung cancer. But the underlying active ingredients and mechanisms are unclear.

Objective: To investigate the active components and functional mechanisms of FJSF in treating lung cancer using a network pharmacology approach and molecular docking combined with vitro experiments

Methods: Based on the TCMSP and related literature, the chemical components of related herbs in FJSF were collected. The active components of FJSF were screened by ADME parameters, and the targets were predicted by the Swiss Target Prediction database. The "drug-active ingredient-target" network was constructed by Cytoscape. Disease-related targets of lung cancer were acquired from GeneCards, OMIM, and TTD databases. Then drug-disease intersection target genes were obtained through the Venn tool. GO analysis and KEGG pathway enrichment analysis were performed via the Metascape database. Cytoscape was used to construct a PPI network and perform topological analysis. Kaplan-Meier Plotter was used to analyze the relationship between DVL2 and the prognosis of lung cancer patients. xCell method was used to estimate the relationship between DVL2 and immune cell infiltration in lung cancer. Molecular docking was performed by AutoDockTools-1.5.6. The results were verified by experiments in vitro.

Results: FJSF contained 272 active ingredients and 52 potential targets for lung cancer. GO enrichment analysis is mainly related to cell migration and movement, lipid metabolism, and protein kinase activity. KEGG pathway enrichment analysis mainly involves PI3K-Akt, TNF, HIF-1, and other pathways. Molecular docking shows that the compound Xambioona, quercetin and methyl palmitate in FJSF has a strong binding ability with NTRK1, APC, and DVL2. Analysis of the data in UCSC to analyze the expression of DVL2 in lung cancer shows that DVL2 was overexpressed in lung adenocarcinoma tissues. Kaplan-Meier analysis shows that the higher DVL2 expression in lung cancer patients was associated with poorer overall survival and poorer survival in stage I patients. It was negatively correlated with the infiltration of various immune cells in the lung cancer microenvironment. Vitro Experiment showed that Methyl Palmitate (MP) can inhibit the proliferation, migration, and invasion of lung cancer cells, and its mechanism of action may be to downregulate the expression of DVL2.

Conclusion: FJSF may play a role in inhibiting the occurrence and development of lung cancer by downregulating the expression of DVL2 in A549 cells through its active ingredient Methyl Palmitate. These results provide scientific evidence for further investigations into the role of FJSF and Methyl Palmitate in the treatment of lung cancer.


Fei Jin Sheng formula, network pharmacology, molecular docking, methyl palmitate, DVL2, prognosis, immune infiltration.


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