Prediction of potential targets of aloe-emodin in the treatment of hepatocellular carcinoma using network pharmacology combined with bioinformatics.

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作者:Wei Jinlong, Chen Haosong, Xu Maoqi, Zhang Zhenglin, Wang Jin, Jiang Wen, Zhou Weiguo, Xiong Maoming
BACKGROUND: Hepatocellular carcinoma is one of the most common and malignant tumors worldwide. Although aloe-emodin (AE), a pure natural drug, can effectively kill hepatocellular carcinoma cells, its internal molecular mechanism has not been fully elucidated. In this study, the anti-hepatocellular carcinoma targets of AE were predicted using network pharmacology and bioinformatics. METHODS: The differentially expressed genes between hepatocellular carcinoma and normal tissues were first identified and then further intersected with the potential pharmacological target genes of AE for subsequent analysis. Moreover, the potential targets of AE were enriched and analyzed to identify potential downstream pathways. The binding ability and interaction between the above drug targets and AE were analyzed by molecular docking. The prognostic model of hepatocellular carcinoma was subsequently constructed via univariate Cox regression analysis, LASSO regression analysis and multivariate Cox regression analysis. Finally, the potential targets that can stably bind to AE were further screened through molecular dynamics simulation. Finally, we validated the potential utility of AE in treating hepatocellular carcinoma through in vitro experiments. RESULTS: After 90 target genes related to AE were crossed with hepatocellular carcinoma differential genes, 13 cross genes were obtained. The above 13 genes might act on hepatocellular carcinoma through the following pathways: p53 signaling pathway, cell cycle, cellular sense, mismatch repair, apoptosis-multiple specifications, base example repair and DNA replication. Molecular docking revealed that the combination of the BAX, FASN, CDK1, PCNA, CLIC1, VWF, RAN, FOXM1, TGM3, CANT1, and NSMCE2 proteins with AE was relatively stable. A 4-gene prognostic model was further constructed. The area under the curve (AUC) values of the 1-year, 3-year and 5-year survival rates from the ROC curve were 0.809, 0.673 and 0.641, respectively. Molecular dynamics analysis revealed that CDK1 and PCNA were the most stable binding targets among the above proteins. CCK8 and wound healing assays revealed that AE inhibited the proliferation and migration of hepatocellular carcinoma cells at increasing concentrations. Western blot experiments revealed that AE achieved therapeutic effects on hepatocellular carcinoma by promoting apoptosis of hepatocellular carcinoma cells. CONCLUSIONS: Based on network pharmacology, bioinformatics, molecular dynamics simulation, and in vitro experimental verification, we found that AE achieved a therapeutic effect on hepatocellular carcinoma by promoting apoptosis of hepatocellular carcinoma cells.

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