
doi: 10.1002/jcb.28513
pmid: 30816612
AbstractRubia cordifolia L. is widely used in Asia and its antihepatoma effect has been proved by in vitro and in vivo experiments. However, there are few studies on its specific mechanism. In the present study, the network pharmacology method was used to construct the component/target/pathway molecular regulatory network for the antihepatoma effect of Rubia cordifolia L. to explore the effective components of Rubia cordifolia L. and its potential mechanism. The chemical components of Rubia cordifolia L. were identified through literature and databases, and the components were evaluated and screened by drug likeness and pharmacokinetic characteristics (ADMET). The targets of active components were predicted according to the reverse pharmacophore matching model. The hepatic carcinoma‐related genes were found in databases, and antihepatoma‐related gene targets were selected through comparison. The functions of target genes and related pathways were analyzed and screened using the Database for Annotation, Visualization and Integrated Discovery, and the component/target/pathways network of antihepatoma effect of Rubia cordifolia L. was constructed using Cytoscape software. Finally, 16 active compounds were screened from Rubia cordifolia L., and 39 gene targets, including AKT1, mitogen‐activated protein kinase 1, and epidermal growth factor receptor, were involved. Rubia cordifolia L. also affected the hepatitis B, phosphoinositide‐3‐kinase‐protein kinase B, and mitogen‐activated protein kinase signaling pathways. Many direct‐acting tumor‐related signaling pathways and indirect‐acting hepatitis pathways inhibit the generation of liver cancer. The present study provided a scientific basis for further elucidating the mechanism of Rubia cordifolia L. against liver cancer.
Carcinoma, Hepatocellular, Plant Extracts, Gene Expression Profiling, Liver Neoplasms, Rubia, Computational Biology, Antineoplastic Agents, Phytogenic, Gene Expression Regulation, Neoplastic, Biomarkers, Tumor, Humans, Gene Regulatory Networks
Carcinoma, Hepatocellular, Plant Extracts, Gene Expression Profiling, Liver Neoplasms, Rubia, Computational Biology, Antineoplastic Agents, Phytogenic, Gene Expression Regulation, Neoplastic, Biomarkers, Tumor, Humans, Gene Regulatory Networks
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