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A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Artemisia annua on the Treatment of Hepatocellular Carcinoma
OBJECTIVE: To investigate the potential active ingredients and underlying mechanisms of Artemisia annua (AA) on the treatment of hepatocellular carcinoma (HCC) based on network pharmacology. METHODS: In the present study, we used a network pharmacological method to predict its underlying complex mec...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7920725/ https://www.ncbi.nlm.nih.gov/pubmed/33688369 http://dx.doi.org/10.1155/2021/8947304 |
Sumario: | OBJECTIVE: To investigate the potential active ingredients and underlying mechanisms of Artemisia annua (AA) on the treatment of hepatocellular carcinoma (HCC) based on network pharmacology. METHODS: In the present study, we used a network pharmacological method to predict its underlying complex mechanism of treating HCC. First, we obtained relative compounds of AA based on the traditional Chinese medicine systems pharmacology (TCMSP) database and collected potential targets of these compounds by target fishing. Then, we built HCC-related targets target by the oncogenomic database of hepatocellular carcinoma (OncoDB.HCC) and biopharmacological network (PharmDB-K) database. Based on the matching results between AA potential targets and HCC targets, we built a protein-protein interaction (PPI) network to analyze the interactions among these targets and screen the hub targets by topology. Furthermore, the function annotation and signaling pathways of key targets were performed by Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis using DAVID tools. Finally, the binding capacity between active ingredients and key targets was validated by molecular docking. RESULTS: A total of 19 main active ingredients of AA were screened as target prediction; then, 25 HCC-related common targets were seeked out via multiple HCC databases. The areas of nodes and corresponding degree values of EGFR, ESR1, CCND1, MYC, EGF, and PTGS2 were larger and could be easily found in the PPI network. Furthermore, GO and KEGG enrichment analysis showed that these key targets were significantly involved in multiple biological processes and pathways which participated in tumor cell proliferation, apoptosis, angiogenesis, tumor invasion, and metastasis to accomplish the anti-HCC activity. The molecular docking analysis showed that quercetin could stably bind to the active pocket of EGFR protein 4RJ5 via LibDock. CONCLUSION: The anticancer effects of AA on HCC were predicted to be associated with regulating tumor cell proliferation, apoptosis, angiogenesis, tumor invasion, and metastasis via various pathways such as the EGFR signaling pathway, ESR1 signaling pathway, and CCND1 signaling pathway. It is suggested that AA might be developed as a broad-spectrum antitumor drug based on its characteristics of multicomponent, multipath, and multitarget. |
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