Mechanism of Callerya nitida var.hirsutissima in treatment of breast cancer based on network pharmacology / 中国药理学通报
Chinese Pharmacological Bulletin
; (12): 767-775, 2022.
Article
en Zh
| WPRIM
| ID: wpr-1014101
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WPRO
ABSTRACT
Aim To explore the mechanism of action of the active ingredients of Callerya nitida var.hirsutissima corresponding to the target gene in the treatment of triple-negative breast cancer(TNBC), using network pharmacology, molecular docking technology and in vitro experimental verification.Methods Based on literature research and combined with database screening, the main active components of Callerya nitida var.hirsutissima and the related targets of TNBC were obtained.Intersection genes were found to construct a protein interaction(PPI)network diagram, and core targets were screened according to the size of the correlation.A core target interaction network model of "Traditional Chinese Medicine-Ingredients-Targets-Disease" was constructed.The intersection targets were analyzed for gene GO function and KEGG pathway enrichment analysis.Finally, molecular docking and in vitro experimental verification of the selected components and the target were carried out.Results A total of 38 active components of Callerya nitida var.hirsutissima were collected, as well as 388 related potential targets, 3 919 TNBC targets, and 277 Callerya nitida var.hirsutissima therapeutic targets for TNBC.It mainly acted on multiple targets such as PIK3R1, PIK3CA, MAPK1, AKT1, SRC, etc.In in vitro experiments, it could be seen that the chloroform fraction of Callerya nitida var.hirsutissima and the monomer compounds luteolin and betulin had certain inhibitory effects on cell proliferation.All groups could inhibit the expression of VEGFA, AKT, PIK3CA, CDK1, CDK4 within the range of administration concentration.Conclusions Based on network pharmacology and molecular docking methods, this study explores the possible targets and signaling pathways of Callerya nitida var.hirsutissima in the treatment of TNBC, and conducts in vitro verification experiments to further verify the prediction of network pharmacology.
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Zh
Revista:
Chinese Pharmacological Bulletin
Año:
2022
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Article