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Network-Based Pharmacological Study on the Mechanism of Guishao-Liujun Decoction in the Treatment of Gastric Cancer

Objective: The aim of the study was to use a network pharmacological method to examine the mechanism of Guishao-Liujun decoction against gastric cancer (GC). Methods: The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) and the Traditional Chinese Medicine Int...

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Detalles Bibliográficos
Autores principales: Qian, Xiaoqing, Zhang, Lingle, Xie, Feng, Cheng, Yingsheng, Cui, Daxiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294375/
https://www.ncbi.nlm.nih.gov/pubmed/35865953
http://dx.doi.org/10.3389/fphar.2022.937439
Descripción
Sumario:Objective: The aim of the study was to use a network pharmacological method to examine the mechanism of Guishao-Liujun decoction against gastric cancer (GC). Methods: The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) and the Traditional Chinese Medicine Integrated Database (TCMID) were used to obtain the chemical composition and targets of all the drugs of Guishao-Liujun decoction, and the targets of GC were screened using GeneCards and Online Mendelian Inheritance in Man (OMIM) databases. The obtained targets were imported into Cytoscape 3.7.2 software by using the R language to take the intersection for a Venn analysis to construct active ingredient target networks, and they were imported into the STRING database to construct protein–protein interaction (PPI) networks, with the BisoGenet plugin in Cytoscape 3.7.2 being used for analyzing network topology. On the potential target of Guishao-Liujun decoction for GC, gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed using the R-language bioconductor platform, and the outcomes were imported into Cytoscape 3.7.2 software to obtain the KEGG network map. The core targets were docked with the active components by the macromolecular docking software application AutoDock Vina. Results: A total of 243 chemical components and 1,448 disease targets including 127 intersecting targets were discovered. AKT1, TP53, and GO functional analysis were mainly associated with ubiquitination and oxidase reduction activity. In GC treatment, the KEGG analysis revealed that Guishao-Liujun decoction mainly acted through the tumor necrosis factor (TNF), interleukin 17 (IL-17), and cancer-related signaling pathways, with the best binding performance with TP53, as indicated by the outcomes of macromolecular docking. Conclusion: In the treatment of GC, Guishao-Liujun decoction works with a variety of components and targets, establishing the groundwork for further research into its mechanism of action.