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Identification of bioactive compounds and potential mechanisms of scutellariae radix-coptidis rhizoma in the treatment of atherosclerosis by integrating network pharmacology and experimental validation

小桶 药物数据库 公共化学 系统药理学 计算生物学 AKT1型 生物 UniProt公司 药理学 信号转导 基因本体论 基因 基因表达 生物化学 PI3K/AKT/mTOR通路 药品
作者
Lingyun Ji,Ting Song,Chunlei Ge,Qiao-Lan Wu,Lanying Ma,Xiubao Chen,Ting Chen,Qian Chen,Zetao Chen,Weida Chen
出处
期刊:Biomedicine & Pharmacotherapy [Elsevier BV]
卷期号:165: 115210-115210 被引量:113
标识
DOI:10.1016/j.biopha.2023.115210
摘要

OBJECTIVE: This study aims at investigating the potential targets and functional mechanisms of Scutellariae Radix-Coptidis Rhizoma (QLYD) against atherosclerosis (AS) through network pharmacology, molecular docking, bioinformatic analysis and experimental validation. METHODS: The compositions of QLYD were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and literature, where the main active components of QLYD and corresponding targets were identified. The potential therapeutic targets of AS were excavated using the OMIM database, DrugBank database, DisGeNET database, CTD database and GEO datasets. The protein-protein interaction (PPI) network of common targets was constructed and visualized by Cytoscape 3.7.2 software. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis were performed to analyze the function of core targets in the PPI network. Molecular docking was carried out using AutoDockTools, AutoDock Vina, and PyMOL software to verify the correlation between the main components of QLYD and the core targets. Mouse AS model was established and the results of network pharmacology were verified by in vivo experiments. RESULTS: Totally 49 active components and 225 corresponding targets of QLYD were obtained, where 68 common targets were identified by intersecting with AS-related targets. Five hub genes including IL6, VEGFA, AKT1, TNF, and IL1B were screened from the PPI network. GO functional analysis reported that these targets had associations mainly with cellular response to oxidative stress, regulation of inflammatory response, epithelial cell apoptotic process, and blood coagulation. KEGG pathway analysis demonstrated that these targets were correlated to AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, IL-17 signaling pathway, MAPK signaling pathway, and NF-kappa B signaling pathway. Results of molecular docking indicated good binding affinity of QLYD to FOS, AKT1, and TNF. Animal experiments showed that QLYD could inhibit inflammation, improve blood lipid levels and reduce plaque area in AS mice to prevent and treat AS. CONCLUSION: QLYD may exert anti-inflammatory and anti-oxidative stress effects through multi-component, multi-target and multi-pathway to treat AS.
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