Niu Kai, Li Qifang, Liu Yuan, Qiao Yi, Li Bingbing, Wei Chao, Wang Kunrui, Cui Lu'an, Zheng Canlei, Wang Rong, Zhang Li, Zhang Honghua, Sun Bing, Yu Bin
College of Integrated Chinese and Western Medicine, Jining Medical University, Jining 272067, China.
Department of Traditional Chinese Medicine, Affiliated Hospital of Jining Medical University, Jining 272060, China.
Evid Based Complement Alternat Med. 2021 Jun 4;2021:9929093. doi: 10.1155/2021/9929093. eCollection 2021.
This study aims to analyze the targets of the effective active ingredients of - drug pair (SCDP) in ulcerative colitis (UC) by network pharmacology and molecular docking and to explore the associated therapeutic mechanism. The effective active ingredients and targets of SCDP were determined from the TCMSP database, and the drug ingredient-target network was constructed using the Cytoscape software. The disease targets related to UC were searched in GeneCards, DisGeNET, OMIM, and DrugBank databases. Then, the drug ingredient and disease targets were intersected to construct a protein-protein interaction network through the STRING database. The Metascape database was used for the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the predicted targets of SCDP for UC. The Autodock software was used for molecular docking between the main active ingredient and the core target to evaluate the binding ability. SCDP has 43 effective active ingredients and 134 intersection targets. Core targets included AKT1, TP53, IL-6, VEGFA, CASP3, JUN, TNF, MYC, EGFR, and PTGS2. GO functional enrichment analysis showed that biological process was mainly associated with a cytokine-mediated signaling pathway, response to an inorganic substance, response to a toxic substance, response to lipopolysaccharide, reactive oxygen species metabolic process, positive regulation of cell death, apoptotic signaling pathway, and response to wounding. KEGG enrichment analysis showed main pathway concentrations were related to pathways in cancer, AGE-RAGE signaling pathway in diabetic complications, bladder cancer, IL-17 signaling pathway, apoptosis, p53 signaling pathway, and PI3K-Akt signaling pathway. The drug active ingredient-core target-key pathway network contains 41 nodes and 108 edges, of which quercetin, wogonin, baicalein, acacetin, oroxylin A, and beta-sitosterol are important active ingredients; PTGS2, CASP3, TP53, IL-6, TNF, and AKT1 are important targets; and the pathways involved in UC treatment include pathways in cancer, PI3K-Akt signaling pathway, AGE-RAGE signaling pathway in diabetic, apoptosis, IL-17 signaling pathway and herpes simplex infection. The active ingredient has a good binding capacity to the core target. SCDP key active ingredients are mainly quercetin, wogonin, baicalein, acacetin, oroxylin A, and beta-sitosterol, which function mainly by regulating targets, such as PTGS2, CASP3, TP53, IL-6, TNF, and AKT1, and are associated with multiple signaling pathways as pathways in cancer, PI3K-Akt signaling pathway, apoptosis, IL-17 signaling pathways.
本研究旨在通过网络药理学和分子对接分析中药药对(SCDP)治疗溃疡性结肠炎(UC)的有效活性成分作用靶点,并探讨其相关治疗机制。从中药系统药理学数据库与分析平台(TCMSP)数据库中确定SCDP的有效活性成分和靶点,使用Cytoscape软件构建药物成分-靶点网络。在基因卡片(GeneCards)、疾病基因数据库(DisGeNET)、在线人类孟德尔遗传数据库(OMIM)和药物银行(DrugBank)数据库中检索与UC相关的疾病靶点。然后,将药物成分靶点与疾病靶点进行交集分析,并通过STRING数据库构建蛋白质-蛋白质相互作用网络。利用Metascape数据库对SCDP治疗UC的预测靶点进行基因本体(Gene Ontology)和京都基因与基因组百科全书(KEGG)通路富集分析。使用Autodock软件对主要活性成分与核心靶点进行分子对接,以评估其结合能力。SCDP有43种有效活性成分和134个交集靶点。核心靶点包括蛋白激酶B1(AKT1)、肿瘤蛋白p53(TP53)、白细胞介素-6(IL-6)、血管内皮生长因子A(VEGFA)、半胱天冬酶3(CASP3)、原癌基因蛋白c-Jun(JUN)肿瘤坏死因子(TNF)、原癌基因c-Myc(MYC)、表皮生长因子受体(EGFR)和前列腺素内过氧化物合酶2(PTGS2)。基因本体功能富集分析表明,生物学过程主要与细胞因子介导的信号通路、对无机物质的反应、对有毒物质的反应、对脂多糖的反应、活性氧代谢过程、细胞死亡的正调控、凋亡信号通路以及对伤口的反应有关。KEGG富集分析表明,主要通路集中在癌症通路、糖尿病并发症中的晚期糖基化终末产物受体(AGE-RAGE)信号通路、膀胱癌、白细胞介素-17信号通路、凋亡、p53信号通路和磷脂酰肌醇-3激酶-蛋白激酶B(PI3K-Akt)信号通路。药物活性成分-核心靶点-关键通路网络包含41个节点和108条边,其中槲皮素、汉黄芩素、黄芩苷、刺槐素、木犀草素和β-谷甾醇是重要活性成分;PTGS2、CASP3、TP53、IL-6、TNF和AKT1是重要靶点;参与UC治疗的通路包括癌症通路、PI3K-Akt信号通路、糖尿病中的AGE-RAGE信号通路、凋亡、IL-17信号通路和单纯疱疹感染。活性成分与核心靶点具有良好的结合能力。SCDP关键活性成分主要为槲皮素、汉黄芩素、黄芩苷、刺槐素、木犀草素和β-谷甾醇,其作用主要通过调节PTGS2、CASP3、TP53、IL-6、TNF和AKT1等靶点实现,并与癌症通路、PI3K-Akt信号通路、凋亡、IL-17信号通路等多条信号通路相关。