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基于网络药理学和动物实验探讨红花与葶苈子药对通过改善心脏微环境抑制心肌纤维化的机制

[Mechanism of Carthami Flos and Lepidii Semen drug pair in inhibition of myocardial fibrosis by improving cardiac microenvironment based on network pharmacology and animal experiment].

作者信息

Wang Yong, Wang Zhen, Wang Cheng, Ma Du-Fang

机构信息

Affiliated Hospital of Shandong University of Traditional Chinese Medicine Ji'nan 250011, China.

Zaozhuang Municipal Hospital Zaozhuang 277000, China.

出版信息

Zhongguo Zhong Yao Za Zhi. 2022 Feb;47(3):753-763. doi: 10.19540/j.cnki.cjcmm.20210929.401.

DOI:10.19540/j.cnki.cjcmm.20210929.401
PMID:35178959
Abstract

Previously, Carthami Flos and Lepidii Semen(CF-LS) drug pair has been proved effective in inhibiting myocardial fibrosis(MF) by blunting the activity of cardiac fibroblasts. The present study explored the underlying mechanism of CF-LS in inhibiting MF by improving the cardiac microenvironment based on network pharmacology combined with experimental verification. Active compounds and potential targets of CF-LS were retrieved from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), and the potential targets of MF were obtained from GeneCards, Online Mendelian Inheritance in Man(OMIM), and Pharmacogenetics and Pharmacogenomics Knowledge Base(PharmGKB). The "active component-target-MF" network was constructed and analyzed by Cytoscape 3.8.1. The protein-protein interaction(PPI) network was constructed by STRING. The Gene Ontology(GO) biological process enrichment analysis was performed by CluoGO plug-in. Kyoto Encyclopedia of Genes and Genomes(KEGG) signaling pathway enrichment analysis was performed by R 4.0.2 and Funrich. Subsequently, the inhibitory effect of CF-LS on MF was investigated based on angiotensin Ⅱ(Ang Ⅱ)-induced MF rats. RT-PCR and ELISA were used to verify the effect of CF-LS on the targets of signaling pathways related to vascular endothelial cells predicted by the network pharmacology. Thirty-one active components and 204 potential targets of CF-LS, 4 671 MF-related targets, and 174 common targets were obtained. The network analysis showed that the key targets of CF-LS against MF included RAC-alpha serine/threonine-protein kinase(AKT1), transcription factor AP-1(JUN), mitogen-activated protein kinase 1(MAPK1), cellular tumor antigen p53(TP53), transcription factor p65(RELA), and mitogen-activated protein kinase 8(MAPK8). Biological processes mainly involved regulation of blood vessel diameter, regulation of blood vessel endothelial cell migration, cell death in response to oxidative stress, etc. Advanced glycation end products(AGE)-receptor for advanced glycation end products(RAGE) signaling pathway, phosphoinositide 3-kinase(PI3 K)-serine/threonine protein kinase(AKT) signaling pathway, hypoxia-inducible factor-1(HIF-1) signaling pathway, integrin signaling pathway, transforming growth factor-β(TGF-β) signaling pathway, etc. were involved in signaling pathway enrichment. Literature retrieval confirmed that some of these signaling pathways were closely related to vascular endothelial cells, including AGE-RAGE, PI3 K-AKT, HIF-1α, p53, the transcription factor activator protein-1(AP-1), integrin, p38 MAPK, and TGF-β. Animal experiments showed that CF-LS inhibited MF induced by Ang Ⅱ in rats by suppressing the expression of RAGE, HIF-1α, integrin β6, and TGF-β1. The inhibitory effect of CF-LS on MF has the characteristics of multiple components, multiple targets, and multiple pathways. CF-LS can inhibit MF by regulating the activity of vascular endothelial cells in the cardiac microenvironment.

摘要

此前,红花-葶苈子药对已被证明可通过抑制心脏成纤维细胞活性来有效抑制心肌纤维化(MF)。本研究基于网络药理学结合实验验证,探讨红花-葶苈子药对通过改善心脏微环境抑制MF的潜在机制。从中药系统药理学数据库与分析平台(TCMSP)检索红花-葶苈子药对的活性成分和潜在靶点,并从基因卡片(GeneCards)、人类孟德尔遗传在线数据库(OMIM)以及药物遗传学与药物基因组学知识库(PharmGKB)获取MF的潜在靶点。利用Cytoscape 3.8.1构建并分析“活性成分-靶点-MF”网络。通过STRING构建蛋白质-蛋白质相互作用(PPI)网络。利用CluoGO插件进行基因本体论(GO)生物学过程富集分析。通过R 4.0.2和Funrich进行京都基因与基因组百科全书(KEGG)信号通路富集分析。随后,基于血管紧张素Ⅱ(AngⅡ)诱导的MF大鼠模型,研究红花-葶苈子药对MF的抑制作用。采用逆转录聚合酶链反应(RT-PCR)和酶联免疫吸附测定(ELISA)验证红花-葶苈子药对网络药理学预测的与血管内皮细胞相关信号通路靶点的作用。获得了红花-葶苈子药对的31种活性成分和204个潜在靶点、4671个MF相关靶点以及174个共同靶点。网络分析表明,红花-葶苈子药对对抗MF的关键靶点包括RAC-α丝氨酸/苏氨酸蛋白激酶(AKT1)、转录因子AP-1(JUN)、丝裂原活化蛋白激酶1(MAPK1)、细胞肿瘤抗原p53(TP53)、转录因子p65(RELA)和丝裂原活化蛋白激酶8(MAPK8)。生物学过程主要涉及血管直径调节、血管内皮细胞迁移调节、氧化应激诱导的细胞死亡等。晚期糖基化终产物(AGE)-晚期糖基化终产物受体(RAGE)信号通路、磷脂酰肌醇3激酶(PI3K)-丝氨酸/苏氨酸蛋白激酶(AKT)信号通路、缺氧诱导因子-1(HIF-1)信号通路、整合素信号通路、转化生长因子-β(TGF-β)信号通路等参与信号通路富集。文献检索证实,其中一些信号通路与血管内皮细胞密切相关,包括AGE-RAGE、PI3K-AKT、HIF-1α、p53、转录因子激活蛋白-1(AP-1)、整合素、p38丝裂原活化蛋白激酶(MAPK)和TGF-β。动物实验表明,红花-葶苈子药对通过抑制RAGE、HIF-1α、整合素β6和TGF-β1的表达,抑制AngⅡ诱导的大鼠MF。红花-葶苈子药对抑制MF具有多成分、多靶点、多途径的特点。红花-葶苈子药对可通过调节心脏微环境中血管内皮细胞的活性来抑制MF。

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