基于网络药理学和分子对接技术探讨升陷化浊颗粒治疗冠心病的分子机制  

Exploring the Molecular Mechanism of Drooping-Raising and Turbidity-Resolving Granules in Treating Coronary Heart Disease Based on Network Pharmacology and Molecular Docking Technology

作　　者：张敏[1] 董政委 邢作英[1] 邱伯雍 王永霞[1,2] ZHANG Min;DONG Zhengwei;XING Zuoying;QIU Boyong;WANG Yongxia(The First Affiliated Hospital of Henan University of Chinese Medicine,Zhengzhou,Henan,China,450001;Henan University of Chinese Medicine,Zhengzhou,Henan,China,450046)

机构地区：[1]河南中医药大学第一附属医院,河南郑州450001 [2]河南中医药大学,河南郑州450046

出　　处：《河南中医》2025年第5期728-736,共9页Henan Traditional Chinese Medicine

基　　金：河南省科技研发计划联合基金项目(优势学科培育类)(232301420021);中原科技创新领军人才项目(244200510002)。

摘　　要：目的:基于网络药理学和分子对接技术探究升陷化浊颗粒治疗冠状动脉粥样硬化性心脏病(coronary heart disease,CHD)的潜在分子机制。方法:使用中药系统药理学数据库与分析平台筛选升陷化浊颗粒的活性成分,通过SwissTargetPrediction及Pubchem获取活性成分的基因靶点。在GSE179789、GenCards、在线人类孟德尔遗传数据库(oline men-delian inheritance,OMIM)及治疗靶点数据库(therapeutic target database,TTD)获得CHD基因靶点。在Veney 2.1.0数据库获得活性成分靶点与疾病靶点交集。使用STRING数据库构建靶蛋白相互作用网络,运用Cytoscape 3.7.2构建“疾病-靶点-成分”网络图。通过微生信-在线生物信息学分析可视化云平台对潜在靶点进行基因本体(Gene Ontology,GO)功能富集分析和京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路富集分析。使用AutoDockTools 1.5.6对筛选的关键活性成分与核心靶点进行分子对接。结果:本研究共筛选出183个有效活性成分,441个活性成分相关靶点。从GSE179789数据集中获得相关疾病靶点273个,GenCards相关疾病靶点1939个,OMIM相关疾病靶点249个,TTD相关疾病靶点52个,合计疾病靶点2467个,药物与疾病交集潜在靶点168个。网络药理学结果显示,CYP3A4、CYP1A1、CYP2E1、STAT3、肿瘤坏死因子(tumor necrosis factor,TNF)等靶点为升陷化浊颗粒治疗CHD的潜在靶点。糖尿病并发症中AGE-RAGE信号通路、IL-17信号通路、TNF信号通路等通路是升陷化浊颗粒治疗CHD的关键通路。GO分析发现类固醇代谢过程是升陷化浊颗粒治疗CHD的生物进程;分子对接表明吴茱萸酰胺甲与细胞色素P450酶家族成员(CYP3A4、CYP2E1、CYP1A1)具有较好的结合性。结论:升陷化浊颗粒通过吴茱萸酰胺甲调节细胞色素P450酶家族成员(CYP3A4、CYP2E1、CYP1A1)以及糖尿病并发症中AGE-RAGE信号通路干预类固醇代谢的反应进程,从而发挥�Objective:To explore the potential molecular mechanism of Drooping-Raising and Turbidity-Resolving Granules in treating coronary atherosclerotic heart disease(CHD)using network pharmacology and molecular docking.Methods:The active components of Drooping-Raising and Turbidity-Resolving Granules were screened using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP).Gene targets of the active components were obtained from Swiss Target and PubChem.CHD-related gene targets were collected from the GSE179789 dataset,GenCards,Online Mendelian Inheritance in Man(OMIM),and Therapeutic Target Database(TTD).Intersection targets between Drooping-Raising and Turbidity-Resolving Granules and CHD were identified using Venny 2.1.0.A protein-protein interaction(PPI)network was constructed using the STRING database,and a"drug-component-target"network was visualized with Cytoscape 3.7.2.Gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses were performed using the Biomicro Bioinformatics Analysis Platform.Molecular docking of key active components and core targets was conducted with AutoDockTools 1.5.6.Results:A total of 183 active components of Drooping-Raising and Turbidity-Resolving Granules with 441 potential targets were screened.A total of 2467 disease targets were obtained,including 273 from the GSE179789 dataset,1939 from GenCards,249 from OMIM,and 52 from TTD.There were 168 potential targets in the intersection of drugs and diseases.The results of network pharmacology indicated that CYP3A4,CYP1A1,CYP2E1,STAT3,tumor necrosis factor(TNF),and other targets were the potential targets for Shengxian Huazhuo Granules in regulating coronary heart disease(CHD).The AGE-RAGE signaling pathway in diabetic complications,IL-17 signaling pathway,TNF signaling pathway,and other pathways were the key pathways for Drooping-Raising and Turbidity-Resolving Granules in treating CHD.GO analysis suggested that the steroid metabolic process was the highest biological

关 键 词：冠状动脉粥样硬化性心脏病 升陷化浊颗粒 网络药理学 分子对接 

分 类 号：R285.5[医药卫生—中药学]