基于数据挖掘及网络药理学方法探究朱文宗治疗神经性失眠伴焦虑状态用药规律及机制  

Exploration of Medication Rules of ZHU Wenzong in Treating Neuropathic Insomnia Complicated with Anxiety and Its Mechanism Based on Data Mining and Network Pharmacology

作　　者：谢佳峄 蒋越 陈婷婷[1] 朱文宗(指导)[1,3] XIE Jiayi;JIANG Yue;CHEN Tingting;ZHU Wenzong(Wenzhou Traditional Chinese Medicine Hospital of Zhejiang Chinese Medical University,Wenzhou Zhejiang 325029,China;The First Affiliated Hospital of Wenzhou Medical University,Wenzhou Zhejiang 325015,China;Wenzhou Hospital of Integrated Traditional Chinese and Western Medicine,Wenzhou Zhejiang 325001,China)

机构地区：[1]浙江中医药大学附属温州市中医院,浙江温州325029 [2]温州医科大学附属第一医院,浙江温州325015 [3]温州市中西医结合医院,浙江温州325001

出　　处：《新中医》2024年第8期14-24,共11页New Chinese Medicine

基　　金：浙江省自然科学基金项目(LY18H270001)。

摘　　要：目的:通过数据挖掘技术以及网络药理学方法探究朱文宗教授治疗神经性失眠伴焦虑状态的用药规律及作用机制。方法:收集2020年2月—2022年12月朱文宗教授于浙江中医药大学附属温州市中医院门诊部治疗神经性失眠伴焦虑状态患者的中药处方,运用中医传承计算平台V3.0对处方中所使用到的中药进行频次、频率统计,运用IBM SPSS Modeler 18.0软件进行关联规则分析,得出核心药物组。通过在中药系统药理学数据库与分析平台(TCMSP)预测核心药物组的活性成分及对应靶点;检索DrugBank数据库、基因组注释数据平台(GeneCards)、药物靶标数据库(TTD)及在线人类孟德尔遗传(OMIM)数据库获取疾病相关靶点,得到药物-疾病交集靶点。将核心药物活性成分及其作用靶点与药物-疾病交集靶点导入Cytoscape 3.9.1软件构建疾病-核心药物-成分-靶点网络图。将药物-疾病交集靶点导入STRING数据库进行蛋白质互相作用(PPI)网络分析。将药物-疾病交集靶点导入Metascape数据库进行基因本体(GO)功能富集分析和京都基因与基因组百科全书(KEGG)通路富集分析。结果:共纳入308个处方,涉及中药共计174味,累计使用频次4064次,其中使用频次≥60次的高频药物共20味。使用频次排在前5位的中药由高到低依次为甘草、半夏、黄芩、柴胡、党参。将174味中药进行性、味、归经分析,结果显示,药性以温性为主,其次为平性、微寒性等。药味以辛味为主,其次为苦味、甘味等。归经以肺、脾两经为主,其次为心经、肝经、胃经。关联规则分析以及复杂网络分析得出核心药物组为半夏-柴胡-黄芩-党参。对核心药物组进行网络药理学分析,得到63个药物-疾病交集靶点以及63个药物核心活性成分,主要包括豆甾醇、槲皮素和β-谷甾醇等。PPI网络分析结果得出15个核心靶点,分别为血管内皮生长因子A(VEGFA)、白细胞介素8(Objective:To explore the medication rules of Professor ZHU Wenzong in treating neuropathic insomnia complicated with anxiety and its mechanism by data mining technology and network pharmacology.Methods:The Chinese medicine prescriptions for patients with neuropathic insomnia complicated with anxiety by Professor ZHU at the Outpatient Department of Wenzhou Traditional Chinese Medicine Hospital of Zhejiang Chinese Medical University from February 2020 to December 2022 were collected,where the frequency of Chinese medicinals used was counted by the Traditional Chinese Medicine Inheritance Computing Platform V3.0,and association rule analysis for core medicinal groups was carried out by using the software IBM SPSS Modeler 18.0.The active components and corresponding targets of core medicinal groups were predicted on the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP);the disease-related targets were obtained by searching the DrugBank database,Genome Annotation Database Platform(GeneCards),Therapeutic Target Database(TTD),and Online Mendelian Inheritance in Man(OMIM).Using the software Cytoscape 3.9.1,the disease-core medicines-components-targets network was established by importing the active components and corresponding targets of core medicine and medicine-disease intersecting targets.The network analysis of protein-protein interaction(PPI)was conducted by importing the medicine-disease intersecting targets into the STRING database.The enrichment analysis of Gene Ontology(GO)function and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway was carried out by importing the medicinedisease intersecting targets into the Metascap database.Results:A total of 308 prescriptions were included and 174 Chinese medicinals were involved,with accumulated times of use of 4064.Among them,a total of 20 Chinese medicinals were highly used for more than 60 times,and the top 5 were subsequently Glycyrrhizae Radix et Rhizoma,Pinelliae Rhizoma,Scutellariae Radix,Bupleuri Radix and Codonopsis Radi

关 键 词：神经性失眠 焦虑 数据挖掘 网络药理学 朱文宗 

分 类 号：R256.23[医药卫生—中医内科学]