目的 基于整合用药网络及靶点网络，筛选中医药治疗2型糖尿病合并高脂血症的核心处方及药对，并探讨潜在的分子作用机制。方法 以中国学术期刊全文数据库（CNKI）、万方数据库（Wanfang Data）、维普生物医学数据库（VIP）及Web of Science、PubMed中英文数据库为数据来源，结合古今医案云平台、R Studio Apriori关联规则函数进行数据挖掘，得到治疗2型糖尿病合并高脂血症的核心处方。通过TCMSP、UniProt、Swiss Target Prediction等数据库得到核心处方药物有效成分及潜在靶点，利用Cytoscape 3.8.1构建中药复方的药物-成分-靶点网络；与OMIM、Therapeutic Target Database、DrugBank等数据库得到的疾病靶点取交集，构建2型糖尿病合并高脂血症核心靶点蛋白质相互作用（PPI）网络。将核心靶点导入Metascape数据库进行基因本体（GO）注释及京都基因与基因组百科全书（KEGG）通路富集分析；并将处方的核心成分及2型糖尿病合并高脂血症的关键靶点逐一进行分子对接以初步验证其有效性。结果 由文献检索共得到中医药治疗糖尿病合并高脂血症经验方256首，涉及组成中药236味。综合数据挖掘结果得到核心处方，包括丹参、黄芪、茯苓、泽泻、山药、山楂、白术、葛根；高频药对有“山楂-丹参”“葛根-黄芪”等。经过数据库综合筛选，得到核心处方中有效活性成分132个。其中芹黄素、木犀草素、异鼠李素、丹参新醌甲、熊竹素为核心活性成分，核心处方治疗的核心靶点为类视黄醇X受体、细胞肿瘤抗原p53、RELA原癌基因、丝氨酸蛋白激酶磷酸、热休克蛋白α等。主要通路包括脂质与动脉粥样硬化通路、化学致癌-受体激活、胰岛素抵抗、PPAR信号通路及胆汁分泌。经分子对接论证，预测的核心靶点与关键成分之间有较强的结合活性。结论 中药治疗2型糖尿病合并高脂血症的核心处方组合可通过多活性成分，于多靶点、多通路调控，可为临床应用及药物开发提供参考思路。

Objective To obtain the core prescription and herb pairs of Chinese medicine in the treatment of type 2 diabetes mellitus with hyperlipidemia, by using data mining, network pharmacology, and molecular docking technology, which further helps explore the potential molecular mechanism. Method This research was built on the retrieval from database like CNKI, Wanfang, VIP, Web of Science and PubMed. Data mining, operated on R Studio, provided the foundation of the core prescription. Then the active ingredients and potential targets were collected from TCMSP, UniProt, and Swiss Target Prediction databases and disease targets from OMIM, Therapeutic Target Database. The network of the ingredient-target of the compound and protein-protein interaction (PPI) of intersection targets between disease and ingredients were constituted via Cytoscape 3.8.1. The core targets extracted from the PPI network were imported into the Metascape website to perform gene ontology (GO) function annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. In the end, the core ingredients and targes were verified by molecular docking seriatim. Results 256 prescriptions consisting of 236 herbs were founded in total. Based on data mining, the core prescription of eight Chinese materia medica (Salviae Miltiorrhizae Radix et Rhizoma, Astragali Radix, Poria, Alismatis Rhizoma, Dioscoreae Rhizoma, Crataegi Fructus, Atractylodis Macrocephalae Rhizoma, Puerariae Lobatae Radix) and herb pairs such as the combination of Crataegi Fructus-Salviae Miltiorrhizae Radix et Rhizoma and Puerariae Lobatae Radix-Astragali Radix were acquired. Through comprehensive screening, 132 active ingredients (i.e., apigenin, luteolin, isorhamnetin, dan-shexinkum A, etc.) and 878 potential targets (i. e., RXRα, TP53, AKT1, CAV1, etc.) were got. The main signal paths include Lipid and atherosclerosis, Chemical carcinogenesis- receptor activation, Insulin resistance, PPAR signalling pathway, etc. The molecular docking results indicated the ideal affinity between the core ingredients and targets. Conclusion The core prescription combination of traditional Chinese medicine for treating type 2 diabetes with hyperlipidemia can be regulated by multiple active ingredients at multiple targets and pathways, which can provide reference ideas for clinical application and drug development.

R285.5

国家中医药管理局2021歧黄学者支持项目（国家中医药人教函［2022］6）；谢雁鸣全国名老中医药专家传承工作室建设项目（国家中医药人教函［2022］75）