目的 基于整合用藥網(wǎng)絡及靶點網(wǎng)絡，篩選中醫(yī)藥治療2型糖尿病合并高脂血癥的核心處方及藥對，并探討潛在的分子作用機制。方法 以中國學術期刊全文數(shù)據(jù)庫（CNKI）、萬方數(shù)據(jù)庫（Wanfang Data）、維普生物醫(yī)學數(shù)據(jù)庫（VIP）及Web of Science、PubMed中英文數(shù)據(jù)庫為數(shù)據(jù)來源，結合古今醫(yī)案云平臺、R Studio Apriori關聯(lián)規(guī)則函數(shù)進行數(shù)據(jù)挖掘，得到治療2型糖尿病合并高脂血癥的核心處方。通過TCMSP、UniProt、Swiss Target Prediction等數(shù)據(jù)庫得到核心處方藥物有效成分及潛在靶點，利用Cytoscape 3.8.1構建中藥復方的藥物-成分-靶點網(wǎng)絡；與OMIM、Therapeutic Target Database、DrugBank等數(shù)據(jù)庫得到的疾病靶點取交集，構建2型糖尿病合并高脂血癥核心靶點蛋白質相互作用（PPI）網(wǎng)絡。將核心靶點導入Metascape數(shù)據(jù)庫進行基因本體（GO）注釋及京都基因與基因組百科全書（KEGG）通路富集分析；并將處方的核心成分及2型糖尿病合并高脂血癥的關鍵靶點逐一進行分子對接以初步驗證其有效性。結果 由文獻檢索共得到中醫(yī)藥治療糖尿病合并高脂血癥經(jīng)驗方256首，涉及組成中藥236味。綜合數(shù)據(jù)挖掘結果得到核心處方，包括丹參、黃芪、茯苓、澤瀉、山藥、山楂、白術、葛根；高頻藥對有“山楂-丹參”“葛根-黃芪”等。經(jīng)過數(shù)據(jù)庫綜合篩選，得到核心處方中有效活性成分132個。其中芹黃素、木犀草素、異鼠李素、丹參新醌甲、熊竹素為核心活性成分，核心處方治療的核心靶點為類視黃醇X受體、細胞腫瘤抗原p53、RELA原癌基因、絲氨酸蛋白激酶磷酸、熱休克蛋白α等。主要通路包括脂質與動脈粥樣硬化通路、化學致癌-受體激活、胰島素抵抗、PPAR信號通路及膽汁分泌。經(jīng)分子對接論證，預測的核心靶點與關鍵成分之間有較強的結合活性。結論 中藥治療2型糖尿病合并高脂血癥的核心處方組合可通過多活性成分，于多靶點、多通路調控，可為臨床應用及藥物開發(fā)提供參考思路。

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

國家中醫(yī)藥管理局2021歧黃學者支持項目（國家中醫(yī)藥人教函［2022］6）；謝雁鳴全國名老中醫(yī)藥專家傳承工作室建設項目（國家中醫(yī)藥人教函［2022］75）