目的 利用網絡藥理學及分子對接探究消渴清顆粒治療糖尿病前期的作用機制。方法 通過中藥系統(tǒng)藥理學數據庫搜索有關于消渴清顆粒中中藥的有效成分與靶點，在GeneCards數據庫、OMIM數據庫搜索糖尿病前期的基因靶點，進而獲得藥物-疾病交集靶點，將交集靶點導入String蛋白質相互作用數據庫和Cytoscape構建蛋白質相互作用（PPI）網絡圖，并篩選核心靶點，再將藥物-疾病交集靶點導入DAVID數據庫，對其分別進行基因本體（GO）功能富集分析和京都基因與基因組百科全書（KEGG）通路富集分析，篩選出與疾病相關的通路，通過Cytoscape得出“通路-靶點”網絡圖，再通過插件分析得出“通路-靶點”網絡核心靶點，取二者度值排名前7位的靶點交集作為消渴清顆粒治療糖尿病前期的關鍵靶點，最后選擇關鍵靶點與有效成分用AutoDock與Pymol軟件進行分子對接及可視化。結果 篩選出消渴清顆粒中藥活性成分36種，其中篩選出6種關鍵活性成分，分別為槲皮素、山柰酚、小檗堿、β-谷甾醇、花生四烯酸、知母皂苷C，靶點基因232個；篩選出糖尿病前期靶點685個，交集靶點93個，關鍵靶點5個，分別為腫瘤壞死因子（TNF）、白細胞介素-6（IL-6）、蛋白激酶B1（Akt1）、白細胞介素-1β（IL-1β）、環(huán)加氧酶2（PTGS2）。GO通路富集主要涉及內容有炎癥、藥物反應，細胞生長凋亡等；KEGG通路富集分析顯示糖尿病并發(fā)癥中的晚期搪基化終產物及其受體（AGE-RAGE）信號通路、TNF信號通路、缺氧誘導因子-1（HIF-1）信號通路、IL-17信號通路、胰島素抵抗通路、磷脂酰肌醇3-激酶（PI3K）/Akt信號通路等，分子對接結果顯示關鍵靶點與有效成分具有較穩(wěn)定的結合能力。結論 消渴清顆粒中各種藥物成分通過多靶點、多通路協(xié)同治療糖尿病前期的作用機制，為進一步研究治療糖尿病提供了線索。

Objective To explore the mechanism of Xiaokeqing Granules in treatment of prediabetes using network pharmacology and molecular docking. Methods The active ingredients and targets of Xiaokeqing Granules were searched in the Chinese medicine system pharmacology database, and the gene targets of prediabetes were searched in the GeneCards database and OMIM database, and the drug-disease intersection targets were obtained. The intersection targets were imported into string protein interaction database and Cytoscape to construct protein-protein interaction networks (PPI) network map, and the core targets were screened, and then the intersection targets of drug-disease were imported into DAVID database. GO functional enrichment analysis and KEGG pathway enrichment analysis were performed to screen out disease-related pathways, and the “pathway-target” network diagram was obtained by Cytoscape. The core targets of the “pathway-target” network were obtained by plug-in analysis, and the intersection of the top 7 targets with the degree value of the two was taken as the key targets for the treatment of pre-diabetes. Finally, the key targets and active ingredients were selected for molecular docking and visualization by AutoDock and Pymol software. Results A total of 36 active ingredients of Xiaokeqing Granules were screened out, of which 6 key active ingredients were screened out, including quercetin, kaempferol, berberine, β-sitosterol, arachidonic acid, and asoside C. 232 target genes, 685 pre-diabetic targets, 93 intersection targets, and 5 key targets were screened out. These were TNF, IL-6, Akt1, IL-1β, and PTGS2. GO pathway enrichment was mainly involved in inflammation, drug response, cell growth and apoptosis. KEGG pathway enrichment analysis showed AGE-RAGE signaling pathway, TNF signaling pathway, HIF-1 signaling pathway, IL-17 signaling pathway, insulin resistance pathway, PI3K/Akt signaling pathway in diabetic complications. Molecular docking results showed that the key targets had stable binding ability with active ingredients. Conclusion The results show that the various drug components in Xiaokeqing Granules treat prediabetes through multi-target and multi-pathway cooperation, which provides clues for further research and treatment of prediabetes.

R285.5

安徽省衛(wèi)生健康科研項目（AHWJ2023BAc10002）；安徽省高等學校科學研究項目（2023AH050782）；安徽省高等學校省級質量工程項目（2021jyxm0834）；新安醫(yī)學與中醫(yī)藥現代化研究所“揭榜掛帥”項目（2023CXMMTCM024，2023CXMMTCM003）；糖脂代謝病教育部重點實驗室開放基金項目（GYDKFXM01)；安徽省名中醫(yī)方朝暉工作室（2019-8-515）；安徽省高校優(yōu)秀拔尖人才培育項目（2022-371）；安徽中醫(yī)藥大學臨床科研項目（2021yfylc01）；安徽省衛(wèi)生健康骨干人才培養(yǎng)對象（2022-392）；2023年度新時代育人省級質量工程項目（研究生教育）建設項目（2023gjxslt014）