目的 利用網(wǎng)絡(luò)藥理學(xué)及分子對接探究消渴清顆粒治療糖尿病前期的作用機(jī)制。方法 通過中藥系統(tǒng)藥理學(xué)數(shù)據(jù)庫搜索有關(guān)于消渴清顆粒中中藥的有效成分與靶點，在GeneCards數(shù)據(jù)庫、OMIM數(shù)據(jù)庫搜索糖尿病前期的基因靶點，進(jìn)而獲得藥物-疾病交集靶點，將交集靶點導(dǎo)入String蛋白質(zhì)相互作用數(shù)據(jù)庫和Cytoscape構(gòu)建蛋白質(zhì)相互作用（PPI）網(wǎng)絡(luò)圖，并篩選核心靶點，再將藥物-疾病交集靶點導(dǎo)入DAVID數(shù)據(jù)庫，對其分別進(jìn)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(guān)的通路，通過Cytoscape得出“通路-靶點”網(wǎng)絡(luò)圖，再通過插件分析得出“通路-靶點”網(wǎng)絡(luò)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(guān)鍵靶點，最后選擇關(guān)鍵靶點與有效成分用AutoDock與Pymol軟件進(jìn)行分子對接及可視化。結(jié)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(guān)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(guān)鍵靶點5個，分別為腫瘤壞死因子（TNF）、白細(xì)胞介素-6（IL-6）、蛋白激酶B1（Akt1）、白細(xì)胞介素-1β（IL-1β）、環(huán)加氧酶2（PTGS2）。GO通路富集主要涉及內(nèi)容有炎癥、藥物反應(yīng)，細(xì)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(chǎn)物及其受體（AGE-RAGE）信號通路、TNF信號通路、缺氧誘導(dǎo)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(jié)果顯示關(guān)鍵靶點與有效成分具有較穩(wěn)定的結(jié)合能力。結(jié)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(jī)制，為進(jìn)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

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