目的 基于網絡藥理學方法探討、篩選經典名方逍遙散治療糖尿病的可能通路、靶點、成分。方法 利用TCMSP、TCMIP、Drugbank、TTD等數(shù)據(jù)庫檢索成分、靶點信息，并進行Cytoscape分析；利用String數(shù)據(jù)庫進行蛋白互作分析，利用ClueGO進行GO等數(shù)據(jù)庫信息富集，并以Autodock Vina進行分子對接驗證。結果 檢索得到逍遙散394個可能的活性成分和558個成分靶點，糖尿病相關靶點4 963個，靶點取交集后得到359個靶點，在Cytoscape進行分析并按Degree排序后取前10個靶點。按Degree、Average Shortest Path Length、Betweenness Centrality和Closeness Centrality排序后各取排名靠前的一半數(shù)據(jù)得到325個靶點，在String數(shù)據(jù)庫中進行檢索利用Cytoscape分析，取Degree大于100的靶點，與中藥-成分-靶點網絡分析中的10個靶點去重合并后得到21個靶點，對這21個靶點進行分子對接驗證和GO、KEGG、REACTOME數(shù)據(jù)庫檢索分析。結論 篩選出8個潛在活性結構，利用分子對接在21個潛在關鍵靶點中篩選出1個與成分結合非常強的靶點即NOS2。

Objective To investigate and screen related pathways, targets and ingredients of classical formula Xiaoyao Powder in treating diabetes based on network pharmacology. Methods The databank TCMSP and TCMSP were used to search and retrieve information of ingredients and targets of Xiaoyao Powder, then data was processed with Cytoscape, protein relationship was analysed by String, the information of GO was enriched by ClueGO, the results were validated by Autodock Vina. Results From TCMSP and TCMIP, 394 ingredients and 558 targets of Xiaoyao Powder were obtained. From GenCLiP3, DisGeNET, DrugBank, OMIM, TTD got 4 963 targets related to diabetes were obtained. Herb-ingredient-target network was created and analyzed by Cytoscape, the results were arranged by Degree, the first ten targets was take to complete a further discussion. The results by Degree, Average Shortest Path Length, Betweenness Centrality and Closeness Centrality were arranged separately, half of each part got 325 targets in total, in String databank, the results were arranged by Degree, the target which has a higher degree value than 100 were analysed, together with the 10 targets above, and with the help of ClueGO the information of Pathway, Molecular Function, etc were enriched. Conclusion Eight molecules may be active to diabetes targets. Among 21 targets, one target, NOS2, can combine with those ingredients in Xiaoyao Powder through docking results.

R285.5

天津市醫(yī)藥科學研究所科研團隊項目（STD-1）