目的 通过网络药理学和分子对接的方法,探究糖脉康颗粒治疗糖尿病周围神经病变(DPN)的机制。方法 利用检索中药系统药理学数据库及分析平台(TCMSP)对筛选糖脉康颗粒的组方药物的化学活性物质,药物靶标采用Swiss Target Prediction平台进行预测,并搜索Genecards数据库、OMIM数据库、TTD数据库和DisGeNET数据库预测DPN相关靶点。对药物与疾病的靶标基因取交集后采用Cytoscape软件构建活性成分-靶点网络图,并导入String数据库构建PPI网络,进行拓扑分析寻找核心基因。采用R软件进行基因本体(GO)注释和京都基因与基因组百科全书(KEGG)信号通路富集分析。结果 糖脉康颗粒治疗糖尿病周围神经病变的关键化学成分为巴马汀、广玉兰内酯和11,14,17-三烯酸甲酯等;药物-疾病的共同靶点共331个,关键蛋白包括细胞肿瘤抗原p53、连环蛋白β-1(CTNNB1)、热休克蛋白90-α(HSP90AA1)等。GO富集分析显示,生物过程主要包括细胞对化学应激的反应、对营养素水平的反应和肽基酪氨酸磷酸化等,细胞组成主要包括膜筏膜微域和膜区等,分子功能主要包括蛋白酪氨酸激酶活性、细胞表面受体蛋白酪氨酸激酶活性和细胞表面受体蛋白激酶活性等。KEGG富集分析所涉及的通路有糖尿病并发症中的高糖基化终产物-高糖基化终产物受体信号通路、脂质和动脉粥样硬化、前列腺癌、表皮生长因子受体酪氨酸激酶抑制剂耐药性和癌症的中枢碳代谢等。分子对接结果显示,糖脉康颗粒中的7个关键活性成分与5个核心靶点蛋白的结合能均 ≤ −5.0 kcal/mol,说明成分和靶点蛋白结合性可能较好。结论 利用网络药理学和分子对接揭示了糖脉康颗粒通过多种途径,多种信号通路作用于多种靶点发挥药效,为进一步阐释糖脉康颗粒治疗糖尿病周围神经病变的作用机制提供了依据。

Objective To explore the mechanism of Tangmaikang Granules in treatment of diabetes peripheral neuropathy based on network pharmacology and molecular docking. Methods The Traditional Chinese Medicine SystemsPharmacology Database and Analysis Platform (TCMSP) was searched to screen the chemical active ingredients in the Tangmaikang Granules. The drug targets were predicted by the SwissTargetPrediction Platform. Genecards Database, OMIM database, TTD database, and DisGeNET database were searched to predict DPN-related targets. After crossing the target genes of drugs and diseases, Cytoscape software was used to construct the drug-ingredient-target-disease network, and the PPI network plot was constructed by importing the String database. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathway enrichment were conducted by R software. Results The key chemical ingredients in Tangmaikang Granules for DPN are palmatine, magnograndiolide, and icosa-11,14,17-trienoic acid methyl ester, etc., there are 331 common targets for drug-disease, the key proteins include cellular tumor antigen p53 (TP53), catenin beta-1 (CTNNB1), heat shock protein HSP 90-alpha (HSP90AA1). GO enrichment analysis showed that biological process included cellular response to chemical stress, response to nutrient levels, and peptidyl-tyrosine phosphorylation. Celelular component included membrane raft, membrane microdomain, and membrane region. Molecular function included protein tyrosine kinase activity, transmembrane receptor protein tyrosine kinase activity, and transmembrane receptor protein kinase activity. The pathways involved in KEGG enrichment analysis are the AGE-RAGE signaling pathway in diabetic complications, lipid and atherosclerosis, prostate cancer, EGFR tyrosine kinase inhibitor resistance, and central carbon metabolism in cancer, etc. The results of molecular docking showed that the binding energies of the seven key active components with the five core target proteins in Tangmaikang Granules were mostly ≤ −5.0 kcal/mol, indicating that the components may possessed good binding ability with the target proteins. Conclusion Network pharmacology and molecular docking have revealed that Tangmaikang Granules exerts its pharmacodynamic effect through multiple pathways and multiple signal pathways acting on multiple targets, it provides a basis for further explaining the mechanism of Tangmaikang Granule in the treatment of DPN.

R914

中医药防治糖尿病国际联合研究中心基金项目（2015B01022）；兵团财政科技计划项目（2020AA005）