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基于NGO算法和网络药理学的桃仁–大黄治疗糖尿病性视网膜病变作用机制分析
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Abstract:
目的：基于网络药理学方法探讨桃仁–大黄治疗糖尿病性视网膜病变的作用机制。方法：运用NGO算法完成对目标药物的优化求解，从中药系统药理学数据库和分析平台(TCMSP)数据库获取桃仁–大黄的药对有效成分及预测药物作用靶点；通过人类基因数据库(GeneCards)和人类基因–疾病关联数据库(DisGeNET)识别与糖尿病性视网膜病变相关的基因。筛选出交集靶标基因后，利用STRING数据库分析这些基因的相互作用，并进一步探讨其潜在作用机制。结果：筛选出桃仁–大黄药对的39个活性成分，并预测出462个靶点基因。在糖尿病性视网膜病变中，鉴定出1352个相关基因，其中155个基因为药物–疾病交集靶标基因。通过基因本体(GO)功能富集分析，这些基因主要涉及分子功能、细胞组成以及生物过程。京都基因和基因组百科KEGG路径富集分析显示，桃仁–大黄药对治疗糖尿病性视网膜病变主要通过癌症通路、AGE-RAGE通路、IL-17通路和TNF通路等途径发挥作用。结论：桃仁–大黄主要通过TNF、AKT1、IL1B、EGFR、PPARG等关键靶点以及调节TNF信号通路、糖尿病并发症中的AGE-RAGE信号通路、血脂与动脉粥样硬化等多途径、多靶点发挥治疗糖尿病性视网膜病变的作用。
Objective: To explore the mechanism of action of peach kernel and rhubarb in the treatment of diabetic retinopathy based on the network pharmacology approach. Methods: The optimisation of the target drug was completed by using the NGO algorithm, and the active ingredients and predicted targets of peach kernel and rhubarb were obtained from the Traditional Chinese Medicine Systematic Pharmacology Database and Platform (TCMSP) database; the genes related to diabetic retinopathy were identified through the GeneCards and DisGeNET databases. After screening the intersecting target genes, the STRING database was used to analyse the interactions of these genes and further explore their potential mechanisms of action. Results: Thirty-nine active components of peach kernel-rhubarb pairs were screened and 462 target genes were predicted. In diabetic retinopathy, 1352 related genes were identified, of which 155 genes were drug-disease intersection target genes. These genes were mainly involved in molecular function, cellular composition, and biological processes by Gene Ontology (GO) functional enrichment analysis. Kyoto Gene and Genome Encyclopedia KEGG pathway enrichment analyses showed that peach kernel-rhubarb drug pairs for the treatment of diabetic retinopathy acted mainly through the cancer pathway, AGE-RAGE pathway, IL-17 pathway, and TNF pathway. Conclusion: Peach kernel-rhubarb exerts its therapeutic effects on diabetic retinopathy mainly through multiple pathways and targets, such as key targets of TNF, AKT1, IL1B, EGFR, and PPARG, as well as regulating the TNF signalling pathway, AGE-RAGE signalling pathway in diabetic complications, and blood lipids and atherosclerosis.
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