小果博落回化学成分的分离鉴定及网络药理学预测其治疗阿尔茨海默病的作用机制

Isolation and Identification of Chemical Compounds from Macleaya Microcarpa and Prediction of Its Mechanism in the Treatment of Alzheimer's Disease by Network Pharmacology

关键词:  阿尔茨海默病  博落回属  小果博落回  黄酮苷  网络药理学  分子对接

Key words:  Alzheimer's disease  Macleaya R. Br  Macleaya microcarpa  flavonoid glycosides  network pharmacology  molecular docking

摘要:

目的 对小果博落回果荚正丁醇萃取物的化学成分进行分离鉴定，通过网络药理学预测其治疗阿尔茨海默病的作用靶点及通路。方法 采用硅胶柱色谱、Sephadex LH-20柱色谱、ODS中高压制备液相色谱等方法对小果博落回果荚正丁醇萃取物进行分离纯化，通过NMR对化合物进行结构鉴定；利用SwissTargetPrediction、Targetnet数据库获取目标化合物的作用靶点，利用Genecard、OMIM及TTD数据库获取阿尔茨海默病相关靶点，将两者输入Venny在线工具获得治疗阿尔茨海默病的作用靶点。通过Cytoscape 3.9.1软件构建“药物-成分-靶点-疾病”相互作用网络，String数据库进行蛋白-蛋白相互作用网络分析，使用Metascape数据库进行KEGG和GO通路富集分析，并用AutoDockTools 1.5.7软件进行分子对接研究。结果 从小果博落回果荚正丁醇萃取物分离得到5个酚苷类化合物；通过网络药理学筛选出TNF、PTGS2、APP等10个关键靶点，Pathways in cancer、Serotonergic synapse、Alzheimer's disease等10条重要通路，分子对接显示活性成分与关键靶点有较好的结合能力。结论 化合物3~5为首次从博落回属分离得到，化合物5 为首次从罂粟科分离得到；小果博落回可能通过作用于TNF、PTGS2、APP、ABCB1等关键靶点，干预APP/Aβ/NMDAR信号通路，来降低炎性因子、抑制炎症反应和减少脑内Aβ肽沉积，起到治疗阿尔茨海默病的作用。

Abstract:

OBJECTIVE To isolate and identify the chemical compounds of the n-butanol fraction of the pods of Macleaya microcarpa, and to predict the targets and pathways for its treatment of Alzheimer's disease by network pharmacology. METHODS Silica gel, Sephadex LH-20 column chromatography and ODS preparative liquid chromatography were used to separate and purify the n-butanol extract of the pods of Macleaya microcarpa, and the structure of the compounds were identified by NMR spectroscopic. The targets of active compounds were obtained using SwissTargetPrediction and Targetnet database. Alzheimer's disease-related target were obtained by Genecard, OMIM and TTD database. The two were imported into Venny online tool to select the effect targets of the active compounds for Alzheimer's disease treatment. The interaction network map of “drug-component-target-disease” was constructed by Cytoscape 3.9.1 software. The String database was used to build the protein protein interaction network analysis. KEGG and GO pathway enrichment analysis were performed with Metascape database, and molecular docking was studied with AutoDockTools 1.5.7 software. RESULTS Five phenolic glycosides were isolated from the n-butanol fraction of the pods of Macleaya microcarpa. Ten key targets such as TNF, PTGS2 and APP, and 10 important pathways such as Pathways in cancer, Serotonergic synapse and Alzheimer's disease were screened by network pharmacology, and molecular docking showed that the active ingredients had good binding ability to the key targets. CONCLUSION Compounds 3-5 are isolated from Macleaya microcarpa for the first time, and compound 5 is isolated from Papaveraceae for the first time. The mechanism of Macleaya microcarpa in the treatment Alzheimer's disease may affect on key targets such as TNF, PTGS2, APP, ABCB1, and influence signaling pathway such as the APP/Aβ/NMDAR, so as to reduce inflammatory factors, inhibit inflammatory responses and reduce Aβ deposition in the brain.