[关键词]
[摘要]
目的 基于网络药理学方法研究香附多成分-多靶点-多途径的抗抑郁潜在作用机制。方法 通过中药系统药理学分析平台(TCMSP)数据库、文献挖掘和本实验室已有研究收集香附化学成分,并依据类药原则进行筛选。使用PhamMapper和DrugBank数据库进行靶点预测和筛选,通过MAS 3.0及KEGG通路注释分析香附抗抑郁效应化学成分的作用通路,采用Cytoscape 3.6.1软件构建"化合物-核心靶点-通路"网络,预测其抗抑郁药效成分及相关作用靶点。结果 香附中的69个化合物作用于103个靶点,29个核心靶点。构建的"化合物-核心靶点-代谢通路"网络预测发现,香附中48个化学成分直接或间接作用于15个核心靶点,8条抑郁相关代谢通路,主要涉及细胞过程、对应激的应答等生物过程,通过调节黏附斑、神经营养因子、血管内皮生长因子(VEGF)、促性腺激素释放激素(GnRH)、NOD样受体、胰岛素、趋化因子、ErbB信号通路发挥抗抑郁作用。结论 网络药理学分析结果初步揭示了香附以多成分、多靶点、多通路的协同作用方式发挥抗抑郁效应机制。
[Key word]
[Abstract]
Objective To explore the antidepressant mechanism of Cyperus rotundus L. based on network pharmacology. Methods Compounds of C. rotundus was collected by retrieving throuh TCMSP database, the literatures mining, and existing research of laboratory. The ingredients selected as the research objects were screened according to the generic drug principle. PhamMapper and DrugBank database were then applied to predict the targets. MAS 3.0 software and KEGG pathways were used to annotate the information of targets. Cytoscape 3.6.1 track software was used to construct "ingredients-targets-pathways" network to predict the components and related targets related to antidepressant efficacy. Results Targets predicting analysis showed that 103 targets and 29 core targets were interacted with 69 compounds of C. rotundus. The network analysis indicated that 48 components directly or indirectly interacted with 15 core targets and 8 depression-related metabolic pathways. The above targets were mainly involved in cell processes, responses to stress, and other biological processes, which played an anti-depressive role by regulating the focal adhesion, neurotrophin, VEGF, GnRH, NOD-like receptor, insulin, chemokines, and ErbB signaling pathways. Conclusion The results of network pharmacology analysis preliminarily revealed that the mechanism of anti-depression effect of Cyperus C. rotundus L. through was the synergistic effect of multiple components, multiple targets, and multiple pathways.
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[基金项目]
国家自然科学基金资助项目(81503230)