目的 基于網絡藥理學方法研究香附多成分-多靶點-多途徑的抗抑郁潛在作用機制。方法 通過中藥系統(tǒng)藥理學分析平臺（TCMSP）數(shù)據(jù)庫、文獻挖掘和本實驗室已有研究收集香附化學成分，并依據(jù)類藥原則進行篩選。使用PhamMapper和DrugBank數(shù)據(jù)庫進行靶點預測和篩選，通過MAS 3.0及KEGG通路注釋分析香附抗抑郁效應化學成分的作用通路，采用Cytoscape 3.6.1軟件構建"化合物-核心靶點-通路"網絡，預測其抗抑郁藥效成分及相關作用靶點。結果 香附中的69個化合物作用于103個靶點，29個核心靶點。構建的"化合物-核心靶點-代謝通路"網絡預測發(fā)現(xiàn)，香附中48個化學成分直接或間接作用于15個核心靶點，8條抑郁相關代謝通路，主要涉及細胞過程、對應激的應答等生物過程，通過調節(jié)黏附斑、神經營養(yǎng)因子、血管內皮生長因子（VEGF）、促性腺激素釋放激素（GnRH）、NOD樣受體、胰島素、趨化因子、ErbB信號通路發(fā)揮抗抑郁作用。結論 網絡藥理學分析結果初步揭示了香附以多成分、多靶點、多通路的協(xié)同作用方式發(fā)揮抗抑郁效應機制。

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.

國家自然科學基金資助項目（81503230）