基于网络药理学与生物信息学预测的大枣抗焦虑、抑郁的潜在活性成分与作用机制研究

目的：通过网络药理学与生物信息学预测与分析大枣抗焦虑抗抑郁的潜在活性成分与作用机制。方法：通过中药系统药理学数据库与分析平台（TCMSP）检索大枣抗焦虑抗抑郁活性成分;结合Therapeutic Target Database（TTD）数据库筛选活性成分潜在的抗焦虑抗抑郁作用靶标,进而构建成分与靶标网络数据库;采用REACTOME（REAC）与g:Profiler软件分别进行GO、KEGG、REAC和WikiPathways（WP）富集分析;最后利用NetworkAnalyst进行蛋白-蛋白相互作用（PPI）和TF-miRNA协同调控网络富集分析。结果：大枣通过(S)-乌药碱、β-胡萝卜素、β-谷甾醇与千金藤啶碱等5种潜在活性成分,通过调控hsa-miR-155和hsa-miR-203等miRNAs与PPARG、CREB1、E2F1-7和SP1等转录因子的表达,进而调控GABRB2、SLC6A4、OPRM1、GABRA1与SLC6A2等基因表达,激活脑源性神经营养因子、血清素受体、γ-氨基丁酸、5-羟色胺、G蛋白偶联受体与受体蛋白酪氨酸激酶等信号通路,影响神经递质释放与传递,起到神经保护作用,发挥抗焦虑、抗抑郁作用。结论：通过生物信息预测并发现了大枣抗焦虑抗抑郁潜在的活性成分、候选靶标和信号通路,为大枣抗焦虑抗抑郁研究提供参考。

Explore the chemical compounds and mechanism of Jujubae Fructus in treating anxiety and depression based on network pharmacology and bioinformatics

Objective: In order to analyze the anti-anxiety and anti-depression ingredients and mechanism of Jujubae Fructus using network pharmacology and bioinformatics analyses.Methods: TCMSP was employed to obtain the anti-anxiety and anti-depressant active ingredients of Jujubae Fructus. TTD was adopted to study the potential targets of these poetical active ingredients. A network of components and targets was established using TCMSP and TTD. GO, KEGG, REAC and WikiPathways (WP) enrichment analyses were carried out with REACTIOME and g:Profiler. PPI and TF-miRNA coregulatory network analyses were made using NetworkAnalyst. Results: Five potential active ingredients of Jujubae Fructus, such as (S)-coclaurine, beta-carotene, beta-sitosterol and stepholidine, could regulate the gene expression of ABRB2, SLC6A4, OPRM1, GABRA1 and SLC6A2 etc. through coregulation of hsa-miR-105 and hsa-miR-203 etc. and the TFs, such as PPARG, CREB1, E2F1-7 and SP1. The active components of Jujubae Fructus may regulate the release and transmission of neurotransmitters, play key roles in the protection of nerve cells anti-anxiety and anti-depression through the signaling of BDNF, serotonin, GABA, 5-HT, GPCR and ERBB4.Conclusion: The potential anti-anxiety and anti-depressant active components, targets and signaling of Jujubae Fructus were predicted through network pharmacology and bioinformatics analyses, which can provide a cornerstone for studying of the anti-anxiety and anti-depressant effects of Jujubae Fructus.