网络药理学联合分子对接技术分析高良姜治疗抑郁症的可能机制

目的　借助网络药理学联合分子对接技术探讨高良姜治疗抑郁症的作用机制。方法　通过TCMSP数据库检索高良姜有效成分及靶点,使用GeneCards数据库获取抑郁症疾病靶点基因,利用STRING数据库和Cytoscape 3.9.1 软件构建PPI网络图并获取蛋白互作关系,筛选出高良姜治疗抑郁症的核心靶点;借助David数据库对相交靶点进行GO功能分析以及KEGG通路富集分析,得到高良姜治疗抑郁症的潜在作用通路。结果　筛选出高良姜 13 种活性成分和 169个高良姜治疗抑郁症的潜在作用靶点,包括JUN、MAPK1、AKT1、RELA、ESR1、IL6、MAPK14、MAPK8、RXRA等核心靶点;GO功能解析得到 654 个生物相关过程、85 个细胞组分及 147 个分子功能;KEGG富集解析获得 171 条相关通路,分子对接验证了核心靶点与高良姜主要成分具有较强结合力。结论　高良姜可通过多个靶点、多条通路治疗抑郁症。

Possible mechanism of galangal on depression using network pharmacology and molecular docking

Objective To investigate the potential mechanism of galangal on depression based on network pharmacology and molecular docking. Methods The active ingredients and targets of galangal, and target genes of depression were searched from TCMSP and GeneCards databases, respectively. Protein interactions and PPI network diagram were obtained and constructed by STRING database and Cytoscape 3.9.1 software, respectively. The core targets of galangal for depression were screened, and their potential pathways were analyzed using GO function and KEGG enrichment analyses. Results Thirteen active ingredients and 169 potential targets including JUN, MAPK1, AKT1, RELA, ESR1, IL6, MAPK14, MAPK8, and RXRA were screened for depression treatment. GO analysis revealed 654 biological processes, 85 cellular components and 147 molecular functions. KEGG analysis uncovered 171 signaling pathways. Molecular docking results showed a strong binding ability between main core targets and ingredients. Conclusion Ggalangal may treat depression through multiple targets and pathways.