Network pharmacological analysis on the active ingredients of Yigan Powder in treating Alzheimer' s disease with depressive disorder

• 作者: Chi Zhao Rong-Juan Guo Fei-Fei Ren Yao Yu Jun-Nan Li Yang Li
• 来源期刊: 海南医科大学学报（英文版）
• 年，卷（期）: 2022,（2）
• 所属期刊栏目: Original article
• 页码范围: 40-47
• 页数: 8页
• 语种: 英文

摘要

Objective: To study the potential therapeutic effect of Yigan Powder on Alzheimer's disease (AD) comorbid Depressive Disorder with Network Pharmacology. Methods: The active ingredients of Yigan Powder were screened from Traditional Chinese Medicine Systems Pharmacology database and analysis platform (TCMSP) by ADME parameters, targets are predicted by Swiss Target Prediction database, disease targets are downloaded from GeneCards, OMIM and PharGKB database. Using R to run GO terms enrichment and KEGG pathway enrichment analysis. Protein interaction data is downloaded from the String database. Cytoscape software is used to build network. AutoDock Vina and PyMOL software are used for molecular docking. Results: There are 125 active ingredients in Yigan Powder with 953 predicted targets, 85 of predicted targets are related to Alzheimer's Disease comorbid Depressive Disorder, shows highly enriched signaling pathways and biological processes. PPI network shows APP, MAPK1 and STAT3 may be important potential treatment of Alzheimer's Disease comorbid Depressive Disorder. The results of AutoDock Vina docking showed that the active ingredients of Yigan Powder had good binding activity with important receptors. Conclusion: Yigan Powder shows effect on neurotransmitter metabolism, synaptic transmission, neuroinflammation and other aspects in the treatment of Alzheimer's Disease comorbid Depressive Disorder.