Mechanism of Kai Xin San in the treatment of Alzheimer's disease based on network pharmacology
10.16438/j.0513-4870.2018-0474
- VernacularTitle:基于网络药理学的开心散治疗阿尔茨海默病的作用机制分析
- Author:
Yue SHI
1
;
Ying-jia YAO
1
;
Ying LIN
1
;
Xi-cai LIANG
1
;
Ying-nan NI
1
;
Yu-tong WU
1
;
Jing-xian YANG
1
Author Information
1. Liaoning University of Traditional Chinese Medicine, Dalian 116600, China
- Publication Type:SPECIAL REPORTS
- Keywords:
Kai Xin San;
Alzheimer;
network pharmacology;
target;
molecular docking
- From:
Acta Pharmaceutica Sinica
2018;53(9):1458-1466
- CountryChina
- Language:Chinese
-
Abstract:
The study was designed to explore the active components and mechanism of Kai Xin San in the treatment of Alzheimer's disease (AD) based on network pharmacology. All targets related to AD were researched in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Therapeutic Targets Database (TTD). The common targets obtained by two databases were determined as candidate proteins involved in AD. All active components related to Kai Xin San were researched from ADME (absorption, distribution, metabolism and excretion). PharmMapper was used to obtain the primary candidate targets of Kai Xin San. The corresponding gene name of each target protein was obtained from the UniProt database and selected human target proteins. Finally, the target proteins related to AD by Kai Xin San were acquired; Cytoscape 3.5.1 was used to construct the topology analysis for the active ingredient-AD target interaction network of Kai Xin San. According to STRING database and DAVID annotation databases, Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the targets was performed. The network pharmacology analysis results were verified by Discovery Studio molecular docking software. There were 31 components meeting the conditions of ADME and 8 targets relating to AD. Thirteen kinds of biological process, 7 related to molecular function and 11 related to cellar components, were included in 31 GO entries. There were 5 KEGG pathways, involving the calcium signaling pathway and PI3K-Akt signaling pathway. The docking results of Discovery Studio showed that active ingredients of Kai Xin San and the positive controls all have good binding activity with important targets. In conclusion, the Kai Xin San as applied for treating AD has the advantages of multi-components and targets, to investigate the active components and mechanism of Kai Xin San for treating AD based on network pharmacology to eludicate possible studies of the mechanisms of action.
