A Network Pharmacology Approach to Investigate the Active Compounds and Mechanisms of Musk for Ischemic Stroke

Changlin Zhang; Yingdi Liao; Lingling Liu; Yifan Sun; Shaoqin Lin; Jiaying Lan; Hui Mao; Haoxuan Chen; Yuanqi Zhao

doi:10.1155/2020/4063180

A Network Pharmacology Approach to Investigate the Active Compounds and Mechanisms of Musk for Ischemic Stroke

Evid Based Complement Alternat Med. 2020 Jul 3:2020:4063180. doi: 10.1155/2020/4063180. eCollection 2020.

Authors

Changlin Zhang^{1

2}, Yingdi Liao^{1

2}, Lingling Liu^{1

2}, Yifan Sun^{1

2}, Shaoqin Lin^{1

2}, Jiaying Lan^{1

2}, Hui Mao^{1

2}, Haoxuan Chen^{1

2}, Yuanqi Zhao^{1

2

3

4}

Affiliations

¹ The Second Clinical School, Guangzhou University of Chinese Medicine, Guangzhou, China.
² The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
³ State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
⁴ Department of Neurology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.

Abstract

Objectives: This study aims to study the material basis and effective mechanism of musk for ischemic stroke (IS) based on the network pharmacology approach.

Methods: We collected the chemical components and target gene of musk from the BATMAN-TCM analytical platform and identified ischemic stroke-related targets from the following databases: DisGeNET, NCBI-Gene, HPO, OMIM, DrugBank, and TTD. The targets of musk and IS were uploaded to the String database to construct the protein-protein interaction (PPI) network, and then, the key targets were analyzed by topological methods. At last, the function biological process and signaling pathways of key targets were carried out by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and cluster analysis by using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) server and Metascape platform.

Results: A total of 29 active compounds involving 1081 predicted targets were identified in musk and there were 1104 IS-related targets. And 88 key targets of musk for IS were obtained including AKT1, MAPK1/3, TP53, TNF, SRC, FOS, CASP3, JUN, NOS3, and IL1B. The GO and KEGG enrichment analysis suggested that these key targets are mainly involved in multiple pathways which participated in TNF signaling pathway, estrogen signaling pathway, prolactin signaling pathway, neurotrophin signaling pathway, T-cell receptor signaling pathway, cAMP signaling pathway, FoxO signaling pathway, and HIF1 signaling pathway.

Conclusion: This study revealed that the effective mechanisms of musk against IS would be associated with the regulation of apoptosis, inflammatory response, and gene transcription.