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Exploring the mechanism of Yishen Daluo decoction in the treatment of multiple sclerosis based on network pharmacology and in vitro experiments

Authors :
Shuo Cheng
Ce Zhang
Qingyuan Cai
Xinghua Wang
Zhaoheng Liu
Peng Wei
Xu Wang
Yan Tan
Qian Hua
Source :
Journal of Traditional Chinese Medical Sciences, Vol 10, Iss 2, Pp 186-195 (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Objective: To explore the mechanism and related active components of Yishen Daluo decoction (YSDLD) in treating multiple sclerosis (MS). Methods: Targets of YSDLD were collected through the TCMSP, Chemistry, and TCMID databases. The MS targets were collected through OMIM, DrugBank, Gencards, TTD, and Pharmgkb databases. We built “component–target” network diagrams and protein–protein interaction (PPI) diagrams and performed topological analysis. The targets were subjected to GO and KEGG enrichment analysis. Molecular docking verification was conducted on selected targets and molecules. Finally, in vitro experiments were conducted. BV2 cells were induced by lipopolysaccharide for model establishment. CCK8 experiment was conducted to explore the effect of YSDLD and RT-qPCR technology was used to explore the expression of key targets. Results: There were 184 active components in YSDLD and 898 targets of its action. There were 940 MS targets, and 215 targets were shared by YSDLD and MS. According to the “component–target” diagram, the top five key components included quercetin, kaempferol, beta-sitosterol, stigmasterol, and naringenin. IL-6, IL-1β, TNF-α, AKT1, and VEGFA were the important targets identified by PPI network topology analysis. A total of 564 functions were identified by GO enrichment analysis (P

Details

Language :
English
ISSN :
20957548
Volume :
10
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Journal of Traditional Chinese Medical Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.b7eaf38e144543d0bcc28e95793306d6
Document Type :
article
Full Text :
https://doi.org/10.1016/j.jtcms.2023.03.002