Network pharmacology study on anti-stroke of Xiaoshuan Tongluo formula based on systematic compound-target interaction prediction models
10.16438/j.0513-4870.2019-0521
- VernacularTitle:基于系统的化合物-靶点相互作用预测模型的消栓通络方抗脑卒中网络药理学研究
- Author:
Yi-fu ZHENG
1
,
2
;
Ling-lei KONG
1
;
Hao JIA
1
;
Bao-yue ZHANG
1
;
Zhe WANG
1
;
Lü-jie XU
1
;
Ai-liu LIU
1
;
Guan-hua DU
1
Author Information
1. Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
2. College of Pharmacy, Wuhan University, Wuhan 430072, China
- Publication Type:Research Article
- Keywords:
Xiaoshuan Tongluo formula;
stroke;
rug target;
machine learning;
molecular docking;
virtual screening;
network pharmacology
- From:
Acta Pharmaceutica Sinica
2020;55(2):256-264
- CountryChina
- Language:Chinese
-
Abstract:
Xiaoshuan Tongluo formula is effective in treating mental retardation and speech astringency caused by cerebral thrombosis, but its mechanism remains unclear. In this investigation, by collecting the chemical constituents from Xiaoshuan Tongluo formula and the targets related to stroke, we obtained 1 251 constituents from the formula and 10 drug targets related with stroke. We established 18 prediction models of compound-target interaction for 10 stroke-related targets, using molecular docking method and machine learning methods includes Naive Bayesian and recursive partitioning based on the input of molecular fingerprints and molecular descriptors. Using these models, we predicted the active chemical constituents from Xiaoshuan Tongluo formula and their drug targets, 153 potential active constituents were discovered, 22 among them could interact with at least two drug targets related with stroke. On this basis, the chemical constituent-target network was constructed using network construction software, and then the important metabolic pathways of the targets were identified by using Gene-Ontology (GO) enrichment analysis, such as blood coagulation, positive regulation of angiogenesis, positive regulation of ion transport and so on. On this basis, a target-pathway network was constructed. In conclusion, using machine learning, molecular docking, virtual screening, data mining and network construction, this study explored and partially revealed the active chemical constituents and chemical constituent-target-pathway network action mechanism of Xiaoshuan Tongluo formula against stroke, which will provide important information for its further study.
