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Gene Network Mechanism of Zhilong Huoxue Tongyu Capsule in Treating Cerebral Ischemia–Reperfusion

Na Li, Jie Sun, Ji-Lin Chen and 3 more

Frontiers in Pharmacology · 2022

doi:10.3389/fphar.2022.912392 (opens in a new tab)

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Abstract

Objective: To investigate the effect of Zhilong Huoxue Tongyu capsule (ZLH) in the treatment of cerebral ischemia–reperfusion injury and determine the underlying molecular network mechanism.Methods: The treatment effect of Zhilong Huoxue Tongyu capsule (ZLH) was evaluated for cerebral ischemia–reperfusion injury in middle cerebral artery occlusion (MACO) rat, and the underlying molecular network mechanism was explored by using molecular network analysis based on network pharmacology, bioinformatics including protein–protein interaction (PPI) network, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG), as well as molecular docking.Results: The neurological function of rats in the ZLH group was significantly improved compared to those in the NS group (p = 0.000), confirming the positive effect of ZLH for the treatment of brain ischemia. There were 126 intersecting genes screened in ischemia–reperfusion cerebrum that are associated with several important biological processes, such as lipopolysaccharide, and the most important cell component, such as raft, as well as the most important molecular function pointed as cytokine receptor binding. The most important KEGG signaling pathway was the AGE-RAGE signaling pathway in diabetic complications. Moreover, according to the STRING interaction in the PPI network, 10 hub genes including MAPK14, FOS, MAPK1, JUN, MYC, RELA, ESR1, STAT1, AKT1, and IL6 were selected and exhibited in Cytoscape and molecular docking. Lastly, the relation between PPI, GO, and KEGG was analyzed. These findings indicated that multiple hub network genes have been involved in behavior improvement in cerebral ischemia–reperfusion rats subjected to ZLH treatment.Conclusion: Zhilong Huoxue Tongyu capsule improves cerebral ischemia–reperfusion and is associated with multiple network gene expressions.

Abstract licence: CC BY

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