Network pharmacology-based prediction and verification of the molecular targets and pathways for schisandrin against cerebrovascular disease

AimTo illuminate the molecular targets for schisandrin against cerebrovascular disease based on the combined methods of network pharmacology prediction and experimental verification.MethodA protein database was established through constructing the drug-protein network from literature mining data. The protein-protein network was built through an in-depth exploration of the relationships between the proteins. The computational platform was implemented to predict and extract the sensitive sub-network with significant P-values from the protein-protein network. Then the key targets and pathways were identified from the sensitive sub-network. The most related targets and pathways were also confirmed in hydrogen peroxide (H2O2)-induced PC12 cells by Western blotting.ResultsTwelve differentially expressed proteins (gene names: NFKB1, RELA, TNFSF10, MAPK1, CHUK, CASP8, PIGS2, MAPK14, CREB1, IFNG, APP, and BCL2) were confirmed as the central nodes of the interaction network (45 nodes, 93 edges). The NF-κB signaling pathway was suggested as the most related pathway of schisandrin for cerebrovascular disease. Furthermore, schisandrin was found to suppress the expression and phosphorylation of IKKα, as well as p50 and p65 induced by H2O2 in PC12 cells by Western blotting.ConclusionThe computational platform that integrates literature mining data, protein-protein interactions, sensitive sub-network, and pathway results in identification of the NF-κB signaling pathway as the key targets and pathways for schisandrin.