Objective:To investigate the pharmacodynamic material basis,mechanism of actions and targeted diseases of Salicornia europaea L.(SE)based on the network pharmacology method,and to verify the antidepressant-like effect of the SE extract by pharmacological experiments.Methods:Retrieval tools including Chinese medicine(CM),PubMed,PharmMapper,MAS 3.0 and Cytoscape were used to search the components of SE,predict its targets and related therapeutic diseases,and construct the"Component-TargetPathway"network of SE for central nervous system(CNS)diseases.Further,protein-protein interaction(PPI)network,Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)function annotation of depression-related targets were analyzed to predict the antidepressant mechanism of SE.Chronic unpredictable mild stress(CUMS)model was used to construct a mouse model with depression-like symptoms.And the animals were randomly divided into 6 groups(n=10)including the normal group(nonstressed mice administered with distilled water),the CUMS group(CUMS mice administered with distilled water),the venlafaxine group(CUMS mice administered with venlafaxine 9.38 mg/kg),SE high-,medium-,and low-dose groups(CUMS mice administered with SE 1.8,1.35 and 0.9 g/kg,respectively).Then some relevant indicators were determined for experimental verification by the forced swim test(FST),the tail suspension test(TST)and open-field test(OFT).Dopamine(DA)concentration in hippocampus and cerebral cortex,IL-2 and corticosterone(CORT)levels in blood,and nuclear factor E2 related factor 2(Nrf2),kelch-like epichlorohydrin related protein 1(Keap1),NAD(P)H dehydrogenase[quinone]1(NQO1)and heme oxygenase-1(HO-1)levels in mice were measured by enzyme linked immunosorbent assay(ELISA)and Western blot respectively to explore the possible mechanisms.Results:The"target-disease"network diagram predicted by network pharmacology,showed that the potential target of SE involves a variety of CNS diseases,among which depression accounts for the majority.The experimental results
SUN Dan-chenWANG Ran-ranXU HaoZHU Xue-huiSUN YanQIAO Shi-qingQIAO Wei
