OBJECTIVE:To decipher the antidepressant targets and mechanisms of Huangqin (Radix Scutellariae Baicalensis) (RSB) by a novel computational system based on prediction and experimental verification.METHODS:The putative targets of RSB against de-pression were identified from Traditional Chinese Medicine Systems Pharmacology (TCMSP) and DrugBank.Next,protein-protein interaction net-work of the anti-depression targets of RSB were identified,and differentially expressed genes(DEGs) of depression were mined from the NCBI da-tabase.Then,Kyoto Encyclopedia of Genes and Ge-nomes and Gene Ontology were used to analysis the common targets.Finally,the selected pathways and functions were verified by experimentation.RESULTS:Thirty active compounds in RSB were pre-dicted with high confidence by TCMSP and Drug-Bank,and seventy-one DEGs were identified in the GEO database.Besides,eight core target proteins were screened out by descending order of degree value,including ACHE,IL6,SLC6A4,FOS,SLC6A3,MAOB,DPP4,and JUN.These target genes were fur-ther found to be associated with pathways in-volved in neuronal apoptosis,such as pathways in cancer,Toll-like receptor signaling pathway,and TNF signaling.The cell proliferation assay and wound-healing assay results showed that RSB does not affect PC12 cell proliferation and chemo-taxis.Unexpectedly,RSB protected PC12 cells from oxidative stress induced by H2O2 via inhibit-ing autophagy and apoptosis.We revealed signifi-cant changes in mice treated with 400 mg/kg RSB compared with the lipopolysaccharide mice.The possible mechanism for the antidepressive action of RSB is by reducing the expression of LC3-B in CA1 neurons.CONCLUSIONS:Our research partially expounds the mechanism of the antidepressant effect of RSB by the combination of network pharmacology pre-diction and experimental verification.Furthermore,it is also conducive to the application of Traditional Chinese Medicine within modern medicine.