Objective: We aim to explore the potential anti-HCC mechanism of Scutellaria barbata  through integrated bioinformatics analysis.
Methods: We searched active ingredients and related targets of Scutellaria barbata  via TCMSP database, PubChem and SwissTargetPrediction database. Then, we identified HCC disease targets from GEO dataset by WGCNA. Next, the intersected targets of disease targets and drug targets were input into STRING database to construct PPI networking in order to obtain potential therapeutic targets of Scutellaria barbata . Cytoscape software was used to carry out network topology analysis of potential targets. We used the R package for GO analysis and KEGG analysis. Finally, we used AutoDock vina and PyMOL software for molecular docking.
Results: Sixteen active components from Scutellaria barbata  were lastly selected for further investigation. A total of 442 component targets were identified from 16 active ingredients of Scutellaria barbata  after the removal of duplicate targets. GSE45436 was selected for construction of WGCNA and screening of differentially expressed genes. A total of 354 genes were up-regulated in HCC samples and 100 were down-regulated in HCC patients. Twenty-one common genes were obtained by intersection and 10 critical targets were filtered for further investigation. The enrichment analysis showed that cell cycle, DNA replication, p53 signaling pathway were mainly involved. The molecular docking results showed that 4 potential combinations were with the best binding energy and molecular interactions.
Conclusion: AURKB, CHEK1 and NEK2 could be the potential target proteins of Scutellaria barbata  in treating HCC. Cell cycle, DNA replication, p53 signaling pathway consist of the fundamental regulation cores in this mechanism.
Keywords: Scutellaria barbata , hepatocellular carcinoma, effector mechanism, network pharmacology, bioinformatics analysis, molecular docking