Objective  To explore the potential targets and mechanisms of Scutellaria baicalensis in the treatment of primary biliary cholangitis (PBC) based on network pharmacology, molecular docking and molecular dynamics simulation.

Methods  The active components and corresponding targets of Scutellaria baicalensis were screened out by TCMSP, and the targets were standardized by UniPort database. GeneCards database was used to screen targets related to PBC. The intersection targets of Scutellaria baicalensis and PBC were selected and imported into STRING database to construct protein-protein interaction network. Cytoscape software was used to construct drug-disease target network map. The DAVID bioinformatics resource was utilized to conduct functional annotation analysis on core targets, followed by the application of computer-aided drug design techniques to validate the binding characteristics of key active components with target proteins.

Results  Network pharmacological analysis showed that the core active components of Scutellaria baicalensis in treating PBC were acacetin, wogonin, baicalin, 5,7,4'-trihydroxy-8-methyldihydroflavone and nor wogonin, and the core targets were tumor protein p53 (TP53), tumor necrosis factor (TNF), protein kinase B1 (AKT1), RELA, and interleukin (IL)-6. The treatment of PBC was mainly through signal pathways such as cancer, inflammation, diabetes mellitus, virus infection, apoptosis and aging, PI3K-AKT and IL-17. Molecular docking results suggest that the core target has strong binding force with the active ingredients of the core drug. Molecular dynamics simulation further confirmed that TP53 formed stable and strong binding with scutellarin and norwogonin.

Conclusion  The active components and possible mechanism of Scutellaria baicalensis in the treatment of PBC were preliminarily revealed, which provided scientific reference for further study on the effective substance basis, mechanism and clinical application. The conclusions obtained in this study are based on computational simulation predictions and still require subsequent experimental verification.

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