Mechanism of Salvia miltiorrhiza in the treatment of periodontitis: integrative analyses via network pharmacology, molecular dynamics, and cellular assays.

Background: Periodontitis is the primary cause of tooth loss in adults and is associated with cardiovascular disorders and type 2 diabetes, etc., significantly impairing patients' quality of life. Salvia miltiorrhiza(S. miltiorrhiza), a traditional Chinese medicine, possesses properties such as anti-inflammatory and antioxidative effects and has potential in the treatment of periodontitis; however, its mechanism of action remains unclear. The aim of this study was to investigate the therapeutic mechanism of S. miltiorrhiza in periodontitis using an integrated approach combining network pharmacology, molecular docking, molecular dynamics simulations, and experimental validation.

Methods: The active components and target genes of Salvia miltiorrhiza were collected from the TCMSP and SwissTargetPrediction databases, while the target genes of periodontitis were obtained from the GeneCards, OMIM, Disgenet, and DrugBank databases. The intersection of these targets was identified using jvenn, followed by network visualization using STRING and Cytoscape 3.10.2 software. CytoNCA plug-ins were used to calculate node scores and identify hub genes. The DAVID database was used to conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Molecular docking and molecular dynamics simulation were employed to evaluate the affinity and stability between key active compounds of S.miltiorrhiza and the hub genes. A RAW264.7 cell model induced by Pg-LPS (Porphyromonas gingivalis-lipopolysaccharide) was established. A CCK-8 assay was used to determine the effects of S.miltiorrhiza on the viability of RAW264.7 cells, thereby screening for appropriate drug concentrations. The Griess method was used to test the effect of S. miltiorrhiza on nitric oxide (NO) in cells. The mRNA expression levels of inflammation-related factors were detected by RT-qPCR.

Results: A total of 65 compounds from S. miltiorrhiza and 132 corresponding target genes were identified, along with 1900 periodontitis-related target genes. The intersection of these targets revealed 60 common targets. PPI network analysis revealed that S. miltiorrhiza may alleviate periodontitis by modulating key genes, including IL-6, BCL2, STAT3, TNF, TP53, CASP3, and MMP9. Molecular docking indicated strong binding affinities between the bioactive compounds in S. miltiorrhiza and these critical targets. Functional enrichment analysis suggested that the anti-inflammatory action of S. miltiorrhiza in periodontitis may involve the regulation of pathways such as AGE-RAGE, TNF and PI3k/AKT1 pathways. The results of cell experiments revealed that S. miltiorrhiza could treat and prevent periodontitis by inhibiting NO production and regulating the mRNA expression of inflammatory factors, including IL-1β, TNF, IL-6, and IL-10.

Conclusion: S. miltiorrhiza exerts therapeutic effects on periodontitis via multiple components, targets and pathways, which provides a sufficient theoretical and practical basis for the further study of S. miltiorrhiza in the treatment of periodontitis.