Integrating network pharmacology, molecular docking, and bioinformatics to explore the mechanism of sparganii rhizoma in the treatment of laryngeal cancer.

Sparganii Rhizoma (SR) has demonstrated promising anticancer effects across various malignancies; however, its mechanisms in laryngeal cancer (LC) remain poorly understood. This study employs network pharmacology and molecular docking to investigate the molecular mechanisms underlying SR's therapeutic effects on LC, providing novel insights for its potential use in treatment. Active compounds and targets of SR were identified through the TCMSP and Pharmmapper databases, while LC-related targets were sourced from GEO, GeneCards, OMIM, and PharmGkb databases. A Venn diagram generated from these datasets highlighted 58 overlapping targets. The STRING database and Cytoscape 3.9.1 software facilitated the construction of a protein-protein interaction network for these targets, and R language analysis revealed 15 core targets. GO and KEGG enrichment analyses, conducted with the ''clusterProfiler'' package, identified relevant biological processes, cellular components, and molecular functions associated with LC treatment. KEGG analysis suggested SR primarily regulates pathways such as TNF, IL-17, and P53. Molecular docking confirmed SR's ability to bind effectively to the 15 core targets. Molecular dynamics simulations further validated stable protein-ligand interactions for MAPK1, GSK3B, and MAPK14. Core target validation across transcriptional, translational, and immune infiltration levels was performed using GEPIA, HPA, cBioPortal, and TIMER databases. In conclusion, network pharmacology, molecular docking, and dynamics simulations provided insights into SR's mechanism in LC treatment, forming a theoretical basis for further investigation of its therapeutic potential.