Rheum palmatum
L. (RPL) is a known traditional herbal medicine with the functions of “
heat-clearing and damp-drying
” in traditional Chinese medicine. Its anti-cancer effect against lung cancer has been confirmed previously, but the related mechanisms and active substances for its action has been little studied. This study adopted the network pharmacology, built the network map of drug ingredients and disease targets (DDN), and discussed the effective components of RPL and its possible mechanisms. All constituents of RPL were collected through database search and literature mining, and the potential active constituents were screened. The inverse pharmacophore matching model was used to predict the targets of active ingredients, and the method was supplemented by database retrieval and literature mining. Compounds-target data were inputted into Cytoscape software to build the DDN of RPL, and functional annotation analysis and pathway enrichment analysis were carried out. Finally, 20 active compounds were screened, which acted on 817 targets. A total of 22,418 lung cancer-related targets were collected, and 761 overlapped with drug targets. By bioinformatics annotation of these overlapping genes, a total of 235 gene ontology (GO) functional annotation analyses and 46 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were obtained. It was found that the enrichment of GO and KEGG was associated with apoptosis, suggesting RPL plays an anti-lung cancer role
via
inducing cell apoptosis. Subsequent cell experiment results showed RPL and its active constituents inhibited the proliferation of A549 cells and reduced clone formation rate of A549 cells
via
induction of apoptosis. In this study, the pharmacodynamic basis and mechanism of RPL against lung cancer were studied from the perspective of systematic pharmacology, which would be beneficial for further elucidating the anticancer effect of RPL on lung cancer.