Abstract

Ethnopharmacological relevance Salvia miltiorrhiza Bunge and Panax ginseng C. A. Meyer have special curative effect on cancer treatment. The optimizing component formula (OCF) extracted from those two herbs was in line with the anti-lung cancer treatment principle of activating blood and supplementing ‘Qi’. However, the study on the mechanism of component formula has always been an insurmountable challenge. Nowadays, the application of network pharmacology and artificial intelligence (AI) in the field of TCM provides new ideas for the study of new targets and mechanisms of TCM, which promotes the modernization of TCM. Aim of the study This study aims to further explore the anti-lung cancer mechanism of OCF by using an integrated strategy of network pharmacology and AI technology. Materials and methods Bioinformatic analysis was used to analyze the expression levels, prognosis and survival of DTL and PDCD4 in cancer patients. The binding strength of OCF and DTL was simulated by molecular docking, and the affinity between them was detected by Bio-layer interferometry. Network pharmacology was used to predict the active components, potential targets and pathways of OCF. The association between key targets and their corresponding components and DTL was analyzed by Ingenuity Pathway Analysis (IPA). MTT assay, colony formation assay, wound-healing assay and transwell assay were used to verify the inhibitory effects of OCF on lung cancer cells in vitro . qRT-PCR and Western blot assay were used to detect the effects of OCF on mRNA and protein expression of DTL, PDCD4 and key genes in MAPK/JNK pathways. Results Bioinformatics analysis showed that DTL was significantly up-regulated in lung cancer, which was associated with high malignancy rate, high metastasis rate and poor prognosis of primary tumor. PDCD4 was down-regulated in lung cancer, and associated with high metasta