AIM: To predict the active components and targets of Piperlongum L. and the associated signaling pathways involved in pulmonary fibrosis using network pharmacology and molecular docking technique and evaluate the mechanism of Piperlongum L against pulmonary fibrosis by in vitro experiments. METHODS: The active ingredients and targets were retrieved from TCMSP, Swiss Target Prediction and PubChem databases. The disease-related targets were retrieved from GeneCards and OMIM databases. The intersection targets of the drugs and disease-related targets were identified using jvenn online tool. String database was used to construct the "drug-component-target" and PPI network and the networks were visualized using Cytoscape 3.9.1 software. GO and KEGG enrichment analysis were performed on the intersection targets using the DAVID tool. The top 20 KEGG pathways, core targets and drug components were used to construct a "component-target-pathway" network and the network visualization was performed using Cytoscape 3.9.1 software. The interactions between drug compounds and the targets were evaluated by molecular docking, and the docking results were visualized using Discovery studio. HFL-1 cells were cultured and the effect of the drug compounds on cell viability was determined by MTT assay. The inhibition rate was then calculated to determine the optimal drug concentration. HFL-1 cells were cultured in vitro and were assigned into 4 groups: control group, TGF-β1 group, TGF-β1+LD group (LD group), TGF-β1+HD group (HD group). CCK-8 kit was used to evaluate the antiproliferative activity of the drug compounds against HFL-1 cells at 24, 48 and 72 h. Plate clone formation assay was performed to evaluate the effect of drugs on the colony formation ability of HFL-1 cells. RT-qPCR and western blot were conducted to determine the effect of the compounds on the mRNA and protein expression levels of α-smooth muscle actin (α-SMA), collagen type I (COI-I), and collagen type III (COI-III) in each group. RESULTS: A total of 197 intersection targets of Piperlongum L and anti-pulmonary fibrosis were identified. The core PPI network comprised 29 nodes (targets) and 199 edges (interactions). GO functional analysis showed that the significantly enriched biological processes associated with the compounds in Piperlongum L included negative regulation of apoptosis, signal transduction, and protein phosphorylation. Significantly enriched cellular components included cytoplasm, nuclear cytoplasm, plasma membrane. Enriched molecular functions associated with the compounds included the same protein binding, serine/threonine/tyrosine kinase activity, and protein binding. A total of 155 significantly enriched KEGG signaling pathways were identified, with PI3K-Akt signaling pathway was highly associated with PF and was the fourth most enriched pathway. PIK3CA, MAPK3, MAPK1, MTOR, SRC, CCND1, EGFR, PRKCA, BCL2, and GSK3B had the highest connectivity in the components-target-pathway network. Piperlongine, N-(2, 5-dimethoxyphenyl) -4-methoxybenzamide, tetrahydrotanshinone, pisigenin and piperine were the key compounds in Piperlongum L. The molecular docking results showed that all the compounds except N-(2,5-dimethoxyphenyl)-4-methoxybenzamide had good binding activities with interactions observed with 10 proteins. The proliferation ability of the cells in the LD group was significantly lower than that of the TGF-β1 group at 48 h and 72 h (P<0.05). The proliferation ability of cells HD group was significantly lower than the LD group at 24, 48 and 72 h. The number of clones in each drug group was significantly reduced after treatment with the drugs (P<0.05). The mRNA and protein expression levels of α-SMA, COI-I, COI-III in LD and HD groups were significantly lower than the expression levels in the TGF-β1 group. The protein expression levels of p-PI3K/PI3K and p-Akt /AKT were significantly lower in the two dose groups compared with the TGF-β1 group (P<0.01). CONCLUSION: The results showed that the effect of Piperlongum L against PF is probably through modulation of the PI3K-Akt signaling pathway.
