The potential targets and pathways of action of artesunate against non-small cell lung cancer were investigated in this study. The two-dimensional chemical structure of artesunate was determined using Pubchem. Several databases, including Swiss Target Prediction, Pharm Mapper, Gene Cards, and OMIM, were used to identify the targets for artesunate and non-small cell lung cancer. Venny online software was used to identify the shared targets between the two drugs, while the STRING database provided the protein-protein interaction network. A "drug component-target-disease" network was created using Cytoscape software. Through the analysis of the OMIM databases, 3280 non-small cell lung cancer disease targets were identified. The potential effects of artesunate against non-small cell lung cancer were determined by finding the intersection of the targets for artesunate and non-small cell lung cancer. GO enrichment analysis using David's database revealed common targets and identified 46 biological pathways that were affected. Further analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified 81 major pathways. The study also conducted molecular docking studies of six important molecules with artesunate, and it was found that all of them displayed strong binding activity. This information suggests that artesunate may have a significant impact on non-small cell lung cancer through its interaction with these key targets. In conclusion, the use of network pharmacology and molecular docking allowed for the prediction of the target and signaling pathway of artesunate against non-small cell lung cancer. These findings provide a scientific basis for further investigation into the anti-non-small cell lung cancer actions of artesunate.

Liu Qi, Shen Faqian, Ma Hu. Exploring the mechanism of action of artesunate against non-small cell lung cancer based on network pharmacology and molecular docking. Frontiers in Medical Science Research (2024), Vol. 6, Issue 2: 98-107. https://doi.org/10.25236/FMSR.2024.060215.

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