<p>This study aims to comprehensively apply network toxicology and molecular dynamics simulation techniques to investigate the molecular mechanisms of DNBaP-induced lung cancer. We first predicted the toxicological characteristics of DNBaP related to carcinogenicity. Subsequently, by integrating multiple databases, 71 potential cross-targets of DNBaP-induced lung cancer were screened. GO analysis and KEGG pathway enrichment analysis of these targets verified their functions in biological processes and signaling pathways, further confirming their association with lung cancer. Using these potential cross-targets, a STRING interaction network was constructed, and five core genes were identified through Cytoscape software. Molecular docking was performed to predict the binding affinity between DNBaP and these core genes. Finally, molecular dynamics simulations were conducted to further validate the stability of the complexes and infer how the biological functions of the protein structures are affected after complex formation. This study systematically reveals the molecular mechanism of DNBaP-induced lung cancer: it disrupts intracellular homeostasis by interfering with core genes (CDKN2A, EGFR, ESR1, TNF, TP53) and activating key signaling pathways such as PI3K-Akt and MAPK. The research demonstrates the effectiveness and feasibility of integrating network toxicology, molecular docking, and molecular dynamics simulation techniques in assessing the toxic mechanisms of environmental pollutants. It provides an important theoretical basis and scientific methodology for understanding the health risks of DNBaP, screening new targets for lung cancer intervention, and developing preventive strategies.</p><p></p>