Network pharmacology and molecular docking reveal mechanisms of amiodarone-induced pulmonary fibrosis

Background Pulmonary fibrosis is a common terminal outcome of various chronic lung diseases, characterized by excessive extracellular matrix deposition, alveolar structural destruction, and progressive loss of pulmonary function. Despite advances in understanding its pathogenesis, effective therapeutic options remain scarce, highlighting the need for novel strategies. Amiodarone, a widely prescribed antiarrhythmic drug, is associated with pulmonary fibrosis as a severe adverse effect; however, its molecular mechanisms remain incompletely understood. Network pharmacology, combined with molecular docking, has recently emerged as a powerful approach to systematically uncover key targets and pathways underlying drug-induced organ toxicity. This study aimed to elucidate the potential mechanisms of amiodarone-induced pulmonary fibrosis by integrating network pharmacology analysis, molecular docking, and experimental validation, thereby providing a theoretical basis for its prevention and treatment. Methods Network pharmacology and molecular docking approaches were applied to explore the mechanisms of amiodarone-induced pulmonary fibrosis. Potential amiodarone targets were predicted using publicly available databases, while pulmonary fibrosis-related genes were retrieved from GeneCards, DisGeNET, and OMIM. Common drug–disease targets were identified through Venn diagram analysis. Protein–protein interaction (PPI) networks were constructed using STRING, and hub genes were determined through topological analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to identify biological processes and pathways involved. Molecular docking was performed to assess the binding affinity of amiodarone to key hub proteins. Finally, the predicted mechanisms were validated through in vitro and/or in vivo pulmonary fibrosis models. Results A total of 101 KEGG pathways were enriched for the intersection of amiodarone and pulmonary fibrosis targets. PPI network analysis identified eight key hub genes: ABCB1 , ERBB2 , XIAP , ABL1 , SRC , HIF1A , AKT1 , and ADRB2 . GO enrichment analysis indicated that these targets are primarily involved in membrane-to-nucleus signaling, regulation of phosphorylation, and chromatin remodeling. KEGG pathway analysis highlighted significant enrichment in neuroactive ligand–receptor interaction, FoxO signaling, and Th17 cell differentiation pathways. Molecular docking demonstrated strong binding affinities between amiodarone and the predicted target proteins, with ABCB1 and AKT1 exhibiting the highest affinity (Kd = 0.37 μM each), followed by ERBB2 (2.9 μM) and ADRB2 (7.0 μM). Collectively, these findings suggest a signaling framework in which membrane receptor activation propagates through tyrosine kinase cascades to regulate gene expression, there by linking extracellular stimuli to transcriptional regulation in the pathogenesis of pulmonary fibrosis. Conclusions This study systematically elucidates the molecular mechanisms underlying amiodarone-induced pulmonary fibrosis by integrating network pharmacology, enrichment analysis, and molecular docking. Eight hub targets ( ABCB1, ERBB2, XIAP, ABL1, SRC, HIF1A, AKT1, and ADRB2 ) and three critical signaling pathways (neuroactive ligand–receptor interaction, FoxO signaling, and Th17 cell differentiation) were identified, providing new insights into the complex mechanisms of amiodarone-associated pulmonary toxicity. The identified membrane-to-nucleus signaling framework, characterized by high-affinity binding interactions and coordinated cellular responses, enhances mechanistic understanding and may inform the development of targeted therapeutic interventions. These findings not only deepen our knowledge of drug-induced pulmonary fibrosis but also establish a foundation for precision medicine strategies aimed at preventing and treating amiodarone-related pulmonary complications in clinical practice.