Anaplastic lymphoma kinase (ALK)-driven lung cancer represents a critical therapeutic target, demanding innovative approaches for the identification of effective inhibitors. Anaplastic lymphoma kinase (ALK), a key protein involved in the pathogenesis of ALK-driven lung cancers, has been the focus of extensive drug discovery efforts. This study employed a comprehensive computational drug discovery approach, integrating virtual screening with the Lipinski filter, re-docking, molecular dynamics (MD) simulations, and free energy calculations to identify potential inhibitors from a natural compound library. Utilizing the MTiOpenScreen web server, we screened for compounds that exhibit favorable interactions with ALK, resulting in 1227 compounds with virtual screening scores ranging from - 10.2 to - 3.7 kcal/mol. Subsequent re-docking of three selected compounds (ZINC000059779788, ZINC000043552589, and ZINC000003594862) and one reference compound against ALK yielded docking scores - 10.4, - 10.2, - 10.2, and - 10.1 kcal/mol, respectively. These compounds demonstrated promising interactions with ALK, suggesting potential inhibitory effects. Advanced analyses, including MD simulation and binding free energy calculations, further supported the potential efficacy of these compounds. MD simulations, particularly the root mean square deviation (RMSD) and root mean square fluctuation (RMSF) analyses, revealed that compounds ZINC000059779788 and ZINC000003594862 achieved better stability compared to compound ZINC000043552589. These stable conformations suggest effective binding over time. Free energy calculations using the MM/GBSA method showed that ZINC000059779788 had the most favorable binding energy, indicating a strong and stable interaction with the ALK protein. The promising computational findings from this study emphasize the necessity for additional experimental testing to verify the therapeutic efficacy of these natural compounds for treating lung cancers.
