BACKGROUND: Anaplastic Lymphoma Kinase (ALK) is implicated in several cancers, including anaplastic large cell lymphoma, non-small cell lung cancer, and neuroblastoma. Targeted inhibition of ALK represents a promising therapeutic strategy. AIMS: This study aimed to identify and evaluate potential ALK inhibitors using virtual screening and computational analyses to determine their binding stability, affinity, and dynamic behavior, ultimately assessing their potential as therapeutic agents for ALK-driven cancers. OBJECTIVE: The objective of this study was to identify potential ALK inhibitors using virtual screening techniques and to evaluate their binding affinities and stability through computational analyses. METHODS: This study utilized virtual screening to identify potential ALK inhibitors from the MTiOpen Screen Diverse library and selected three compounds (24331480, 26536128, and 24353407) based on their binding affinities. These compounds underwent optimization using Density Functional Theory (DFT) and were redocked to confirm binding stability. Molecular dynamics simulations, hydrogen bond analysis, MM/PBSA calculations, and PCA-based free energy landscape analysis were also carried out. RESULTS: The re-docking experiments confirmed the stable and strong binding affinities of the selected compounds to the ALK active site. Molecular dynamics simulations revealed stable interactions throughout the 200 ns simulation period. Hydrogen bond analysis demonstrated consistent hydrogen bonds between key residues and the inhibitors. MM/PBSA calculations indicated favorable binding free energies, suggesting strong binding affinities. Finally, PCA-based free energy landscape analysis highlighted energetically favorable binding modes. CONCLUSION: The identified compounds (24331480, 26536128, and 24353407) exhibited promising inhibitory potential against ALK. These findings warrant further experimental validation to confirm their potential as therapeutic agents for ALK-driven cancers.