Computational Insights into the Polypharmacological Landscape of BCR-ABL Inhibitors: Emphasis on Imatinib and Nilotinib

Background: BCR-ABL inhibitors such as imatinib and nilotinib exhibit multi-kinase activity that extends beyond oncology, offering significant potential for drug repurposing. Objectives: This study aims to systematically evaluate and prioritize the repurposing potential of BCR-ABL inhibitors, particularly imatinib and nilotinib. Methods: An integrated pharmacoinformatics framework was applied to analyze seven BCR-ABL inhibitors. Structural clustering, cheminformatics analysis, and transcriptomic profiling using the Connectivity Map were employed to evaluate structural relationships, target profiles, and gene expression signatures associated with non-oncology indications. Results: Structurally, imatinib and nilotinib clustered closely, while HY-11007 exhibited distinct features. Nilotinib’s high selectivity correlated with strong transcriptional effects in neurodegeneration-related pathways (e.g., HSP90 and LYN), whereas imatinib’s broader kinase profile (PDGFR and c-KIT) was linked to fibrosis and metabolic regulation. Connectivity Map analysis identified more than 30 non-cancer indications, including known off-target uses (e.g., imatinib for pulmonary hypertension) and novel hypotheses (e.g., nilotinib for Alzheimer’s via HSPA5 modulation). A substantial portion of these predictions aligned with the existing literature, underscoring the translational relevance of the approach. Conclusions: These findings highlight the importance of integrating structure–activity relationships and transcriptomic signatures to guide rational repurposing. We propose prioritizing nilotinib for CNS disorders and imatinib for systemic fibrotic diseases, supporting their advancement into preclinical and clinical evaluation. More broadly, this framework offers a versatile platform for uncovering hidden therapeutic potential across other drug classes with complex polypharmacology.