Identification of potential Abl kinase inhibitors using virtual screening and free energy calculations for the treatment of chronic myeloid leukemia

Abstract

Abl kinase, particularly the Bcr-Abl fusion protein, is a critical driver of chronic myeloid leukemia (CML) and remain significant therapeutic target in hematologic malignancies. Although first-generation tyrosine kinase inhibitors (TKIs) such as Imatinib have revolutionized CML treatment, resistance due to kinase domain mutations (e.g., T315I gatekeeper mutation) and side effects highlight needs for another candidate inhibitors. In this study, we employed a combined virtual screening strategy to discover novel Abl kinase inhibitors from an extensive chemical database (∼670 million compounds). Initially, shape-based similarity (USR/USRCAT) and electrostatic potential filters were used to refine the candidate compounds, followed by structure-based molecular docking against the Abl kinase domain. Top-ranked candidates were evaluated using molecular dynamics (MD) simulations and binding free energy calculations, such as MM/GBSA and free energy perturbation (FEP), to confirm stability and binding affinity. Five candidate compounds emerged with binding energies comparable to or higher than known Abl kinase inhibitors, including Imatinib and Bafetinib. Finally, based on these calculations, we selected two compounds as candidates as Abl tyrosine kinase inhibitors. Overall, the results showed the effectiveness of combining ligand-based and structure-based drug design strategies to identify new Abl kinase inhibitor leads for improved the CML therapy.