In silico design and computational evaluation of novel 2-arylaminopyrimidine-based compounds as potential multi-targeted protein kinase inhibitors: application for the native and mutant (T315I) Bcr-Abl tyrosine kinase

Abstract

An integrated computational approach to drug discovery was used to identify novel potential inhibitors of the native and mutant (T³¹⁵I) Bcr-Abl tyrosine kinase, the enzyme playing a key role in the pathogenesis of chronic myeloid leukemia (CML). This approach included i) design of chimeric molecules based on the 2-arylaminopyrimidine fragment, the main pharmacophore of the Abl kinase inhibitors imatinib and nilotinib used in the clinic for the CML treatment, ii) molecular docking of these compounds with the ATP-binding site of the native and mutant Abl kinase, iii) refinement of the ligand-binding poses by the quantum chemical method PM7, iv) molecular dynamics simulations of the ligand/Abl complexes, and v) prediction of the ligand/Abl binding affinity in terms of scoring functions of molecular docking, machine learning, quantum chemistry, and molecular dynamics. As a result, five top-ranking compounds able to effectively block the enzyme catalytic site were identified. According to the data obtained, these compounds exhibit close modes of binding to the Abl kinase active site that are mainly provided by hydrogen bonds and multiple van der Waals contacts. The identified compounds show high binding affinity to the native and mutant Abl kinase comparable with the one calculated for the FDA-approved kinase-targeted inhibitors imatinib, nilotinib, and ponatinib used in the calculations as a positive control. The results obtained testify to the predicted drug candidates against CML may serve as good scaffolds for the design of novel anticancer agents able to target the ATP-binding pocket of the native and mutant Abl kinase.

Communicated by Ramaswamy H. Sarma

Keywords:

• Bcr-Abl tyrosine kinase
• Abl kinase inhibitors
• molecular modeling
• chronic myeloid leukemia

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was supported by a grant of the State Program of Scientific Research “Convergence 2025” (subprogram “Interdisciplinary research and emerging technologies”, project 3.4.1).