Computational identification and molecular characterization of novel Aurora-B kinase inhibitors: Pharmacophore modeling, docking, and molecular dynamics simulations

Abstract

Aurora-B, a serine-threonine kinase, plays a critical role in spindle assembly, chromosome alignment, mitotic checkpoint activation, and cytokinesis. The overexpression of Aurora-B leads to abnormal cell division, multinucleation, and centrosome amplification, contributing to cancer. To identify potential Aurora-B inhibitors, a 3D-quantitative structure-activity relationship study was conducted, leading to the selection of a five-feature pharmacophore model (AADRR) with optimal partial least square parameters for virtual screening. Molecular docking was performed to determine the binding interactions of the candidate ligands with the human Aurora-B: inner centromere protein complex (PDB ID: 4AF3), identifying LYS 106, ALA 157, GLU 161, and PHE 219 as key residues crucial for the enzyme inhibition. Based on virtual screening, pharmacokinetic properties, and docking analysis, five lead compounds were selected from the national cancer institute (NCI) database: Compound 1 (NCI ID: 695163), Compound 2 (NCI ID: 327359), Compound 3 (NCI ID: 721045), Compound 4 (NCI ID: 711797), and Compound 5 (NCI ID: 104546). To clarify the interactions between Aurora-B protein and lead compounds, molecular dynamics simulations were carried out. The results demonstrated strong interactions between the lead compounds and critical active-site residues such as ALA 157 and LYS 106. The active site interactions of the protein-ligand complex were further validated through molecular dynamics simulation studies, providing insights into their binding stability and inhibitory potential.

Keywords

Aurora-B kinase / Cytokinesis / 3D-quantitative structure-activity relationship / Molecular docking / Molecular dynamics simulations

Funding

None.

Conflict of interest

The authors declare that they have no competing interests.

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