Computational study of interactions of anti-cancer drug eribulin with human tubulin isotypes

Abstract

Microtubules (MTs) are widely targeted for the treatment of various types of cancer due to their essential role in cell division. MTs are polymers made of αβ-tubulin heterodimers. These α- and β-tubulins have 8 and 10 different isotypes, respectively. It is known that a few tubulin isotypes have anti-cancer drug resistance properties, especially β_III, which shows poor sensitivity to many potent anti-cancer drugs such as eribulin. However, the molecular-level understanding of drug-resistance due to tubulin isotype variation is poorly understood. This paper presents the study of differential binding affinities of different tubulin isotypes with the potent anti-cancer drug eribulin. Eribulin (MT destabilizer) binds at the inter-dimer interface of MTs near the vinca site and induces a lattice deformation, which results in catastrophic events in MT dynamics. In this study, sequence analysis has been done throughway and the binding sites and based on that 2α-tubulin isotypes (α_I and α_VIII) and 7β tubulin isotypes (β_I, β_IIa, β_III, β_IVa, β_VI, β_VII and β_VIII) were selected. In total, 14 combinations were prepared after building homology models of these selected isotypes. Molecular docking and molecular dynamics simulations were performed to deeply understand the binding mode of eribulin at different MT compositions. RMSD, RMSF, radius of gyration, SASA, ligand-protein interactions, and calculations of binding free energy were performed to investigate the eribulin binding variations to tubulin isotypes and it was found that α_Iβ_II showed the maximum binding affinity among all 14 systems to eribulin. The β_III-tubulin isotype, which shows low sensitivity to eribulin in experimental results, had the least binding affinity in the system α_VIIIβ_III complex and the average binding affinity in the system α_Iβ_III among all 14 systems. Additionally, we performed steered MD simulations and DynDom analysis of the systems with the lowest binding energy (α_Iβ_II) and the highest binding energy (α_VIIIβ_III) and extracted force, displacement, and H-bonding profiles during the pulling simulations to get a better insight.