Identification of potential tubulin polymerization inhibitors by 3D-QSAR, molecular docking and molecular dynamics

Abstract

Combretastatin A-4 (CA-4) is one of the most potent tubulin polymerization inhibitors. In this paper, the identification of some new CA-4 analogues as potential tubulin polymerization inhibitors is performed by combination of molecular modeling techniques including 3D-QSAR, molecular docking and molecular dynamics (MD) simulation. The built 3D-QSAR models show significant statistical quality and excellent predictive ability. The square correlation coefficient (r2) and cross-validated squared correlation coefficient (q2) of CoMFA are 0.974 and 0.724; the r2 and q2 of CoMSIA are 0.976 and 0.710, respectively. To further verify the reliability of the models, the inhibitory activity of our synthetic CA-4 analogues to tubulin polymerization was evaluated and predicted. It is interesting to find that the predicted values of the 3D-QSAR models are in good agreement with the experimental values. Several new inhibitors were designed and predicted. Molecular docking elucidates the conformations of compounds and key amino acid residues at the active site of tubulin protein. 30 ns MD simulations were successfully performed to confirm the detailed binding mode and calculate the binding free energies. Some new CA-4 analogues were identified as good potential tubulin polymerization inhibitors.