Computational Analysis of Triazole-Based Kojic Acid Analogs as Tyrosinase Inhibitors by Molecular Dynamics and Free Energy Calculations

Molecular docking, molecular dynamics (MD) simulations and the linear interaction energy (LIE) method were used here to predict binding modes and free energy for a set of 1,2,3-triazole-based KA analogs as potent inhibitors of Tyrosinase (TYR), a key metalloenzyme of the melanogenesis process. Initially, molecular docking calculations satisfactorily predicted the binding mode of evaluated KA analogs, where the KA part overlays the crystal conformation of the KA inhibitor into the catalytic site of TYR. The MD simulations were followed by the LIE method, which reproduced the experimental binding free energies for KA analogs with an r(2) equal to 0.97, suggesting the robustness of our theoretical model. Moreover, the van der Waals contributions performed by some residues such as Phe197, Pro201, Arg209, Met215 and Val218 are responsible for the binding recognition of 1,2,3-triazole-based KA analogs in TYR catalytic site. Finally, our calculations provide suitable validation of the combination of molecular docking, MD, and LIE approaches as a powerful tool in the structure-based drug design of new and potent TYR inhibitors.

Automated summary

In this study, molecular docking, molecular dynamics simulations, and the linear interaction energy method were used to predict binding modes and free energy of KA analogs as tyrosinase inhibitors. The results showed that the docking calculations accurately predicted the binding modes, and the MD simulations followed by the LIE method reproduced the experimental binding free energies, indicating the robustness of the theoretical model. It was found that specific residues played an important role in the binding recognition of KA analogs in the catalytic site. This study provides valuable validation for the structure-based drug design of new and potent tyrosinase inhibitors.