Identification of a Potential Thiazole Inhibitor Against Biofilms by 3D QSAR, Molecular Docking, DFT Analysis, MM-PBSA Binding Energy Calculations, and Molecular Dynamics Simulation

In this study, computational approaches were invested on a thiazole derivatives as biofilm inhibitor agents. CoMFA and CoMSIA models constructed presented a significant predictive capacity, including Q(2) values of 0.538 and 0.593 and R-2 values of 0.925 and 0.905 and R-pred(2) values of 0.867 and 0.913, and ESS values of 0.185 and 0.208, respectively. The predictability check was performed by external validation, which shows that the CoMSIA model strongly explains the inhibitory activity against biofilms. The information generated by the CoMSIA model has guided us to propose some candidates as a potent biofilm inhibitor. The mode of interaction was examined by molecular docking on a protein-binding pocket (ID: 2XF). The results obtained highlight the key amino acids involved in the ligand/protein interaction and show that the complexes bound to the designed compounds showed the best conformations in the binding site. An ADMET study was carried out on the various compounds proposed to ensure their pharmacokinetics and bioavailability in the body. The binding stability of the most active compound No22, the lowest active compound No8, and the newly designed compound Pred01 was assessed by molecular dynamics simulations accompanied by the calculation of the binding free energy according to a simulation trajectory of 100 ns. Furthermore, the energy profiles of these selected compounds were described by DFT analysis. Finally, these findings could lead to the discovery of new, more effective thiazole-based antibiofilm inhibitors.