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 investigated on a thiazole derivatives as biofilm inhibitor agents. The 3D-QSAR model constructed presented a significant predictive capacity with statistical values R2 = 0.925, Q² = 0.538 for the CoMFA, and R2 = 0.905, Q² = 0.593 for CoMSIA. The predictability check was performed by external validation, which shows that the CoMSIA model strongly explains the inhibitory activity against biofilms. Based on the information generated by the CoMSIA model, we propose some candidates as a potent biofilm inhibitor. The mode of interaction was examined by molecular docking. The results obtained highlight the key amino acids involved in the ligand / protein interaction, and showing that the complexes bound to the designed compounds showed the best conformations in the active site. An ADMET study was carried out on the various compounds proposed to ensure their pharmacocentitics and bioavailability in the body. Moreover, the stability of the model was evaluated using MD simulations accompanied by calculating the binding free energy, DFT studies carried out to clearly describe the energy profiles of the studied compounds. All these results build an information base that can be invested in the design of thiazole-based biofilm inhibitors.