In Silico Prediction of Novel (TRIM24) Bromodomain Inhibitors: A Combination of 3D-QSAR, Molecular Docking, ADMET Prediction, and Molecular Dynamics Simulation

Recently, a new series of N-benzyl-3,6-dimethylbenzo[d]-isoxazol-5-amine derivatives were produced and their prostate anti-cancer activities were evaluated. Its compounds were perceived to have a strong inhibitory effect on the bromodomain of Tripartite motifcontaining protein 24 (TRIM24). The 3D-QSAR study was performed, utilizing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The values of cross-validation coefficient (Q2) were 0.850 and 0.92, and the values of determination coefficient (R2) were 0.998 and 0.987. The predictive capacity of these models was based on a test set of seven molecules, which generated acceptable values of 0.793 and 0.804 for determination coefficient (R2), corresponding respectively to CoMFA and CoMSIA. In This study, molecular docking analysis was used to validate the 3D-QSAR models and explain the binding site interactions and energy between the TRIM24 bromodomain receptor and the most active ligands. The results of the previous models allowed us to predict new and active compounds, and their pharmacokinetic properties were verified using drug-likeness and ADMET prediction. Finally, to affirm the dynamic stability and behavior of the molecules, the most appropriate docked candidate molecules were simulated by molecular dynamics.