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

Recently, a new series of N-benzyl-3,6-dimethylbenzo[d]-isoxazol-5-amine derivatives and its prostate anti-cancer activity were produced and evaluated, respectively. Its compounds were perceived to have a strong inhibitory effect on the bromodomain of the related Tripartite motif-containing protein 24 (TRIM24). The 3D-QSAR study was applied utilizing the methods of Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). This gave result to the cross-validation coefficient (Q2) values of 0.850 and 0.92, the determination coefficient (R2) values of 0.998 and 0.987, respectively. The predictive capacity of these models is based on a test set of seven molecules that generated acceptable values of coefficient of determination (R2 test) of 0.793 and 0.804, corresponding respectively to CoMFA and CoMSIA., respectively. The study used molecular docking analysis to validate 3D-QSAR methods and to explain the binding site interactions and energy between the TRIM24 bromodomain receptor and the most active ligands. Based on the results of the previous model, it was allowed for us to predict new and active compounds and its 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

Language:
English
Published:
Physical Chemistry Research, Volume:10 Issue: 4, Autumn 2022
Pages:
519 to 535
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