Novel antiproliferative inhibitors from salicylamide derivatives with dipeptide moieties using 3D-QSAR, molecular docking, molecular dynamic simulation and ADMET studies
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Original research


Currently, most cancers cannot be cured permanently. Therefore, the search of new anticancer drugs is an urgent unmet need. In order to solve this problem, we can use computational chemistry as it represents a sensitive step in the procedure of rational drugs development and design. For this study, we performed several in silico approaches such as: 3D QSAR study, molecular docking and molecular dynamics simulation for a database forming of 28 salicylamide compounds with dipeptide moieties that are inhibitors of antiproliferative activity on CEM cancer cell lines. The established CoMSIA/SH model showed a high reliability reflected by an important value of the coefficient of determination (R2 = 0.969), and a reasonable value of the cross-validation coefficient Q² = 0.637, the validity of this model is ensured by the high value of the prediction coefficient for the test set with R2pred = 0.913. The treatment of the different extracted results provides important information about the structures favored to improve the inhibitory activity. These results have guided to propose new antiproliferative inhibitors with high pGI50 values. Subsequently, these new compounds were analyzed using a molecular docking for determine the essential ligand-receptor interactions, then we performed a molecular dynamics simulation that showed the stability of the proposed new compounds, since no significant fluctuation is detected in these validity parameters, finally, to test the possibility of these new inhibitors to become drug candidates we used the ADMET properties.

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