Combined 3D-QSAR and Molecular Docking Analysis of Styrylquinoline Derivatives as Potent anti-cancer Agents

3D-QSAR has indeed established itself as a very useful component in the design of compounds with biological potential. The use of this tool will therefore make it possible to more easily target the modulations to be carried out in order to improve the inhibitory capacity of the series studied. Statistical analyses of CoMFA and CoMSIA molecular interaction field descriptors and the model validation methods they generate are presented and applied to the three-dimensional quantitative structure-activity relationships study of a series of 32 wildtypes HCT116 p53 inhibitor styrylquinolines. The selected CoMFA and CoMSIA models were generated by the partial least squares "PLS" method and all had very good internal prediction and cross-validation coefficient values Q² of 0.601 and 0.6, respectively. In view of the results obtained by the contour maps of the developed models as well as the results of molecular docking, new analogues of styrylquinoline were designed. The study of the physicochemical, pharmacokinetic, and potential toxicity properties shows that the two newly predicted compounds T1 and T3 presented a better ADMET profile, in particular a good gastrointestinal absorption, compared to the most active compound taken from the literature, which reveals their promising interest as potential new drug candidates against wild human colon cancer.