Modeling studies using 3D-QSAR and molecular docking methods were performed on a set of 34 hybrids of 4-aminoquinoline derivatives previously studied as effective antimalarial agents of wild type and quadruple mutant Plasmodium falciparum dihydrofolate reductase (DHFR). So, the famous mathematical method multiple linear regression (MLR) was explored to build the QSAR model. The DFT-B3LYP method with the basis set 6-31G was used to calculate the quantum chemical descriptors, chosen to represent the electronic descriptors of molecular structures. On the contrary, the MM2 method was used to calculate lipophilic, geometrical, physicochemical, and steric descriptors. The QSAR model tested with artificial neural network (ANN) method shows high performance towards its predictability. The predicted model was confirmed by three validation methods: leave-one-out (LOO) cross validation, Y-randomization, and validation external. The molecular docking study of three compounds 9, 11, and 26 on both wild and quadruple mutant types of pf-DHFR-TS as the protein target helps to understand more and then predict the binding modes with the binding sites.
Discovery of unsymmetrical aromatic disulfides as novel inhibitors of SARS-CoV main protease: Chemical synthesis, biological evaluation, molecular docking and 3D-QSAR study