Malaria persists as the most infectious vector-borne disease in the world.

Forty-four bicyclo ((aryl) methyl) benzamides, acting as glycine transporter type 1 (GlyT1) inhibitors, are developed using molecular modeling techniques. QSAR models generated by multiple linear and non-linear regressions affirm that the biological inhibitory activity against the schizophrenia disease is strongly and significantly correlated with physicochemical, geometrical and topological descriptors, in particular: Hydrogen bond donor, polarizability, surface tension, stretch and torsion energies and topological diameter. According to in silico ADMET properties, the most active ligands (L6, L9, L30, L31 and L37) are the molecules having the highest probability of penetrating the central nervous system (CNS), but the molecule 32 has the highest probability of being absorbed by the gastrointestinal tract. Molecular docking results indicate that Tyr124, Phe43, Phe325, Asp46, Phe319 and Val120 amino acids are the active sites of the dopamine transporter (DAT) membrane protein, in which the most active ligands can inhibit the glycine transporter type 1 (GlyT1). The results of molecular dynamics (MD) simulation revealed that all five inhibitors remained stable in the active sites of the DAT protein during 100 ns, demonstrating their promising role as candidate drugs for the treatment of schizophrenia.

The development of multi-resistant strains of plasmodium parasite has become a global problem, therefore, the discovery of new antimalarial agents is the only available solution. In order to improve and propose new compounds with antimalarial activity, the three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking studies were carried on aurone analogues acting as Qo site inhibitors in cytochrome b. The 3D-QSAR model was established in this study based on the Comparative Molecular Field Analysis (CoMFA) and the Comparative Molecular Similarity Indices Analysis (CoMSIA). The good predictability was obtained using the CoMFA model (Q 2 ¼ 0.5; R 2 ¼ 0.97; R 2 pred ¼ 0.72) and the best CoMSIA model (Q 2 ¼ 0.526; R 2 ¼ 0.915; R 2 pred ¼ 0.765). The predictive capacity of the developed model was evaluated through external validation using a test set compound and an applicability domain technique. In this study, the Steric, electrostatic and hydrogen bond acceptor fields played a key role in antimalarial activity. The results of the molecular docking revealed theoretically the importance of the residues his183 and his82 in the active site of the heme b L , this result was validated by a new assessment method. Based on the previous results, we designed several new potent Cytochrome b inhibitors and their inhibitory activities were predicted by the best model. Furthermore, these new inhibitors were analyzed for their ADMET properties and drug likeness. These results would be of great help in leading optimization for new drug discovery that can solve the problem of multiple drug resistance.

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.

A new class of selective antagonists of the N-Methyl-D-Aspartate (NMDA) receptor subunit 2B have been developed using molecular modeling techniques. The three-dimensional quantitative structure–activity relationship (3D-QSAR) study, based on comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models, indicate that steric, electrostatic and hydrogen bond acceptor fields have a key function in the analgesic activity against neuropathic pain. The predictive accuracy of the developed CoMFA model (Q2 = 0.540, R2 = 0.980, R2 pred = 0.613) and the best CoMSIA model (Q2 = 0.665, R2 = 0.916, R2 pred = 0.701) has been successfully examined through external and internal validation. Based on ADMET in silico properties, L1, L2 and L3 ligands are non-toxic inhibitors of 1A2, 2C19 and 2C9 cytochromes, predicted to passively cross the blood–brain barrier (BBB) and have the highest probability to penetrate the central nervous system (CNS). Molecular docking results indicate that the active ligands (L1, L2 and L3) interact specifically with Phe176, Glu235, Glu236, Gln110, Asp136 and Glu178 amino acids of the transport protein encoded as 3QEL. Therefore, they could be used as analgesic drugs for the treatment of neuropathic pain.