No abstract

A blend of genetic algorithm with multiple linear regression (GA-MLR) method was utilized in generating a quantitative structure–activity relationship (QSAR) model on the antimalarial activity of aryl and aralkyl amine-based triazolopyrimidine derivatives. The structures of derivatives were optimized using density functional theory (DFT) DFT/B3LYP/6–31 + G* basis set to generate their molecular descriptors, where two (2) predictive models were developed with the aid of these descriptors. The model with an excellent statistical parameters; high coefficient of determination (R2) = 0.8884, cross-validated R2 (Q2cv) = 0.8317 and highest external validated R2 (R2pred) = 0.7019 was selected as the best model. The model generated was validated through internal (leave-one-out (LOO) cross-validation), external test set, and Y-randomization test. These parameters are indicators of robustness, excellent prediction, and validity of the selected model. The most relevant descriptor to the antimalarial activity in the model was found to be GATS6p (Geary autocorrelation—lag 6/weighted by polarizabilities), in the model due to its highest mean effect. The descriptor (GATS6p) was significant in the in-silico design of sixteen (16) derivatives of aryl and aralkyl amine-based triazolopyrimidine adopting compound DSM191 with the highest activity (pEC50 = 7.1805) as the design template. The design compound D8 was found to be the most active compound due to its superior hypothetical activity (pEC50 = 8.9545).

Background The sixteen (16) designed data set of substituted aryl amine-based triazolopyrimidine were docked against Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) employing Molegro Virtual Docker (MVD) software and their pharmacokinetic property determined through SwissADME predictor. Results The docking studies shows compound D16, 5-((6-methoxy-5-methyl-[1,2,4]triazolo[1,5-a]pyrimidin-7-yl)amino)benzo[b]thiophen-4-ol to be the most interactive and stable derivative (re-rank score = − 114.205 kcal/mol) resulting from the hydrophobic as well as hydrogen interactions. The hydrogen interaction produced one hydrogen bond with the active residues LEU359 (H∙∙H∙∙O) at a bond distances of 2.2874 Å. All the designed derivatives were found to pass the Lipinski rule of five tests, supporting the drug-likeliness of the designed compounds. Conclusion The ADME analysis revealed a perfect concurrence with the Lipinski Ro5, where the derivatives were found to possess good pharmacokinetic properties such as molar refractivity (MR), number of rotatable bonds (nRotb), log of skin permeability (log Kp), blood-brain barrier (BBB). These results could a deciding factor for the optimization of novel antimalarial compounds.

Malaria, a disease caused by one of the world's fatal parasites Plasmodium falciparum, is responsible for over a million death annually. P. falciparum dihydroorotate dehydrogenase (PfDHODH) is a validated target of this deadly parasite. Quantitative structure-activity relationship and molecular docking in silico methods were employed in the discovery of unique PfDHODH inhibitors from the computational design derivatives of indolyl-3-ethanone-α-thioethers through models generation via a genetic function algorithm methods. The best model indicates good power of prediction with coefficient of determination, R 2 = 0.9482, adjusted coefficient of determination ( R 2 adj ) = 0.9288, Leave one out cross-validation coefficient (Q 2 ) = 0.9201 and the external validation ( R 2 pred ) = 0.6467. The contribution of every descriptor in the model was investigated through finding their mean effect to (pIC 50 ) the activities of the compounds. With MATS5m (− 0.11725), RDF75m (− 0.12097), VE3_Dzp (0.14697), and MLFER_BH (1.08528) contributing more to the model, while AATSC8p (− 0.04833) and minHBa (0.05430) contributed the least to the model. Hence, the mean effect indicated MLFER_BH to be the most relevant descriptor, which aided the design of five derivatives of indolyl-3-ethanone-α-thioethers. All the designed antimalarial compounds were deeply docked within the binding region thereby forming several hydrogens and hydrophobic bonds leading to the generation of better binding affinity and high binding scores (− 156.181 kcal/ mol) compared to the design template (− 138.201 kcal/mol) and the standard drug (− 128.467 kcal/mol). Furthermore, all the five designed antimalarial compounds were found to be better bonded to the binding pocket of PfDHODH than other compounds reported by other researchers.

In an attempt to design compounds with higher antimalarial activities, quantitative structure-activity relationship (QSAR) technique was utilized in the development of a molecular model for some synthesized 2′-substituted triclosan derivatives through a hybrid of the GA-MLR method. The model was found to have excellent statistical parameters (R 2 = 0.8919, R 2 Adj = 0.8728, LOF = 0.2563). The descriptors mean effect (MF) revealed BCUTw-1l, which increases with an increase in molecular weight, to be the most contributive to the antimalarial activity. Consequently, compound 3, with the highest activities (pEC 50 = 6.9586) was deployed as the design template. The molecular weight of the template was increasing through substitutions of its atoms at several positions with heavier atoms/groups to increases the descriptor (BCUTw-1l) value. Twelves (12) theoretical derivatives of the template were designed where six of the designed derivatives have better activity than the design template. The most active designed compound, 3L was found to have the highest antimalarial activity (pEC 50 = 7.930) than that of the design template.