In silico modeling of tetraoxane-8-aminoquinoline hybrids active against Plasmodium falciparum

Abstract

Background: Quantitative structure-activity relationships (QSAR) is a technique that is used to produce a model that connects biological activities of compounds to their chemical structures, and molecular docking is a technique that reveals the binding mode and interactions between a drug and its target enzyme. These techniques have been successfully applied in the design and development of many drug candidates and herein were employed to build a model that could help in the development of more potent antimalaria drugs. Results: Descriptors of the compounds were calculated using the PaDEL-Descriptor software, and Genetic Function Algorithm (GFA) was used to select descriptors and build the model. A robust and reliable model was generated and validated to have internal and external squared correlation coefficient (R2) of 0.9622 and 0.8191, respectively, adjusted squared correlation coefficient (Radj) of 0.9471, and leave-one-out (LOO) cross-validation coefficient (Q2cv) of 0.9223. The model revealed that the antiplasmodial activities of 1,2,4,5-tetraoxane-8-aminoquinoline hybrids depend on MATS3m, GATS8p, GATS8i, and RDF50s descriptors. MATS3m, GATS8i, and RDF50s influenced the antiplasmodial activities of the compounds positively while GATS8p negatively with the greatest influence. The docking result shows strong interactions between 1,2,4,5-tetraoxane-8-aminoquinoline hybrids and Plasmodium falciparum lactate dehydrogenase (pfLDH) with binding affinities ranging from − 6.3 to − 10.9 kcal/mol which were better than that of chloroquine (− 6.1 kcal/mol), suggesting that these compounds could be better inhibitors of pfLDH than chloroquine. Conclusion: The results of this study could serve as a model for designing new potent 1,2,4,5-tetraoxane-8-aminoquinolines with better antiplasmodial activities for the development of highly active antimalaria drugs.