2D/3D-QSAR Model Development Based on a Quinoline Pharmacophoric Core for the Inhibition of Plasmodium falciparum: An In Silico Approach with Experimental Validation

Abstract

Malaria is an infectious disease caused by Plasmodium spp. parasites, with widespreaddrug resistance to most antimalarial drugs. We report the development of two 3D-QSAR modelsbased on comparative molecular field analysis (CoMFA), comparative molecular similarity indexanalysis (CoMSIA), and a 2D-QSAR model, using a database of 349 compounds with activity againstthe P. falciparum 3D7 strain. The models were validated internally and externally, complying with allmetrics (q2 > 0.5, r2test > 0.6, r2m > 0.5, etc.). The final models have shown the following statisticalvalues: r2test CoMFA = 0.878, r2test CoMSIA = 0.876, and r2test 2D-QSAR = 0.845. The models wereexperimentally tested through the synthesis and biological evaluation of ten quinoline derivativesagainst P. falciparum 3D7. The CoMSIA and 2D-QSAR models outperformed CoMFA in terms ofbetter predictive capacity (MAE = 0.7006, 0.4849, and 1.2803, respectively). The physicochemicaland pharmacokinetic properties of three selected quinoline derivatives were similar to chloroquine.Finally, the compounds showed low cytotoxicity (IC50 > 100 μM) on human HepG2 cells. Theseresults suggest that the QSAR models accurately predict the toxicological profile, correlating wellwith experimental in vivo data.