Genetic function algorithm (GFA) based QSAR, molecular design, and ADMET screening to assess the antimalarial potential of Amodiaquine derivatives

Abstract

The ongoing fight against endemic diseases is complicated by the increasing resistance of malaria parasites to widely used drugs. As a result, the search for more effective antimalarial treatments continues. This research focuses on developing modified Amodiaquine analogues with enhanced efficacy. Additionally, the designed derivatives will be evaluated for their drug-likeness and pharmacokinetic properties. A predictive QSAR model was created using twenty-two Amodiaquine derivatives in the Material Studio to estimate the activity of newly designed derivatives. The most active derivative (used as a design template) was modified by applying descriptor implications at various positions, resulting in different derivatives. The drug-likeness and pharmacokinetic properties of these derivatives were assessed using SwissADME software and the pkCSM web application. Compound A-01, with the highest activity (pIC50 = 9.491), was selected as the prototype for designing thirteen improved derivatives. These derivatives were systematically created by altering substituents and saturations at specific positions on the template. All designed derivatives demonstrated greater activity than the template, Amodiaquine (pIC50 = 8.668), and Chloroquine (pIC50 = 8.111). Among them, the derivative ac, 4-((7-chloroquinolin-4-yl)amino)-2-(cyclohexyl(4-(pyridin-2-yl)piperazin-1-yl)methyl)phenol, proved to be the most potent. The designed derivatives functioned as substrates for P-glycoprotein, showed limited permeability across the blood-brain barrier, did not significantly penetrate the central nervous system, inhibited CYP1A2 and CYP2C19, and showed potential as renal OCT2 substrates. Thirteen Amodiaquine derivatives were developed with improved efficacy while adhering to Lipinski and Veber rules. These derivatives are largely non-toxic, skin-safe, and show promise for the development of effective antimalarial drugs.

Keywords

• QSAR
• Molecular design
• ADMET screening
• Amodiaquine