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

Zakari Ya’u Ibrahim , Usman Abdulfatai , Stephen Ejeh , Abduljelil Ajala , Samuel Ndaghiya Adawara , Olasupo Sabitu Babatunde
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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.
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基于遗传功能算法(GFA)的QSAR、分子设计和ADMET筛选评估阿莫地喹衍生物的抗疟潜力
疟疾寄生虫对广泛使用的药物的耐药性日益增强,使正在进行的防治地方病的斗争复杂化。因此,寻找更有效的抗疟疾治疗方法仍在继续。本研究的重点是开发具有增强疗效的改性阿莫地喹类似物。此外,设计的衍生物将评估其药物相似性和药代动力学性质。在Material Studio中使用22种阿莫地喹衍生物创建了预测QSAR模型,以估计新设计的衍生物的活性。通过在不同位置应用描述符隐含来修改最活跃的导数(用作设计模板),从而产生不同的导数。使用SwissADME软件和pkCSM web应用程序评估这些衍生物的药物相似性和药代动力学性质。以活性最高(pIC50 = 9.491)的化合物A-01为原型,设计了13个改进衍生物。这些衍生物是通过改变模板上特定位置的取代基和饱和而系统地产生的。所有设计的衍生物的活性均高于模板、阿莫地喹(pIC50 = 8.668)和氯喹(pIC50 = 8.111)。其中,衍生物ac, 4-((7-氯喹啉-4-基)氨基)-2-(环己基(4-(吡啶-2-基)哌嗪-1-基)甲基)苯酚被证明是最有效的。所设计的衍生物作为p -糖蛋白的底物,通过血脑屏障的渗透性有限,不显着渗透中枢神经系统,抑制CYP1A2和CYP2C19,并具有作为肾脏OCT2底物的潜力。在遵守Lipinski和Veber规则的情况下,开发了13种阿莫地喹衍生物,提高了疗效。这些衍生物基本上无毒,对皮肤安全,有望开发有效的抗疟疾药物。
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