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Study of the antimalarial activity of 4-aminoquinoline compounds against chloroquine-sensitive and chloroquine-resistant parasite strains

机译:4-氨基喹啉化合物对氯喹敏感性和氯喹抗性寄生虫菌株的抗疟活性研究

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摘要

This study is concerned with identifying features of 4-aminoquinoline scaffolds that can help pinpoint characteristics that enhance activity against chloroquine-resistant parasites. Statistically valid predictive models are reported for a series of 4-aminoquinoline analogues that are active against chloroquine-sensitive (NF54) and chloroquine-resistant (K1) strains of Plasmodium falciparum. Quantitative structure activity relationship techniques, based on statistical and machine learning methods such as multiple linear regression and partial least squares, were used with a novel pruning method for the selection of descriptors to develop robust models for both strains. Inspection of the dominant descriptors supports the hypothesis that chemical features that enable accumulation in the food vacuole of the parasite are key determinants of activity against both strains. The hydrophilic properties of the compounds were found to be crucial in predicting activity against the chloroquine-sensitive NF54 parasite strain, but not in the case of the chloroquine-resistant K1 strain, in line with previous studies. Additionally, the models suggest that ‘softer’ compounds tend to have improved activity for both strains than do ‘harder’ ones. The internally and externally validated models reported here should also prove useful in the future screening of potential antimalarial compounds for targeting chloroquine-resistant strains. >Graphical Abstract Predictive models reveal linear relationships for activity of 4-aminoquinoline analogues active against chloroquine-sensitive strains of Plasmodium falciparum
机译:这项研究与确定4-氨基喹啉骨架的特征有关,这些特征可以帮助查明增强针对氯喹抗性寄生虫的活性的特征。统计上有效的预测模型针对一系列4-氨基喹啉类似物,它们对恶性疟原虫的氯喹敏感性(NF54)和氯喹抗性(K1)菌株具有活性。基于统计和机器学习方法(例如多元线性回归和偏最小二乘)的定量结构活性关系技术与一种新颖的修剪方法一起用于选择描述符,从而为这两种菌株建立了稳健的模型。对主要描述语的检查支持了以下假说:使寄生虫在食物液泡中积累的化学特征是针对两种菌株的活性的关键决定因素。与先前的研究一致,发现该化合物的亲水性对于预测对氯喹敏感的NF54寄生虫菌株的活性至关重要,但对于耐氯喹的K1菌株则不重要。此外,这些模型表明,“较软”的化合物比“较硬”的化合物具有更高的活性。在此报告的内部和外部验证的模型也应被证明在将来针对潜在抗疟疾化合物的抗氯喹耐药菌株的筛选中很有用。 <!-fig ft0-> <!-fig @ position =“ anchor” mode =文章f4-> <!-fig mode =“ anchred” f5-> >图形摘要<!-无花果/图形|无花果/替代品/图形模式=“ anchored” m1-> <!-标题a7->预测模型揭示了4-氨基喹啉类似物对恶性疟原虫氯喹敏感菌株有活性的活性的线性关系

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