首页> 外文期刊>Journal of Pharmaceutical and Biomedical Analysis: An International Journal on All Drug-Related Topics in Pharmaceutical, Biomedical and Clinical Analysis >Development of predictive quantitative retention-activity relationship models of HMG-CoA reductase inhibitors by biopartitioning micellar chromatography.
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Development of predictive quantitative retention-activity relationship models of HMG-CoA reductase inhibitors by biopartitioning micellar chromatography.

机译:通过生物分配胶束色谱法开发HMG-CoA还原酶抑制剂的预测定量保留-活性关系模型。

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摘要

Biological fluid cell membranes are barriers for the uptake of many kinds of drugs and their metabolites, along with passive transport across membranes and bioaccumulation. Biopartitioning micellar chromatography (BMC) is a mode of micellar liquid chromatography that uses micellar mobile phases of Brij35 under adequate experimental conditions and can be useful to simulate the drug's passive absorption and the transport in biological systems. The use of micellar aqueous solutions of Brij35 as mobile phases in reversed-phase liquid chromatography has proven to be valid to predict the biological activities of barbiturates, benzodiazepines, catecholamines, local anesthetics, non-steriodal anti-inflammatory drugs and tricyclic antidepressants. In this study, the relationships between the capacity factor in BMC and some pharmacokinetic and pharmacodynamic parameters of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors are studied. Predictive quantitative retention-activity relationship (QRAR) models describing some of the biological activities and pharmacokinetic properties of HMG-CoA reductase inhibitors are obtained. The results indicate that QRAR model may be a useful tool during the drug discovery process.
机译:生物流体细胞膜是多种药物及其代谢产物以及跨膜的被动转运和生物蓄积的障碍。生物分配胶束色谱(BMC)是一种胶束液相色谱的模式,它在适当的实验条件下使用Brij35的胶束流动相,可用于模拟药物在生物系统中的被动吸收和运输。已证明在反相液相色谱中使用Brij35的胶束水溶液作为流动相可有效预测巴比妥类药物,苯二氮卓类药物,儿茶酚胺,局部麻醉药,非杀菌性抗炎药和三环类抗抑郁药的生物活性。在这项研究中,研究了BMC中的容量因子与3-羟基-3-甲基戊二酰辅酶A(HMG-CoA)还原酶抑制剂的某些药代动力学和药效学参数之间的关系。获得了预测性定量保留-活性关系(QRAR)模型,该模型描述了HMG-CoA还原酶抑制剂的某些生物学活性和药代动力学特性。结果表明,QRAR模型可能是药物发现过程中的有用工具。

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