In this study, a poly(glycidyl methacrylate) nanoparticle (PGMA NP)-coated column system with two antibiotics as selector was constructed for enantioseparation. The PGMA NP coating inside the capillary columns could be easily introduced by a simple ring open reaction. Five basic drugs were used as the model to evaluate the enantioselectivity of Azithromycin Lactobionate (AL) and Clindamycin phosphate (CP)-based separation system. Factors that influence the chiral separation resolution were systematically investigated, such as chiral selector concentration, background electrolyte (BGE) pH, applied voltage and system temperature. Under the optimized conditions, improved enantioseparations were obtained for all enantiomers and the maximum column efficiency of model drugs could reach 120,000 plates/m. The repeatability of relative standard deviations for EOF representing run-to-run, day-to-day and column-to-column was less than 4.32%. In addition, molecular modeling with AutoDock was applied to elucidate the explored potential mechanism of AL/CP for recognizing racemic drugs.

Graphic Abstract

中文翻译：

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毛细管电泳中以阿奇霉素乳酸酯和磷酸克林霉素为手性选择剂的对映体的聚甲基丙烯酸缩水甘油酯包被的色谱柱的评价

在这项研究中，构建了一种以两种抗生素为选择剂的聚甲基丙烯酸缩水甘油酯纳米颗粒（PGMA NP）涂层的色谱柱系统，用于对映体分离。毛细管柱内的PGMA NP涂层可通过简单的开环反应轻松引入。使用五种基本药物作为模型，以评估乳酸阿奇霉素（AL）和磷酸克林霉素（CP）分离系统的对映选择性。系统地研究了影响手性分离分辨率的因素，例如手性选择剂浓度，背景电解质（BGE）pH，施加电压和系统温度。在优化的条件下，所有对映异构体均得到了改进的对映体分离，模型药物的最大柱效可达到120,000板/ m。EOF的相对标准偏差的重复性（代表逐次运行，每天和列之间）小于4.32％。此外，使用AutoDock进行分子建模来阐明AL / CP用于识别外消旋药物的潜在机制。

图形摘要