Salary Mina, Hadjmohammadi Mohammadreza
Department of Analytical Chemistry, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran.
Department of Analytical Chemistry, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran.
J Pharm Biomed Anal. 2015 Oct 10;114:1-7. doi: 10.1016/j.jpba.2015.04.040. Epub 2015 May 7.
Human serum albumin (HSA) is the most important drug carrier in humans mainly binding acidic drugs. Negatively charged compounds bind more strongly to HSA than it would be expected from their lipophilicity alone. With the development of new acidic drugs, there is a high need for rapid and simple protein binding screening technologies. Biopartitioning micellar chromatography (BMC) is a mode of micellar liquid chromatography, which can be used as an in vitro system to model the biopartitioning process of drugs when there are no active processes. In this study, a new kind of BMC using hexadecyltrimethylammonium bromide (CTAB) as micellar mobile phases was used for the prediction of protein binding of acidic drugs based on the similar property of CTAB micelles to HSA. The use of BMC is simple, reproducible and can provide key information about the pharmacological behavior of drugs such as protein binding properties of new compounds during the drug discovery process. The relationships between the MLC retention data of a heterogeneous set of 17 acidic and neutral drugs and their plasma protein binding parameter were studied and second-order polynomial models obtained in two different concentrations (0.07 and 0.09M) of CTAB. However, the developed models are only being able to distinguish between strongly and weakly binding drugs. Also, the developed models were characterized by both the descriptive and predictive ability (R(2)=0.885, RCV(2)=0.838 and R(2)=0.898, RCV(2)=0.859 for 0.07 and 0.09M CTAB, respectively). The application of the developed model to a prediction set demonstrated that the model was also reliable with good predictive accuracy.
人血清白蛋白（HSA）是人体内最重要的药物载体，主要结合酸性药物。带负电荷的化合物与HSA的结合比仅根据其亲脂性预期的更强。随着新型酸性药物的开发，迫切需要快速简单的蛋白质结合筛选技术。生物分配胶束色谱法（BMC）是胶束液相色谱的一种模式，在没有活性过程时，它可以用作体外系统来模拟药物的生物分配过程。在本研究中，一种以十六烷基三甲基溴化铵（CTAB）为胶束流动相的新型BMC，基于CTAB胶束与HSA的相似性质，用于预测酸性药物的蛋白质结合。BMC的使用简单、可重复，并且可以在药物发现过程中提供有关药物药理行为的关键信息，如新化合物的蛋白质结合特性。研究了17种酸性和中性药物的多分散体系的胶束液相色谱保留数据与其血浆蛋白结合参数之间的关系，并在两种不同浓度（0.07和0.09M）的CTAB中获得了二阶多项式模型。然而，所开发的模型仅能够区分强结合和弱结合药物。此外，所开发的模型具有描述性和预测能力（对于0.07和0.09M CTAB，R(2)=0.885，RCV(2)=0.838和R(2)=0.898，RCV(2)=0.859）。将所开发的模型应用于预测集表明，该模型也具有良好的预测准确性且可靠。
