Department of Analytical Chemistry, Faculty of Pharmacy, Medical University of Lodz, 90-419 Łódź, Poland.
Molecules. 2022 May 26;27(11):3441. doi: 10.3390/molecules27113441.
Protein binding (PB) is indicated as the factor most severely limiting distribution in the organism, reducing the bioavailability of the drug, but also minimizing the penetration of xenobiotics into the fetus or the body of a breastfed child. Therefore, PB is an important aspect to be analyzed and monitored in the design of new drug substances. In this paper, several statistical analyses have been introduced to find the relationship between protein binding and the amount of drug in breast milk and to select molecular descriptors responsible for both pharmacokinetic phenomena. Along with descriptors related to the physicochemical properties of drugs, chromatographic descriptors from TLC and HPLC experiments were also used. Both methods used modification of the stationary phase, using bovine serum albumin (BSA) in TLC and human serum albumin (HSA) in HPLC. The use of the chromatographic data in the protein binding study was found to be positive -the most effective application of normal-phase TLC and HPLC data was found. Statistical analyses also confirmed the prognostic value of affinity chromatography data and protein binding itself as the most important parameters in predicting drug excretion into breast milk.
蛋白质结合（PB）被认为是在体内分布中限制最严重的因素，降低了药物的生物利用度，但也最大限度地减少了外源性物质进入胎儿或母乳喂养婴儿体内的渗透。因此，在新药物物质的设计中，PB 是一个需要分析和监测的重要方面。在本文中，介绍了几种统计分析方法，以找到蛋白质结合与母乳中药物含量之间的关系，并选择负责这两种药代动力学现象的分子描述符。除了与药物理化性质相关的描述符外，还使用了 TLC 和 HPLC 实验中的色谱描述符。这两种方法都使用了固定相的修饰，TLC 中使用牛血清白蛋白（BSA），HPLC 中使用人血清白蛋白（HSA）。研究发现，在蛋白质结合研究中使用色谱数据是积极的——正相 TLC 和 HPLC 数据的应用最为有效。统计分析还证实了亲和色谱数据和蛋白质结合本身作为预测药物排入母乳中最重要参数的预后价值。
