Wanat Karolina, Żydek Grażyna, Hekner Adam, Brzezińska Elżbieta
Department of Analytical Chemistry, Faculty of Pharmacy, Medical University of Lodz, 92-216 Lodz, Poland.
Pharmaceuticals (Basel). 2021 Feb 28;14(3):202. doi: 10.3390/ph14030202.
Plasma protein binding is an important determinant of the pharmacokinetic properties of chemical compounds in living organisms. The aim of the present study was to determine the index of protein binding affinity based on chromatographic experiments. The question is which chromatographic environment will best mimic the drug-protein binding conditions. Retention data from normal phase thin-layer liquid chromatography (NP TLC), reversed phase (RP) TLC and HPLC chromatography experiments with 129 active pharmaceutical ingredients (APIs) were collected. The stationary phase of the TLC plates was modified with protein and the HPLC column was filled with immobilized human serum albumin. In both chromatographic methods, the mobile phase was based on a buffer with a pH of 7.4 to mimic physiological conditions. Chemometric analyses were performed to compare multiple linear regression models (MLRs) with retention data, using protein binding values as the dependent variable. In the course of the analysis, APIs were divided into acidic, basic and neutral groups, and separate models were created for each group. The MLR models had a coefficient of determination between 0.73 and 0.91, with the highest values from NP TLC data.
血浆蛋白结合是生物体内化合物药代动力学性质的一个重要决定因素。本研究的目的是基于色谱实验确定蛋白结合亲和力指数。问题在于哪种色谱环境最能模拟药物与蛋白的结合条件。收集了129种活性药物成分（API）在正相薄层液相色谱（NP TLC）、反相（RP）TLC和HPLC色谱实验中的保留数据。TLC板的固定相用蛋白质进行了修饰，HPLC柱填充了固定化人血清白蛋白。在这两种色谱方法中，流动相均基于pH为7.4的缓冲液以模拟生理条件。进行了化学计量学分析，以将多元线性回归模型（MLR）与保留数据进行比较，使用蛋白结合值作为因变量。在分析过程中，将API分为酸性、碱性和中性组，并为每组创建单独的模型。MLR模型的决定系数在0.73至0.91之间，其中NP TLC数据的值最高。
