Forgács E, Cserháti T
Central Research Institute for Chemistry, Hungarian Academy of Sciences, Budapest.
J Chromatogr B Biomed Appl. 1995 Feb 3;664(1):277-85. doi: 10.1016/0378-4347(94)00398-o.
The hydrophobicity and specific hydrophobic surface area of 21 commercial anticancer drugs were determined by reversed-phase high-performance liquid chromatography on an octadecyl-silica column using methanol-water mixtures as eluents. Linear correlations were calculated between the log k' values and the methanol concentration of the eluent, the intercept and slope were considered as the best estimation of the hydrophobicity and specific hydrophobic surface area. The relationship between retention characteristics and physicochemical parameters of drugs was evaluated by multivariate mathematical statistical methods, such as principal component analysis followed by two-dimensional non-linear mapping, varimax rotation and by cluster analysis. Anticancer drugs can be well separated by reversed-phase HPLC. Various multivariate mathematical statistical calculations indicate that the retention of the investigated drugs is mainly governed by hydrophobic and steric parameters. The results suggest that the use of principal component analysis followed by two-dimensional non-linear mapping is superior to cluster analysis for the evaluation of large retention data matrices.
采用十八烷基硅胶柱,以甲醇 - 水混合液为洗脱剂,通过反相高效液相色谱法测定了21种市售抗癌药物的疏水性和比疏水表面积。计算了log k'值与洗脱剂甲醇浓度之间的线性相关性,将截距和斜率视为疏水性和比疏水表面积的最佳估计值。通过多元数学统计方法,如主成分分析后进行二维非线性映射、方差最大化旋转和聚类分析,评估了药物保留特性与理化参数之间的关系。反相高效液相色谱法可很好地分离抗癌药物。各种多元数学统计计算表明,所研究药物的保留主要受疏水和空间参数控制。结果表明,在评估大量保留数据矩阵时,主成分分析后进行二维非线性映射的方法优于聚类分析。