Two homologous series of alkoxyphenylcarbamic acids esters with biological activities were subjected to the QSRR (Quantitative Structure–Retention Relationships) study. Retention factors of studied derivatives were measured in four different HPLC (High Performance Liquid Chromatography) systems. Experimental data in combination with in silico calculated molecular descriptors were used for development complex QSRR model for prediction of retention factor and partially for elucidation of separation mechanisms. The best results in QSRR modelling were given by artificial neural networks in the terms of developing one single robust model with high accuracy of logk prediction (\({Q}_{\mathrm{F}3}^{2}\) = 0.998) for all studied chromatographic systems. Chemometrical techniques were also used to elucidate the separation mechanisms occurring in the HPLC systems. We found similarities between particular systems and we identified systems which were the most suitable for separation of positional isomers of studied compounds. We observed that solvent significantly influenced the chromatographic separation of positional isomers depending on the used column, whereas combination of acetonitrile and C18-phenyl column caused suppression of π − π interactions, so retention was wholly determined by the hydrophobic interactions.

对具有生物学活性的两个系列烷氧基苯基氨基甲酸酯进行了QSRR（定量结构-保留关系）研究。在四种不同的HPLC（高效液相色谱）系统中测量了研究衍生物的保留因子。实验数据与计算机计算的分子描述符相结合，用于开发复杂的QSRR模型，以预测保留因子并部分阐明分离机理。通过开发具有log k预测精度（\（{Q} _ {\ mathrm {F} 3} ^ {2} \）的高精度的单个鲁棒模型，人工神经网络给出了QSRR建模的最佳结果。= 0.998），适用于所有研究的色谱系统。化学计量学技术也用于阐明HPLC系统中发生的分离机理。我们发现了特定系统之间的相似之处，并且确定了最适合于分离所研究化合物的位置异构体的系统。我们观察到，取决于所使用的色谱柱，溶剂会显着影响位置异构体的色谱分离，而乙腈和C18-苯基色谱柱的结合会抑制π  -  π相互作用，因此保留率完全由疏水相互作用决定。