交互柱法研究固定相极性参数对饱和酯QSRR建模的影响

Research on the effect of the column polarity on QSRR model for saturated esters compounds

用Chemoffice建构和优化了90个饱和酯的分子结构,运用Dragon6.0计算了2337个结构参数,采用Minitab15进行逐步回归筛选出2个结构参数SpPosA_Dz(Z)和RDF020p,通过多元线性回归方法构建了饱和酯化合物在7种不同极性色谱固定相上的定量结构-色谱保留相关关系(QSRR)模型,模型方程的相关系数在0.99以上。在此基础上建立交互柱QSRR模型,考察色谱固定相极性参数麦克雷诺常数(Mp)对保留指数的影响。研究结果表明:包含固定相极性参数Mp的交互柱QSRR模型方程对饱和酯化合物在不同极性色谱柱上的色谱保留指数都能得到较准确的预测结果。

The molecular structures of 90 saturated esters were constructed and optimized by Chemoffice 3D. 2337 structural parametersof each compound were extracted by the soRware of Dragon6.0. Two molecular descriptors SpPosADz（Z） and RDFO20p were selected using Minitabl5 software by stepwise regression method. Quantitative structure-retention relationships （QSRR） on single column was established by multiple linear regression with the correlation coefficient R 〉 0.99. The sum of the first five McReynolds phase constants combing SpPosADz（Z） and RDFO20p molecular descriptors were used to establish the cross-colunm QSRR. Cross-column retention prediction was evaluated on an internal validation set consisting of 30 esters collected with each of the seven columns, sequentially ex- cluded from calibration. The statistical analysis showed that the QSRR models had high internal stability and good predictive ability.