交互柱法研究固定相极性参数对饱和醇QSRR建模的影响  

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

作　　者：刘凤萍[1] 刘万强[1] 谢文林[1] 周甦[1] 

机构地区：[1]湖南科技大学化学化工学院,湖南湘潭411201

出　　处：《湖南科技大学学报（自然科学版）》2017年第1期79-84,共6页Journal of Hunan University of Science And Technology：Natural Science Edition

基　　金：国家自然科学基金资助项目(21472040);湖南省教育厅基金项目(13C302)

摘　　要：运用chemoffice2004对25个饱和醇的分子结构进行优化,通过Dragon6.0获得1 897个分子结构参数值,再用逐步回归、最佳子集等方法筛选出Chi_H2,REIG等参数,运用多元线性回归(MLR)方法构建了饱和醇在6个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,相关系数R达到0.98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M_p)对饱和醇保留指数的影响.研究结果表明:包含固定相极性参数M_p的交互柱QSRR模型方程对饱和醇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.25 saturated alcohols compounds molecular structure were optimized by chemoffice2004. 1897 molecular structural parameters were obtained by Dragon6.0. Two molecular descriptors （ Chi_H2 and REIG） were selected using Minitabl5 by stepwise regression method. Quantitative structure-retention relationships （QSRR） on single column were established by multiple linear regression with the correlation coefficient R〉0.98. The sum of the first five McReynolds phase constants combing Chi_H2 and REIG molecular descriptors were used to establish the cross-column QSRR. Cross-column retention prediction was evaluated on an internal validation set consisting of 5 alcohols collected with each of the six columns, sequentially excluded from calibration. The statistical analysis showed that the QSRR models have high internal stability and good predictive ability.

关 键 词：饱和醇 定量结构-色谱保留相关关系(QSRR) 麦克雷诺常数 交互柱 

分 类 号：O651[理学—分析化学]