电拓扑状态预测多氯二苯并噻吩及噻吩砜化合物的气相色谱保留指数

摘要

Structures of 135 polychlorinated dibenzothiophenes （PCDTs） and 135 polychlorinated dibenzothiophene sulfones （PCDTO2s） were characterized using electrotopological state index （ETSI） for atom types. Quantitative linear relationship models were built between gas chromatographic retention index （R/） from DB-5 GC column and ETSI descriptors were established for PCDT and PCDTO2. The models derived from the variable selection and modeling based on prediction （VSMP） technique present correlation coeffi cient （2） of 0.9939 for PCDT and of 0.9729 for PCDTO2, leave-one-out cross-validation coefficient （q2） of 0.9921 for PCDT and of 0.9692 for PCDTO2, respectively. In order to validate the stability and predictive power of the models, 17 PCDT and PCDTO2 were used as training sets to build QSRR models. The models present r2 of 0.9959 for PCDT and of 0.9783 for PCDTO2, q2 of 0.9921 for PCDT and of 0.9740 for PCDTO2. The results demonstrate the robusmess of the QSRR models. The models were used to predict the R/of test set with 8 compounds and predict set with 110 compounds, and the result of test set with 8 com- pounds show that the training set has a good predictive ability.%以原子类型电拓扑状态指数（ETSI）有效表征了135个多氯二苯并噻吩（PCDT）和135个多氯二苯并噻吩砜（PCDTO2）的分子结构，应用基于预测的变量选择与模型化（VSMP）方法建立PCDT和PCDTO2化合物在DB．5气相色谱柱上的气相色谱保留指数（脚与分子结构（ETSI）的定量相关模型，模型的相关系数，分别为0．9939和0．9729，LOO交叉验证相关系数q^2分别为0．9921和0．9692．为验证模型稳定性和预测能力，应用17个PCDT和PCDTO2训练集样本构建的QSRR模型的，分别为0．9959和0．9783，LOO交叉验证相关系数q^2分别为0．9921和0．9740，说明模型具有良好的稳定性．以此模型预测外部8个检验集及110个预测集的RI值，8个检验集样本的结果表明训练集模型具有良好预测能力．