研究论文

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

  • 莫凌云 ,
  • 刘红艳 ,
  • 温焕宁
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  • a. 桂林理工大学广西环境工程与保护评价重点实验室 桂林 541004;
    b. 桂林理工大学化学与生物工程学院 桂林 541004;
    c. 广西师范大学珍稀濒危动植物生态与环境保护省部共建教育部重点实验室 桂林 541004

收稿日期: 2011-11-11

  修回日期: 2012-03-07

  网络出版日期: 2012-03-20

基金资助

广西自然科学基金(No. 2011XNSFA018059)、广西壮族自治区教育厅科研(Nos. 201010LX174, 200103YB065)、珍稀濒危动植物生态与环境保护省部共建教育部重点实验室研究基金(No. 1002K001)资助项目.

Prediction of Gas Chromatographic Retention Indices of Polychlorinated Dibenzothiophenes and Polychlorinated Dibenzothiophene Sulfones by Electrotopological State Index

  • Mo Lingyun ,
  • Liu Hongyan ,
  • Wen Huanning
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  • a. The Guangxi Key Laboratory of Environmental Engineering, Protection and Assessment, Guilin University of Technology, Guilin 541004;
    b. College of Chemistry and Bioengineering, Guilin University of Technology, Guilin 541004;
    c. Key Laboratory of Ecology of Rare and Endangered Species and Environmental Protection, Ministry of Education of China, Guangxi Normal University, Guilin 541004

Received date: 2011-11-11

  Revised date: 2012-03-07

  Online published: 2012-03-20

Supported by

Project was supported by the Provincial Natural Science Foundation of Guangxi (No. 2011XNSFA018059), the Ministry of Education of Guangxi Zhuang Autonomous Region (Nos. 201010LX174, 200103YB065) and Key Laboratory of Ecology of Rare and Endangered Species and Environmental Protection (Guangxi Normal University), Ministry of Education, China (No. 1002K001).

摘要

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(RI)与分子结构(ETSI)的定量相关模型, 模型的相关系数r2 分别为0.9939 和0.9729, LOO 交叉验证相关系数 q2 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r2 分别为0.9959 和0.9783, LOO 交叉验证相关系数 q2 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.

本文引用格式

莫凌云 , 刘红艳 , 温焕宁 . 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[J]. 化学学报, 2012 , 70(9) : 1117 -1124 . DOI: 10.6023/A1111113

Abstract

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 (RI) 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 coefficient (r2) 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 robustness of the QSRR models. The models were used to predict the RI of test set with 8 compounds and predict set with 110 compounds, and the result of test set with 8 compounds show that the training set has a good predictive ability.

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