Acta Chimica Sinica ›› 2012, Vol. 70 ›› Issue (9): 1117-1124.DOI: 10.6023/A1111113 Previous Articles     Next Articles

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莫凌云a,b,c, 刘红艳a,b, 温焕宁b   

  1. 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
  • 投稿日期:2011-11-11 修回日期:2012-03-07 发布日期:2012-03-20
  • 通讯作者: 莫凌云
  • 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 Lingyuna,b,c, Liu Hongyana,b, Wen Huanningb   

  1. 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:2011-11-11 Revised:2012-03-07 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).

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.

Key words: polychlorinated dibenzothiophene (PCDT), polychlorinated dibenzothiophene sulfone (PCDTO2), quantitative structure-retention relationship (QSRR), electrotopological state index (ETSI)