Citation:
MO Ling-Yun, QIN Ru-Qiong, QIN Li-Tang, ZENG Hong-Hu, LIANG Yan-Peng. Study on the Quantitative Relationship between the Structure and Toxicity of Organophosphorus Pesticide[J]. Chinese Journal of Structural Chemistry,
2016, 34(10): 1473-1478.
doi:
10.14102/j.cnki.0254-5861.2011-0793
Study on the Quantitative Relationship between the Structure and Toxicity of Organophosphorus Pesticide
摘要:
The molecular electronegativity distance vector (MEDV) was applied to characterize the molecular structures of 30 organophosphorous compounds. Optimum MEDV descriptors were selected by using the variable selection and modeling method based on the prediction (VSMP) technique. The quantitative structure-toxicity relationship (QSTR) model was built for acute toxicity (96h pLC50) of organophosphorous compounds to steelhead. The developed QSTR model with strictly internal and external validations presents relatively high correlation coefficient (R2) of 0.9518, leave-one-out (LOO) cross-validated correlation coefficient (QLOO2) of 0.9355, and leave-many-out (LMO) cross-validated correlation coefficient (QLMO2) of 0.9290. The robustness of the model was confirmed by the y-randomization test (Ryrand2=0.0772 and Qyrand2=-0.5313) and bootstrapping (Rbstr2=0.9502 and Qbstr2=0.9177) method. The result of external validation, QF12=0.9336, QF22=0.9336, QF32=0.9447, rm2=0.8120, and CCC=0.9602, shows that the QSTR model has a high predictive ability.
English
Study on the Quantitative Relationship between the Structure and Toxicity of Organophosphorus Pesticide
Abstract:
The molecular electronegativity distance vector (MEDV) was applied to characterize the molecular structures of 30 organophosphorous compounds. Optimum MEDV descriptors were selected by using the variable selection and modeling method based on the prediction (VSMP) technique. The quantitative structure-toxicity relationship (QSTR) model was built for acute toxicity (96h pLC50) of organophosphorous compounds to steelhead. The developed QSTR model with strictly internal and external validations presents relatively high correlation coefficient (R2) of 0.9518, leave-one-out (LOO) cross-validated correlation coefficient (QLOO2) of 0.9355, and leave-many-out (LMO) cross-validated correlation coefficient (QLMO2) of 0.9290. The robustness of the model was confirmed by the y-randomization test (Ryrand2=0.0772 and Qyrand2=-0.5313) and bootstrapping (Rbstr2=0.9502 and Qbstr2=0.9177) method. The result of external validation, QF12=0.9336, QF22=0.9336, QF32=0.9447, rm2=0.8120, and CCC=0.9602, shows that the QSTR model has a high predictive ability.
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Key words:
- molecular electronegativity distance vector (MEDV)
- / QSTR
- / organophosphorus
- / pLC50
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