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醚类有机污染物结构与毒性关系研究
引用本文:廖立敏.醚类有机污染物结构与毒性关系研究[J].内江师范学院学报,2009,24(10):44-48.
作者姓名:廖立敏
作者单位:内江师范学院资源与环境科学学院,四川,内江,641112
摘    要:采用分子电性相互作用矢量对25种醚类化合物进行了结构表征,并与其对幼鼠的毒性值(pC50)建立定量结构一活性关系(QSAR)模型.利用多元线性回归(MLR),得到的5变量模型(M1)复相关系数(Ri)为0.918、标准偏差(SD,)为0.128,留一法(LOO)交互校验(CV)预测值的复相关系数(R^2CV1)为0.845、标准偏差(SDcv1)为0.175.用逐步回归的方法筛选3变量进行建模(M2),复相关系数(R2^2)为0.912、标准偏差(SD2)为0.125,留一法(LOO)交互校验(CV)预测值的复相关系数(R^2CV2)为0.871、标准偏差(SDcv2)为0.152.结果表明模型具有良好的预-测能力与稳定性.

关 键 词:醚类化合物  毒性  结构描述子  定量结构一活性相关

Research into the Quantitative Structure-Toxicity Relationships in Etheric Compounds
LIAO Li-min.Research into the Quantitative Structure-Toxicity Relationships in Etheric Compounds[J].Journal of Neijiang Teachers College,2009,24(10):44-48.
Authors:LIAO Li-min
Institution:LIAO Li-min (School of Resource and Entironmental Sciences, Neijiang Normal University, Neijiang, Sichuan 641112, China)
Abstract:Molecular electronegativity-interaction vector (MEIV) was used to describe the structures of 25 etheric compounds and, in combination of the toxicity value (pC50) upon young mice, a QSAR model was established, By the use of multiple linear regression (MLR), the correlation coefficient (R1^2) of the 5-variable model (M1) turned out to be 0. 918, and the standard deviation (SD1) was 0. 128. Then the model was evaluated by performing the cross validation(CV) with the leaveone-out (LOO) procedure and the results became 0. 845 in the correlation coefficient(R^2cv1 ) and 0. 175 the in standard deviation (SDcv1). By adopting the method of stepwise multiple regression (SMR), 3 variables were selected to build another model (M2), the correlation coefficient (R2^2 ) of which became 0.912 and the standard deviation (SD2) was 0. 125, respectively. The model also was evaluated by performing the cross validation with the LOO procedure and the results showed the correlation coefficient (R^2cv2 ) was 0. 871 and the standard deviation (SDcv2 ) was 0. 152, respectively. The results showed that the models had nice predictive power and stability.
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