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含氯苯酚类化合物结构表征与毒性预测

本站小编 Free考研考试/2021-12-30

廖立敏,
李建凤,
雷光东
内江师范学院化学化工学院, 内江 641100
作者简介: 廖立敏(1981-),男,硕士,副教授,研究方向为分子结构与性能方面,E-mail:liaolimin523@126.com.
基金项目: 四川省教育厅青年基金项目(13ZB0003);四川省科技厅应用基础项目(2015JY0077)


中图分类号: X171.5


Structural Characterization and Toxicity Prediction of Chlorinated Phenolic Compounds

Liao Limin,
Li Jianfeng,
Lei Guangdong
College of Chemistry and Chemical Engineering, Neijiang Normal University, Neijiang 641100, China

CLC number: X171.5

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摘要:将有机化合物中的不同非氢原子及非氢原子之间的关系参数化得到新的结构描述符,运用该描述符对部分含氯苯酚类化合物分子结构进行了参数化表征。采用偏最小二乘回归(PLS)方法构建了化合物结构与毒性(-lgIC50)之间的关系模型,模型的建模相关系数(R2)为0.948,“留一法”交互检验的相关系数(Q2)为0.922,标准偏差(SD)为0.184。结果表明结构描述符能较好地表征化合物分子结构特征,所建模型稳定性好、预测能力强,对于酚类化合物QSAR研究具有一定的参考价值。
关键词: 含氯苯酚类化合物/
毒性值(-lgIC50)/
结构描述符/
结构与活性的关系(QSAR)

Abstract:New structural descriptors were obtained through parameterization of the different non-hydrogen atoms and the relationship between them in organic molecules. Then the molecular structures of some chlorinated phenolic compounds were characterized by the structural descriptors. The partial least squares regression (PLS) method was used to construct a model of relationship between the structures and toxicity (-lgIC50) of chlorinated phenolic compounds. The modeling correlation coefficient (R2) was 0.948, the "leave one out" cross validation correlation coefficient (Q2) was 0.922 and the standard deviation (SD) was 0.184, respectively. The results showed that the structural descriptors could well characterize the molecular structures of the compounds, the stability of the model was good, and the predictive power was strong. This study shows a certain reference value for QSAR study of phenolic compounds.
Key words:chlorinated phenolic compounds/
toxicity (-lgIC50)/
structural descriptor/
structure and activity relationship (QSAR).

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