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首页> 外文期刊>Journal of Molecular Modeling >QSTR with extended topochemical atom (ETA) indices. VI. Acute toxicity of benzene derivatives to tadpoles (Rana japonica)
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QSTR with extended topochemical atom (ETA) indices. VI. Acute toxicity of benzene derivatives to tadpoles (Rana japonica)

机译:具有扩展的拓扑化学原子(ETA)指数的QSTR。 VI。苯衍生物对t的急性毒性

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摘要

Quantitative structure-toxicity relationship (QSTR) studies have proved to be a valuable approach in research on the toxicity of organic chemicals for ranking chemical substances with respect to their potential hazardous effects on living systems. With this background, we have modeled here the acute lethal toxicity of 51 benzene derivatives with recently introduced extended topochemical atom (ETA) indices [Roy and Ghosh, Internet Electron J Mol Des 2:599–620 (2003)]. We also compared the ETA relations with non-ETA models derived from different topological indices (Wiener W, Balaban J, flexibility index ϕ, Hosoya Z, Zagreb, molecular connectivity indices, E-state indices and kappa shape indices) and physicochemical parameters (AlogP98, MolRef,H_bond_donor and H_bond_acceptor). Genetic function approximation (GFA) and factor analysis (FA) were used as the data-preprocessing steps for the development of final multiple linear regression (MLR) equations. Principal-component regression analysis (PCRA) was also used to extract the total information from the ETAon-ETA/combined matrices. All the models developed were cross-validated using leave-one-out (LOO) and leave-many-out techniques. The summary of the statistics of the best models is as follows: (1) FA-MLR: ETA model- Q 2 (LOO)=0.852, R 2=0.894; non-ETA model- Q 2=0.782, R 2=0.835; ETA + non-ETA model-Q 2 =0.815, R 2=0.859. (2) GFA-MLR: ETA model-Q 2 =0.847, R 2=0.915; non-ETA model-Q 2 =0.863, R 2=0.898; ETA + non-ETA model-Q 2 =0.859, R 2=0.893. 3. PCRA: ETA model-Q 2 =0.864, R 2=0.901; non-ETA model- Q 2=0.866, R 2=0.922; ETA + non-ETA model-Q 2=0.846, R 2=0.890. The statistical quality of the ETA models is comparable to that of non-ETA models. Again, use of non-ETA descriptors in addition to ETA descriptors does not increase the statistical acceptance of the relations significantly. The predictive potential of these models was better than that of the previously reported models using physicochemical parameters [Huang et al., Chemosphere 53:963–970 (2003)]. The relations from ETA descriptors suggest a parabolic dependence of the toxicity on molecular size. Furthermore, the toxicity increases with functionality contribution of chloro substituent and decreases with those of methoxy, hydroxy, carboxy and amino groups. This study suggests that ETA parameters are sufficiently rich in chemical information to encode the structural features that contribute significantly to the acute toxicity of benzene derivatives to Rana japonica.
机译:定量结构-毒性关系(QSTR)研究已被证明是有机化学的毒性研究中一种有价值的方法,该化学方法用于根据化学物质对生物系统的潜在危害进行分类。在此背景下,我们以最近引入的扩展拓扑化学原子(ETA)指数为模型,对51种苯衍生物的急性致死毒性进行了建模[Roy and Ghosh,Internet Electron J Mol Des 2:599-620(2003)]。我们还将ETA关系与衍生自不同拓扑指数(维纳W,巴拉邦J,柔韧性指数ϕ,Hosoya Z,萨格勒布,分子连通性指数,电子状态指数和kappa形状指数)的非ETA模型进行了比较,以及理化参数(AlogP98 ,MolRef,H_bond_donor和H_bond_acceptor)。遗传函数近似(GFA)和因子分析(FA)被用作开发最终多元线性回归(MLR)方程的数据预处理步骤。主成分回归分析(PCRA)也用于从ETA /非ETA /组合矩阵中提取总信息。所有开发的模型都使用留一法(LOO)和留多法进行交叉验证。最佳模型的统计总结如下:(1)FA-MLR:ETA模型-Q 2 (LOO)= 0.852,R 2 = 0.894;非ETA模型-Q 2 = 0.782,R 2 = 0.835; ETA +非ETA模型-Q 2 = 0.815,R 2 = 0.859。 (2)GFA-MLR:ETA模型-Q 2 = 0.847,R 2 = 0.915;非ETA模型-Q 2 = 0.863,R 2 = 0.898; ETA +非ETA模型-Q 2 = 0.859,R 2 = 0.893。 3.PCRA:ETA模型-Q 2 = 0.864,R 2 = 0.901;非ETA模型-Q 2 = 0.866,R 2 = 0.922; ETA +非ETA模型-Q 2 = 0.846,R 2 = 0.890。 ETA模型的统计质量可与非ETA模型的统计质量相比。同样,除了ETA描述符外,使用非ETA描述符也不会显着增加关系的统计接受度。这些模型的预测潜力比以前报道的使用物理化学参数的模型更好[Huang et al。,Chemosphere 53:963-970(2003)]。来自ETA描述子的关系表明,毒性与分子大小呈抛物线关系。此外,毒性随着氯取代基的官能度贡献而增加​​,并且随着甲氧基,羟基,羧基和氨基的毒性而降低。这项研究表明,ETA参数在化学信息方面足够丰富,可以编码对苯衍生物对日本蛙的急性毒性有重大贡献的结构特征。

著录项

  • 来源
    《Journal of Molecular Modeling》 |2006年第3期|306-316|共11页
  • 作者

    Kunal Roy; Gopinath Ghosh;

  • 作者单位

    Division of Medicinal and Pharmaceutical Chemistry Department of Pharmaceutical Technology Drug Theoretics and Cheminformatics Lab Jadavpur University;

    Division of Medicinal and Pharmaceutical Chemistry Department of Pharmaceutical Technology Drug Theoretics and Cheminformatics Lab Jadavpur University;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    QSTR; QSAR; ETA; TAU; VEM; Factor analysis; Genetic function approximation;

    机译:QSTR;QSAR;ETA;TAU;VEM;因子分析;遗传函数逼近;

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