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首页> 外文期刊>SAR and QSAR in Environmental Research >QSPR-based estimation of the half-lives for poh chlorinated biphenyl congeners
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QSPR-based estimation of the half-lives for poh chlorinated biphenyl congeners

机译:基于QSPR的Poh氯化联苯同源物半衰期估算

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摘要

In this, study, the depuration half-lives of 62 polychlorinated biphenyl (PCB) congeners in juvenile rainbow trout (Oncorhynchus mykiss) were estimated from their structural features based on QSPR methodology. A genetic algorithm (GA) was applied as avariable subset selection strategy and QSPR models established upon multiple linear regression (MLR), multilayer perceptron neural network (MLP NN) and support vector regression (SVR) procedures. Robustness and predictive stability of the constructed models were evaluated through internal and external validation methods. The high numerical values of Q_(1.00)`2> and r~2 and low RMSE in the case of the MLP NN model, confirm the supremacy of this model as well as nonlinear dependency of molecular structural features to the PCB congeners half-lives. In the best developed QSPR model the following four descriptors are used; lopping centric index (Lop), mean topological charge index of order 1 (JGI1), Geary autocorrelation lag-8/weighted by atomic Sandersonelectronegativities (GATS8e) and highest eigenvalue of Burden matrix/weighted by atomic masses (BEHm3). Analysis of the descriptors involved in these models revealed that 2D molecular structural features, compactness and electronegativities are the mainfactors contributing to the half-lives of PCBs. The structural information presented in this work can be used for further evaluation of half-lives of PCBs and other similar structural compounds in the environment.
机译:在这项研究中,根据QSPR方法,根据其结构特征估算了62个多氯联苯(PCB)同系物在虹鳟(Oncorhynchus mykiss)中的净化半衰期。应用遗传算法(GA)作为可变子集选择策略,并基于多元线性回归(MLR),多层感知器神经网络(MLP NN)和支持向量回归(SVR)程序建立了QSPR模型。通过内部和外部验证方法评估了构建模型的鲁棒性和预测稳定性。对于MLP NN模型,Q_(1.00)`2>和r〜2的高数值和低RMSE,证实了该模型的优越性以及分子结构特征对PCB同类化合物半衰期的非线性依赖性。在最佳开发的QSPR模型中,使用了以下四个描述符:倾角中心指数(Lop),1级平均拓扑电荷指数(JGI1),吉利自相关滞后8 /由原子Sanderson电负性(GATS8e)加权和Burden矩阵的最高特征值/由原子质量(BEHm3)加权对这些模型中涉及的描述符的分析表明,二维分子结构特征,紧密度和电负性是影响PCBs半衰期的主要因素。这项工作中介绍的结构信息可用于进一步评估环境中PCBs和其他类似结构化合物的半衰期。

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