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DFT-Based Prediction of Bioconcentration Factors of Polychlorinated Biphenyls in Fish Species Using Molecular Descriptors

机译:使用分子描述夹的鱼类多氯联苯的生物浓度的基于DFT的预测

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Experimental determination of BCFs is expensive and demanding if performed correctly. Because of this, measuring the BCFs of many thousands of chemical substances that are potential regulatory interest is simply not possible. Hence, prediction of BCFs of the PCBs based on QSAR were made time to time to increase the probability of success and reduce the time and cost in exploring the toxicological and ecological characteristics of molecules. DFT methods are, in general, capable of generating a variety of isolated molecular descriptors as well as local reactivity descriptors quite accurately. In this work, prediction of BCFs of the fifty seven PCBs based on quantum chemical descriptors derived from DFT method using the B88-PW91 GGA energy function with the DZVP basis set have been made. The study concluded that dipole moment and ionization potential are reliable descriptors for correlation of bioconcentration factors of polychlorinated biphenyls with their electronic structures. The resulted QSAR model (r~2 = 0.9139, = 0.8986, k = 2, SE = 0.2668) can be useful for predicting the BCFs of compounds prior to their synthesis.
机译:如果正确执行,BCFS的实验确定是昂贵的,并且需要苛刻。因此,测量许多有潜在的监管兴趣的化学物质的BCF是不可能的。因此,基于QSAR预测基于QSAR的PCB的BCFS,以增加成功的可能性,并减少探索分子毒理学和生态特征的时间和成本。通常,DFT方法能够精确地产生各种分子描述符以及局部反应性描述符。在这项工作中,已经制作了使用与DZV基础组的B88-PW91 GGA能量函数衍生自DFT方法的量子化学描述符的五十七种PCB的BCF的预测。该研究得出结论,偶极矩和电离势是可靠的描述符,用于与其电子结构的多氯联苯的生物浓度因素相关。得到的QSAR模型(​​R〜2 = 0.9139,= 0.8986,k = 2,SE = 0.2668)可用于预测合成之前的化合物的BCF。

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