Quantitative structure–biodegradability relationships for biokinetic parameter of polycyclic aromatic hydrocarbons

Prediction of the biodegradability of organic pollutants is an ecologically desirable and economically feasible tool for estimating the environmental fate of chemicals. In this paper,stepwise multiple linear regression analysis method was applied to establish quantitative structure biodegradability...

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Bibliographic Details
Published inJournal of environmental sciences (China) Vol. 30; no. 4; pp. 180 - 185
Main Authors Xu, Peng, Ma, Wencheng, Han, Hongjun, Jia, Shengyong, Hou, Baolin
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier B.V 01.04.2015
Subjects
Bacteria - metabolism
Biodegradation, Environmental
Environmental Monitoring
Leave-one-out cross-validation
Linear Models
Polycyclic aromatic hydrocarbons
Polycyclic Aromatic Hydrocarbons - chemistry
Polycyclic Aromatic Hydrocarbons - metabolism
QSBR
Quantitative Structure-Activity Relationship
Stepwise multiple linear regression
动力学参数
回归分析方法
多环芳烃
定量结构
有机污染物
生物降解性
生物降解活性
预测能力
Leave-one-out cross-validation
Polycyclic aromatic hydrocarbons
QSBR
Stepwise multiple linear regression
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Summary:Prediction of the biodegradability of organic pollutants is an ecologically desirable and economically feasible tool for estimating the environmental fate of chemicals. In this paper,stepwise multiple linear regression analysis method was applied to establish quantitative structure biodegradability relationship（QSBR） between the chemical structure and a novel biodegradation activity index（qmax） of 20 polycyclic aromatic hydrocarbons（PAHs）. The frequency B3LYP/6-311＋G（2df,p） calculations showed no imaginary values, implying that all the structures are minima on the potential energy surface. After eliminating the parameters which had low related coefficient with qmax, the major descriptors influencing the biodegradation activity were screened to be Freq, D, MR, EHOMOand To IE. The evaluation of the developed QSBR mode, using a leave-one-out cross-validation procedure, showed that the relationships are significant and the model had good robustness and predictive ability. The results would be helpful for understanding the mechanisms governing biodegradation at the molecular level.
Bibliography:Leave-one-out cross-validation Stepwise multiple linear regression Polycyclic aromatic hydrocarbons QSBR
Prediction of the biodegradability of organic pollutants is an ecologically desirable and economically feasible tool for estimating the environmental fate of chemicals. In this paper,stepwise multiple linear regression analysis method was applied to establish quantitative structure biodegradability relationship（QSBR） between the chemical structure and a novel biodegradation activity index（qmax） of 20 polycyclic aromatic hydrocarbons（PAHs）. The frequency B3LYP/6-311＋G（2df,p） calculations showed no imaginary values, implying that all the structures are minima on the potential energy surface. After eliminating the parameters which had low related coefficient with qmax, the major descriptors influencing the biodegradation activity were screened to be Freq, D, MR, EHOMOand To IE. The evaluation of the developed QSBR mode, using a leave-one-out cross-validation procedure, showed that the relationships are significant and the model had good robustness and predictive ability. The results would be helpful for understanding the mechanisms governing biodegradation at the molecular level.
11-2629/X
ObjectType-Article-1
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content type line 23
ISSN:1001-0742
1878-7320
DOI:10.1016/j.jes.2014.07.030