Estimation of n-octanol/water partition coefficients of polycyclic aromatic hydrocarbons by quantum chemical descriptors

• Authors: Gui-Ning Lu , Xue-Qin Tao , Zhi Dang , Xiao-Yun Yi , Chen Yang
• Languages of publication: EN

Abstracts

EN

Quantitative structure-property relationship (QSPR) modeling is a powerful approach for predicting environmental behavior of organic pollutants with their structure descriptors. This study reports an optimal QSPR model for estimating logarithmic n-octanol/water partition coefficients (log K OW) of polycyclic aromatic hydrocarbons (PAHs). Quantum chemical descriptors computed with density functional theory at B3LYP/6-31G(d) level and partial least squares (PLS) analysis with optimizing procedure were used for generating QSPR models for log K OW of PAHs. The squared correlation coefficient (R 2) of the optimal model was 0.990, and the results of crossvalidation test (Q 2cum=0.976) showed this optimal model had high fitting precision and good predictability. The log K OW values predicted by the optimal model are very close to those observed. The PLS analysis indicated that PAHs with larger electronic spatial extent and lower total energy values tend to be more hydrophobic and lipophilic. [...]

Keywords

EN

PAH; QSPR; Quantum chemical descriptors

• Publisher: De Gruyter Open
• Journal: Open Chemistry
• Year: 2008
• Volume: 6
• Issue: 2
• Pages: 310-318

Dates

published

1 - 6 - 2008

online

17 - 4 - 2008

Contributors

author

Gui-Ning Lu

author

Xue-Qin Tao

• Department of Environmental Science and Engineering, Zhongkai University of Agriculture and Technology, Guangzhou, 510225, P.R. China

author

Zhi Dang

• School of Environmental Science and Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou, 510006, P.R. China

author

Xiao-Yun Yi

• School of Environmental Science and Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou, 510006, P.R. China

author

Chen Yang

• School of Environmental Science and Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou, 510006, P.R. China

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Identifiers

DOI

10.2478/s11532-008-0010-y