TY - JOUR
T1 - QSPR Modeling of Bioconcentration Factors of Nonionic Organic Compounds
AU - Deeb, Omar
AU - Khadikar, Padmakar V.
AU - Goodarzi, Mohammad
N1 - Funding Information:
Omar Deeb acknowledges Prof. Dr. Jingwen Chen, Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), School of Environmental Science and Technology, Dalian University of Technology (China) for his valuable suggestions to improve the manuscript. He also acknowledges Dr. Kunal Roy, Drug Theoretics and Cheminformatics Lab, Department of Pharmaceutical Technology, Jadavpur University, Kolkata (India) for his suggestions concerning validation of the proposed models.
Publisher Copyright:
© 2010 SAGE Publications.
PY - 2010
Y1 - 2010
N2 - The terms bioaccumulation and bioconcentration refer to the uptake and build-up of chemicals that can occur in living organisms. Experimental measurement of bioconcentration is time-consuming and expensive, and is not feasible for a large number of chemicals of potential regulatory concern. A highly effective tool depending on a quantitative structure-property relationship (QSPR) can be utilized to describe the tendency of chemical concentration organisms represented by, the important ecotoxicological parameter, the logarithm of Bio Concentration Factor (log BCF) with molecular descriptors for a large set of non-ionic organic compounds. QSPR models were developed using multiple linear regression, partial least squares and neural networks analyses. Linear and non-linear QSPR models to predict log BCF of the compounds developed for the relevant descriptors. The results obtained offer good regression models having good prediction ability. The descriptors used in these models depend on the volume, connectivity, molar refractivity, surface tension and the presence of atoms accepting H-bonds.
AB - The terms bioaccumulation and bioconcentration refer to the uptake and build-up of chemicals that can occur in living organisms. Experimental measurement of bioconcentration is time-consuming and expensive, and is not feasible for a large number of chemicals of potential regulatory concern. A highly effective tool depending on a quantitative structure-property relationship (QSPR) can be utilized to describe the tendency of chemical concentration organisms represented by, the important ecotoxicological parameter, the logarithm of Bio Concentration Factor (log BCF) with molecular descriptors for a large set of non-ionic organic compounds. QSPR models were developed using multiple linear regression, partial least squares and neural networks analyses. Linear and non-linear QSPR models to predict log BCF of the compounds developed for the relevant descriptors. The results obtained offer good regression models having good prediction ability. The descriptors used in these models depend on the volume, connectivity, molar refractivity, surface tension and the presence of atoms accepting H-bonds.
KW - BCF
KW - non-ionic organic compounds
KW - partial least square (PLS)
KW - principal components artificial neural networks (PC-ANN)
KW - structure property relationships (QSPR)
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U2 - 10.4137/EHI.S5168
DO - 10.4137/EHI.S5168
M3 - Article
AN - SCOPUS:79954993114
VL - 4
JO - Environmental Health Insights
JF - Environmental Health Insights
SN - 1178-6302
ER -