QSAR modelling of bioconcentration factor using hydrophobicity, hydrogen bonding and topological descriptors
Authors:
- 1 October 2010
- journal article
- research article
- Published by Taylor & Francis in SAR and QSAR in Environmental Research
- Vol. 21 (7-8) , 671-680
Abstract
Bioconcentration factor (BCF) is an important step in the uptake of environmental pollutants in the food chain. It is expensive and time-consuming to measure, so predictive methods are of value. We have used an artificial neural network QSAR approach involving descriptors for hydrophobicity, hydrogen bonding and molecular topology, obtained from commercially available software, to predict the fish BCF values of a diverse data set of 624 chemicals. The training set statistics were: r 2 = 0.765, q 2 = 0.763, s = 0.610, and those of the external test set were: r 2 = 0.739, s = 0.627. The model complies with the OECD Principles for the Validation of (Q)SARs.Keywords
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