Use of Quantitative Structural Analysis to Predict Fish Bioconcentration Factors for Pesticides

  • Publication Date :
  • Publication Type : Journal Article
  • Author(s) : Jackson SH, Cowan-Ellsberry CE, Thomas G
  • Journal Name : Journal of Agricultural and Food Chemistry

Journal of Agricultural and Food Chemistry. 2009;57(3):958-967

Abstract: The focus of this research was to develop a model based solely on molecular descriptors capable of predicting fish bioconcentration factors (BCF). A fish BCF database was developed from high-quality, regulatory agency reviewed studies for pesticides based on the same laboratory protocol and the same fish species, Lepomis macrochirus. A commercially available software program was used to create a quantitative structure−activity relationship (QSAR) from 93 BCF studies based on unique molecules. An additional 16 molecules were used to test the accuracy of QSAR model predictions for a variety of pesticide classes. Regression of the measured versus predicted log BCF values yielded a regression coefficient of 0.88 for the validation data set. On the basis of the results from this research, the ability to predict BCF by a QSAR regression model is improved using a fully structurally derived model based solely on structural data such as the number of atoms for a given group (e.g., −CH3) or the local topology of each atom as derived from electron counts. Such descriptors provide insightful information on a molecule’s potential BCF behavior in aquatic systems.

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