Get access

A quantitative structure-activity relationship for predicting metabolic biotransformation rates for organic chemicals in fish

Authors

  • Jon A. Arnot,

    Corresponding author
    1. Centre for Environmental Modelling and Chemistry, Trent University, 1600 West Bank Drive, Peterborough, Ontario K9H 7B8, Canada
    • Centre for Environmental Modelling and Chemistry, Trent University, 1600 West Bank Drive, Peterborough, Ontario K9H 7B8, Canada
    Search for more papers by this author
  • William Meylan,

    1. Syracuse Research Corporation, Environmental Sciences Center, 6225 Running Ridge Road, North Syracuse, New York 13212, USA
    Search for more papers by this author
  • Jay Tunkel,

    1. Syracuse Research Corporation, Environmental Sciences Center, 6225 Running Ridge Road, North Syracuse, New York 13212, USA
    Search for more papers by this author
  • Phil H. Howard,

    1. Syracuse Research Corporation, Environmental Sciences Center, 6225 Running Ridge Road, North Syracuse, New York 13212, USA
    Search for more papers by this author
  • Don Mackay,

    1. Centre for Environmental Modelling and Chemistry, Trent University, 1600 West Bank Drive, Peterborough, Ontario K9H 7B8, Canada
    Search for more papers by this author
  • Mark Bonnell,

    1. Science and Technology Division, Environment Canada, 351 St-Joseph Boulevard, Gatineau, Quebec K1A 0H3, Canada
    Search for more papers by this author
  • Robert S. Boethling

    1. U.S. Environmental Protection Agency, Office of Pollution Prevention and Toxics, 1200 Pennsylvania Avenue Northwest, Washington, DC 20460
    Search for more papers by this author

Abstract

An evaluated database of whole body in vivo biotransformation rate estimates in fish was used to develop a model for predicting the primary biotransformation half-lives of organic chemicals. The estimated biotransformation rates were converted to half-lives and divided into a model development set (n = 421) and an external validation set (n = 211) to test the model. The model uses molecular substructures similar to those of other biodegradation models. The biotransformation half-life predictions were calculated based on multiple linear regressions of development set data against counts of 57 molecular substructures, the octanol-water partition coefficient, and molar mass. The coefficient of determination (r2) for the development set was 0.82, the cross-validation (leave-one-out coefficient of determination, q2) was 0.75, and the mean absolute error (MAE) was 0.38 log units (factor of 2.4). Results for the external validation of the model using an independent test set were r2 = 0.73 and MAE = 0.45 log units (factor of 2.8). For the development set, 68 and 95% of the predicted values were within a factor of 3 and a factor of 10 of the expected values, respectively. For the test (or validation) set, 63 and 90% of the predicted values were within a factor of 3 and a factor of 10 of the expected values, respectively. Reasons for discrepancies between model predictions and expected values are discussed and recommendations are made for improving the model. This model can predict biotransformation rate constants from chemical structure for screening level bioaccumulation hazard assessments, exposure and risk assessments, comparisons with other in vivo and in vitro estimates, and as a contribution to testing strategies that reduce animal usage.

Get access to the full text of this article

Ancillary