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

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.

Development and evaluation of a mechanistic bioconcentration model for ionogenic organic chemicals in fish

“…Arnot and colleagues compiled a database [55] of wholebody biotransformation rate constants (k M , 1/d) for organic chemicals in fish and subsequently developed a screening level quantitative structure-activity relationship (QSAR) model to predict k M from chemical structure [56]. In that QSAR, K OW is one of the parameters included in the prediction of k M .…”

“…Although deriving regression-based equations to describe the relationship between log BCF and hydrophobicity can be successful, it is also apparent that a substantial portion of the variability in empirical BCFs cannot be explained without introducing additional parameters, most importantly to represent susceptibility to biotransformation [55,56]. For example, empirical BCFs for acids with log K OW,N ¼ 6 span approximately three orders of magnitude.…”

“…Relatively low bioaccumulation potential compared to neutral organic compounds is not unexpected, given the effect of ionization on overall sorption capacity. Ionizable functional groups on the molecule such as hydroxyl groups can also result in inherently greater susceptibility to biotransformation [56]. With respect to ecological risk assessment, it is important to reiterate that relatively low bioaccumulation potential (i.e., categorization as ''not B'') may be countered by elevated inherent toxicity, particularly in the case of ionogenic pharmaceuticals and pesticides, which may be more likely to act through specific modes of toxicity (as opposed to via baseline narcosis).…”

“…6.0), no empirical k M data are available for these compounds so estimated values were used in all cases. Carboxylic acids are not well represented in the training and validation sets for the k M -QSAR [55,56]; therefore, these k M predictions may have substantial errors.…”

Fish Toxicity Testing Framework

“…There is on-going work in various arenas to enhance models (Arnot et al 2009), develop novel in vitro approaches (for review, see Weisbrod et al 2009), and to revise the existing OECD TG on bioaccumulation in fish. This revision includes measuring BCF via uptake from water according to the current TG; also an option to reduce the number of fish used in the existing in vivo BCF test (OECD TG 305) (Springer et al 2008); and another option suitable for very hydrophobic substances to measure BAF after dietary uptake.…”