Applicability and Limitation of QSARs for the Toxicity of Electrophilic Chemicals

Abstract

The appropriate selection and application of quantitative structure-activity relationships (QSARs) for the prediction of toxicity is based on the prior assignment of a chemical to its mode of toxic action. This classification is often derived from structural characteristics with the underlying assumption that chemically similar compounds have similar mechanisms of action, which is often but not necessarily the case. Instead of using structural characteristics for classification toward a mode of toxic action, we used Escherichia coli based bioanalytical assays to classify electrophilic chemicals. Analyzing a series of reactive organochlorines, epoxides, and compounds with an activated double bond, three subclasses of reactive toxicity were distinguished: "glutathione depletion-related toxicity", "DNA damage", and "unspecific reactivity". For both subsets of specifically reacting compounds a direct correlation between effects and chemical reactivity was found. Reaction rate constants with either glutathione or 2'-deoxyguanosine, which was used as a model for complex DNA, served well to set up preliminary QSARs for either glutathione depletion-related toxicity or toxicity based on DNA damage in the model organism E. coli. The applicability of QSARs for electrophilic chemicals based on mechanistically relevant reaction rate constants is a priori limited to a small subset of compounds with strictly identical mechanism of toxic action and similar metabolic rates. In contrast, the proposed bioanalytical assays not only allowed the experimental identification of molecular mechanisms underlying the observable toxicity but also their toxicity values are applicable to quantitatively predict toxic effects in higher organisms by linear correlation models, independent of the assigned mode of toxic action.

Structure–activity relationships for thiol reactivity and rat or human hepatocyte toxicity induced by substituted p‐benzoquinone compounds

“…QSAR is a tool that should be looked upon as an aid in chemical risk assessments, and an alternative non-animal method for predicting toxicity that is easy and efficient in terms of time and financial costs (Lessigiarska et al, 2006). However, as advised by Harder et al (2003) the potential influence of metabolism on the occurrence of reactive modes of toxic action should be realized, and therefore we should be looking for toxicity indicators that clearly link observable toxicity with mechanisms of toxic action. QSARs should not be looked at as a final decision predictive tool, but rather as an exploratory tool to provide insight into the functionalities of structure on a particular biological effect (Harder et al, 2003).…”

“…However, as advised by Harder et al (2003) the potential influence of metabolism on the occurrence of reactive modes of toxic action should be realized, and therefore we should be looking for toxicity indicators that clearly link observable toxicity with mechanisms of toxic action. QSARs should not be looked at as a final decision predictive tool, but rather as an exploratory tool to provide insight into the functionalities of structure on a particular biological effect (Harder et al, 2003). This method may help to screen out potentially toxic compounds during the early drug discovery stages and help access risks for chemical toxins.…”

Identification of reactive toxicants: Structure–activity relationships for amides

“…One of the more critical issues in predicting toxicity of industrial organic chemicals in a transparent manner is determining whether a toxicant is reactive and, especially in the case of electrophiles, the correct mechanism of that reactivity (Veith, 2004). Previous analyses, including those of Karabunarliev et al (1996a) and Harder et al (2003), have shown that a priori selection of the correct mode and in some cases the mechanism is essential to an accurate toxicity prediction. This selection is predicated on knowing the domain of applicability for each particular mode and mechanism of toxicity.…”

Developing Methods to Predict Chemical Fate and Effect Endpoints for Use Within REACH

“…The effects were related to reaction rate constants towards model nucleophiles [54]. However, the entire data set needed to be broken down into a number of different subsets because of distinct differences in the reaction mechanism of the nucleophilic substitution reaction and differences in preferred target nucleophile, which resulted in very small data sets and a large number of different QSAR equations unsuitable for further use in regulatory applications [57].…”