Quantitative and mechanistic read across for predicting the skin sensitization potential of alkenes acting via...

Read across is a powerful tool to predict toxicity from structure: It relies on "obvious" chemical similarities to allow for interpolation of activity. This study has extended the read across concept within a known mechanism of action to be quantitative. The chemicals that have been chosen are skin sensitizers and are considered to elicit this response by direct interaction through a direct-acting Michael type addition electrophilic mechanism of action. The Michael addition domain is well-defined for skin sensitizers; however, developing quantitative models for predicting potency within the domain has proven to be difficult. This study highlights the ability of an electrophilicity index (omega) to be used as a measure of similarity for sensitizing chemicals acting through the Michael addition mechanism. The index is shown to offer a chemically interpretable qualitative ranking of the chemicals within the Michael acceptor domain, enabling potentially nonsensitizing and extremely sensitizing chemicals to be easily identified. This study also demonstrates the utility of omega to make predictions of skin sensitization using a mechanism-based read across model. Predictions were made for 19 chemicals within the Michael acceptor domain, with the majority being in good agreement with the experimentally determined values. The mechanism-based read across predictions are in keeping with the OECD principles of transparency and simplicity for quantitative structure-activity relationships and are likely to be of significant benefit to regulators and risk assessors.