Desenvolvimento de modelos de QSAR e análise quimioinformática da sensibilização e permeabilidade da pele - Alves, Vinícius de Medeiros (2014)
Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few reports analyzing the relationships between their molecular structure and the sensitization potential including the connection to skin permeability, which is widely considered to be mechanistically implicated in sensitization. In this study, we have compiled, curated, and integrated the largest publicly available datasets related to chemically-induced skin sensitization and skin permeability. Unexpectedly, no correlation between sensitization and permeability has been found. Predictive QSAR models have been developed and validated for both skin sensitization and skin permeability using a standardized workflow fully compliant with the OECD guidelines. The classification accuracies of QSAR models discriminating sensitizers from non-sensitizers were 0.68-0.88 when evaluated on several external validation sets. When compared to the predictions generated by the OECD QSAR Toolbox skin sensitization module, our models had significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate and Negative Predicted Rate as well as Correct Classification Rate. We have also developed QSAR models of skin permeability measured quantitatively. Cross-species correlation between human and rodent permeability data was found to be low (r²=0.44); thus, skin permeability models were developed using human data only and their external accuracy was q²ext = 0.87 (for 62% of external compounds found within the model applicability domain). Skin sensitization models have been employed to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants that should be regarded as primary candidates for the experimental validation.