Predicting toxic potencies of metal oxide nanoparticles by means of nano-QSARs

AbstractBackground: The enormous physicochemical and structural diversity of metal oxide nanoparticles (MeONPs) poses significant challenges to the testing of their biological uptake, biodistribution, and effects that can be used to develop understanding of key nano-bio modes of action. This has generated considerable uncertainties in the assessment of their human health and environmental risks and has raised concerns about the adequacy of their regulation. In order to surpass the extremely resource intensive case-by-case testing, intelligent strategies combining testing methods and non-testing predictive modeling should be developed.Methods: The quantitative structure-activity relationship (QSARs) in silico tools can be instrumental in understanding properties that affect the potencies of MeONPs and in predicting toxic responses and thresholds of effects.Results: The present study proposes a predictive nano-QSAR model for predicting the cytotoxicity of MeONPs. The model was applied to test the relationsh...