CORAL and Nano-OFAR: Quantitative feature – activity relationships (QFAR) for bioavailability of nanoparticles (ZnO, CuO, Co3O4, and TiO2)

Quantitative feature – activity relationships (QFAR) approach was applied to prediction of bioavailability of metal oxide nanoparticles. ZnO, CuO, Co₃O₄, and TiO₂ nanoxides were considered. The computational model for bioavailability of investigated species is asserted. The model was calculated using the Monte Carlo method. The CORAL free software (http://www.insilico.eu/coral) was used in this study. The developed model was tested by application of three different splits of data into the training and validation sets. So-called, quasi-SMILES are used to represent the conditions of action of metal oxide nanoparticles. A new paradigm of building up predictive models of endpoints related to nanomaterials is suggested. The paradigm is the following “An endpoint is a mathematical function of available eclectic data (conditions)”. Recently, the paradigm has been checked up with endpoints related to metal oxide nanoparticles, fullerenes, and multi-walled carbon-nanotubes.