Development of Cytotoxicity Prediction Models of Metal Oxide Nanomaterials Towards L02 Cells and Hep G2 Cells

Objective To build two quantitative nanostructure activity relationship (QNAR) models to predict the cytotoxicity of metal oxide nanomaterials towards human normal liver cells (L02 cells) and human liver cancer cells (Hep G2 cells).

Methods Sixteen metal oxide nanomaterials were selected, twelve of them were put into training set to build model, and the other four were put into validation set to validate model. The study attempted to correlate the eighteen structural descriptors of these metal oxide nanomaterials with their median inhibition concentration (IC₅₀) towards L02 cells and Hep G2 cells by conducting multiple regression analysis.

Results Finally, core-core repulsion energy (CORE) was used to build a statistically significant QNAR model for L02 cells, lgIC₅₀=-0.000 056 2E_CORE+3.34 (fit statistics: n=12, F=35.38, R²=0.72, P < 0.005). Conduction band (Ec) and Schuurmann MO shift alpha (shift) were used to build a statistically significant QNAR model for Hep G2 cells, lgIC₅₀=-0.1E_Ec+0.307E_Shift+3.67 (fit statistics: n=12, F=10.53, R²=0.70, P < 0.005).

Conclusion The correlation coefficients of the two models are larger than 0.6, which meet the criterion of a good model, and these two models can provide supportive information on the design and safety assessment of metal oxide nanomaterials.