From basic physics to mechanisms of toxicity: the “liquid drop” approach applied to develop predictive classification models for toxicity of metal oxide nanoparticles

What is it about?

In this study, the predictive modeling based on comparative Quantitative-Structure Activity Relationships (nano-QSARs) analyses of a series of nanoparticles on their toxicity towards E.coli and HaCaT cells were established. A new approach for representation of nanoparticles' structure was presented - a liquid drop approach to model a toxicity. It is expected that novel, proposed approach could be of general use for predictions related to nanomaterials.

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Why is it important?

A novel Liquid Drop approach is offered to model toxicity of metal oxide nanoparticles.