ИСТИНА

In the recent decades, nanomaterials have deeply integrated into our everyday’s life. There are numerous examples of already established and possible applications of using nanoparticles such as textile, cosmetics, optical, pharmacy, electronics, etc. Although the nanotechnology field is growing rapidly, the potential harmful effects of nanomaterials on human’s health or the environment have not yet been identified. Thus, there is a clear need for assessment of such potentially dangerous toxic effects of nanomaterials. The classical way of assessing toxicity, e.g. by performing in-vivo experiments of hydrobionts, is very expensive and time consuming. Performing such tests for all possible nanoparticle types, sizes and concentrations is practically infeasible. A cheap and efficient alternative to such tests is using predictive computational models, for example Quantitative Structure-Activity Relationship (QSAR) models. Using QSARs for nanoparticles is a new and still developing area of research. Within our study, we have collected toxicity data for a number of nanoparticles (currently, metals and metal oxides) for different species: daphnids, planaria worms, mussels. Additionally, we have collected the information for different nanoparticles sizes, under different concentrations and exposure intervals. The data has been uploaded to the Online Chemical Modeling Environment (www.ochem.eu) and is publicly accessible by everyone on the Web. In our studies, we plan to use this data to develop predictive QSAR models for nanoparticles toxicity. Several models calculated using measured properties of nanoparticles are presented. The further work will include development of new descriptors to characterize nano-particles according to their chemical composition and size.