Bakhtiyor Rasulev - Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles

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  Publication Details (including relevant citation   information):

  Puzyn, Tomasz; Rasulev,   Bakhtiyor; Gajewicz, Agnieszka; Hu, Xiaoke; Dasari, Thabitha P.;   Michalkova, Andrea; Hwang, Huey-Min; Toropov, Andrey;   Leszczynska, Danuta; Leszczynski, Jerzy;

 
    Nature Nanotechnology 6, 175–178 (2011)  

    doi:10.1038/nnano.2011.10

  Abstract:

  It is expected that the number and variety of engineered   nanoparticles will increase rapidly over the next few   years1,   and there is a need for new methods to quickly test the potential   toxicity of these materials2.   Because experimental evaluation of the safety of chemicals is   expensive and time-consuming, computational methods have been   found to be efficient alternatives for predicting the potential   toxicity and environmental impact of new nanomaterials before   mass production. Here, we show that the quantitative   structure–activity relationship (QSAR) method commonly used to   predict the physicochemical properties of chemical compounds can   be applied to predict the toxicity of various metal oxides. Based   on experimental testing, we have developed a model to describe   the cytotoxicity of 17 different types of metal oxide   nanoparticles to bacteria Escherichia coli. The model   reliably predicts the toxicity of all considered compounds, and   the methodology is expected to provide guidance for the future   design of safe nanomaterials.

   

  Address (URL): http://www.nature.com/nnano/journal/v6/n3/abs/nnano.2011.10.html

 

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