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

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

Research output: Contribution to journalArticlepeer-review


It is expected that the number and variety of engineered nanoparticles will increase rapidly over the next few years, and there is a need for new methods to quickly test the potential toxicity of these materials. 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.

Original languageEnglish
Pages (from-to)175-178
Number of pages4
JournalNature Nanotechnology
Issue number3
Publication statusPublished - Mar 2011

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering
  • Materials Science(all)
  • Electrical and Electronic Engineering
  • Condensed Matter Physics
  • Atomic and Molecular Physics, and Optics


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