Classification NanoSAR Development for Cytotoxicity of Metal Oxide Nanoparticles
- 24 March 2011
- Vol. 7 (8), 1118-1126
- https://doi.org/10.1002/smll.201002366
Abstract
A classification‐based cytotoxicity nanostructure–activity relationship (nanoSAR) is presented based on a set of nine metal oxide nanoparticles to which transformed bronchial epithelial cells (BEAS‐2B) were exposed over a range of concentrations (0.375–200 mg L−1) and exposure times up to 24 h. The nanoSAR is developed using cytotoxicity data from a high‐throughput screening assay that was processed to identify and label toxic (in terms of the propidium iodide uptake of BEAS‐2B cells) versus nontoxic events relative to an unexposed control cell population. Starting with a set of fourteen intuitive but fundamental physicochemical nanoSAR input parameters, a number of models were identified which had a classification accuracy above 95%. The best‐performing model had a 100% classification accuracy in both internal and external validations. This model is based on three descriptors: atomization energy of the metal oxide, period of the nanoparticle metal, and nanoparticle primary size, in addition to nanoparticle volume fraction (in solution). Notwithstanding the success of the present modeling approach with a relatively small nanoparticle library, it is important to recognize that a significantly larger data set would be needed in order to expand the applicability domain and increase the confidence and reliability of data‐driven nanoSARs.This publication has 51 references indexed in Scilit:
- Quantitative Nanostructure−Activity Relationship ModelingACS Nano, 2010
- Comparative Study of Predictive Computational Models for Nanoparticle-Induced CytotoxicityRisk Analysis, 2010
- Effects of Titanium Dioxide Nanoparticle Aggregate Size on Gene ExpressionInternational Journal of Molecular Sciences, 2010
- Computational methods to predict the reactivity of nanoparticles through structure–property relationshipsExpert Opinion on Drug Delivery, 2010
- Statistical methods for analysis of high-throughput RNA interference screensNature Methods, 2009
- Toxicity and Environmental Risks of Nanomaterials: Challenges and Future NeedsJournal of Environmental Science and Health, Part C, 2009
- Macrophage Responses to Silica Nanoparticles are Highly Conserved Across Particle SizesToxicological Sciences, 2008
- Perturbational profiling of nanomaterial biologic activityProceedings of the National Academy of Sciences of the United States of America, 2008
- Molecular dynamics simulations of nanoparticlesAnnual Reports Section "C" (Physical Chemistry), 2008
- Elucidating the Mechanism of Cellular Uptake and Removal of Protein-Coated Gold Nanoparticles of Different Sizes and ShapesNano Letters, 2007