(Q)SAR modelling of nanomaterial toxicity: A critical review |
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| Institution: | 1. Institute of Particle Science and Engineering, School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, UK;2. School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510641, China;1. MicroElectronics-Photonics Program, University of Arkansas, Fayetteville, AR 72701, USA;2. Ralph E. Martin Department of Chemical Engineering, University of Arkansas, Fayetteville, AR 72701, USA;3. Department of Mechanical Engineering, University of Tulsa, Tulsa, OK 74104, USA;1. Institute for Software Integrated Systems, Vanderbilt University, Nashville, TN, USA;2. Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN, USA |
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| Abstract: | There is increasing recognition that some nanomaterials may pose a risk to human health and the environment. Moreover, the industrial use of the novel engineered nanomaterials (ENMs) increases at a higher rate than data generation for hazard assessment; consequently, many of them remain untested. The large number of nanomaterials and their variants (e.g., different sizes and coatings) requiring testing and the ethical pressure towards nonanimal testing means that in a first instance, expensive animal bioassays are precluded, and the use of (quantitative) structure–activity relationships ((Q)SARs) models as an alternative source of (screening) hazard information should be explored. (Q)SAR modelling can be applied to contribute towards filling important knowledge gaps by making best use of existing data, prioritizing the physicochemical parameters driving toxicity, and providing practical solutions for the risk assessment problems caused by the diversity of ENMs. This paper covers the core components required for successful application of (Q)SAR methods to ENM toxicity prediction, summarizes the published nano-(Q)SAR studies, and outlines the challenges ahead for nano-(Q)SAR modelling. It provides a critical review of (1) the present availability of ENM characterization/toxicity data, (2) the characterization of nanostructures that meet the requirements for (Q)SAR analysis, (3) published nano-(Q)SAR studies and their limitations, (4) in silico tools for (Q)SAR screening of nanotoxicity, and (5) prospective directions for the development of nano-(Q)SAR models. |
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| Keywords: | Nanomaterial toxicity Nanotoxicology QSAR NanoSAR In silico toxicity prediction |
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