Articles | Volume 18, issue 3
Atmos. Chem. Phys., 18, 2329–2340, 2018
https://doi.org/10.5194/acp-18-2329-2018
Atmos. Chem. Phys., 18, 2329–2340, 2018
https://doi.org/10.5194/acp-18-2329-2018

Research article 16 Feb 2018

Research article | 16 Feb 2018

Evaluating the mutagenic potential of aerosol organic compounds using informatics-based screening

Stefano Decesari et al.

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Cited articles

Alves, D. K. M., Kummrow, F., Cardoso, A. A., Morales, D. A., and Umbuzeiro, G. A.: Mutagenicity Profile of Atmospheric Particulate Matter in a Small Urban Center Subjected to Airborne Emission From Vehicle Traffic and Sugar Cane Burning, Environ. Mol. Mutagen., 57, 41–50, 2016.
Atkinson, R. W., Fuller, G. W., Anderson, H. R., Harrison, R. M., and Armstrong, B.: Urban ambient particle metrics and health: a time-series analysis, Epidemiology, 21, 501–511, 2010.
Barale, R., Giromini, L., Del Ry, S., Barnini, B., Bulleri, M., Barrai, I., Valerio, F., Pala, M., and He, J.: Chemical and Mutagenic Patterns of Airborne Particulate Matter Collected in 17 Italian Towns, Environ. Health Perspect., 102, 67–73, 1994.
Benfenati, E.: In Silico Methods for Predicting Drug Toxicity, in: Methods in Molecular Biology, Vol 1425, Humana press – Springer Science+Business Media: New York, 2016.
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Short summary
Particulate matter (PM) chemical composition includes thousands of individual organic compounds that have never been tested for their toxicological potential. Computational (in silico) screenings represent a promising approach to identify new target compounds for more in-depth toxicological analyses. We provide here a proof-of-concept evaluation based on ca. 100 aerosol organic compounds. Reliable toxicological predictions were obtained for more than 80 % of them.
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