Literature DB >> 24923263

Application of in silico modelling to estimate toxicity of migrating substances from food packaging.

Nicholas Price1, Qasim Chaudhry2.   

Abstract

This study derived toxicity estimates for a set of 136 chemical migrants from food packaging materials using in silico (computational) modelling and read across approaches. Where available, the predicted results for mutagenicity and carcinogenicity were compared with published experimental data. As the packaging compounds are subject to safety assessment, the migrating substances were more likely to be negative for both the endpoints. A set of structural analogues with positive experimental data for carcinogenicity and/or mutagenicity was therefore used as a positive comparator. The results showed that a weight of evidence assembled from different in silico models and read-across from already-tested structurally similar compounds can provide a rapid and reliable means for rapid screening of new yet-untested intentional or unintentional chemical compounds that may migrate to packaged foodstuffs. Crown
Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  (Q)SAR; Computational toxicology; In silico methods; Packaging migrants; Read across; Weight of evidence

Mesh:

Year:  2014        PMID: 24923263     DOI: 10.1016/j.fct.2014.05.022

Source DB:  PubMed          Journal:  Food Chem Toxicol        ISSN: 0278-6915            Impact factor:   6.023


  2 in total

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Authors:  Vinicius Alves; Eugene Muratov; Stephen Capuzzi; Regina Politi; Yen Low; Rodolpho Braga; Alexey V Zakharov; Alexander Sedykh; Elena Mokshyna; Sherif Farag; Carolina Andrade; Victor Kuz'min; Denis Fourches; Alexander Tropsha
Journal:  Green Chem       Date:  2016-06-28       Impact factor: 10.182

2.  Chemistry-Wide Association Studies (CWAS): A Novel Framework for Identifying and Interpreting Structure-Activity Relationships.

Authors:  Yen S Low; Vinicius M Alves; Denis Fourches; Alexander Sedykh; Carolina Horta Andrade; Eugene N Muratov; Ivan Rusyn; Alexander Tropsha
Journal:  J Chem Inf Model       Date:  2018-11-09       Impact factor: 4.956

  2 in total

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