Title: In silico modelling of microbial and human metabolism: a case study with the fungicide carbendazim
Publisher: Publications Office of the European Union
Publication Year: 2010
JRC N°: JRC60264
ISBN: 978-92-79-16744-7
ISSN: 1018-5593
Other Identifiers: EUR 24523 EN
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC60264
DOI: 10.2788/98567
Type: EUR - Scientific and Technical Research Reports
Abstract: A major source of uncertainty when assessing the human health and environmental risks of chemicals is the paucity of experimental information on the metabolic and (bio)degradation pathways of parent compounds and the toxicological properties of their metabolites and (bio)degradation products. Taking into account animal welfare and cost-effectiveness considerations, the only practical means of obtaining the information needed to reduce this uncertainty, is to use alternative (non-animal) methods, such as in vitro tests and in silico models. In this report, we explore the usefulness of in silico metabolic simulation tools (expert systems) as a means of supporting the regulatory assessment of chemicals. In particular, we investigate the use of selected in silico tools to: (i) simulate microbial and mammalian metabolic pathways; (ii) identify potential metabolites resulting from biotransformation; and (iii) gain insights into the mechanistic rationale of simulated metabolic reactions and the likelihood of their occurrence. For illustrative purposes, the microbial and mammalian biotransformation pathways of a case study compound, the fungicide carbendazim, were generated by using the CRAFT Explorer 1.0 (Molecular Networks GmbH) and Meteor 12.0.0 (Lhasa Ltd.) software tools. Additionally, the set of potential metabolites resulting from microbial and mammalian metabolism was predicted with the OECD QSAR Application Toolbox 2.0 (beta version). Comparison of the in silico predictions with existing experimental data on carbendazim metabolism showed the potential usefulness of using software tools for metabolite prediction. However, the results are strongly dependent on the software constraints specified by the user, and require careful interpretation, taking into account the needs of the exercise and the availability of existing information. Further efforts are needed to develop guidance on the use of in silico metabolic simulation tools for the purposes of regulatory risk assessments.
JRC Directorate:Institute for Health and Consumer Protection Historical Collection

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