Biochemical Reaction Network Modeling: Predicting Metabolism of Organic Chemical Mixtures
| Autor: | Raymond S. H. Yang, Brad Reisfeld, Arthur N. Mayeno |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
Trichloroethylene
Chemical compound Metabolite Reactive intermediate General Chemistry Risk Assessment Xenobiotics chemistry.chemical_compound Metabolic pathway Metabolomics chemistry Biotransformation Water Supply Environmental chemistry Environmental Chemistry Computer Simulation Xenobiotic Water Pollutants Chemical Forecasting |
| Zdroj: | Environmental Science & Technology. 39:5363-5371 |
| ISSN: | 1520-5851 0013-936X |
| DOI: | 10.1021/es0479991 |
| Popis: | All organisms are exposed to multiple xenobiotics, through food, environmental contamination, and drugs. These xenobiotics often undergo biotransformation, a complex process that plays a critical role in xenobiotic elimination or bioactivation to toxic metabolites. Here we describe the results of a new computer-based simulation tool that predicts metabolites from exposure to multiple chemicals and interconnects their metabolic pathways, using four common drinking water pollutants (trichloroethylene, perchloroethylene, methylchloroform, and chloroform) as a test case. The simulation tool interconnected the metabolic pathways for these compounds, predicted reactive intermediates, such as epoxides and acid chlorides, and uncovered points in the metabolic pathways where typical endogenous compounds, such as glutathione or carbon dioxide, are consumed or generated. Moreover, novel metabolites, not previously reported, were predicted via this methodology. Metabolite prediction is based on a reaction-mechanism-based methodology, which applies fundamental organic and enzyme chemistry. The tool can be used to (a) complement experimental studies of chemical mixtures, (b) aid in risk assessment, and (c) help understand the effects of complex chemical mixtures. Our results indicate that this tool is useful for predictive xenobiotic metabolomics, providing new and important insights into metabolites and the interrelationship between diverse chemicals that hitherto may have remained unnoticed. |
| Databáze: | OpenAIRE |
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