ArticleTheoretical biology & medical modelling2014
Mathematical modeling of the effects of glutathione on arsenic methylation.
Article in Theoretical biology & medical modelling, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 21 citations in OpenAlex.
- Assessing the Impact of PMEnvironmental science & technology · 2024Article
- Mathematical model for glutathione dynamics in the retina.Scientific reports · 2023Article
- Arsenic toxicokinetic modeling and risk analysis: Progress, needs and applications.Toxicology · 2021Review
- Nutritional Influences on One-Carbon Metabolism: Effects on Arsenic Methylation and Toxicity.Annual review of nutrition · 2018Review
- Arsenic-induced oxidative stress, cholinesterase activity in the brain of Swiss albino mice, and its amelioration by antioxidants Vitamin E and Coenzyme Q10.Environmental science and pollution research international · 2018Article
- Including Rebinding Reactions in Well-Mixed Models of Distributive Biochemical Reactions.Biophysical journal · 2016Article
- Mathematical Models for Immunology: Current State of the Art and Future Research Directions.Bulletin of mathematical biology · 2016Review
- Arsenic and Environmental Health: State of the Science and Future Research Opportunities.Environmental health perspectives · 2016Review
- Mathematical analysis of the regulation of competing methyltransferases.BMC systems biology · 2015Article
- Using mathematical models to understand metabolism, genes, and disease.BMC biology · 2015Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundArsenic is a major environmental toxin that is detoxified in the liver by biochemical mechanisms that are still under study. In the traditional metabolic pathway, arsenic undergoes two methylation reactions, each followed by a reduction, after which it is exported and released in the urine. Recent experiments show that glutathione plays an important role in arsenic detoxification and an alternative biochemical pathway has been proposed in which arsenic is first conjugated by glutathione after which the conjugates are methylated. In addition, in rats arsenic-glutathione conjugates can be exported into the plasma and removed by the liver in the bile.
methodsWe have developed a mathematical model for arsenic biochemistry that includes three mechanisms by which glutathione affects arsenic methylation: glutathione increases the speed of the reduction steps; glutathione affects the activity of arsenic methyltranferase; glutathione sequesters inorganic arsenic and its methylated downstream products. The model is based as much as possible on the known biochemistry of arsenic methylation derived from cellular and experimental studies.
resultsWe show that the model predicts and helps explain recent experimental data on the effects of glutathione on arsenic methylation. We explain why the experimental data imply that monomethyl arsonic acid inhibits the second methylation step. The model predicts time course data from recent experimental studies. We explain why increasing glutathione when it is low increases arsenic methylation and that at very high concentrations increasing glutathione decreases methylation. We explain why the possible temporal variation of the glutathione concentration affects the interpretation of experimental studies that last hours.
conclusionsThe mathematical model aids in the interpretation of data from recent experimental studies and shows that the Challenger pathway of arsenic methylation, supplemented by the glutathione effects described above, is sufficient to understand and predict recent experimental data. More experimental studies are needed to explicate the detailed mechanisms of action of glutathione on arsenic methylation. Recent experimental work on the effects of glutathione on arsenic methylation and our modeling study suggest that supplements that increase hepatic glutathione production should be considered as strategies to reduce adverse health effects in affected populations.
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