A novel mathematical model describing adaptive cellular drug metabolism and toxicity in the chemoimmune system
Cells cope with the threat of xenobiotic stress by activating a complex molecular network that recognizes and eliminates chemically diverse toxic compounds. This "chemoimmune system" consists of cellular Phase I and Phase II metabolic enzymes, Phase 0 and Phase III ATP Binding Cassette (AB...
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Published in | PloS one Vol. 10; no. 2; p. e0115533 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Public Library of Science
20.02.2015
Public Library of Science (PLoS) |
Subjects | |
Online Access | Get full text |
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Summary: | Cells cope with the threat of xenobiotic stress by activating a complex molecular network that recognizes and eliminates chemically diverse toxic compounds. This "chemoimmune system" consists of cellular Phase I and Phase II metabolic enzymes, Phase 0 and Phase III ATP Binding Cassette (ABC) membrane transporters, and nuclear receptors regulating these components. In order to provide a systems biology characterization of the chemoimmune network, we designed a reaction kinetic model based on differential equations describing Phase 0-III participants and regulatory elements, and characterized cellular fitness to evaluate toxicity. In spite of the simplifications, the model recapitulates changes associated with acquired drug resistance and allows toxicity predictions under variable protein expression and xenobiotic exposure conditions. Our simulations suggest that multidrug ABC transporters at Phase 0 significantly facilitate the defense function of successive network members by lowering intracellular drug concentrations. The model was extended with a novel toxicity framework which opened the possibility of performing in silico cytotoxicity assays. The alterations of the in silico cytotoxicity curves show good agreement with in vitro cell killing experiments. The behavior of the simplified kinetic model suggests that it can serve as a basis for more complex models to efficiently predict xenobiotic and drug metabolism for human medical applications. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Conceived and designed the experiments: AT AB GS BS TH. Analyzed the data: AT GS BS TH. Wrote the paper: AT AB GS BS TH. Conducted simulations: AT. Competing Interests: The authors declare that co-author Gergely Szakacs is a PLOS ONE Editorial Board member. This does not alter the authors’ adherence to PLOS ONE Editorial policies and criteria. |
ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0115533 |