Molecular circuits, biological switches, and nonlinear dose-response relationships
| Autor: | C. Tenley French, Raymond S. H. Yang, Melvin E. Andersen, James E. Dennison, Laura S. Chubb |
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| Rok vydání: | 2002 |
| Předmět: |
Cell signaling
Cell division Health Toxicology and Mutagenesis Cellular differentiation Endocrine System Endogeny Computational biology Biology Risk Assessment Xenobiotics Toxicity Tests Humans Receptor Regulation of gene expression Dose-Response Relationship Drug Public Health Environmental and Occupational Health Cell Differentiation Models Theoretical Phenotype Cell biology Cell Transformation Neoplastic Gene Expression Regulation Environmental Pollutants Signal transduction Cell Division Signal Transduction Research Article |
| Zdroj: | Environmental Health Perspectives |
| ISSN: | 1552-9924 0091-6765 |
| DOI: | 10.1289/ehp.02110s6971 |
| Popis: | Signaling motifs (nuclear transcriptional receptors, kinase/phosphatase cascades, G-coupled protein receptors, etc.) have composite dose-response behaviors in relation to concentrations of protein receptors and endogenous signaling molecules. "Molecular circuits" include the biological components and their interactions that comprise the workings of these signaling motifs. Many of these molecular circuits have nonlinear dose-response behaviors for endogenous ligands and for exogenous toxicants, acting as switches with "all-or-none" responses over a narrow range of concentration. In turn, these biological switches regulate large-scale cellular processes, e.g., commitment to cell division, cell differentiation, and phenotypic alterations. Biologically based dose-response (BBDR) models accounting for these biological switches would improve risk assessment for many nonlinear processes in toxicology. These BBDR models must account for normal control of the signaling motifs and for perturbations by toxic compounds. We describe several of these biological switches, current tools available for constructing BBDR models of these processes, and the potential value of these models in risk assessment. |
| Databáze: | OpenAIRE |
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