Introducing spatial information into predictive NF-kappaB modelling--an agent-based approach.
Nature is governed by local interactions among lower-level sub-units, whether at the cell, organ, organism, or colony level. Adaptive system behaviour emerges via these interactions, which integrate the activity of the sub-units. To understand the system level it is necessary to understand the underlying local interactions. Successful models of local interactions at different levels of biological organisation, including epithelial tissue and ant colonies, have demonstrated the benefits of such 'agent-based' modelling. Here we present an agent-based approach to modelling a crucial biological system--the intracellular NF-kappaB signalling pathway. The pathway is vital to immune response regulation, and is fundamental to basic survival in a range of species. Alterations in pathway regulation underlie a variety of diseases, including atherosclerosis and arthritis. Our modelling of individual molecules, receptors and genes provides a more comprehensive outline of regulatory network mechanisms than previously possible with equation-based approaches. The method also permits consideration of structural parameters in pathway regulation; here we predict that inhibition of NF-kappaB is directly affected by actin filaments of the cytoskeleton sequestering excess inhibitors, therefore regulating steady-state and feedback behaviour.
Department of Computer Science, University of Sheffield, Sheffield, United Kingdom.
Mark
M
Pogson
Mike
M
Holcombe
Rod
R
Smallwood
Eva
E
Qwarnstrom
D015153:Blotting, Western; D004591:Electrophoresis, Polyacrylamide Gel; D031541:Fluorescence Resonance Energy Transfer; D006367:HeLa Cells; D006801:Humans; D047468:Immunoprecipitation; D018613:Microscopy, Confocal; D008958:Models, Molecular; D016328:NF-kappa B / Q000378:metabolism*; D015398:Signal Transduction
D016328:NF-kappa B