Williams, Richard Alun and Timmis, Jon and Qwarnstrom, Eva E. (2017) Investigating IKK Dynamics in the NF-κB Signalling Pathway using X-Machines. In: Proceedings of the 2017 IEEE Congress on Evolutionary Computation : Special Session on Artificial Immune Systems: Algorithms, Simulation, Modelling and Theory. IEEE, pp. 249-256. ISBN 9781509046027
Abstract
The transcription factor NF-κB is a biological component that is central to the regulation of genes involved in the innate immune system. Dysregulation of the pathway is known to be involved in a large number of inflammatory diseases. Although considerable research has been performed since its discovery in 1986, we are still not in a position to control the signalling pathway, and thus limit the effects of NF-κB within promotion of inflammatory diseases. We have developed an agent-based model of the IL-1 stimulated NF-κB signalling pathway, which has been calibrated to wet-lab data at the single-cell level. Through rigorous software engineering, we believe our model provides an abstracted view of the underlying real-world system, and can be used in a predictive capacity through in silico experimentation. In this study, we have focused on the dynamics of the IKK complex and its activation of NF-κB. Our agent-based model suggests that the pathway is sensitive to: variations in the binding probability of IKK to the inhibited NF-κB-IκBα complex; and variations in the temporal rebinding delay of IKK.