Sensitivity analysis of parameters controlling oscillatory signalling in the NF-κB pathway: the roles of IKK and IκBα

A.E.C. Ihekwaba, D.S. Broomhead, N. Benson, R.L. Grimley, D.B. Kell

Research output: Contribution to journalArticlepeer-review

121 Citations (Scopus)

Abstract

Analysis of cellular signalling interactions is expected to create an enormous informatics challenge, perhaps even greater than that of analysing the genome. A key step in the evolution towards a more quantitative understanding of signalling is to specify explicitly the kinetics of all chemical reaction steps in a pathway. We have reconstructed a model of the nuclear factor, κB (NF-κB) signalling pathway, containing 64 parameters and 26 variables, including steps in which the activation of the NF-κB transcription factor is intimately associated with the phosphorylation and ubiquitination of its inhibitor κB by a membrane-associated kinase, and its translocation from the cytoplasm to the nucleus. We apply sensitivity analysis to the model. This identifies those parameters in this (IκB)/NF-κB signalling system (containing only induced IκBα isoform) that most affect the oscillatory concentration of nuclear NF-κB (in terms of both period and amplitude). The intention is to provide guidance on which proteins are likely to be most significant as drug targets or should be exploited for further, more detailed experiments. The sensitivity coefficients were found to be strongly dependent upon the magnitude of the parameter change studied, indicating the highly non-linear nature of the system. Of the 64 parameters in the model, only eight to nine exerted a major control on nuclear NF-κB oscillations, and each of these involved as reaction participants either the IκB kinase (IKK) or IκBα, directly. This means that the dominant dynamics of the pathway can be reflected, in addition to that of nuclear NF-κB itself, by just two of the other pathway variables. This is conveniently observed in a phase-plane plot.
Original languageEnglish
Pages (from-to) 93–103
Number of pages11
JournalSystems Biology
Volume1
Issue number1
DOIs
Publication statusPublished - 1 Jun 2004
Externally publishedYes

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