Literature DB >> 17052119

Sensitivity analysis of parameters controlling oscillatory signalling in the NF-kappaB pathway: the roles of IKK and IkappaBalpha.

A E C Ihekwaba1, D S Broomhead, R L Grimley, N Benson, D B Kell.   

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, kappaB (NF-kappaB) signalling pathway, containing 64 parameters and 26 variables, including steps in which the activation of the NF-kappaB transcription factor is intimately associated with the phosphorylation and ubiquitination of its inhibitor kappaB 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 (IkappaB)/NF-kappaB signalling system (containing only induced IkappaBalpha isoform) that most affect the oscillatory concentration of nuclear NF-kappaB (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-kappaB oscillations, and each of these involved as reaction participants either the IkappaB kinase (IKK) or IkappaBalpha, directly. This means that the dominant dynamics of the pathway can be reflected, in addition to that of nuclear NF-kappaB itself, by just two of the other pathway variables. This is conveniently observed in a phase-plane plot.

Entities:  

Mesh:

Substances:

Year:  2004        PMID: 17052119     DOI: 10.1049/sb:20045009

Source DB:  PubMed          Journal:  Syst Biol (Stevenage)        ISSN: 1741-2471


  42 in total

1.  A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling.

Authors:  T Sumner; E Shephard; I D L Bogle
Journal:  J R Soc Interface       Date:  2012-04-04       Impact factor: 4.118

2.  Population robustness arising from cellular heterogeneity.

Authors:  Pawel Paszek; Sheila Ryan; Louise Ashall; Kate Sillitoe; Claire V Harper; David G Spiller; David A Rand; Michael R H White
Journal:  Proc Natl Acad Sci U S A       Date:  2010-06-07       Impact factor: 11.205

3.  Oncogenes are to lose control on signaling following mutation: should we aim off target?

Authors:  Jorrit J Hornberg; Hans V Westerhoff
Journal:  Mol Biotechnol       Date:  2006-10       Impact factor: 2.695

4.  NETWORKS, BIOLOGY AND SYSTEMS ENGINEERING: A CASE STUDY IN INFLAMMATION.

Authors:  P T Foteinou; E Yang; I P Androulakis
Journal:  Comput Chem Eng       Date:  2009-12-10       Impact factor: 3.845

5.  Mapping global sensitivity of cellular network dynamics: sensitivity heat maps and a global summation law.

Authors:  D A Rand
Journal:  J R Soc Interface       Date:  2008-08-06       Impact factor: 4.118

6.  Calibration of dynamic models of biological systems with KInfer.

Authors:  Paola Lecca; Alida Palmisano; Adaoha Ihekwaba; Corrado Priami
Journal:  Eur Biophys J       Date:  2009-08-11       Impact factor: 1.733

7.  Modeling autonomic regulation of cardiac function and heart rate variability in human endotoxemia.

Authors:  Jeremy D Scheff; Panteleimon D Mavroudis; Steven E Calvano; Stephen F Lowry; Ioannis P Androulakis
Journal:  Physiol Genomics       Date:  2011-06-14       Impact factor: 3.107

8.  Robust simplifications of multiscale biochemical networks.

Authors:  Ovidiu Radulescu; Alexander N Gorban; Andrei Zinovyev; Alain Lilienbaum
Journal:  BMC Syst Biol       Date:  2008-10-14

9.  In silico simulation of corticosteroids effect on an NFkB- dependent physicochemical model of systemic inflammation.

Authors:  Panagiota T Foteinou; Steve E Calvano; Stephen F Lowry; Ioannis P Androulakis
Journal:  PLoS One       Date:  2009-03-10       Impact factor: 3.240

10.  Elucidation of functional consequences of signalling pathway interactions.

Authors:  Adaoha E C Ihekwaba; Phuong T Nguyen; Corrado Priami
Journal:  BMC Bioinformatics       Date:  2009-11-06       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.