Interactions among cell signalling systems; CIBA foundation symposium No. 164

1992 ◽  
Vol 23 (6) ◽  
pp. 1230
2012 ◽  
Vol 367 (1602) ◽  
pp. 2540-2555 ◽  
Author(s):  
Jing Jin ◽  
Tony Pawson

Phosphorylation sites are formed by protein kinases (‘writers’), frequently exert their effects following recognition by phospho-binding proteins (‘readers’) and are removed by protein phosphatases (‘erasers’). This writer–reader–eraser toolkit allows phosphorylation events to control a broad range of regulatory processes, and has been pivotal in the evolution of new functions required for the development of multi-cellular animals. The proteins that comprise this system of protein kinases, phospho-binding targets and phosphatases are typically modular in organization, in the sense that they are composed of multiple globular domains and smaller peptide motifs with binding or catalytic properties. The linkage of these binding and catalytic modules in new ways through genetic recombination, and the selection of particular domain combinations, has promoted the evolution of novel, biologically useful processes. Conversely, the joining of domains in aberrant combinations can subvert cell signalling and be causative in diseases such as cancer. Major inventions such as phosphotyrosine (pTyr)-mediated signalling that flourished in the first multi-cellular animals and their immediate predecessors resulted from stepwise evolutionary progression. This involved changes in the binding properties of interaction domains such as SH2 and their linkage to new domain types, and alterations in the catalytic specificities of kinases and phosphatases. This review will focus on the modular aspects of signalling networks and the mechanism by which they may have evolved.


2008 ◽  
Vol 8 (1) ◽  
pp. 61-64 ◽  
Author(s):  
Cristina Ripoll ◽  
Ana Ropero ◽  
Paloma Alonso-Magdalena ◽  
Ivan Quesada ◽  
Esther Fuentes ◽  
...  

2008 ◽  
Vol 45 ◽  
pp. 83-94 ◽  
Author(s):  
Padmini Rangamani ◽  
Ravi Iyengar

Cell signalling pathways and networks are complex and often non-linear. Signalling pathways can be represented as systems of biochemical reactions that can be modelled using differential equations. Computational modelling of cell signalling pathways is emerging as a tool that facilitates mechanistic understanding of complex biological systems. Mathematical models are also used to generate predictions that may be tested experimentally. In the present chapter, the various steps involved in building models of cell signalling pathways are discussed. Depending on the nature of the process being modelled and the scale of the model, different mathematical formulations, ranging from stochastic representations to ordinary and partial differential equations are discussed. This is followed by a brief summary of some recent modelling successes and the state of future models.


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