Cell behaviour as a dynamic attractor in the intracellular signalling system.
We present a model of the cell signalling network based on the generic properties of interactions between protein kinases (PKs) and protein phosphatases (PPs) inside cells. The model is designed to examine the global properties and intrinsic dynamics of the phosphorylation system. A genetic algorithm (GA) is used to evolve populations of "cells". The GA selects cells and ranks them based on an analysis of the dynamics of the proteins within the networks from a series of different random starting conditions. The fittest cells are taken to be those which can generate a variety of different "behaviours" from a series of different initial conditions. During the GA, intracellular protein interactions evolve via mutation and an analogue of domain shuffling between protein types that is thought to occur during biological evolution. The dynamics of the simulated networks are presented and we discuss the hypothesis that changes in the behaviour of a cell may be interpretable as a switch between attractor basins in the intracellular signalling network.
Department of Computer and Information Science, New Jersey Institute of Technology, Newark 07102, USA. ajames@ncrl.njit.edu
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D000465:Algorithms; D000818:Animals; D002468:Cell Physiological Phenomena; D016000:Cluster Analysis; D003198:Computer Simulation; D007424:Intracellular Fluid / Q000378:metabolism*; D008954:Models, Biological; D009010:Monte Carlo Method; D017711:Nonlinear Dynamics; D010749:Phosphoprotein Phosphatases / Q000378:metabolism; D010766:Phosphorylation; D011494:Protein Kinases / Q000378:metabolism; D015398:Signal Transduction / Q000502:physiology*
D011494:Protein Kinases; D010749:Phosphoprotein Phosphatases