Modelling cellular signalling systems

Abstract

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.

Impact of host genetic polymorphisms on vaccine induced antibody response

“…95,96 Such mechanistic models can be also applied to test hypotheses on how SNPs modulate the immunological signaling network and cause the observed variability in vaccine response: Cell signaling and effector cell communication can be formalized in mathematical models and simulated. 97,98 The consequences of the investigated genetic polymorphism need to be implemented, for instance in the form of changes in protein concentration or changes in kinetic factors. If the simulation results do not match the observed vaccine response phenotype, further experiments are required to identify missing parts in the model such as crucial interactions.…”

Paradoxical signaling regulates structural plasticity in dendritic spines

“…We also assumed that the spine is a well-mixed compartment so that we could follow the temporal evolution of the concentrations of the different components. Each interaction was modeled as a chemical reaction using either mass action kinetics for bindingunbinding reactions or Michaelis-Menten kinetics for enzymecatalyzed reactions (29,37). The network of interactions was constructed using the Virtual Cell modeling platform (http://www.vcell.org).…”

Receptors, endocytosis, and trafficking: the biological basis of targeted delivery of antisense and siRNA oligonucleotides

“…While this classic example of RTK signaling nicely illustrates ideas about multi-protein complexes and the triggering of pathways, we now know that the reality is far more complex. Rather than triggering simple linear pathways, RTK activation modulates complex signaling networks (Lazzara and Lauffenburger, 2009; Rangamani and Iyengar, 2008) that include multiple branch points and negative and positive feedback loops.…”