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A boolean network modelling of receptor mosaics relevance of topology and cooperativity

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Summary.

In the last five years data have been obtained showing that a functional cross-talk among G Protein Coupled receptors (GPCR) exists at the plasma membrane level where they can dimerise and are able to generate high order oligomers. These findings are in agreement with the receptor mosaic (RM) hypothesis that claims the existence of clusters of receptor proteins at the plasma membrane level, where they establish mutual interactions and work as ‘intelligent interfaces’ between the extra-cellular and the intra-cellular environments. Individual receptor dimers can be considered to have two stable conformational states with respect to the macromolecular effectors: one active, one inactive. Owing to receptor–receptor interactions, however, a state change of a given receptor will change the probability of changing the state for the adjacent receptors in the RM and the effect will propagate throughout the cluster, leading to a complex cooperative behaviour. In this study we explore the properties of a RM on the basis of an equivalence with a Boolean network, a mathematical framework able to describe how complex properties may emerge from systems characterized by deterministic local interactions of many simple components acting in parallel. Computer simulations of receptor clusters arranged according to topologies consistent with available experimental ultrastructural data were performed. They indicated that RMs after a stimulation can achieve a limited number of specific temporary equilibrium configurations (attractors), characterized by the presence of receptor units frozen in the active state. They could be interpreted as a form of information storage and a role of RM in learning and memory could be hypothesized. Moreover, they seem to be at the basis of very common ‘macroscopical’ properties of a receptor system, such as a sigmoidal response curve to an extracellular ligand, the sensitivity of the mosaic being modulated by changes in the topology and/or in the level of cooperativity among receptors.

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Agnati, L., Guidolin, D., Leo, G. et al. A boolean network modelling of receptor mosaics relevance of topology and cooperativity. J Neural Transm 114, 77–92 (2007). https://doi.org/10.1007/s00702-006-0567-6

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