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Modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3DSpi, a multi-agent-based software

Hédi Soula1, Céline Robardet1, François Perrin1, Sébastien Gripon1, Guillaume Beslon1 and Olivier Gandrillon2*

Author Affiliations

1 Laboratoire de Productique et d'Informatique des Systèmes Manufacturiers, Institut National des Sciences Appliquées de Lyon, Villeurbanne, France

2 Centre de Génétique Moléculaire et Cellulaire CNRS UMR 5534; Université Claude Bernard Lyon 1, Villeurbanne, France

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BMC Bioinformatics 2005, 6:228  doi:10.1186/1471-2105-6-228

Published: 19 September 2005

Abstract

Background

There is an increasing need for computer-generated models that can be used for explaining the emergence and predicting the behavior of multi-protein dynamic structures in cells. Multi-agent systems (MAS) have been proposed as good candidates to achieve this goal.

Results

We have created 3DSpi, a multi-agent based software that we used to explore the generation of multi-protein dynamic structures. Being based on a very restricted set of parameters, it is perfectly suited for exploring the minimal set of rules needed to generate large multi-protein structures. It can therefore be used to test the hypothesis that such structures are formed and maintained by principles of self-organization. We observed that multi-protein structures emerge and that the system behavior is very robust, in terms of the number and size of the structures generated. Furthermore, the generated structures very closely mimic spatial organization of real life multi-protein structures.

Conclusion

The behavior of 3DSpi confirms the considerable potential of MAS for modeling subcellular structures. It demonstrates that robust multi-protein structures can emerge using a restricted set of parameters and allows the exploration of the dynamics of such structures. A number of easy-to-implement modifications should make 3DSpi the virtual simulator of choice for scientists wishing to explore how topology interacts with time, to regulate the function of interacting proteins in living cells.