Combinatorial complexity and compositional drift in protein interaction networks.

Eric Deeds 1, * Jean Krivine 2 Jérôme Feret 3 Vincent Danos 4 Walter Fontana 5, *
* Auteur correspondant
1 Deeds lab
Deeds Lab
3 ABSTRACTION - Abstract Interpretation and Static Analysis
DI-ENS - Département d'informatique de l'École normale supérieure, ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR 8548
5 Fontana lab
HMS - Harvard Medical School [Boston]
Abstract : The assembly of molecular machines and transient signaling complexes does not typically occur under circumstances in which the appropriate proteins are isolated from all others present in the cell. Rather, assembly must proceed in the context of large-scale protein-protein interaction (PPI) networks that are characterized both by conflict and combinatorial complexity. Conflict refers to the fact that protein interfaces can often bind many different partners in a mutually exclusive way, while combinatorial complexity refers to the explosion in the number of distinct complexes that can be formed by a network of binding possibilities. Using computational models, we explore the consequences of these characteristics for the global dynamics of a PPI network based on highly curated yeast two-hybrid data. The limited molecular context represented in this data-type translates formally into an assumption of independent binding sites for each protein. The challenge of avoiding the explicit enumeration of the astronomically many possibilities for complex formation is met by a rule-based approach to kinetic modeling. Despite imposing global biophysical constraints, we find that initially identical simulations rapidly diverge in the space of molecular possibilities, eventually sampling disjoint sets of large complexes. We refer to this phenomenon as ''compositional drift". Since interaction data in PPI networks lack detailed information about geometric and biological constraints, our study does not represent a quantitative description of cellular dynamics. Rather, our work brings to light a fundamental problem (the control of compositional drift) that must be solved by mechanisms of assembly in the context of large networks. In cases where drift is not (or cannot be) completely controlled by the cell, this phenomenon could constitute a novel source of phenotypic heterogeneity in cell populations.
Type de document :
Article dans une revue
PLoS ONE, Public Library of Science, 2012, 7 (3), 〈10.1371/journal.pone.0032032〉
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Contributeur : Jérôme Feret <>
Soumis le : samedi 10 mars 2012 - 14:31:27
Dernière modification le : vendredi 9 mars 2018 - 13:54:02

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Eric Deeds, Jean Krivine, Jérôme Feret, Vincent Danos, Walter Fontana. Combinatorial complexity and compositional drift in protein interaction networks.. PLoS ONE, Public Library of Science, 2012, 7 (3), 〈10.1371/journal.pone.0032032〉. 〈hal-00677889〉



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