Rule-based Computational Modeling of Modular Signaling Protein Interactions

Abstract

Intracellular signal transduction pathways are comprised of complex interactions among cellular proteins and other biomolecules. The structures of signaling proteins/enzymes are often modular, with conserved domains that carry out specific interactions or catalytic functions, and their core activities are dictated through coordinated intra- and inter-molecular interactions. In collaboration with Prof. James Faeder (Computational Biology, University of Pittsburgh), we have applied a computational algorithm for generating large networks of kinetic equations based on a much smaller set of mechanistic rules. Using this rule-based approach, we have formulated kinetic models that account for the modular domain structure of specific signaling proteins, including Shp2 (Src homology-2 domain containing protein tyrosine phosphatase 2), PI3K (phosphatidilinositol-3-kinase) regulatory subunit, and SH2-B (a Jak2 kinase activating adaptor protein). Analysis of these models reveals the combinatorial possibilities of reactions and interactions that might occur in living cells. We propose here to extend this rule-based approach for larger pathway models through systematic reduction and integration of small subsystem models.