Rule-based Computational Modeling of Modular Signaling Protein Interactions

BioNetGen;Cell Signal Transduction;SH2-B;Shp2;Protein domain;PI3K;Rule-based model

Barua, Dipak ; Orlin D. Velev, Committee Member,Jason M. Haugh, Committee Chair,Alun L. Lloyd, Committee Member,Balaji M. Rao, Committee Member,Barua, Dipak ; Orlin D. Velev ; Committee Member ; Jason M. Haugh ; Committee Chair ; Alun L. Lloyd ; Committee Member ; Balaji M. Rao ; Committee Member

University:North Carolina State University

关键词: BioNetGen;    Cell Signal Transduction;    SH2-B;    Shp2;    Protein domain;    PI3K;    Rule-based model;   

Others  :  https://repository.lib.ncsu.edu/bitstream/handle/1840.16/5168/etd.pdf?sequence=1&isAllowed=y

美国|英语

来源: null

【 摘 要 】

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.