Modeling cell line-specific recruitment of signaling proteins to the insulin-like growth factor 1 receptor.
Keesha E EricksonOleksii S RukhlenkoMd ShahinuzzamanKalina P SlavkovaYen Ting LinRyan SudermanEdward C StitesMarian AnghelRichard G PosnerDipak BaruaBoris N KholodenkoWilliam S HlavacekPublished in: PLoS computational biology (2019)
Receptor tyrosine kinases (RTKs) typically contain multiple autophosphorylation sites in their cytoplasmic domains. Once activated, these autophosphorylation sites can recruit downstream signaling proteins containing Src homology 2 (SH2) and phosphotyrosine-binding (PTB) domains, which recognize phosphotyrosine-containing short linear motifs (SLiMs). These domains and SLiMs have polyspecific or promiscuous binding activities. Thus, multiple signaling proteins may compete for binding to a common SLiM and vice versa. To investigate the effects of competition on RTK signaling, we used a rule-based modeling approach to develop and analyze models for ligand-induced recruitment of SH2/PTB domain-containing proteins to autophosphorylation sites in the insulin-like growth factor 1 (IGF1) receptor (IGF1R). Models were parameterized using published datasets reporting protein copy numbers and site-specific binding affinities. Simulations were facilitated by a novel application of model restructuration, to reduce redundancy in rule-derived equations. We compare predictions obtained via numerical simulation of the model to those obtained through simple prediction methods, such as through an analytical approximation, or ranking by copy number and/or KD value, and find that the simple methods are unable to recapitulate the predictions of numerical simulations. We created 45 cell line-specific models that demonstrate how early events in IGF1R signaling depend on the protein abundance profile of a cell. Simulations, facilitated by model restructuration, identified pairs of IGF1R binding partners that are recruited in anti-correlated and correlated fashions, despite no inclusion of cooperativity in our models. This work shows that the outcome of competition depends on the physicochemical parameters that characterize pairwise interactions, as well as network properties, including network connectivity and the relative abundances of competitors.
Keyphrases
- binding protein
- copy number
- molecular dynamics
- stem cells
- dna binding
- systematic review
- emergency department
- single cell
- genome wide
- randomized controlled trial
- dna methylation
- microbial community
- mass spectrometry
- bone marrow
- white matter
- tyrosine kinase
- gene expression
- oxidative stress
- endothelial cells
- cell proliferation
- men who have sex with men
- protein protein
- stress induced
- drug induced
- electronic health record