Abstract
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 K D 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.
Recommended Citation
K. E. Erickson et al., "Modeling Cell Line-Specific Recruitment of Signaling Proteins to the Insulin-Like Growth Factor 1 Receptor," PLoS Computational Biology, vol. 15, no. 1, PLOS, Jan 2019.
The definitive version is available at https://doi.org/10.1371/journal.pcbi.1006706
Department(s)
Chemical and Biochemical Engineering
Keywords and Phrases
protein tyrosine kinase; protein tyrosine phosphatase; SHC transforming protein 2; somatomedin C; somatomedin C receptor; protein; protein binding; somatomedin C receptor, Article; autophosphorylation; binding affinity; binding site; clinical outcome; copy number variation; gene cluster; HeLa S3 cell line; human; human cell; molecular dynamics; physical chemistry; protein binding; protein function; protein interaction; signal transduction; animal; biological model; biology; cell line; chemistry; cluster analysis; metabolism; mouse; phosphorylation; physiology; signal transduction; Src homology domain, Animals; Binding Sites; Cell Line; Cluster Analysis; Computational Biology; Humans; Mice; Models, Biological; Phosphorylation; Protein Binding; Proteins; Receptor, IGF Type 1; Signal Transduction; src Homology Domains
International Standard Serial Number (ISSN)
1553-734X; 1553-7358
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2019 The Authors, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
01 Jan 2019
PubMed ID
30653502
