Do low-affinity ErbB receptor protein interactions represent the base of a cell signaling iceberg?

Jones, Richard B.

doi:10.1586/epr.12.78

Cited by 5 publications

(5 citation statements)

References 31 publications

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“…At the most direct level, our approach enables a confident assessment of binding priority between competing PIDs for binding sites. This ability is critically important for the development of testable hypotheses examining time-dependent signal propagation and information integration at hub proteins (70), which are often aberrant processes in cancers (42,71) and require the processing of high and low affinity interactions (34,(72)(73)(74). In addition, the CPCMA platform is capable of explicit measurement of nonbinding events, can resolve interplay between neighboring amino acids within a ligand, does not require the purification of both interacting components, and is economical to employ.…”

Section: Figmentioning

confidence: 99%

The Development and Application of a Quantitative Peptide Microarray Based Approach to Protein Interaction Domain Specificity Space

Engelmann

Kim

Wang

et al. 2014

Molecular & Cellular Proteomics

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Protein interaction domain (PID) linear peptide motif interactions direct diverse cellular processes in a specific and coordinated fashion. PID specificity, or the interaction selectivity derived from affinity preferences between possible PID-peptide pairs is the basis of this ability. Here, we develop an integrated experimental and computational cellulose peptide conjugate microarray (CPCMA) based approach for the high throughput analysis of PID specificity that provides unprecedented quantitative resolution and reproducibility. As a test system, we quantify the specificity preferences of four Src Homology 2 domains and 124 physiological phosphopeptides to produce a novel quantitative interactome. The quantitative data set covers a broad affinity range, is highly precise, and agrees well with orthogonal biophysical validation, in vivo interactions, and peptide library trained algorithm predictions. In contrast to preceding approaches, the CPCMAs proved capable of confidently assigning interactions into affinity categories, resolving the subtle affinity contributions of residue correlations, and yielded predictive peptide motif affinity matrices. Unique CPCMA enabled modes of systems level analysis reveal a physiological interactome with expected node degree value decreasing as a function of affinity, resulting in minimal high affinity binding overlap between domains; uncover that Src Homology 2 domains bind ligands with a similar average affinity yet strikingly different levels of promiscuity and binding dynamic range; and parse with unprecedented quantitative resolution contextual factors directing specificity. The CPCMA platform promises broad application within the fields of PID specificity, synthetic biology, specificity focused drug design, and network biology. Molecular & Cellular Proteomics 13: 10.1074/mcp.O114.038695, 3647-3662, 2014. Protein interaction domains (PIDs)1 often compete for the same linear motif binding sites across a range of affinities, resulting in many potential interactions that may enable the rapid assembly and disassembly of signaling proteins in response to external and internal cues (1, 2). PID-peptide interactions have small binding interfaces, resulting in moderate affinity interactions mediated primarily by a few amino acid "hot-spots" within motifs specific for a particular PID family (3-5). The power of individual residues to direct interactions, the absence of structural constraint for linear motifs, and the modularity of PIDs has enabled the rapid evolution of these networks resulting in many large multimember PID families in higher eukaryotes (6 -9). For these large families dedicated to the recognition of similar ligands, PID specificity-or the interaction selectivity derived from affinity preferences between possible PID-peptide pairs-underpins the effective conveyance of specific cell signals. High throughput interaction mapping efforts are used to decipher how this PID "specificity space" is populated, thereby providing insight into protein function and the principles ...

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Section: Figmentioning

confidence: 99%

The Development and Application of a Quantitative Peptide Microarray Based Approach to Protein Interaction Domain Specificity Space

Engelmann

Kim

Wang

et al. 2014

Molecular & Cellular Proteomics

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“…SH2 binding in vivo is highly dynamic (17,18). Not only do SH2 domains bind to and dissociate from phosphosites rapidly, but phosphosites themselves turn over rapidly, with half-times in the range of seconds; the rate of phosphosite turnover is dependent on both kinase and phosphatase activity (17,19).…”

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confidence: 99%

Src homology 2 domains enhance tyrosine phosphorylation in vivo by protecting binding sites in their target proteins from dephosphorylation

Jadwin

Curran

Lafontaine

et al. 2018

Journal of Biological Chemistry

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Phosphotyrosine (pTyr)-dependent signaling is critical for many cellular processes. It is highly dynamic, as signal output depends not only on phosphorylation and dephosphorylation rates but also on the rates of binding and dissociation of effectors containing phosphotyrosine-dependent binding modules such as Src homology 2 (SH2) and phosphotyrosine-binding (PTB) domains. Previous studies suggested that binding of SH2 and PTB domains can enhance protein phosphorylation by protecting the sites bound by these domains from phosphatase-mediated dephosphorylation. To test whether this occurs, we used the binding of growth factor receptor bound 2 (GRB2) to phosphorylated epidermal growth factor receptor (EGFR) as a model system. We analyzed the effects of SH2 domain overexpression on protein tyrosine phosphorylation by quantitative Western and far-Western blotting, mass spectrometry, and computational modeling. We found that SH2 overexpression results in a significant, dose-dependent increase in EGFR tyrosine phosphorylation, particularly of sites corresponding to the binding specificity of the overexpressed SH2 domain. Computational models using experimentally determined EGFR phosphorylation and dephosphorylation rates, and pTyr-EGFR and GRB2 concentrations, recapitulated the experimental findings. Surprisingly, both modeling and biochemical analyses suggested that SH2 domain overexpression does not result in a major decrease in the number of unbound phosphorylated SH2 domain-binding sites. Our results suggest that signaling via SH2 domain binding is buffered over a relatively wide range of effector concentrations and that SH2 domain proteins with overlapping binding specificities are unlikely to compete with one another for phosphosites .

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“…As reported previously for the ErbB receptors (28), many interaction affinities were relatively weak ( K D >2 μ m ). These low affinity interactions may represent transient signaling events that would not have been easily observed using traditional in-cell interaction methodologies (75) and are likely of biological relevance (76). The protein interactions from this publication have been submitted to the IMEx consortium through IntAct (77) and assigned the identifier IM-22269.…”

Section: Discussionmentioning

confidence: 99%

Enhanced Prediction of Src Homology 2 (SH2) Domain Binding Potentials Using a Fluorescence Polarization-derived c-Met, c-Kit, ErbB, and Androgen Receptor Interactome

Leung

Hause

Barkinge

et al. 2014

Molecular & Cellular Proteomics

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Many human diseases are associated with aberrant regulation of phosphoprotein signaling networks. Src homology 2 (SH2) domains represent the major class of protein domains in metazoans that interact with proteins phosphorylated on the amino acid residue tyrosine. Although current SH2 domain prediction algorithms perform well at predicting the sequences of phosphorylated peptides that are likely to result in the highest possible interaction affinity in the context of random peptide library screens, these algorithms do poorly at predicting the interaction potential of SH2 domains with physiologically derived protein sequences. We employed a high throughput interaction assay system to empirically determine the affinity between 93 human SH2 domains and phosphopeptides abstracted from several receptor tyrosine kinases and signaling proteins. The resulting interaction experiments revealed over 1000 novel peptide-protein interactions and provided a glimpse into the common and specific interaction potentials of c-Met, c-Kit, GAB1, and the human androgen receptor. We used these data to build a permutation-based logistic regression classifier that performed considerably better than existing algorithms for predicting the interaction potential of several SH2 domains.

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Do low-affinity ErbB receptor protein interactions represent the base of a cell signaling iceberg?

Cited by 5 publications

References 31 publications

The Development and Application of a Quantitative Peptide Microarray Based Approach to Protein Interaction Domain Specificity Space

The Development and Application of a Quantitative Peptide Microarray Based Approach to Protein Interaction Domain Specificity Space

Src homology 2 domains enhance tyrosine phosphorylation in vivo by protecting binding sites in their target proteins from dephosphorylation

Enhanced Prediction of Src Homology 2 (SH2) Domain Binding Potentials Using a Fluorescence Polarization-derived c-Met, c-Kit, ErbB, and Androgen Receptor Interactome

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