Manipulation of EphB2 Regulatory Motifs and SH2 Binding Sites Switches MAPK Signaling and Biological Activity
Bibliographic record
Abstract
Signaling by the Eph family of receptor tyrosine kinases (RTKs) is complex, because they can interact with a variety of intracellular targets, and can potentially induce distinct responses in different cell types. In NG108 neuronal cells, activated EphB2 recruits p120RasGAP, in a fashion that is associated with down-regulation of the Ras-Erk mitogen-activated kinase (MAPK) pathway and neurite retraction. To pursue the role of the Ras-MAPK pathway in EphB2-mediated growth cone collapse, and to explore the biochemical and biological functions of Eph receptors, we sought to re-engineer the signaling properties of EphB2 by manipulating its regulatory motifs and SH2 binding sites. An EphB2 mutant that retained juxtamembrane (JM) RasGAP binding sites but incorporated a Grb2 binding motif at an alternate RasGAP binding site within the kinase domain had little effect on basal Erk MAPK activation. In contrast, elimination of all RasGAP binding sites, accompanied by the addition of a Grb2 binding site within the kinase domain, led to an increase in phospho-Erk levels in NG108 cells following ephrin-B1 stimulation. Functional assays indicated a correlation between neurite retraction and the ability of the EphB2 mutants to down-regulate Ras-Erk MAPK signaling. These data suggest that EphB2 can be designed to repress, stabilize, or activate the Ras-Erk MAPK pathway by the manipulation of RasGAP and Grb2 SH2 domain binding sites and support the notion that Erk MAPK regulation plays a significant role in axon guidance. The behavior of EphB2 variants with mutations in the JM region and kinase domains suggests an intricate pattern of regulation and target recognition by Eph receptors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".