Expanding the Repertoire of an ERK2 Recruitment Site: Cysteine Footprinting Identifies the D-Recruitment Site as a Mediator of Ets-1 Binding
Bibliographic record
Abstract
Many substrates of ERK2 contain a D-site, a sequence recognized by ERK2 that is used to promote catalysis. Despite lacking a canonical D-site, the substrate Ets-1 is displaced from ERK2 by peptides containing one. This suggests that Ets-1 may contain a novel or cryptic D-site. To investigate this possibility a protein footprinting strategy was developed to elucidate ERK2-ligand interactions. Using this approach, single cysteine reporters were placed in the D-recruitment site (DRS) of ERK2 and the resulting ERK2 proteins subjected to alkylation by iodoacetamide. The ability of residues 1-138 of Ets-1 to protect the cysteines from alkylation was determined. The pattern of protection observed is consistent with Ets-1 occupying a hydrophobic binding site within the DRS of ERK2. Significantly, a peptide derived from the D-site of Elk-1, which is known to bind the DRS, exhibits a similar pattern of cysteine protection. This analysis expands the repertoire of the DRS on ERK2 and suggests that other targeting sequences remain to be identified. Furthermore, cysteine-footprinting is presented as a useful way to interrogate protein-ligand interactions at the resolution of a single amino acid.
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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) | 0.002 | 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".