Modification by covalent reaction or oxidation of cysteine residues in the tandem-SH2 domains of ZAP-70 and Syk can block phosphopeptide binding
Bibliographic record
Abstract
Zeta-chain associated protein of 70 kDa (ZAP-70) and spleen tyrosine kinase (Syk) are non-receptor tyrosine kinases that are essential for T-cell and B-cell antigen receptor signalling respectively. They are recruited, via their tandem-SH2 (Src-homology domain 2) domains, to doubly phosphorylated immunoreceptor tyrosine-based activation motifs (ITAMs) on invariant chains of immune antigen receptors. Because of their critical roles in immune signalling, ZAP-70 and Syk are targets for the development of drugs for autoimmune diseases. We show that three thiol-reactive small molecules can prevent the tandem-SH2 domains of ZAP-70 and Syk from binding to phosphorylated ITAMs. We identify a specific cysteine residue in the phosphotyrosine-binding pocket of each protein (Cys39 in ZAP-70, Cys206 in Syk) that is necessary for inhibition by two of these compounds. We also find that ITAM binding to ZAP-70 and Syk is sensitive to the presence of H2O2 and these two cysteine residues are also necessary for inhibition by H2O2. Our findings suggest a mechanism by which the reactive oxygen species generated during responses to antigen could attenuate signalling through these kinases and may also inform the development of ZAP-70 and Syk inhibitors that bind covalently to their SH2 domains.
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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".