Identification of a single amino acid in GluN1 that is critical for glycine-primed internalization of NMDA receptors
Bibliographic record
Abstract
BACKGROUND: NMDA receptors are ligand-gated ion channels with essential roles in glutamatergic synaptic transmission and plasticity in the CNS. As co-receptors for glutamate and glycine, gating of the NMDA receptor/channel pore requires agonist binding to the glycine sites, as well as to the glutamate sites, on the ligand-binding domains of the receptor. In addition to channel gating, glycine has been found to prime NMDA receptors for internalization upon subsequent stimulation of glutamate and glycine sites. RESULTS: Here we address the key issue of identifying molecular determinants in the glycine-binding subunit, GluN1, that are essential for priming of NMDA receptors. We found that glycine treatment of wild-type NMDA receptors led to recruitment of the adaptor protein 2 (AP-2), and subsequent internalization after activating the receptors by NMDA plus glycine. However, with a glycine-binding mutant of GluN1 - N710R/Y711R/E712A/A714L - we found that treating with glycine did not promote recruitment of AP-2 nor were glycine-treated receptors internalized when subsequently activated with NMDA plus glycine. Likewise, GluN1 carrying a single point mutation - A714L - did not prime upon glycine treatment. Importantly, both of the mutant receptors were functional, as stimulating with NMDA plus glycine evoked inward currents. CONCLUSIONS: Thus, we have identified a single amino acid in GluN1 that is critical for priming of NMDA receptors by glycine. Moreover, we have demonstrated the principle that while NMDA receptor gating and priming share a common requirement for glycine binding, the molecular constraints in GluN1 for gating are distinct from those for priming.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".