Protein-Protein Coupling/Uncoupling Enables Dopamine D<sub>2</sub>Receptor Regulation of AMPA Receptor-Mediated Excitotoxicity
Bibliographic record
Abstract
here is considerable evidence that dopamine D2 receptors can modulate AMPA receptor-mediated neurotoxicity. However, the molecular mechanism underlying this process remains essentially unclear. Here we report that D2 receptors inhibit AMPA-mediated neurotoxicity through two pathways: the activation of phosphoinositide-3 kinase (PI-3K) and downregulation of AMPA receptor plasma membrane expression, both involving a series of protein-protein coupling/uncoupling events. Agonist stimulation of D2 receptors promotes the formation of the direct protein-protein interaction between the third intracellular loop of the D2 receptor and the ATPase N-ethylmaleimide-sensitive factor (NSF) while uncoupling the NSF interaction with the carboxyl tail (CT) of the glutamate receptor GluR2 subunit of AMPA receptors. Previous studies have shown that full-length NSF directly couples to the GluR2CT and facilitates AMPA receptor plasma membrane expression. Furthermore, the CT region of GluR2 subunit is also responsible for several other intracellular protein couplings, including p85 subunit of PI-3K. Therefore, the direct coupling of D2-NSF and concomitant decrease in the NSF-GluR2 interaction results in a decrease of AMPA receptor membrane expression and an increase in the interaction between GluR2 and the p85 and subsequent activation of PI-3K. Disruption of the D2-NSF interaction abolished the ability of D2 receptor to attenuate AMPA-mediated neurotoxicity by blocking the D2 activation-induced changes in PI-3K activity and AMPA receptor plasma membrane expression. Furthermore, the D2-NSF-GluR2-p85 interactions are also responsible for the D2 inhibition of ischemia-induced cell death. These data may provide a new avenue to identify specific targets for therapeutics to modulate glutamate receptor-governed diseases, such as stroke.
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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".