Allosteric modulation of metabotropic glutamate receptors by chloride ions
Bibliographic record
Abstract
Metabotropic glutamate receptors (mGluRs) play key roles in the modulation of many synapses. Chloride (Cl(-)) is known to directly bind and regulate the function of different actors of neuronal activity, and several studies have pointed to the possible modulation of mGluRs by Cl(-). Herein, we demonstrate that Cl(-) behaves as a positive allosteric modulator of mGluRs. For example, whereas glutamate potency was 3.08 ± 0.33 μM on metabotropic glutamate (mGlu) 4 receptors in high-Cl(-) buffer, signaling activity was almost abolished in low Cl(-) in cell-based assays. Cl(-) potency was 78.6 ± 3.5 mM. Cl(-) possesses a high positive cooperativity with glutamate (Hill slope ≈6 on mGlu4), meaning that small variations in [Cl(-)] lead to large variations in glutamate action. Using molecular modeling and mutagenesis, we have identified 2 well-conserved Cl(-) binding pockets in the extracellular domain of mGluRs. Moreover, modeling of activity-dependent Cl(-) variations at GABAergic synapses suggests that these variations may be compatible with a dynamic modulation of the most sensitive mGluRs present in these synapses. Taken together, these data reveal a necessary role of Cl(-) for the glutamate activation of many mGluRs. Exploiting Cl(-) binding pockets may yield to the development of innovative regulators of mGluR activity.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".