Mutagenesis of the GABA<sub>A</sub> receptor α1 subunit reveals a domain that affects sensitivity to GABA and benzodiazepine‐site ligands
Bibliographic record
Abstract
We have mutated several amino acids in the region of the GABA(A) receptor alpha1 subunit predicted to form a small extracellular loop between transmembrane domains two and three to investigate its possible role in ligand sensitivity. The mutations were S275T, L276A, P277A, V279A, A280S and Y281F. Mutant alpha1 subunits were co-expressed with beta2 and gamma2 subunits in tsA201 cells or Xenopus oocytes. Binding studies revealed that the only mutation that significantly affected [3H]Ro15-4513 binding was the V279A substitution which reduced the affinity for this ligand. Electrophysiological examination of mutant receptors revealed that L276A, P277A and V279A displayed rightward shifts of their GABA concentration-response curves, the largest occurring with the L276A mutant. The impact of these mutations on allosteric modulation by benzodiazepine-site ligands was examined. V279A reduced the potency of both flunitrazepam and Ro15-4513 but, in each case, their efficacy was enhanced. A280S resulted in a decrease in flunitrazepam efficacy without affecting its potency. Additionally, P277A and A280S resulted in Ro15-4513 losing its inverse agonist effect at these receptors. These results suggest that a domain within this small extracellular loop between TMII-TMIII plays a role in determining the sensitivity of GABA(A) receptors to both GABA and benzodiazepine-site ligands.
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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) | 0.001 | 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) | 0.001 | 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".