Identification of a domain in the δ subunit (S238‐V264) of the α4β3δ GABA<sub>A</sub>receptor that confers high agonist sensitivity
Bibliographic record
Abstract
We have expressed the alpha4beta3delta and alpha4beta3gamma2L subtypes of the rat GABAA receptor in Xenopus oocytes and have investigated their agonist activation properties. GABA was a more potent agonist of the alpha4beta3delta receptor (EC50 approximately 1.4 micromol/L) than of the alpha4beta3gamma2L subtype (EC50 approximately 27.6 micromol/L). Other GABAA receptor agonists (muscimol, 4,5,6,7-tetrahydroisoxazolo[5,4-c]pyridin-3-ol, imidazole-4-amino acid) displayed similar subtype selectivity. The structural determinants underlying these differences have been investigated by co-expressing chimeric delta/gamma2L subunits with alpha4 and beta3 subunits. A stretch of amino acids in the delta subunit, S238-V264, is shown to play an important role in determining both agonist potency and the efficacies of full or partial agonists. This segment includes transmembrane domain 1 and the short intracellular loop that leads to the second transmembrane domain. The effects of the competitive antagonists, bicuculline and SR95531, and the channel blocker, picrotoxin, were not significantly affected by the incorporation of chimeric subunits. As the delta and gamma2L subunits have not been previously implicated directly in agonist binding, we suggest that the effects are likely to arise from changes in the transduction mechanisms that link agonist binding to channel activation.
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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 | 0.001 |
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".