Enhanced Efficacy without Further Cleft Closure: Reevaluating Twist as a Source of Agonist Efficacy in AMPA Receptors
Bibliographic record
Abstract
AMPA receptors (AMPARs) are tetrameric ligand-gated ion channels that couple the energy of glutamate binding to the opening of a transmembrane channel. Crystallographic and electrophysiological analysis of AMPARs has suggested a coupling between (1) cleft closure in the bilobate ligand-binding domain (LBD), (2) the resulting separation of transmembrane helix attachment points across subunit dimers, and (3) agonist efficacy. In general, more efficacious agonists induce greater degrees of cleft closure and transmembrane separation than partial agonists. Several apparent violations of the cleft-closure/efficacy paradigm have emerged, although in all cases, intradimer separation remains as the driving force for channel opening. Here, we examine the structural basis of partial agonism in GluA4 AMPARs. We find that the L651V substitution enhances the relative efficacy of kainate without increasing either LBD cleft closure or transmembrane separation. Instead, the conformational change relative to the wild-type:kainate complex involves a twisting motion with the efficacy contribution opposite from that expected based on previous analyses. As a result, channel opening may involve transmembrane rearrangements with a significant rotational component. Furthermore, a two-dimensional analysis of agonist-induced GluA2 LBD motions suggests that efficacy is not a linearly varying function of lobe 2 displacement vectors, but is rather determined by specific conformational requirements of the transmembrane domains.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".