Stoichiometry for drug potentiation of a pentameric ion channel
Bibliographic record
Abstract
Drug modulation of ion channels is a powerful means to alter physiological responses for therapeutic benefit, yet the structural bases of modulation remain poorly understood. Here we study potentiation of nicotinic α7 acetylcholine receptors, which are emerging drug targets in several neurological disorders. α7 receptors are ligand-gated ion channels composed of five identical subunits, each bearing a site for the potentiating drug PNU-120596 (PNU). How the individual subunits contribute to PNU potentiation is not known. Taking advantage of a PNU-resistant mutant, we generated receptors composed of normal and PNU-resistant subunits and tagged one of the subunits with conductance mutations to report subunit stoichiometry. We then used patch clamp recording to monitor PNU potentiation of single α7 receptors with defined stoichiometry in real time. We find that potentiation depends steeply on the number of PNU-resistant subunits and that four, and possibly five, subunits must be sensitive to PNU for potentiation to occur. Thus, by monitoring the activity of every possible subunit combination, our findings predict that at the macroscopic level, PNU potentiation is highly cooperative.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".