The functional role of the αM4 transmembrane helix in the muscle nicotinic acetylcholine receptor probed through mutagenesis and coevolutionary analyses
Bibliographic record
Abstract
The activity of the muscle-type Torpedo nicotinic acetylcholine receptor (nAChR) is highly sensitive to lipids, but the underlying mechanisms remain poorly understood. The nAChR transmembrane α-helix, M4, is positioned at the perimeter of each subunit in direct contact with lipids and likely plays a central role in lipid sensing. To gain insight into the mechanisms underlying nAChR lipid sensing, we used homology modeling, coevolutionary analyses, site-directed mutagenesis, and electrophysiology to examine the role of the α-subunit M4 (αM4) in the function of the adult muscle nAChR. Ala substitutions for most αM4 residues, including those in clusters of polar residues at both the N and C termini, and deletion of up to 11 C-terminal residues had little impact on the agonist-induced response. Even Ala substitutions for coevolved pairs of residues at the interface between αM4 and the adjacent helices, αM1 and αM3, had little effect, although some impaired nAChR expression. On the other hand, Ala substitutions for Thr422 and Arg429 caused relatively large losses of function, suggesting functional roles for these specific residues. Ala substitutions for aromatic residues at the αM4-αM1/αM3 interface generally led to gains of function, as previously reported for the prokaryotic homolog, the Erwinia chrysanthemi ligand-gated ion channel (ELIC). The functional effects of individual Ala substitutions in αM4 were found to be additive, although not in a completely independent manner. Our results provide insight into the structural features of αM4 that are important. They also suggest how lipid-dependent changes in αM4 structure ultimately modify nAChR function.
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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 | 0.000 |
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".