Cytoplasmic Autoinhibition in HCN Channels is Regulated by the Transmembrane Region
Bibliographic record
Abstract
Hyperpolarization-activated cation-nonselective (HCN) channels regulate electrical activity in the brain and heart in a cAMP-dependent manner. The voltage-gating of these channels is mediated by a transmembrane (TM) region but is additionally regulated by direct binding of cAMP to a cyclic nucleotide-binding (CNB) fold in the cytoplasmic C-terminal region. Cyclic AMP potentiation has been explained by an autoinhibition model which views the unliganded CNB fold as an inhibitory module whose influence is disrupted by cAMP binding. However, the HCN2 subtype uses two other CNB fold-mediated mechanisms called open-state trapping and Quick-Activation to respectively slow the deactivation kinetics and speed the activation kinetics, against predictions of an autoinhibition model. To test how these multiple mechanisms are influenced by the TM region, we replaced the TM region of HCN2 with that of HCN4. This HCN4 TM-replacement preserved cAMP potentiation but augmented the magnitude of autoinhibition by the unliganded CNB fold; it moreover disrupted open-state trapping and Quick-Activation so that autoinhibition became the dominant mechanism contributed by the C-terminal region to determine kinetics. Truncation within the CNB fold partially relieved this augmented autoinhibition. This argues against the C-terminal region acting like a portable module with consistent effects on TM regions of different subtypes. Our findings provide evidence that functional interactions between the HCN2 TM region and C-terminal region govern multiple CNB fold-mediated mechanisms, implying that the molecular mechanisms of autoinhibition, open-state trapping, and Quick-Activation include participation of TM region structures.
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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".