Extracellular protons accelerate hERG channel deactivation by destabilizing voltage sensor relaxation
Bibliographic record
Abstract
), which is crucial for membrane repolarization and therefore termination of the cardiac action potential. hERG channels display unusually slow deactivation gating, which contributes to a resurgent current upon repolarization and may protect against post-depolarization-induced arrhythmias. hERG channels also exhibit robust mode shift behavior, which reflects the energetic separation of activation and deactivation pathways due to voltage sensor relaxation into a stable activated state. The mechanism of relaxation is unknown and likely contributes to slow hERG channel deactivation. Here, we use extracellular acidification to probe the structural determinants of voltage sensor relaxation and its influence on the deactivation gating pathway. Using gating current recordings and voltage clamp fluorimetry measurements of voltage sensor domain dynamics, we show that voltage sensor relaxation is destabilized at pH 6.5, causing an ∼20-mV shift in the voltage dependence of deactivation. We show that the pH dependence of the resultant loss of mode shift behavior is similar to that of the deactivation kinetics acceleration, suggesting that voltage sensor relaxation correlates with slower pore gate closure. Neutralization of D509 in S3 also destabilizes the relaxed state of the voltage sensor, mimicking the effect of protons, suggesting that acidic residues on S3, which act as countercharges to S4 basic residues, are involved in stabilizing the relaxed state and slowing deactivation kinetics. Our findings identify the mechanistic determinants of voltage sensor relaxation and define the long-sought mechanism by which protons accelerate hERG deactivation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".