Components of gating charge movement and S4 voltage-sensor exposure during activation of hERG channels
Bibliographic record
Abstract
The human ether-á-go-go-related gene (hERG) K(+) channel encodes the pore-forming α subunit of the rapid delayed rectifier current, IKr, and has unique activation gating kinetics, in that the α subunit of the channel activates and deactivates very slowly, which focuses the role of IKr current to a critical period during action potential repolarization in the heart. Despite its physiological importance, fundamental mechanistic properties of hERG channel activation gating remain unclear, including how voltage-sensor movement rate limits pore opening. Here, we study this directly by recording voltage-sensor domain currents in mammalian cells for the first time and measuring the rates of voltage-sensor modification by [2-(trimethylammonium)ethyl] methanethiosulfonate chloride (MTSET). Gating currents recorded from hERG channels expressed in mammalian tsA201 cells using low resistance pipettes show two charge systems, defined as Q(1) and Q(2), with V(1/2)'s of -55.7 (equivalent charge, z = 1.60) and -54.2 mV (z = 1.30), respectively, with the Q(2) charge system carrying approximately two thirds of the overall gating charge. The time constants for charge movement at 0 mV were 2.5 and 36.2 ms for Q(1) and Q(2), decreasing to 4.3 ms for Q(2) at +60 mV, an order of magnitude faster than the time constants of ionic current appearance at these potentials. The voltage and time dependence of Q2 movement closely correlated with the rate of MTSET modification of I521C in the outermost region of the S4 segment, which had a V(1/2) of -64 mV and time constants of 36 ± 8.5 ms and 11.6 ± 6.3 ms at 0 and +60 mV, respectively. Modeling of Q(1) and Q(2) charge systems showed that a minimal scheme of three transitions is sufficient to account for the experimental findings. These data point to activation steps further downstream of voltage-sensor movement that provide the major delays to pore opening in hERG channels.
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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".