A physiologically-relevant intermediate state structure of a voltage-gated potassium channel
Bibliographic record
Abstract
Voltage-gated potassium ion (K+) channels perform critical roles in many physiological processes, while gain- or loss-of-function mutations lead to life-threatening pathologies. Here, we establish the high-resolution structure of a pivotal intermediate state of the Kv7.1 (KCNQ1) channel using cryogenic electron microscopy. The 3.53 Å resolution structure reveals straightened upper S1 and S2 voltage sensor helices, distancing them from the pore filter helix compared to fully activated channels. The outward translation of the S4 voltage sensor is essentially complete in this intermediate state, and the S4-S6 helices and the S4-S5 linker do not change position significantly between intermediate and activated states. The PIP2 ligand can bind in both states. Movement of S1 and S2 helices towards the filter helix from intermediate to activated states may explain smaller components of KCNQ1 voltage sensor fluorescence, differential Rb+/K+ selectivity, and pharmacological responses to activators and inhibitors. Single channel recordings and the location of long QT mutations suggest the potential physiological and disease importance of the intermediate state. KCNQ1 (Kv7.1) channels are critical for heart rhythm homeostasis. Here, the authors report the KCNQ1 structure in an intermediate state, revealing unique S1–S2 conformations that illuminate channel gating and may aid targeted drug development.
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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 | 0.001 |
| 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".