Electrophysiological characterization of the state-dependent inhibition of Kv7.1 and IKs by UCL2077
Bibliographic record
Abstract
In cardiomyocytes, Kv7.1 associates with the regulatory subunit KCNE1 to generate the delayed rectifier potassium current I Ks , which plays a crucial role in cardiac repolarization at elevated heart rates. Gain-of-function mutations in either of these subunits are associated with short QT syndrome (SQTS), a condition that increases the risk of cardiac arrhythmias including atrial fibrillation, syncope and sudden death. Therefore, the study of pharmacological inhibitors of Kv7.1 and I Ks is of significant therapeutic interest. In this work, we used whole-cell patch clamp recordings to characterize the electrophysiological effects of the Kv7.1 blocker 3-(triphenylmethylaminomethyl)pyridine (UCL2077) in both Kv7.1 and I Ks (Kv7.1 + KCNE1) channels. We found that UCL2077 inhibited both Kv7.1 and I Ks channels with high affinity (IC 50 in the picomolar range) and mild voltage-dependence. The drug induced a biphasic time-dependent current decay and reduced current reactivation of Kv7.1, while the kinetics of I Ks were unaffected. We examined state-dependence using mutations that functionally stabilize Kv7.1/ I Ks in either the intermediate-open (IO; E160R/R231E) or in the activated-open (AO; E160R/R237E) state. In both channels, UCL2077 potency correlated with the strength of the electromechanical coupling. Our results are further supported by a kinetic Markov model simulating UCL2077 binding that closely resembles the experimental currents. Overall, our work provides an in-depth characterization of UCL2077's action on Kv7.1 and I Ks channels, offering valuable insights for the development of Kv7.1/ I Ks inhibitors in the context of short QT syndrome and other cardiac arrhythmias.
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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 | 0.001 |
| 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) | 0.002 | 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".