Rescue of expression and function of long QT syndrome-causing mutant hERG channels by enhancing channel stability in the plasma membrane
Bibliographic record
Abstract
The human ether- a -go-go-related gene ( hERG ) encodes the Kv11.1 (or hERG) channel that conducts the rapidly activating delayed rectifier potassium current (I Kr ). Naturally occurring mutations in hERG impair the channel function and cause long QT syndrome type 2. Many missense hERG mutations lead to a lack of channel expression on the cell surface, representing a major mechanism for the loss-of-function of mutant channels. While it is generally thought that a trafficking defect underlies the lack of channel expression on the cell surface, in the present study, we demonstrate that the trafficking defective mutant hERG G601S can reach the plasma membrane but is unstable and quickly degrades, which is akin to WT hERG channels under low K + conditions. We previously showed that serine (S) residue at 624 in the innermost position of the selectivity filter of hERG is involved in hERG membrane stability such that substitution of serine 624 with threonine (S624T) enhances hERG stability and renders hERG insensitive to low K + culture. Here, we report that the intragenic addition of S624T substitution to trafficking defective hERG mutants G601S, N470D, and P596R led to a complete rescue of the function of these otherwise loss-of-function mutant channels to a level similar to the WT channel, representing the most effective rescue means for the function of mutant hERG channels. These findings not only provide novel insights into hERG mutation-mediated channel dysfunction but also point to the critical role of S624 in hERG stability on the plasma membrane.
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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".