Unique Sensitivity to Extracellular Proteases and Peptide Protection of the HERG Potassium Channel
Bibliographic record
Abstract
The human ether‐a‐go‐go–related gene ( hERG ) encodes the pore‐forming subunit of the rapidly activating delayed rectifier potassium channel (I Kr ), which is important for cardiac repolarization. Dysfunction of hERG causes long QT syndrome, arrhythmias and sudden death, which occur in patients with cardiac ischemia. Cardiac ischemia is also associated with activation of various proteases. We characterized the effects of proteases on hERG/I Kr with the aim to develop novel strategies to prevent protease‐mediated damage. Using whole‐cell patch clamp and Western blot analysis we demonstrated that the hERG/I Kr channel is selectively cleaved by the serine proteases, proteinase K and protease XXIV. Using molecular biology including making chimerical channels between protease K‐sensitive hERG and insensitive hEAG, we identified that the S5‐pore linker of hERG is the target domain for proteinase K. We discovered that the scorpion toxin BeKm‐1, which binds to the S5‐pore linker of hERG, can effectively protect hERG from proteinase K‐mediated damage. The reduction in mature ERG expression was observed in a rabbit cardiac ischemia model and in hERG‐HEK cells cultured in hypoxic conditions. BeKm‐1 effectively prevented the hypoxia‐induced reduction of the mature hERG expression. In conclusion, hERG is uniquely susceptible to proteases, which may contribute to arrhythmias under conditions such as cardiac ischemia. Protecting hERG channels from proteolytic damage using specific peptides may represent a novel strategy to prevent and treat arrhythmias associated with ischemic heart disease. (Supported by the Canadian Institutes of Health Research & the Heart and Stroke Foundation of Ontario)
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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) | 0.000 | 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 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".