Glycosylation stabilizes hERG channels on the plasma membrane by decreasing proteolytic susceptibility
Bibliographic record
Abstract
The human ether-a-go-go related gene (hERG)-encoded channel hERG undergoes N-linked glycosylation at position 598, which is located in the unusually long S5-pore linker of the channel. In other work we have demonstrated that hERG is uniquely susceptible to proteolytic cleavage at the S5-pore linker by proteinase K (PK) and calpain (CAPN). The scorpion toxin BeKm-1, which binds to the S5-pore linker of hERG, protects hERG from such cleavage. In the present study, our data revealed that, compared with normal glycosylated hERG channels, nonglycosylated hERG channels were significantly more susceptible to cleavage by extracellular PK. Furthermore, the protective effect of BeKm-1 on hERG from PK-cleavage was lost when glycosylation of hERG was inhibited. The inactivation-deficient mutant hERG channels S620T and S631A were resistant to PK cleavage, and inhibition of glycosylation rendered both mutants susceptible to PK cleavage. Compared with normal glycosylated channels, nonglycosylated hERG channels were also more susceptible to cleavage mediated by CAPN, which was present in the medium of human embryonic kidney cells under normal culture conditions. Inhibition of CAPN resulted in an increase of nonglycosylated hERG current. In summary, our results revealed that N-linked glycosylation protects hERG against protease-mediated degradation and thus contributes to hERG channel stability on the plasma membrane.- Lamothe, S. M., Hulbert, M., Guo, J., Li, W., Yang, T., Zhang, S. Glycosylation stabilizes hERG channels on the plasma membrane by decreasing proteolytic susceptibility. FASEB J. 32, 1933-1943 (2018). www.fasebj.org.
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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".