SCAM analysis reveals a discrete region of the pore turret that modulates slow inactivation in Kv1.5
Bibliographic record
Abstract
In Kv1.5, protonation of histidine 463 in the S5-P linker (turret) increases the rate of depolarization-induced inactivation and decreases the peak current amplitude. In this study, we examined how amino acid substitutions that altered the physico-chemical properties of the side chain at position 463 affected slow inactivation and then used the substituted cysteine accessibility method (SCAM) to probe the turret region (E456-P468) to determine whether residue 463 was unique in its ability to modulate the macroscopic current. Substitutions at position 463 of small, neutral (H463G and H463A) or large, charged (H463R, H463K, and H463E) side groups accelerated inactivation and induced a dependency of the current amplitude on the external potassium concentration. When cysteine substitutions were made in the distal turret (T462C-P468C), modification with either the positively charged [2-(trimethylammonium)ethyl] methanethiosulfonate bromide (MTSET) or negatively charged sodium (2-sulfonatoethyl) methanethiosulfonate reagent irreversibly inhibited current. This inhibition could be antagonized either by the R487V mutation (homologous to T449V in Shaker) or by raising the external potassium concentration, suggesting that current inhibition by MTS reagents resulted from an enhancement of inactivation. These results imply that protonation of residue 463 does not modulate inactivation solely by an electrostatic interaction with residues near the pore mouth, as proposed by others, and that residue 463 is part of a group of residues within the Kv1.5 turret that can modulate P/C-type inactivation.
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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".