Intermediate state trapping of a voltage sensor
Bibliographic record
Abstract
Voltage sensor domains (VSDs) regulate ion channels and enzymes by undergoing conformational changes depending on membrane electrical signals. The molecular mechanisms underlying the VSD transitions are not fully understood. Here, we show that some mutations of I241 in the S1 segment of the Shaker Kv channel positively shift the voltage dependence of the VSD movement and alter the functional coupling between VSD and pore domains. Among the I241 mutants, I241W immobilized the VSD movement during activation and deactivation, approximately halfway between the resting and active states, and drastically shifted the voltage activation of the ionic conductance. This phenotype, which is consistent with a stabilization of an intermediate VSD conformation by the I241W mutation, was diminished by the charge-conserving R2K mutation but not by the charge-neutralizing R2Q mutation. Interestingly, most of these effects were reproduced by the F244W mutation located one helical turn above I241. Electrophysiology recordings using nonnatural indole derivatives ruled out the involvement of cation-Π interactions for the effects of the Trp inserted at positions I241 and F244 on the channel's conductance, but showed that the indole nitrogen was important for the I241W phenotype. Insight into the molecular mechanisms responsible for the stabilization of the intermediate state were investigated by creating in silico the mutations I241W, I241W/R2K, and F244W in intermediate conformations obtained from a computational VSD transition pathway determined using the string method. The experimental results and computational analysis suggest that the phenotype of I241W may originate in the formation of a hydrogen bond between the indole nitrogen atom and the backbone carbonyl of R2. This work provides new information on intermediate states in voltage-gated ion channels with an approach that produces minimum chemical perturbation.
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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) | 0.002 | 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".