Epilepsy-associated mutations in the voltage sensor of KCNQ3 affect voltage dependence of channel opening
Bibliographic record
Abstract
One of the major factors known to cause neuronal hyperexcitability is malfunction of the potassium channels formed by KCNQ2 and KCNQ3. These channel subunits underlie the M current, which regulates neuronal excitability. Here, I investigate the molecular mechanisms by which epilepsy-associated mutations in the voltage sensor (S4) of KCNQ3 cause channel malfunction. Voltage clamp fluorometry reveals that the R230C mutation in KCNQ3 allows S4 movement but shifts the open/closed transition of the gate to very negative potentials. This results in the mutated channel remaining open throughout the physiological voltage range. Substitution of R230 with natural and unnatural amino acids indicates that the functional effect of the arginine residue at position 230 depends on both its positive charge and the size of its side chain. I find that KCNQ3-R230C is hard to close, but it is capable of being closed at strong negative voltages. I suggest that compounds that shift the voltage dependence of S4 activation to more positive potentials would promote gate closure and thus have therapeutic potential.
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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".