Biophysical Investigation of Sodium Channel Interaction with β-Subunit Variants Associated with Arrhythmias
Bibliographic record
Abstract
Background: Voltage-gated sodium (Na V ) channels help regulate electrical activity of the plasma membrane. Mutations in associated subunits can result in pathological outcomes. Here we examined the interaction of Na V channels with cardiac arrhythmia-linked mutations in SCN2B and SCN4B , two genes that encode auxiliary β-subunits. Materials and Methods: To investigate changes in SCN2B R137H and SCN4B I80T function, we combined three-dimensional X-ray crystallography with electrophysiological measurements on Na V 1.5, the dominant subtype in the heart. Results: SCN4B I80T alters channel activity, whereas SCN2B R137H does not have an apparent effect. Structurally, the SCN4B I80T perturbation alters hydrophobic packing of the subunit with major structural changes and causes a thermal destabilization of the folding. In contrast, SCN2B R137H leads to structural changes but overall protein stability is unaffected. Conclusion: SCN4B I80T data suggest a functionally important region in the interaction between Na V 1.5 and β4 that, when disrupted, could lead to channel dysfunction. A lack of apparent functional effects of SCN2B R137H on Na V 1.5 suggests an alternative working mechanism, possibly through other Na V channel subtypes present in heart tissue. Indeed, mapping the structural variations of SCN2B R137H onto neuronal Na V channel structures suggests altered interaction patterns.
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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".