Differential Lipid Dependence of the Function of Bacterial Sodium Channels
Bibliographic record
Abstract
The lipid bilayer is important for maintaining the integrity of cellular compartments and plays a vital role in providing the hydrophobic and charged interactions necessary for membrane protein structure, conformational flexibility and function. To directly assess the lipid dependence of activity for voltage-gated sodium channels, we compared the activity of three bacterial sodium channel homologues (NaChBac, NavMs, and NavSp) by cumulative (22)Na(+) uptake into proteoliposomes containing a 3∶1 ratio of 1-palmitoyl 2-oleoyl phosphatidylethanolamine and different "guest" glycerophospholipids. We observed a unique lipid profile for each channel tested. NavMs and NavSp showed strong preference for different negatively-charged lipids (phosphatidylinositol and phosphatidylglycerol, respectively), whilst NaChBac exhibited a more modest variation with lipid type. To investigate the molecular bases of these differences we used synchrotron radiation circular dichroism spectroscopy to compare structures in liposomes of different composition, and molecular modeling and electrostatics calculations to rationalize the functional differences seen. We then examined pore-only constructs (with voltage sensor subdomains removed) and found that in these channels the lipid specificity was drastically reduced, suggesting that the specific lipid influences on voltage-gated sodium channels arise primarily from their abilities to interact with the voltage-sensing subdomains.
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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 | 0.001 |
| 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) | 0.000 | 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".