Catalysis of Na <sup>+</sup> permeation in the bacterial sodium channel Na <sub>V</sub> Ab
Bibliographic record
Abstract
Determination of a high-resolution 3D structure of voltage-gated sodium channel Na(V)Ab opens the way to elucidating the mechanism of ion conductance and selectivity. To examine permeation of Na(+) through the selectivity filter of the channel, we performed large-scale molecular dynamics simulations of Na(V)Ab in an explicit, hydrated lipid bilayer at 0 mV in 150 mM NaCl, for a total simulation time of 21.6 μs. Although the cytoplasmic end of the pore is closed, reversible influx and efflux of Na(+) through the selectivity filter occurred spontaneously during simulations, leading to equilibrium movement of Na(+) between the extracellular medium and the central cavity of the channel. Analysis of Na(+) dynamics reveals a knock-on mechanism of ion permeation characterized by alternating occupancy of the channel by 2 and 3 Na(+) ions, with a computed rate of translocation of (6 ± 1) × 10(6) ions⋅s(-1) that is consistent with expectations from electrophysiological studies. The binding of Na(+) is intimately coupled to conformational isomerization of the four E177 side chains lining the extracellular end of the selectivity filter. The reciprocal coordination of variable numbers of Na(+) ions and carboxylate groups leads to their condensation into ionic clusters of variable charge and spatial arrangement. Structural fluctuations of these ionic clusters result in a myriad of ion binding modes and foster a highly degenerate, liquid-like energy landscape propitious to Na(+) diffusion. By stabilizing multiple ionic occupancy states while helping Na(+) ions diffuse within the selectivity filter, the conformational flexibility of E177 side chains underpins the knock-on mechanism of Na(+) permeation.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".