Mechanism of sodium channel block by local anesthetics, antiarrhythmics, and anticonvulsants
Bibliographic record
Abstract
Local anesthetics, antiarrhythmics, and anticonvulsants include both charged and electroneutral compounds that block voltage-gated sodium channels. Prior studies have revealed a common drug-binding region within the pore, but details about the binding sites and mechanism of block remain unclear. Here, we use the x-ray structure of a prokaryotic sodium channel, NavMs, to model a eukaryotic channel and dock representative ligands. These include lidocaine, QX-314, cocaine, quinidine, lamotrigine, carbamazepine (CMZ), phenytoin, lacosamide, sipatrigine, and bisphenol A. Preliminary calculations demonstrated that a sodium ion near the selectivity filter attracts electroneutral CMZ but repels cationic lidocaine. Therefore, we further docked electroneutral and cationic drugs with and without a sodium ion, respectively. In our models, all the drugs interact with a phenylalanine in helix IVS6. Electroneutral drugs trap a sodium ion in the proximity of the selectivity filter, and this same site attracts the charged group of cationic ligands. At this position, even small drugs can block the permeation pathway by an electrostatic or steric mechanism. Our study proposes a common pharmacophore for these diverse drugs. It includes a cationic moiety and an aromatic moiety, which are usually linked by four bonds.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".