New insights into the therapeutic inhibition of voltage-gated sodium channels
Bibliographic record
Abstract
Antiarrhythmics, anticonvulsants and local anesthetics inhibit voltage-gated sodium channels and reduce membrane excitability in neurons and muscle, making them useful in the management of cardiac arrhythmias, epilepsy and pain. These compounds, which are often termed singly in the literature as 'local anesthetics', have at least two inhibitory states: a resting inhibition that develops with intermittent stimulation and a higher affinity inhibition that arises upon repeated depolarization and likely involves the inactivated state of the channel. Although elucidating their mechanism of inhibition has been an active area of research for decades, many questions remain unanswered. Do these two inhibitory states share a common, but guarded or modulated receptor? Or do they represent different protonated states of the drugs, many of which have pKa's close to physiological pH, thereby yielding a significant population of both charged and uncharged compound inside cells. Some mechanistic clues can be found by mutating conserved phenylalanine and tyrosine residues of the 'local anesthetic receptor' in the channel's inner vestibule. Mutations of these aromatic residues universally disrupt the mechanism of drug inhibition in numerous channel isoforms. For instance, non aromatic substitutions of Phe1579 (Na(V) numbering) in the pore lining S6 segment of domain four (DIVS6) can abolish inactivated state inhibition.(1,2) The strict conservation of Phe1579 and other DIVS6 aromatic residues in all nine sodium channel isoforms led us to further dissect the role of this and other aromatic residues on local anesthetic inhibition. We recently employed subtly modified phenylalanine derivatives to better understand the role of these aromatics in the binding of local anesthetics and found a significant electrostatic interaction at one site, Phe1579, contributes to channel inhibition.(3) What follows is a self guided tour of our motivation and experimental findings.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".