Folding similarity of the outer pore region in prokaryotic and eukaryotic sodium channels revealed by docking of conotoxins GIIIA, PIIIA, and KIIIA in a NavAb-based model of Nav1.4
Bibliographic record
Abstract
Voltage-gated sodium channels are targets for many drugs and toxins. However, the rational design of medically relevant channel modulators is hampered by the lack of x-ray structures of eukaryotic channels. Here, we used a homology model based on the x-ray structure of the NavAb prokaryotic sodium channel together with published experimental data to analyze interactions of the μ-conotoxins GIIIA, PIIIA, and KIIIA with the Nav1.4 eukaryotic channel. Using Monte Carlo energy minimizations and published experimentally defined pairwise contacts as distance constraints, we developed a model in which specific contacts between GIIIA and Nav1.4 were readily reproduced without deformation of the channel or toxin backbones. Computed energies of specific interactions between individual residues of GIIIA and the channel correlated with experimental estimates. The predicted complexes of PIIIA and KIIIA with Nav1.4 are consistent with a large body of experimental data. In particular, a model of Nav1.4 interactions with KIIIA and tetrodotoxin (TTX) indicated that TTX can pass between Nav1.4 and channel-bound KIIIA to reach its binding site at the selectivity filter. Our models also allowed us to explain experimental data that currently lack structural interpretations. For instance, consistent with the incomplete block observed with KIIIA and some GIIIA and PIIIA mutants, our computations predict an uninterrupted pathway for sodium ions between the extracellular space and the selectivity filter if at least one of the four outer carboxylates is not bound to the toxin. We found a good correlation between computational and experimental data on complete and incomplete channel block by native and mutant toxins. Thus, our study suggests similar folding of the outer pore region in eukaryotic and prokaryotic sodium channels.
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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".