Mapping the interaction surface of scorpion β-toxins with an insect sodium channel
Bibliographic record
Abstract
The interaction of insect-selective scorpion depressant β-toxins (LqhIT2 and Lqh-dprIT3 from Leiurus quinquestriatus hebraeus) with the Blattella germanica sodium channel, BgNav1-1a, was investigated using site-directed mutagenesis, electrophysiological analyses, and structural modeling. Focusing on the pharmacologically defined binding site-4 of scorpion β-toxins at the voltage-sensing domain II (VSD-II), we found that charge neutralization of D802 in VSD-II greatly enhanced the channel sensitivity to Lqh-dprIT3. This was consistent with the high sensitivity of the splice variant BgNav2-1, bearing G802, to Lqh-dprIT3, and low sensitivity of BgNav2-1 mutant, G802D, to the toxin. Further mutational and electrophysiological analyses revealed that the sensitivity of the WT = D802E < D802G < D802A < D802K channel mutants to Lqh-dprIT3 correlated with the depolarizing shifts of activation in toxin-free channels. However, the sensitivity of single mutants involving IIS4 basic residues (K4E = WT << R1E < R2E < R3E) or double mutants (D802K = K4E/D802K = R3E/D802K > R2E/D802K > R1E/D802K > WT) did not correlate with the activation shifts. Using the cryo-EM structure of the Periplaneta americana channel, NavPaS, as a template and the crystal structure of LqhIT2, we constructed structural models of LqhIT2 and Lqh-dprIT3-c in complex with BgNav1-1a. These models along with the mutational analysis suggest that depressant toxins approach the salt-bridge between R1 and D802 at VSD-II to form contacts with linkers IIS1-S2, IIS3-S4, IIIP5-P1 and IIIP2-S6. Elimination of this salt-bridge enables deeper penetration of the toxin into a VSD-II gorge to form new contacts with the channel, leading to increased channel sensitivity to Lqh-dprIT3.
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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) | 0.000 | 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".