Pyrethroids in an AlphaFold2 Model of the Insect Sodium Channel
Bibliographic record
Abstract
Pyrethroid insecticides stabilize the open state of insect sodium channels. Previous mutational, electrophysiological, and computational analyses led to the development of homology models predicting two pyrethroid receptor sites, PyR1 and PyR2. Many of the naturally occurring sodium channel mutations, which confer knockdown resistance (kdr) to pyrethroids, are located within or close to these receptor sites, indicating that these mutations impair pyrethroid binding. However, the mechanism of the state-dependent action of pyrethroids and the mechanisms by which kdr mutations beyond the receptor sites confer resistance remain unclear. Recent advances in protein structure prediction using the AlphaFold2 (AF2) neural network allowed us to generate a new model of the mosquito sodium channel AaNav1-1, with the activated voltage-sensing domains (VSMs) and the presumably inactivated pore domain (PM). We further employed Monte Carlo energy minimizations to open PM and deactivate VSM-I and VSM-II to generate additional models. The docking of a Type II pyrethroid deltamethrin in the models predicted its interactions with many known pyrethroid-sensing residues in the PyR1 and PyR2 sites and revealed ligand-channel interactions that stabilized the open PM and activated VSMs. Our study confirms the predicted two pyrethroid receptor sites, explains the state-dependent action of pyrethroids, and proposes the mechanisms of the allosteric effects of various kdr mutations on pyrethroid action. The AF2-based models may assist in the structure-based design of new insecticides.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".