Scanning Mutagenesis of ω-Atracotoxin-Hv1a Reveals a Spatially Restricted Epitope That Confers Selective Activity against Insect Calcium Channels
Bibliographic record
Abstract
We constructed a complete panel of alanine mutants of the insect-specific calcium channel blocker omega-atracotoxin-Hv1a. Lethality assays using these mutant toxins identified three spatially contiguous residues, Pro10, Asn27, and Arg35, that are critical for insecticidal activity against flies (Musca domestica) and crickets (Acheta domestica). Competitive binding assays using radiolabeled omega-atracotoxin-Hv1a and neuronal membranes prepared from the heads of American cockroaches (Periplaneta americana) confirmed the importance of these three residues for binding of the toxin to target calcium channels presumably expressed in the insect membranes. At concentrations up to 10 microm, omega-atracotoxin-Hv1a had no effect on heterologously expressed rat Cav2.1, Cav2.2, and Cav1.2 calcium channels, consistent with the previously reported insect selectivity of the toxin. 30 microm omega-atracotoxin-Hv1a inhibited rat Cav currents by 10-34%, depending on the channel subtype, and this low level of inhibition was essentially unchanged when Asn27 and Arg35, which appears to be critical for interaction of the toxin with insect Cav channels, were both mutated to alanine. We propose that the spatially contiguous epitope formed by Pro10, Asn27, and Arg35 confers specific binding to insect Cav channels and is largely responsible for the remarkable phyletic selectivity of omega-atracotoxin-Hv1a. This epitope provides a structural template for rational design of chemical insecticides that selectively target insect Cav channels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".