Evidence for Dual Binding Sites for 1,1,1-Trichloro-2,2-bis(p-chlorophenyl)ethane (DDT) in Insect Sodium Channels
Bibliographic record
Abstract
1,1,1-Trichloro-2,2-bis(p-chlorophenyl)ethane (DDT), the first organochlorine insecticide, and pyrethroid insecticides are sodium channel agonists. Although the use of DDT is banned in most of the world due to its detrimental impact on the ecosystem, indoor residual spraying of DDT is still recommended for malaria control in Africa. Development of resistance to DDT and pyrethroids is a serious global obstacle for managing disease vectors. Mapping DDT binding sites is necessary for understanding mechanisms of resistance and modulation of sodium channels by structurally different ligands. The pioneering model of the housefly sodium channel visualized the first receptor for pyrethroids, PyR1, in the II/III domain interface and suggested that DDT binds within PyR1. Previously, we proposed the second pyrethroid receptor, PyR2, at the I/II domain interface. However, whether DDT binds to both pyrethroid receptor sites remains unknown. Here, using computational docking of DDT into the Kv1.2-based mosquito sodium channel model, we predict that two DDT molecules can bind simultaneously within PyR1 and PyR2. The bulky trichloromethyl group of each DDT molecule fits snugly between four helices in the bent domain interface, whereas two p-chlorophenyl rings extend into two wings of the interface. Model-driven mutagenesis and electrophysiological analysis confirmed these propositions and revealed 10 previously unknown DDT-sensing residues within PyR1 and PyR2. Our study proposes a dual DDT-receptor model and provides a structural background for rational development of new insecticides.
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 | 0.001 | 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".