3′-(Phenyl alkynyl) analogs of abscisic acid: synthesis and biological activity of potent ABA antagonists
Bibliographic record
Abstract
We report here the synthesis and biological testing of 3'-(phenyl alkynyl) abscisic ABA analogs, a new class of potent ABA antagonists. These ABA analogs incorporate a rigid framework of eight carbon atoms attached at the 3'-carbon atom of ABA that prevents folding of the ABA analog-bound receptor required for ABA signalling. The two-step synthesis is based upon the optimized conversion of natural (S)-ABA to 3'-iodo ABA which can be coupled to phenyl acetylenes using Sonogashira conditions, or to styryl compounds through Suzuki chemistry. The parent 3'-(phenyl alkynyl) ABA analog 7 was obtained in 29% yield, 74% yield based on recovered starting material. In a lentil seed germination assay, compound 7 was found to have more potent activity than other known 3'-substituted ABA antagonists to date. In a structure activity study parasubstituted phenyl alkynyl analogs had comparable activity to the analog 7 while the 3'-styryl ABA 18 was only slightly less active. Analog 7 overcame ABA inhibition of germination and seedling growth in a wide range of mono and dicot plant species, including canola, lentil, soybean, rice, wheat, barley, cannabis and canary seed. 3'-(Phenyl alkynyl) ABA analogs have numerous potential practical agricultural applications including promoting ripening of crops, dormancy breaking of seeds and woody perennials, as well as promoting seed germination, and growth under stress conditions as demonstrated in this report.
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) | 0.002 | 0.001 |
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".