Synthesis, Biological Activity, and Hologram Quantitative Structure−Activity Relationships of Novel Allatostatin Analogues
Bibliographic record
Abstract
Cockroach-type allatostatins (FGLamides) (ASTs) can inhibit the production of juvenile hormone in vitro, and they therefore are regarded as possible insect growth regulator (IGR) candidates for pest control. However, several shortcomings, such as the absence of in vivo effects, rapid degradation, and high production costs, preclude their practical use in pest management. To discover new IGRs, 25 novel analogues of pentapeptide (Y/FXFGLa) were designed and synthesized with different aromatic acids, fatty acids, and dicarboxylic acids as the Y/FX region replacements on the basis of previous results. Their bioactivities in vitro were determined, and the results showed that eight analogues (K14, K15, K17, K18, K19, K23, K24, and K25) were more active than the lead, core region pentapeptide. The IC(50) values of K15 and K24 (IC(50) = 1.79 and 5.32 nM, respectively) were even lower than that of the natural AST, Dippu-AST 1(IC(50) = 8 nM), which indicated both analogues have better activity than Dippu-AST 1; particularly, K15 has better activity than most natural Dippu-ASTs. A predictable and statistically meaningful hologram quantitative structure-activity relationship (HQSAR) model of 32 AST analogues (28 as training sets and 4 as test sets) was obtained. The final model suggested that a potent AST analogue should contain an aromatic group, a linker of appropriate length, and the FGLa portion. These results will be useful in the design of new AST analogues that are structurally related to the training set compounds.
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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 | 0.001 |
| 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".