Discovery of a Potent Conorfamide from <i>Conus episcopatus</i> Using a Novel Zebrafish Larvae Assay
Bibliographic record
Abstract
Natural products such as conotoxins have tremendous potential as tools for biomedical research and for the treatment of different human diseases. Conotoxins are peptides present in the venoms of predatory cone snails that have a rich diversity of pharmacological functions. One of the major bottlenecks in natural products research is the rapid identification and evaluation of bioactive molecules. To overcome this limitation, we designed a set of light-induced behavioral assays in zebrafish larvae to screen for bioactive conotoxins. We used this screening approach to test several unique conotoxins derived from different cone snail clades and discovered that a conorfamide from Conus episcopatus, CNF-Ep1, had the most dramatic alterations in the locomotor behavior of zebrafish larvae. Interestingly, CNF-Ep1 is also bioactive in several mouse assay systems when tested in vitro and in vivo . Our novel screening platform can thus accelerate the identification of bioactive marine natural products, and the first compound discovered using this assay has intriguing properties that may uncover novel neuronal circuitry.
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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) | 0.001 | 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".