Research into the Bioengineering of a Novel α-Conotoxin from the Milked Venom of Conus obscurus
Bibliographic record
Abstract
The marine cone snail produces one of the fastest prey strikes in the animal kingdom. It injects highly efficacious venom, often causing prey paralysis and death within seconds. Each snail has hundreds of conotoxins, which serve as a source for discovering and utilizing novel analgesic peptide therapeutics. In this study, we discovered, isolated, and synthesized a novel α3/5-conotoxins derived from the milked venom of Conus obscurus (α-conotoxin OI) and identified the presence of α-conotoxin SI-like sequence previously found in the venom of Conus striatus. Five synthetic analogs of the native α-conotoxin OI were generated. These analogs incorporated single residue or double residue mutations. Three synthetic post-translational modifications (PTMs) were synthetically incorporated into these analogs: N-terminal truncation, proline hydroxylation, and tryptophan bromination. The native α-conotoxin OI demonstrated nanomolar potency in Poecilia reticulata and Homosapiens muscle-type nicotinic acetylcholine receptor (nAChR) isoforms. Moreover, the synthetic α-[P9K] conotoxin OI displayed enhanced potency in both bioassays, ranging from a 2.85 (LD50) to 18.4 (IC50) fold increase in comparative bioactivity. The successful incorporation of PTMs, with retention of both potency and nAChR isoform selectivity, ultimately pushes new boundaries of peptide bioengineering and the generation of novel α-conotoxin-like sequences.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".