Isolation and characterization of five novel disulfide-poor conopeptides from Conus marmoreus venom
Bibliographic record
Abstract
Abstract Background: Conopeptides from cone snail venom have aroused great interest related to the discovery of novel bioactive candidates, due to their excellent prospects for the treatment of various health problems such as pain, addiction, psychosis and epilepsy. In order to explore novel biopeptides, we investigated the structure and function of five novel conopeptides isolated from the venom of Conus marmoreus from South China Sea. Methods: C. marmoreus crude venom was prepared, fractionated and purified by HPLC system. The primary sequences of the five novel disulfide-poor conopeptides Mr-1 to Mr-5 were identified by comprehensive analysis of de novo MALDI-TOF tandem mass spectrometry and Edman degradation data. In order to investigate their function, these five conopeptides were synthesized by Fmoc-SPPS chemistry, and their biological effects at several heterologous rat nicotinic acetylcholine receptor (nAChR) subtypes (α1β1δε, α3β2, α3β4, α4β2) were determined by electrophysiological technique. Results: Five novel disulfide-poor conopeptides were identified and named as follows: Mr-1 (DWEYHAHPKPNSFWT), Mr-2 (YPTRAYPSNKFG), Mr-3 (NVIQAPAQSVAPP NTST), Mr-4 [KENVLNKLKSK(L/I)] and Mr-5 [NAVAAAN(L/I)PG(L/I)V]. None of them contains a disulfide bond. The sequences of conopeptides Mr-2 to Mr-5 do not belong to any category of the known disulfide-poor conopeptides. No significant activity against the above nAChR subtypes were observed for the five conopeptides at 100 µM. Conclusion: We purified and structurally characterized five novel disulfide-poor conopeptides from C. marmoreus crude venom and first investigated their nAChR inhibitory effects. This work expanded our knowledge on the structure and function of disulfide-poor conopeptides from this cone snail venom.
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) | 0.001 | 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".