Evidence map›Paper›PMID 40272992›Full record

ArticleThe Biochemical journal2025

Structural characterisation of a cysteine-rich conotoxin, sigma(σ)S-GVIIIA, extracted from the defensive venom of the marine cone snail Conus geographus.

Yoshimi Peck, David Wilson, Danica Lennox-Bulow, Julien Giribaldi, Jamie Seymour, Sebastien Dutertre, K Rosengren, Michael Liddell, Norelle Daly

Abstract read
In one paragraph

Article in The Biochemical journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yoshimi PeckAustralian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia.
David WilsonAustralian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia.
Danica Lennox-BulowAustralian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia.
Julien GiribaldiIBMM, University of Montpellier, CNRS, ENSCM, Montpellier, France.
Jamie SeymourAustralian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia.
Sebastien DutertreIBMM, University of Montpellier, CNRS, ENSCM, Montpellier, France.
K RosengrenSchool of Biomedical Sciences, The University of Queensland, Brisbane, QLD, Australia.
Michael LiddellCollege of Science and Engineering, James Cook University, Cairns, QLD, Australia.
Norelle DalyAustralian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia.ORCID 0000-0002-4697-6602

Funding

Department of Education and Training | Australian Research Council (ARC) LE160100218James Cook University (JCU) Not applicable
6 · The paper itself

Abstract

The activity of the serotonin type 3 (5-HT3) receptor is associated with neurodegenerative, inflammatory and metabolic diseases, neuropsychiatric disorders, and cancer. Structural analysis of modulators of this receptor is likely to aid in future medicinal chemistry studies aimed at developing lead molecules targeting this receptor. Here we report the structure of a cone snail venom peptide that was purified from the crude venom of Conus geographus and shown to be an antagonist of the 5-HT3 receptor more than 25 years ago, sigma(σ)GVIIIA. This lag in structural characterisation studies is likely due to challenges in isolating the native peptide and difficulties in producing synthetic peptide due to the presence of ten cysteine residues involved in five disulfide bonds. Using NMR spectroscopy, we show that σS-GVIIIA adopts a growth factor cystine knot (GFCK) fold. This is the first example of a cone snail venom peptide experimentally determined to contain the GFCK structural motif, and the first example of a 5-HT3 receptor antagonist containing this motif. Our study also highlights complexities in the use of artificial intelligence-based structure prediction models. Peptide structure predictions using AlphaFold 3 were consistent with our NMR structure when the input sequence contained the well-conserved precursor sequence, but inconsistent when the precursor sequence was excluded. AI-based structure prediction of proteins is a rapidly advancing field, but this inconsistency emphasises the need for more experimental structural training data when novel structures are involved, as was the case here for a cysteine-rich peptide.

Indexed as

AlphaFoldconotoxincysteine-rich peptidegrowth factor cystine knotgrowth factor cystine knot (GFCK)NMR spectroscopyNuclear Magnetic Resonance (NMR) spectroscopy

Identifiers

PMID40272992
PMCPMC12203953

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.