Evidence map›Paper›PMID 40796375›Full record

ArticleGigaScience2025

PeptideMiner-neuropeptide discovery across the animal kingdom.

Helen C Mendel, Gene Hopping, Eivind A B Undheim, Johannes Zuegg, Richard J Lewis, Briony E Forbes, Quentin Kaas, Markus Muttenthaler

Abstract read
In one paragraph

Article in GigaScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Helen C MendelInstitute for Molecular Bioscience, The University of Queensland, 4072 Brisbane, Australia.ORCID 0000-0003-1165-4459
Gene HoppingInstitute for Molecular Bioscience, The University of Queensland, 4072 Brisbane, Australia.ORCID 0000-0001-8409-1867
Eivind A B UndheimCentre for Ecological and Evolutionary Synthesis, Department of Biosciences, The University of Oslo, 0371 Oslo, Norway.ORCID 0000-0002-8667-3999
Johannes ZueggInstitute for Molecular Bioscience, The University of Queensland, 4072 Brisbane, Australia.ORCID 0000-0001-6240-6020
Richard J LewisInstitute for Molecular Bioscience, The University of Queensland, 4072 Brisbane, Australia.ORCID 0000-0003-3470-923X
Briony E ForbesDiscipline of Medical Biochemistry, Flinders Health and Medical Research Institute, Flinders University, 5042 Adelaide, Australia.ORCID 0000-0003-4360-9927
Quentin KaasInstitute for Molecular Bioscience, The University of Queensland, 4072 Brisbane, Australia.ORCID 0000-0001-9988-6152
Markus MuttenthalerInstitute for Molecular Bioscience, The University of Queensland, 4072 Brisbane, Australia.ORCID 0000-0003-1996-4646

Funding

Australian Research Council DE150100784Australian Research Council DP190101667Australian Research Council FT210100266European Research Council 101039862Horizon 2020 714366National Health and Medical Research Council 2037680Norwegian Research Council 287462
6 · The paper itself

Abstract

Neuropeptides represent the largest and most diverse class of cell-to-cell signaling molecules, holding important roles in animal physiology and behavior. They are evolutionarily ancient and widely distributed across the animal kingdom. Although over 200 neuropeptides have been identified, only a small fraction has been functionally characterized. A recognized bottleneck is the lack of effective tools to study their biological roles and therapeutic potential. Interestingly, neuropeptide-like peptides are also found in animal venoms, where they contribute to prey capture or defensive strategies. Mapping neuropeptide families across the animal kingdom is challenging due to their high sequence divergence and short mature peptide sequences. To address this, we developed PeptideMiner, a search tool that employs profile-hidden Markov models (profile-HMMs) for family-specific peptide discovery. PeptideMiner was systematically validated and benchmarked against existing methods, demonstrating its superior performance. By applying PeptideMiner to several venom transcriptomes-including 24 previously unpublished datasets-we identified 10 novel natriuretic peptides from distantly related species and 57 novel insulin-like sequences from marine predatory cone snails. Chemical synthesis and structure-activity relationship studies of newly identified conoinsulins at human insulin receptors emphasized the value of our approach in elucidating ligand-receptor interactions and discovering new pharmacological probes and therapeutic leads. PeptideMiner offers a powerful platform for discovering new bioactive peptides and family-specific analogues, accelerating both natural product discovery and evolutionary research.

Indexed as

NeuropeptidesAmino Acid SequenceAnimalsHumansMarkov ChainsNeuropeptidesinsulinnatriuretic peptidesneuropeptidetranscriptomicsvenom

Identifiers

PMID40796375
PMCPMC12343078

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.