Evidence map›Paper›PMID 42653488›Full record

ArticleInternational journal of molecular sciences2026

Structure-Guided Discovery Reveals Recurrent Bioactive Peptide Architectures Across Coleoptera.

Thaís Caroline Gonçalves, João Alfredo Teodoro, Danilo T Amaral

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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

3 authors.

Thaís Caroline GonçalvesCentro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André 09210-580, SP, Brazil.ORCID 0009-0001-3039-7366
João Alfredo TeodoroCentro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André 09210-580, SP, Brazil.ORCID 0009-0003-5601-0814
Danilo T AmaralCentro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André 09210-580, SP, Brazil.ORCID 0000-0002-8940-6546

Funding

Fundação de Amparo à Pesquisa do Estado de São Paulo 2023/05589-4
6 · The paper itself

Abstract

Bioactive peptides are an important source of therapeutic molecules and molecular scaffolds involved in defense, signaling, and immune regulation. Despite the extraordinary diversity of Coleoptera, the structural landscape of beetle-derived bioactive peptides remains largely unexplored, limiting our understanding of their evolutionary diversity and biotechnological potential. Here, we performed a large-scale structural survey of predicted toxin-like peptide scaffolds across publicly available Coleoptera transcriptomes by integrating transcriptome mining, peptide maturation prediction, physicochemical characterization, AlphaFold 3 structural modeling, structural similarity analyses, and interpretable machine learning. We identified 291 candidate peptides, of which 155 contained canonical signal peptides and 273 produced mature peptides within the expected size range of known bioactive peptides. Structural analyses revealed that, despite extensive sequence diversity, many candidates were organized into a comparatively restricted repertoire of compact cysteine-rich architectures, indicating that structural similarity is retained across peptides exhibiting substantial primary-sequence variation. Comparative structural analyses further identified recurrent protein architectures shared across multiple beetle lineages, while machine learning prioritization integrated structural and biochemical descriptors to identify high-confidence candidates for future functional characterization. These analyses establish the first structural atlas of predicted toxin-like peptides across Coleoptera and demonstrate that structure-guided transcriptome mining provides a powerful framework for uncovering recurrent bioactive peptide scaffolds that would remain largely undetected using sequence-based approaches alone. Beyond expanding our understanding of peptide evolution in beetles, this resource is a foundation for future structural, functional, and biotechnological exploration of bioactive peptides in underexplored animal groups.

Indexed as

ColeopteraInsect ProteinsPeptidesAmino Acid SequenceAnimalsMachine LearningModels, MolecularProtein ConformationTranscriptomeInsect ProteinsPeptidesAlphaFoldbioactive peptidesColeopteramachine learningstructural bioinformatics

Identifiers

PMID42653488
PMCPMC13513286

What Socratic holds

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Registered trials

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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 Socratic graph.