Evidence map›Paper›PMID 42681295›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

An Introduction to Structural Phylogenetics for Biomedical Sciences.

Caroline Puente-Lelievre, Nicholas Matzke, Jordan Douglas

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 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.

Caroline Puente-LelievreSchool of Biological Sciences, The University of Auckland, Auckland, New Zealand. caroline.puente-lelievre@auckland.ac.nz.
Nicholas MatzkeSchool of Biological Sciences, The University of Auckland, Auckland, New Zealand.
Jordan DouglasCentre for Computational Evolution, The University of Auckland, Auckland, New Zealand. jordan.douglas@auckland.ac.nz.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Structural phylogenetics offers a powerful framework for understanding the molecular basis of neural function and disease by combining evolutionary analysis with three-dimensional protein structure. While traditional protein-based phylogenetics relies mostly on amino acid sequences, recent advances in computational structure prediction have accelerated the integration of protein tertiary structures into phylogenetic studies. Since structure is more conserved than sequence, this approach may provide increased resolution in cases of high sequence divergence or mutational saturation, common issues in the study of complex, ancient, or fast-evolving protein families. In biomedical research, phylogenetics is a powerful approach for tracing the evolutionary origins and diversification of disease-related proteins. It provides a comparative framework to identify conserved structural motifs, function shifts, and predict potential targets for drug discovery and innovation. In neuroscience, these insights are especially valuable for uncovering the evolutionary basis of neural signaling, plasticity, and dysfunction. This chapter serves as a user-friendly practical tutorial for conducting structural phylogenetic analyses using accessible and computationally efficient tools, using synaptotagmins-calcium-sensing proteins essential for synaptic vesicle fusion-as a running example. This resource is designed for biomedical researchers seeking to integrate phylogenetics as a tool to build a comparative basis to strengthen their experimental design and improve their understanding of protein diversity and function.

Indexed as

Biomedical ResearchComputational BiologyPhylogenyProteinsAnimalsEvolution, MolecularHumansProtein ConformationSoftwareSynaptotagminsProteinsSynaptotagmins3DiBiomedicineHomology searchNeurosciencePhylogeneticsProteinStructural phylogeneticsSynaptotagminsSynthetic BiologyTutorial

Identifiers

PMID42681295

What OpenQuestion 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 OpenQuestion graph.