Evidence map›Paper›PMID 39102416›Full record

ArticlePLoS computational biology2024

DepoScope: Accurate phage depolymerase annotation and domain delineation using large language models.

Robby Concha-Eloko, Michiel Stock, Bernard De Baets, Yves Briers, Rafael Sanjuán, Pilar Domingo-Calap, Dimitri Boeckaerts

Abstract read
In one paragraph

Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
–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

30 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  7. Isolation and characterization of broad-rangeMicrobiology (Reading, England) · 2026
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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

7 authors.

Robby Concha-ElokoInstitute for Integrative Systems Biology (I2SysBio), Universitat de Valencia-CSIC, Paterna, Spain.
Michiel StockKERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium.
Bernard De BaetsKERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium.ORCID 0000-0002-3876-620X
Yves BriersLaboratory of Applied Biotechnology, Department of Biotechnology, Ghent University, Ghent, Belgium.
Rafael SanjuánInstitute for Integrative Systems Biology (I2SysBio), Universitat de Valencia-CSIC, Paterna, Spain.
Pilar Domingo-CalapInstitute for Integrative Systems Biology (I2SysBio), Universitat de Valencia-CSIC, Paterna, Spain.
Dimitri BoeckaertsKERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium.ORCID 0000-0002-7668-2840

Funding

Conselleria d’Innovació, Universitats, Ciència i Societat Digital (Generalitat Valenciana GRISOLIAP/2020/158Flemish Government under the “Onderzoeksprogramma Articiële Intelligentie (AI) Vlaanderen” programRamón y Cajal RYC2019-028015-I
6 · The paper itself

Abstract

Bacteriophages (phages) are viruses that infect bacteria. Many of them produce specific enzymes called depolymerases to break down external polysaccharide structures. Accurate annotation and domain identification of these depolymerases are challenging due to their inherent sequence diversity. Hence, we present DepoScope, a machine learning tool that combines a fine-tuned ESM-2 model with a convolutional neural network to identify depolymerase sequences and their enzymatic domains precisely. To accomplish this, we curated a dataset from the INPHARED phage genome database, created a polysaccharide-degrading domain database, and applied sequential filters to construct a high-quality dataset, which is subsequently used to train DepoScope. Our work is the first approach that combines sequence-level predictions with amino-acid-level predictions for accurate depolymerase detection and functional domain identification. In that way, we believe that DepoScope can greatly enhance our understanding of phage-host interactions at the level of depolymerases.

Indexed as

BacteriophagesComputational BiologyCarboxylic Ester HydrolasesGenome, ViralMachine LearningMolecular Sequence AnnotationNeural Networks, ComputerProtein DomainsSoftwareViral ProteinsCarboxylic Ester HydrolasesViral Proteins

Identifiers

PMID39102416
PMCPMC11326577

What OpenQuestion holds

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LicenceCC BY
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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.