GP4: an integrated Gram-Positive Protein Prediction Pipeline for subcellular localization mimicking bacterial sorting.

GP4 Gram-positive homology-based prediction prediction methods protein subcellular localization prediction sorting signals

Journal

Briefings in bioinformatics
ISSN: 1477-4054
Titre abrégé: Brief Bioinform
Pays: England
ID NLM: 100912837

Informations de publication

Date de publication:
20 07 2021
Historique:
received: 29 07 2020
revised: 08 10 2020
accepted: 09 10 2020
pubmed: 24 11 2020
medline: 20 11 2021
entrez: 23 11 2020
Statut: ppublish

Résumé

Subcellular localization is a critical aspect of protein function and the potential application of proteins either as drugs or drug targets, or in industrial and domestic applications. However, the experimental determination of protein localization is time consuming and expensive. Therefore, various localization predictors have been developed for particular groups of species. Intriguingly, despite their major representation amongst biotechnological cell factories and pathogens, a meta-predictor based on sorting signals and specific for Gram-positive bacteria was still lacking. Here we present GP4, a protein subcellular localization meta-predictor mainly for Firmicutes, but also Actinobacteria, based on the combination of multiple tools, each specific for different sorting signals and compartments. Novelty elements include improved cell-wall protein prediction, including differentiation of the type of interaction, prediction of non-canonical secretion pathway target proteins, separate prediction of lipoproteins and better user experience in terms of parsability and interpretability of the results. GP4 aims at mimicking protein sorting as it would happen in a bacterial cell. As GP4 is not homology based, it has a broad applicability and does not depend on annotated databases with homologous proteins. Non-canonical usage may include little studied or novel species, synthetic and engineered organisms, and even re-use of the prediction data to develop custom prediction algorithms. Our benchmark analysis highlights the improved performance of GP4 compared to other widely used subcellular protein localization predictors. A webserver running GP4 is available at http://gp4.hpc.rug.nl/.

Identifiants

pubmed: 33227814
pii: 5998864
doi: 10.1093/bib/bbaa302
pmc: PMC8294519
pii:
doi:

Substances chimiques

Bacterial Proteins 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press.

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Auteurs

Tjeerd van Rij (T)

DSM Biotechnology Center in Delft, the Netherlands.

Jan Maarten van Dijl (JM)

University of Groningen and the University Medical Center Groningen, the Netherlands.

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