Fungtion: A Server for Predicting and Visualizing Fungal Effector Proteins.
fungal effector prediction
machine learning
pre-trained protein language models
protein sequence analysis
web server
Journal
Journal of molecular biology
ISSN: 1089-8638
Titre abrégé: J Mol Biol
Pays: Netherlands
ID NLM: 2985088R
Informations de publication
Date de publication:
01 Sep 2024
01 Sep 2024
Historique:
received:
21
02
2024
revised:
11
05
2024
accepted:
13
05
2024
medline:
6
9
2024
pubmed:
6
9
2024
entrez:
5
9
2024
Statut:
ppublish
Résumé
Fungal pathogens pose significant threats to plant health by secreting effectors that manipulate plant-host defences. However, identifying effector proteins remains challenging, in part because they lack common sequence motifs. Here, we introduce Fungtion (Fungal effector prediction), a toolkit leveraging a hybrid framework to accurately predict and visualize fungal effectors. By combining global patterns learned from pretrained protein language models with refined information from known effectors, Fungtion achieves state-of-the-art prediction performance. Additionally, the interactive visualizations we have developed enable researchers to explore both sequence- and high-level relationships between the predicted and known effectors, facilitating effector function discovery, annotation, and hypothesis formulation regarding plant-pathogen interactions. We anticipate Fungtion to be a valuable resource for biologists seeking deeper insights into fungal effector functions and for computational biologists aiming to develop future methodologies for fungal effector prediction: https://step3.erc.monash.edu/Fungtion/.
Identifiants
pubmed: 39237206
pii: S0022-2836(24)00208-0
doi: 10.1016/j.jmb.2024.168613
pii:
doi:
Substances chimiques
Fungal Proteins
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
168613Informations de copyright
Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.