Phylogeny-aware linear B-cell epitope predictor detects targets associated with immune response to orthopoxviruses

Felipe Campelo, Ana Laura Grossi de Oliveira, João Reis-Cunha, Vanessa Gomes Fraga, Pedro Henrique Bastos, Jodie Ashford, Anikó Ekárt, Talita Emile Ribeiro Adelino, Marcos Vinicius Ferreira Silva, Felipe Campos de Melo Iani, Augusto César Parreiras de Jesus, Daniella Castanheira Bartholomeu, Giliane de Souza Trindade, Ricardo Toshio Fujiwara, Lilian Lacerda Bueno, Francisco Pereira Lobo

Research output: Contribution to journalArticlepeer-review

Abstract

We introduce a phylogeny-aware framework for predicting linear B-cell epitope (LBCE)-containing regions within proteins. Our approach leverages evolutionary information by using a taxonomic scaffold to build models trained on hierarchically structured data. The resulting models present performance equivalent or superior to generalist methods, despite using simpler features and a fraction of the data volume required by current state-of-the-art predictors. This allows the utilization of available data for major pathogen lineages to facilitate the prediction of LBCEs for emerging infectious agents. We demonstrate the efficacy of our approach by predicting new LBCEs in the monkeypox (MPXV) and vaccinia viruses. Experimental validation of selected targets using sera from infected patients confirms the presence of LBCEs, including candidates for the differential serodiagnosis of recent MPXV infections. These results point to the use of phylogeny-aware predictors as a useful strategy to facilitate the targeted development of immunodiagnostic tools.
Original languageEnglish
Article numberbbae527
Number of pages12
JournalBriefings in Bioinformatics
Volume25
Issue number6
Early online date6 Nov 2024
DOIs
Publication statusPublished - Nov 2024

Bibliographical note

Copyright © The Author(s) 2024. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Keywords

  • Orthopoxvirus
  • Epitope prediction
  • Diagnostics
  • Machine Learning
  • Monkeypox Virus
  • Phylogeny-aware Methods
  • Humans
  • Vaccinia virus
  • Epitopes, B-Lymphocyte
  • Computational Biology
  • Phylogeny

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