DiscoTope-3.0: improved B-cell epitope prediction using inverse folding latent representations

Research output: Contribution to journalJournal articleResearchpeer-review


  • Fulltext

    Final published version, 3.87 MB, PDF document

  • Magnus Haraldson Høie
  • Frederik Steensgaard Gade
  • Julie Maria Johansen
  • Charlotte Würtzen
  • Winther, Ole
  • Morten Nielsen
  • Paolo Marcatili

Accurate computational identification of B-cell epitopes is crucial for the development of vaccines, therapies, and diagnostic tools. However, current structure-based prediction methods face limitations due to the dependency on experimentally solved structures. Here, we introduce DiscoTope-3.0, a markedly improved B-cell epitope prediction tool that innovatively employs inverse folding structure representations and a positive-unlabelled learning strategy, and is adapted for both solved and predicted structures. Our tool demonstrates a considerable improvement in performance over existing methods, accurately predicting linear and conformational epitopes across multiple independent datasets. Most notably, DiscoTope-3.0 maintains high predictive performance across solved, relaxed and predicted structures, alleviating the need for experimental structures and extending the general applicability of accurate B-cell epitope prediction by 3 orders of magnitude. DiscoTope-3.0 is made widely accessible on two web servers, processing over 100 structures per submission, and as a downloadable package. In addition, the servers interface with RCSB and AlphaFoldDB, facilitating large-scale prediction across over 200 million cataloged proteins. DiscoTope-3.0 is available at: https://services.healthtech.dtu.dk/service.php?DiscoTope-3.0.

Original languageEnglish
Article number1322712
JournalFrontiers in Immunology
Number of pages12
Publication statusPublished - 2024

Bibliographical note

Publisher Copyright:
Copyright © 2024 Høie, Gade, Johansen, Würtzen, Winther, Nielsen and Marcatili.

    Research areas

  • antibody epitope prediction, B cell epitope prediction, ESM-IF1, immunogenicity prediction, inverse-folding, structure-based, vaccine design

ID: 384491742