TY - JOUR
T1 - DiscoTope-3.0
T2 - improved B-cell epitope prediction using inverse folding latent representations
AU - Høie, Magnus Haraldson
AU - Gade, Frederik Steensgaard
AU - Johansen, Julie Maria
AU - Würtzen, Charlotte
AU - Winther, Ole
AU - Nielsen, Morten
AU - Marcatili, Paolo
N1 - Publisher Copyright:
Copyright © 2024 Høie, Gade, Johansen, Würtzen, Winther, Nielsen and Marcatili.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Antibody epitope prediction
KW - B cell epitope prediction
KW - ESM-IF1
KW - Immunogenicity prediction
KW - Inverse-folding
KW - Structure-based
KW - Vaccine design
U2 - 10.3389/fimmu.2024.1322712
DO - 10.3389/fimmu.2024.1322712
M3 - Journal article
C2 - 38390326
AN - SCOPUS:85185854796
SN - 1664-3224
VL - 15
JO - Frontiers in Immunology
JF - Frontiers in Immunology
M1 - 1322712
ER -