Computational Methods to Predict Conformational B-Cell Epitopes.
B-cell epitopes
computational identification of epitopes
conformational epitopes
Journal
Biomolecules
ISSN: 2218-273X
Titre abrégé: Biomolecules
Pays: Switzerland
ID NLM: 101596414
Informations de publication
Date de publication:
10 Aug 2024
10 Aug 2024
Historique:
received:
09
07
2024
revised:
04
08
2024
accepted:
08
08
2024
medline:
31
8
2024
pubmed:
31
8
2024
entrez:
29
8
2024
Statut:
epublish
Résumé
Accurate computational prediction of B-cell epitopes can greatly enhance biomedical research and rapidly advance efforts to develop therapeutics, monoclonal antibodies, vaccines, and immunodiagnostic reagents. Previous research efforts have primarily focused on the development of computational methods to predict linear epitopes rather than conformational epitopes; however, the latter is much more biologically predominant. Several conformational B-cell epitope prediction methods have recently been published, but their predictive performances are weak. Here, we present a review of the latest computational methods and assess their performances on a diverse test set of 29 non-redundant unbound antigen structures. Our results demonstrate that ISPIPab performs better than most methods and compares favorably with other recent antigen-specific methods. Finally, we suggest new strategies and opportunities to improve computational predictions of conformational B-cell epitopes.
Identifiants
pubmed: 39199371
pii: biom14080983
doi: 10.3390/biom14080983
pii:
doi:
Substances chimiques
Epitopes, B-Lymphocyte
0
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM