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
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

Auteurs

M Carroll (M)

Department of Chemistry and Biochemistry, Yeshiva College, Yeshiva University, New York, NY 10033, USA.

E Rosenbaum (E)

Department of Chemistry and Biochemistry, Yeshiva College, Yeshiva University, New York, NY 10033, USA.

R Viswanathan (R)

Department of Chemistry and Biochemistry, Yeshiva College, Yeshiva University, New York, NY 10033, USA.

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Classifications MeSH