Review
Version 1
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Computational Methods to Predict Conformational B-cell Epitopes
Version 1
: Received: 10 July 2024 / Approved: 11 July 2024 / Online: 11 July 2024 (10:13:47 CEST)
How to cite: Carroll, M.; Rosenbaum, E.; Viswanathan, R. Computational Methods to Predict Conformational B-cell Epitopes. Preprints 2024, 2024070943. https://doi.org/10.20944/preprints202407.0943.v1 Carroll, M.; Rosenbaum, E.; Viswanathan, R. Computational Methods to Predict Conformational B-cell Epitopes. Preprints 2024, 2024070943. https://doi.org/10.20944/preprints202407.0943.v1
Abstract
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, although 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 outperformed all other methods. Finally, we suggest new strategies and opportu-nities to improve computational predictions of conformational B-cell epitopes.
Keywords
B-cell epitopes; conformational epitopes; computational identification of epitopes
Subject
Biology and Life Sciences, Biology and Biotechnology
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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