Abstract
The identification of B-cell epitopes is imperative for the rational design of vaccines, diagnostics and immunotherapeutics. Several bioinformatics resources are freely available for the prediction of B-cell epitopes, however despite advances in recent years, they still possess limited predictive capabilities. The aim of this review is to highlight and describe the algorithms of the most widely used free B-cell epitope prediction resources. The reasons behind the limited predictive powers of these algorithms are also discussed.
Highlights
A B-cell epitope is a collection of distinct amino acid residues on an antigen that antibodies recognize and bind to, thereby activating a protective immune response [1,2,3]
Linear B-cell epitopes are composed of contiguous residues in the primary structure [1]
Discontinuous B-cell epitopes comprise residues remotely located in the primary structure that are brought into close proximity due to the folding of the protein [1]
Summary
A B-cell epitope is a collection of distinct amino acid residues on an antigen that antibodies recognize and bind to, thereby activating a protective immune response [1,2,3]. B-cell epitopes are classified according to their orientation in space as being either linear or discontinuous. Linear B-cell epitopes are composed of contiguous residues in the primary structure [1]. Discontinuous B-cell epitopes comprise residues remotely located in the primary structure that are brought into close proximity due to the folding of the protein [1]. 10% of B-cell epitopes are linear and 90% are discontinuous [3]. Since linear B-cell epitopes do adopt a conformation, the distinction between linear and discontinuous Bcell epitopes is a grey area [2,4]
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