COBEpro: A novel system for predicting continuous B-cell epitopes

Abstract

Accurate prediction of B-cell epitopes has remained a challenging task in computational immunology despite several decades of research. Only 10% of the known B-cell epitopes are estimated to be continuous, yet they are often the targets of predictors because a solved tertiary structure is not required and they are integral to the development of peptide vaccines and engineering therapeutic proteins. In this article, we present COBEpro, a novel two-step system for predicting continuous B-cell epitopes. COBEpro is capable of assigning epitopic propensity scores to both standalone peptide fragments and residues within an antigen sequence. COBEpro first uses a support vector machine to make predictions on short peptide fragments within the query antigen sequence and then calculates an epitopic propensity score for each residue based on the fragment predictions. Secondary structure and solvent accessibility information (either predicted or exact) can be incorporated to improve performance. COBEpro achieved a cross-validated area under the curve (AUC) of the receiver operating characteristic up to 0.829 on the fragment epitopic propensity scoring task and an AUC up to 0.628 on the residue epitopic propensity scoring task. COBEpro is incorporated into the SCRATCH prediction suite at http://scratch.proteomics.ics.uci.edu. © The Author 2008. Published by Oxford University Press. All rights reserved.