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For over 30 years, computational methods have been developed for facilitating epitope recognition (El-Manzalawy and Honavar, 2010). In the past, the majority of the in silico methods were focused on linear epitopes. Most of these approaches are sequence-based and use amino acid-based propensity scales, such as hydrophilicity, solvent accessibility, secondary structure and flexibility; a score derived from the propensity scales is assigned to each residue, and the whole sequence is examined for high-scoring window fragments, which are then predicted as epitopes (Hopp and Woods, 1981; Parker et al., 1986; Pellequer et al., 1991; Emini et al., 1985; Karplus and Schulz, 1985; Kolaskar and Tongaonkar, 1990; Welling et al., 1985).
(El-Manzalawy and Honavar, 2010) Recent advances in B-cell epitope prediction methods. Immunome Res.
(Hopp and Woods, 1981) Prediction of protein antigenic determinants from amino acid sequences. Proc Natl Acad Sci U S A.
(Parker et al., 1986) New hydrophilicity scale derived from high-performance liquid chromatography peptide retention data: correlation of predicted surface residues with antigenicity and X-ray-derived accessible sites. Biochemistry.
(Pellequer et al., 1991) Predicting location of continuous epitopes in proteins from their primary structures. Methods Enzymol.
(Emini et al., 1985) Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptide. J Virol.
(Karplus and Schulz, 1985) Prediction of chain flexibility in proteins. Naturwissenschaften.
(Kolaskar and Tongaonkar, 1990) A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett.
(Welling et al., 1985) Prediction of sequential antigenic regions in proteins. FEBS Lett.
(Dalkas and Rooman, 2017) SEPIa, a knowledge-driven algorithm for predicting conformational B-cell epitopes from the amino acid sequence. BMC Bioinformatics.