Prediction of MHC binder for fragment based viral peptide vaccines from cabbage leaf curl virus

摘要

Cabbage leaf curl viral peptides are most suitable for subunit vaccine development because with single epitope, the immune response can be generated in large population. The MHC peptide binding of pathogenicity proteins is predicted using neural networks trained on C terminals of known epitopes. In analysis predicted MHC/peptide binding of pathogenicity proteins is a log-transformed value related to the IC50 values in nM units. We describe an improved method for predicting linear epitopes (Table 1). The region of maximal hydrophilicity is likely to be an antigenic site, having hydrophobic characteristics, because terminal regions of pathogenicity protein is solvent accessible and unstructured, antibodies against those regions are also likely to recognize the native protein. It was shown that a pathogenicity protein is hydrophobic in nature and contains segments of low complexity and high- predicted flexibility. Predicted antigenic fragments can bind to MHC molecule is the first bottlenecks in vaccine design.