Importance

Loading Importance Indicators...

Abstract

The present invention relates to the identification of CTL epitopes by the combination of biochemical assays, statistical matrix calculations, and artificial neural networks. A set of peptide libraries are used to generate complete unbiased matrices representing peptide-MHC interactions used to generate a primary prediction of MHC binding for all possible non-redundant peptides. The best binders are subject to a quantitative biochemical binding assay and subsequently a computerised artificial neural network prediction program built from these in vitro experimental MHC-I binding data. The method further comprises improving the identified epitope by replacing amino acids, and testing the identified CTL epitopes in in vitro and in vivo models. Thus, one aspect of the invention relates to the identification of a CTL component of a vaccine and the development of said CTL component. Another aspect of the invention relates to the identified epitopes of said CTL component.

Loading the Abstract Image...

First Claim