Patent attributes
Methodology for the automated selection and/or optimization of T-cell epitopes is disclosed. The invention provides a data processing system which utilizes sequence-based statistical pattern recognition to compute an epitope selection matrix based on the informational content of epitopes known to bind to a particular major histocompatibility class I allele. The resulting Bayes-corrected scoring matrix is used to predict the relative binding affinities of candidate T-cell epitopes derived from immunologically relevant antigens of self or foreign origin. One aspect of the invention describes an analytical method for identification of modifications in known or predicted T-cell epitopes that confer upon the epitopes the ability to elicit stronger cellular immune response due to more efficient processing and/or presentation to T-cells. The disclosed epitope identification algorithm is applicable to the design of vaccines for infectious diseases, cancer and autoimmune diseases as well as for developing methods for the in vitro evaluation of cellular immunity.
