Patent ID: 7756644
Filing Date: 2010-07-13
Classification: G16B

Abstract:
1. A computer-assisted method for identifying T-cell epitopes of a target protein that are likely to bind to an MHC class I allele of interest comprising: a) selecting an MHC allele of interest; b) collecting and curating a training set which comprises peptide sequences which are known to bind to the MHC allele, wherein the peptide sequences consist of 9 amino acid positions (9mers) or 10 amino acid positions (10mers); c) grouping the peptide sequences in the training set into clusters based on a predetermined amino acid sequence identity threshold; d) determining an empirical binding score matrix (ESM) which summarizes the fraction of clusters that contain each of 20 amino acids at each of the 9 or 10 positions of the peptide sequences in the training set; wherein the values of the ESM (F) are calculated: e) calculating a Bayes-corrected scoring matrix (BSM) from the ESM, wherein the values of the BSM (B) are calculated B(i,j)=log [{(F(i,j)/S f) using the BSM to calculate a predicted binding score for a test series of candidate T-cell epitopes derived from the target protein, wherein the candidate T-cell epitopes consist of 9 or 10 amino acids, wherein the predicted binding score (S) is calculated: g) identifying T-cell epitopes of the target protein that are likely to bind to the MHC allele of interest, wherein the candidate T-cell epitopes of the test series having a binding score that is equal to or greater than a predetermined threshold when compared to the binding score of all other candidate T-cell epitopes in the test series are identified as T-cell epitopes likely to bind to the MHC class I allele of interest, wherein the predetermined threshold is based on a percentile at which a fraction of randomly generated peptides have a lower binding score; h) outputting the result of at least one of steps g) and h) to at least one of a data storage system and an output device.