US 2004/0072162 A1 · Hiv peptides and nucleic acids encoding them for diagnosis and control of hiv infection

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.

Claims17

Dependent claims

A method to identify a CTL epitope comprising the steps of:

(a) generating primary position specific prediction means from experimental MHC class I structural or peptide binding data;
(b) identifying potentially high affinity binding epitopes by scanning a set of protein sequences and calculating the binding affinity according to the primary prediction means obtained in step (a);
(c) optionally reducing the high number of peptides identified in step (b) by exclusion means based on sequence similarity;
(d) generating experimental binding data for the peptides identified in step (c) or (b);
(e) training one or more artificial neural networks to predict binding affinities to MHC class I, using the experimental binding data from step (d) such that the individual peptide binding data examples, weighted according to their frequency in sub-intervals in the binding affinity range of 1 nM to 50,000 nM, are equally presented;
and
(f) estimating the binding affinity of a query peptide by testing said query peptide in each of the artificial neural networks trained in step (e) obtaining an approximate binding affinity of the query peptide from each of the artificial neural networks, and calculating the weighted average of the approximate bindings thereby obtaining the estimated binding affinity of the query peptide;
the CTL epitope having a weighted average of the MHC class I binding affinity of less than 500 nM.

5 more elements

A CTL epitope identified by the method according to any of the preceding claims.

Dependencies are inferred from the claim text.

Hiv peptides and nucleic acids encoding them for diagnosis and control of hiv infection

Life of this patent

Hiv peptides and nucleic acids encoding them for diagnosis and control of hiv infection

Life of this patent

Abstract

Claims17