Background: HLA-C locus products are poorly understood in part due to their low expression at the cell surface. Recent data indicate that these molecules serve as major restriction elements for human immunodeficiency virus type I (HIV-I) cytotoxic T lymphocyte (CTL) epitopes. We report here a structure-based technique for the prediction of peptides binding to Cw*0401. The models were rigorously trained, tested and validated using experimentally verified Cw*0401 binding and non-binding peptides obtained from biochemical studies. A new scoring scheme facilitates the identification of immunological hot spots within antigens, based on the sum of predicted binding energies of the top four binders within a window of 30 amino acids. Results: High predictivity is achieved when tested on the training (r2 = 0.88, s = 3.56 kj/mol, q2 = 0.84, Spress = 5.18 kj/mol) and test (AROC = 0.93) datasets. Characterization of the predicted Cw*0401 binding sequences indicate that amino acids at key anchor positions share common physico-chemical properties which correlate well with existing experimental studies. Conclusion: The analysis of predicted Cw*0401 -binding peptides showed that anchor residues may not be restrictive and the Cw*0401 binding pockets may possibly accommodate a wide variety of peptides with common physico-chemical properties. The potential Cw*0401-specific T-cell epitope repertoires for HIV-I p24gag and gp160gag glycoproteins are well distributed throughout both glycoproteins, with thirteen and nine immunological hot spots for HIV-I p24gag and gp 160gag glycoproteins respectively. These findings provide new insights into HLA-C peptide selectivity, indicating that pre-selection of candidate HLA-C peptides may occur at the TAP level, prior to peptide loading in the endoplasmic reticulum.
|Publication status||Published - 2007|
ASJC Scopus subject areas
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Applied Mathematics