Recent research has implicated a large number of gluten-derived peptides in the pathogenesis of celiac disease, a preponderantly HLA-DQ2-associated disorder. Current evidence indicates that the core of some of those peptides is ten amino acids long, while HLA class II normally accommodates nine amino acids in the binding groove. We have now investigated this in detail, using gluten-specific T-cell clones, HLA-DQ2-specific peptide-binding assays and molecular modelling. T-cell recognition of both a gamma-gliadin peptide and a low-molecular-weight glutenin peptide was found to be strictly dependent on a ten-amino acids-long peptide. Subsequent peptide-binding studies indicated that the glutenin peptide bound in a conventional p1/p9 register, with an additional proline at p-1. Testing of substitution analogues demonstrated that the nature of the amino acid at p-1 strongly influenced T-cell recognition of the peptide. Moreover, molecular modelling confirmed that the glutenin peptide binds in a p1/p9 register, and that the proline at p-1 points upward towards the T-cell receptor. Database searches indicate that a large number of potential T-cell stimulatory gluten peptides with an additional proline at relative position p-1 exist, suggesting that the recognition of other gluten peptides may depend on this proline as well. This knowledge may be of importance for the identification of additional T-cell stimulatory gluten peptides and the design of a peptide-based, tolerance-inducing therapy.
The MIR algorithm provides an ab initio prediction of a protein's core residues. An improved version, the MIR2, is presented and validated on 3203 proteins from PDB. Structures are decomposed in Closed Loops, their limits constituting the observed core residues. They are predicted by MIR2 with an accuracy approaching 80%.
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