3-Layer-based analysis of peptide–MHC interaction: In silico prediction, peptide binding affinity and T cell activation in a relevant allergen-specific model

Abstract

CD4+ T cells recognize peptides bound to major histocompatibility complex (MHC) class II molecules on the surface of antigen presenting cells by their T cell receptor (TCR). Using a well-characterized allergen-specific model we studied peptide/MHC (pMHC) interactions by combining computational methods with experimental analyses. A 12-mer and an 18-mer peptide, both containing the human leukocyte antigen (HLA)-DR1-restricted, immunodominant T cell epitope of Art v 1, the major mugwort pollen allergen, were compared. A Molecular Dynamics simulation for a real time of 20 ns using GROMACS was performed. To this aim, the peptides were modelled into the binding groove of HLA-DRB1*0101 using different amino acid substitution tools. Binding of synthetic peptides to purified HLA-DRB1*0101 molecules was analysed in competition assays. The potency of the peptides to activate Art v 1-specific T cells was assessed using oligo- and monoclonal Art v 1-specific T cell cultures expanded from mugwort allergic individuals. All approaches revealed that the 18-mer peptide possessed higher HLA DR affinity as compared to the 12-mer. Computer modelling indicated that a loop-like structure within the additional N-terminal peptide flanking region of the 18-mer contributed to the pMHC interaction. Our approach, to combine computational methods validated by experimental results, demonstrates that Molecular Dynamics simulation may be a useful tool for the prediction of pMHC interactions in the future with possible applications in T cell-based immunotherapy e.g. in Type I allergy.