Abstract
Abstract
Multiple sclerosis (MS) shows a strong genetic association with HLA-DRB1 alleles and a consistent epidemiological association with Epstein–Barr virus (EBV) infection. However, it remains unclear how HLA-DRB1 polymorphisms modulate the presentation of autoantigens and viral antigens potentially involved in cross-reactivity. In this study, peptide–HLA (pHLA) complexes formed by six HLA-DRB1 alleles associated with different MS risk profiles were investigated in interaction with CLIP103–117, MBP85–99, and EBNA1400–413. To this end, molecular dynamics simulations were integrated with machine learning models trained using inter-residue distances at the pHLA interface as input attributes, allowing evaluation of how different peptides modulate the conformational stability of the complexes and identification of which interface regions contribute to distinguishing alleles associated with higher and lower risk. The results show that EBNA1400–413 does not globally reproduce the interaction mode of MBP85–99 within the binding groove. Compared with MBP85–99 and CLIP103–117, EBNA1400–413 exhibited fewer intermolecular contacts, greater solvent exposure, and less favorable binding energy. Despite this, in the higher-risk alleles DRB1*15:01 and DRB1*15:03, complexes containing EBNA1400–413 showed lower conformational variability and occupied low-energy regions that partially overlapped with those observed for MBP85–99. The machine learning models indicated distinct discriminatory patterns for the autoantigen and the viral antigen. However, in the combined MBP85–99 and EBNA1400–413 model, the most informative pairs converged on the β:70−β:72 region, including β:71, with more pronounced differences in complexes containing EBNA1400–413. This result suggests that β:71 contributes to interface organization in a peptide- and allele-dependent manner. In addition, the proximity between C:R402 of EBNA1400–413 and the region occupied by C:K93 in MBP85–99 suggests a local physicochemical similarity between the complexes, despite the absence of global structural equivalence between the peptides. These findings indicate that EBNA1400–413 does not act as an ideal structural mimic of MBP85–99, but may favor partially compatible conformational states in alleles associated with higher MS risk. Thus, this study proposes a mechanism of functional mimicry dependent on pHLA interface dynamics, in which HLA-DRB1 polymorphisms modulate the presentation of self and viral peptides. This model provides a molecular basis for investigating how the interaction between HLA-associated genetic risk and the immune response to EBV may contribute to autoimmune mechanisms in MS.