Structural Homology and Biding Ability Comparisons of Epitope Pair Candidates for Molecular Mimicry Triggering of Type 1 Diabetes Mellitus

Background: Molecular mimicry is the process by which foreign peptides contain epitopes similar to self-peptides, potentially inducing autoimmune responses. Identifying potential molecular mimics and studying their properties is key to understanding the onset of autoimmune diseases such as type 1 diabetes mellitus (T1DM). Previous work identified pairs of infectious epitopes (EINF) and T1DM epitopes (ET1D) that demonstrated sequence homology; however, structural homology and binding ability to HLA molecules were not considered. Correlating sequence homology with structural properties and binding ability is important for translational investigation of potential molecular mimics. This work compares sequence homology with structural homology and binding ability by calculating the structures and binding ability of the epitope pairs identified in previous work. Results: For each pair of EINF and ET1D we calculated the root mean square deviations (RMSD) between their predicted isolated structures and their percent (%) overlap when bound to the corresponding HLA molecule using the Boltz-2. Of the 53 epitope pairs considered here, only 6 were found to not exhibit any matching (defined as less than 3 residues overlap). For the other epitopes, the RMSD ranges from 0.13 Å to 1.39 Å with an average of 0.56 Å. The calculated % overlaps between the infectious and T1DM epitopes when bound to the corresponding HLA molecules ranges from 0% to 93.3%. There are 3 pairs that show nearly identical HLA footprints, 15 very similar binding mode, 19 similar binding mode, 11 moderately similar, and only 5 showing a totally different footprint. Conclusions: Most of the EINF/ET1D pairs selected by sequence homology show similar structural and binding ability to HLA molecules, indications that may lead to disease onset due to molecular mimicry. These findings suggest that searching for epitope pairs using sequence homology, a much less computationally demanding approach, leads to strong candidates for molecular mimicry that should be considered for further study. However, full binding ability calculations at scale may be necessary to advance the in-silico molecular mimicry predictions, which may be useful to select the most promising candidates for experimental studies. Keywords: Type 1 Diabetes Mellitus; Molecular Mimicry; Protein Structure Prediction, binding ability.