RESUMEN
Background: Multiple sclerosis [MS] is the most common autoimmune disease of the central nervous system [CNS]. The main cause of the MS is yet to be revealed, but the most probable theory is based on the molecular mimicry that concludes some infections in the activation of T cells against brain auto-antigens that initiate the disease cascade
Objectives: The Purpose of this research is the prediction of the auto-antigen potency of the myelin proteolipid protein [PLP] in multiple sclerosis
Materials and Methods: As there wasn't any tertiary structure of PLP available in the Protein Data Bank [PDB] and in order to characterize the structural properties of the protein, we modeled this protein using prediction servers. Meta prediction method, as a new perspective in silico, was performed to find PLPs epitopes. For this purpose, several T cell epitope prediction web servers were used to predict PLPs epitopes against Human Leukocyte Antigens [HLA]. The overlap regions, as were predicted by most web servers were selected as immunogenic epitopes and were subjected to the BLASTP against microorganisms
Results: Three common regions, AA[58-74], AA[161-177], and AA[238-254] were detected as immunodominant regions through meta-prediction. Investigating peptides with more than 50% similarity to that of candidate epitope AA[58-74] in bacteria showed a similar peptide in bacteria [mainly consistent with that of clostridium and mycobacterium] and spike protein of Alphacoronavirus 1, Canine coronavirus, and Feline coronavirus. These results suggest that cross reaction of the immune system to PLP may have originated from a bacteria or viral infection, and therefore molecular mimicry might have an important role in the progression of MS
Conclusions: Through reliable and accurate prediction of the consensus epitopes, it is not necessary to synthesize all PLP fragments and examine their immunogenicity experimentally [in vitro]. In this study, the best encephalitogenic antigens were predicted based on bioinformatics tools that may provide reliable results for researches in a shorter time and at a lower cost