In Silico Perspectives on the Prediction of the PLP’s Epitopes involved in Multiple Sclerosis

Abstract

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 fi nd 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, AA58-74, AA161-177, and AA238-254 were detected as immunodominant regions through meta-prediction. Investigating peptides with more than 50% similarity to that of candidate epitope AA58-74 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.

Molecular mimicry between Zika virus and central nervous system inflammatory demyelinating disorders: the role of NS5 Zika virus epitope and PLP autoantigens

“… 31 A recent study involving PLP's Epitopes involved in MS, found CSAVPV (in PLP 161-177 residues) among the most immunogenic regions of PLP. 32 In addition, the crystal structure of the NS5 ZikV protein reveals a conserved domain conformation of Flaviviruses, a genus that includes a variety of human pathogens such as dengue virus, yellow fever virus, WNV, Spondweni virus, and the Japanese encephalitis virus. 33 So, the presence of high identity between NS5 ZikV and PLP, an autoantigen widely implicated in the pathogenesis of MS, 34 leads us to postulate that molecular mimicry may have a role in the development of inflammatory demyelinating damage, a hallmark of the IDD produced by this genus of virus.…”

Molecular Mimicry between Zika virus and central nervous system inflammatory demyelinating disorders: the role of NS5 Zika virus epitope and PLP autoantigens

“…Autoreactivity to PLP in patients with MS has been investigated in human and animal model by various groups worldwide (30). A recent study involving PLP's Epitopes involved in MS, found CSAVPV (in PLP 161-177 residues) among the most immunogenic regions of PLP (31). In addition, the crystal structure of the NS5 ZikV protein reveals a conserved domain conformation of Flaviviruses, a genus that includes a variety of human pathogens such as dengue virus, yellow fever virus, West Nile virus, Spondweni virus and the Japanese encephalitis virus (32).…”