Abstract
Background: Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system(CNS). It is widely accepted that the development and progression of MS result from aberrant activation of potentially encephalitogenic reactive-T cells against CNS antigens. The pathologic roles of both CD4+ (T helper; Th) and CD8+ T cells have been demonstrated in MS lesions.
Objective: In the present work, we applied a series of bioinformatics tools to design a dendritic cell (DC)-targeting Tregitope-based multi-epitope vaccine for MS to induce tolerance in pathogenic myelin-specific T cells.
Methods: The 3D structure of anti-DEC205 scFv and the remaining part of the vaccine were modeled by ROSIE Antibody server and ITASSER software, respectively. AIDA web server (ab initio domain assembly server) was applied to assemble two parts of the vaccine and build the full construct. Following modeled structure refinement and validation, physicochemical properties, and allergenicity of the vaccine were assessed. In the final step, in silico cloning was done to ensure high-level expression in the desired host.
Results: This vaccine consists of three main parts; 1) Anti-DEC205 scFv antibody, 2) multiepitope vaccine part composed of multiple pathogenic CD4+, and CD8+ T cell epitopes originated from multiple known antigens in MS patients, as well as T-regulatory (Treg)-inducing epitopes (Tregitopes), and 3) vasoactive intestinal peptide (VIP). All parts of the final vaccine were joined together with the help of proper linkers. After vaccine construction, the three-D structure, as well as different physicochemical and immunological features of the vaccine were predicted. Finally, in silico gene cloning was also carried out to assure efficient production of protein vaccine in Escherichia coli K12 expression strain.
Conclusion: Computational study revealed that this vaccination can regulate MS disease progression and even relapse by harnessing pathogenic T cells.
Keywords: Multi-epitope vaccine, Multiple sclerosis, Tregitope, Vasoactive intestinal peptide, Bioinformatics aided design, CNS.
Graphical Abstract
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