Reverse vaccinology approach to design a novel multi-epitope vaccine candidate against COVID-19: an in silico study.

Journal of Biomolecular Structure & Dynamics
Maryam EnayatkhaniKhadijeh Ahmadi

Abstract

At present, novel Coronavirus (2019-nCoV, the causative agent of COVID-19) has caused worldwide social and economic disruption. The disturbing statistics of this infection promoted us to develop an effective vaccine candidate against the COVID-19. In this study, bioinformatics approaches were employed to design and introduce a novel multi-epitope vaccine against 2019-nCoV that can potentially trigger both CD4+ and CD8+ T-cell immune responses and investigated its biological activities by computational tools. Three known antigenic proteins (Nucleocapsid, ORF3a, and Membrane protein, hereafter called NOM) from the virus were selected and analyzed for prediction of the potential immunogenic B and T-cell epitopes and then validated using bioinformatics tools. Based on in silico analysis, we have constructed a multi-epitope vaccine candidate (NOM) with five rich-epitopes domain including highly scored T and B-cell epitopes. After predicting and evaluating of the third structure of the protein candidate, the best 3 D predicted model was applied for docking studies with Toll-like receptor 4 (TLR4) and HLA-A*11:01. In the next step, molecular dynamics (MD) simulation was used to evaluate the stability of the designed fusion protein wit...Continue Reading

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Methods Mentioned

BETA
in silico methods

Software Mentioned

MolProbity
VMD
BepiPred
BLAST
Ellipro Server
USCF Chimera
PyMol
MMPBSA
Allertop
Rankpep

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