Abstract
BackgroundThe lack of effective treatment against the highly infectious SARS-CoV-2 has aggravated the already catastrophic global health issue. Here, in an attempt to design an efficient vaccine, a thorough immunoinformatics approach was followed to predict the most suitable viral proteins epitopes for building that vaccine.MethodsThe amino acid sequences of four structural proteins (S, M, N, E) along with one potentially antigenic accessory protein (ORF1a) of SARS-CoV-2 were inspected for the most appropriate epitopes to be used for building the vaccine construct. Several immunoinformatics tools were used to assess the antigenicity (VaxiJen server), immunogenicity (IEDB immunogenicity tool), allergenicity (AlgPred), toxigenicity (ToxinPred server), interferon-gamma inducing capacity (IFNepitope server), and the physicochemical properties of the construct (ProtParam tool).ResultsThe final candidate vaccine construct consisted of 468 amino acids, encompassing 29 epitopes. The CTL epitopes that passed the antigenicity, allergenicity, toxigenicity and immunogenicity assessment were four epitopes from S protein, one from M protein, two from N protein, 12 from the ORF1a polyprotein and none from E protein. While the HTL epitopes that passed the antigenicity, allergenicity, toxigenicity and INF-gamma were one from S protein, three from M protein, six from the ORF1a polyprotein and none from N and E proteins.All the vaccine properties and its ability to trigger the humoral and cell-mediated immune response were validated computationally. Molecular modeling, docking to TLR3, simulation, and molecular dynamics were also carried out. Finally, a molecular clone using pET28::mAID expression plasmid vector was prepared.ConclusionThe overall results of the study suggest that the final multi-epitope chimeric construct is a potential candidate for an efficient protective vaccine against SARS-CoV-2.
Highlights
In early December 2019, an acute respiratory disease of unknown etiology emerged in Wuhan, China, which was subsequently found to be caused by a novel coronavirus
The aim of this study is to design a multi-epitope vaccine against severe acute respiratory syndrome (SARS)-CoV-2 based on four structural proteins along with the nonstructural polyprotein of open reading frame 1a (ORF1a), using an immunoinformatics approach
This study is an attempt to design an efficient multi-epitope chimeric subunit vaccine that is capable of mounting a strong immune response by induction of both humoral and cellular mediated immunity, with the help of a large number of immunoinformatics tools
Summary
In early December 2019, an acute respiratory disease of unknown etiology emerged in Wuhan, China, which was subsequently found to be caused by a novel coronavirus. The virus was initially described as 2019-nCoV and later named by the international committee on taxonomy of viruses (ICTV) as severe acute respiratory syndrome coronavirus-2 (SARSCoV-2), while the World Health Organization (WHO) named the disease Coronavirus disease-19 (COVID19) [1,2,3,4,5]. COVID19 is characterized by a broad clinical spectrum, ranging from asymptomatic, to mild to severe respiratory illness requiring intubation and intensive care. Acute respiratory distress syndrome (ARDS), acute cardiac injury, and acute kidney injury and death can occur [8, 9]. In an attempt to design an efficient vaccine, a thorough immunoinformatics approach was followed to predict the most suitable viral proteins epitopes for building that vaccine
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