Bioinformatics analysis of Epitope-based candidate vaccine against the novel (SARS-CoV-۲)

The complete sequence of SARS-CoV-۲ genome that get from NCBI (ACCESSION number: NC_۰۴۵۵۱۲.۲)use in this study, and find ORF in the genome and to find signal peptide, use signalp database. for assessmentof allergenicity of these proteins, use ALGpred database and filter protein based on amino acid compositionand Blast search on allergen representative peptides (ARPs), and choose a protein that both algorithmsconfirmed that proteins are not Allergen. To investigate immunogenicity of proteins, use the vaxijen serverand choose proteins with a threshold Overall Prediction for the Protective Antigen score up to ۰.۹.for toxicityanalysis of proteins uses the Toxinpred database. To remove inside cell membrane proteins use (TMHMM)database. To Epitope prediction use IEDB, for linear epitope prediction and CBTOPE database forconformational epitope prediction. Epitopes that pass the criteria of toxicity, allergenicity, antigenicity arechose and sort based on scores, then get-togethers with linker (KK, GGGGS), and adjuvant (OmpA)(GenBank: AFS۸۹۶۱۵.۱) add. (۶xHis-tag) adds at the C terminal end of the vaccine construct. Use clusproserver for molecular docking study to identify binding affinity characterizing of candidate vaccines ۱ and ۲with MHC Class I and MHC Class II.

Keywords:

SARS-CoV-۲: Epitope-based , vaccine design