| dc.description.abstract | SARS-CoV-2 was the cause of the recent global pandemic, COVID-19, which killed many people. Several vaccines were used to deal with this disease, but the side effects are one of the most critical challenges of the produced vaccines. Therefore, it is possible to produce vaccines with fewer side effects and more effective by using bioinformatics tools. Target :
Identification of potential immunogenic regions in SARS-CoV-2 virus proteins using bioinformatics tools. Method :First, the sequences of individual SARS-CoV-2 proteins were obtained from the NCBI site. After submitting it to the IEDB database using the recommended method for MHC class II and MHC class I for all alleles presented in that database, possible epitopes were created. Then, epitopes with higher affinity were screened using Vaxijen, ToxinPred, and AllerTop servers in terms of immunogenicity and toxicity, and allergenicity, respectively. Also, the possible epitopes of linear B cells were analyzed by the IEDB server in the surface proteins of the virus. Results:Based on the analysis of the obtained data, in MHC class I alleles A*30:02, A*26:01, and A*32:01 and in MHC class II alleles DPA1*01:03/DPB1*04:01, DRB3 *02:02 and DPA1*01:03/DPB1*02:01 produced the highest number of epitopes with high affinity among all virus proteins. Spike, NSP12, and NSP3 proteins also produced the highest number of epitopes with high affinity for MHC class I and II.Conclusion:Based on immunoinformatics tools, proteins that produce the maximum number of high-affinity epitopes with the minimum amino acid sequence can be selected and used in vaccine design. | en_US |
