Epitope-based Vaccine Design from Alpha and Beta Variant of SARS-CoV-2: An Immunoinformatics Approach

Hendyco Pratama, Nur Imaniati Sumantri, Siti Fauziyah Rahman, Viol Dhea Kharisma, Arif Nur Muhammad Ansori

Research output: Contribution to journalArticlepeer-review


Coronavirus disease 2019, also known as COVID-19, is a respiratory disease. Symptoms of COVID-19 include fever, dry cough, inflammation of the throat area, loss of smell, and even breathing difficulty. COVID-19 is caused by SARS-CoV-2 infection, a virus that is a member of the coronavirus family. The SARS-CoV-2 structure consists of S (spike), M (membrane), E (envelope), and N (nucleocapsid) protein. Two SARS-CoV-2 variants, namely alpha (B.1.1.7) and beta (B.1.351) variants are considered a variant of concern (VoC) due to their increased infectivity. It has been reported that the vaccine's efficacy against these two variants decreased. The purpose of this study is to compare epitopes from S and N proteins of alpha and beta variants to find the most suitable vaccine candidate through reverse vaccinology. In this study, physicochemical properties, antigenicity, and epitope prediction, as well as molecular docking of the epitope and B cell receptor, 5IFH, were done. The result suggested that the epitope from S protein was more suitable as a vaccine candidate. S protein epitope has a lower global energy value which means that it can bind to 5IFH more spontaneously compared to N protein epitopes. The most suitable vaccine candidate for the alpha variant is Pep_B, with a global energy value of-48.77 kcal/mol, and Pep_F, for the beta variant, with a global energy value of-61.61 kcal/mol. These results would recommend the epitopes to be used in further COVID-19 vaccine development.

Original languageEnglish
Pages (from-to)4617-4625
Number of pages9
JournalResearch Journal of Pharmacy and Technology
Issue number10
Publication statusPublished - 2023


  • COVID-19
  • immunoinformatic
  • N Protein
  • reverse vaccinology
  • S Protein


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