Designing multi-epitope based peptide vaccine candidates against SARS-CoV-2 using immunoinformatics approach

Ysrafil Ysrafil; Zulfiayu Sapiun; Indwiani Astuti; Mohammad Anas Anasiru; Nangsih Sulastri Slamet; Hartati Hartati; Fadli Husain; Sukmawati Ahmad Damiti

doi:10.34172/bi.2022.23769

Designing multi-epitope based peptide vaccine candidates against SARS-CoV-2 using immunoinformatics approach

Bioimpacts. 2022;12(4):359-370. doi: 10.34172/bi.2022.23769. Epub 2022 Feb 27.

Authors

Ysrafil Ysrafil¹, Zulfiayu Sapiun^{2

3}, Indwiani Astuti⁴, Mohammad Anas Anasiru⁵, Nangsih Sulastri Slamet², Hartati Hartati², Fadli Husain², Sukmawati Ahmad Damiti⁶

Affiliations

¹ Faculty of Medicine, Universitas Palangka Raya, Palangka Raya 73111, Indonesia.
² Department of Pharmacy, Health Polytechnic of Gorontalo, Gorontalo 96135, Indonesia.
³ Department of Pharmacy, Faculty of Pharmacy, Universitas Hasanuddin, Makassar 90245, Indonesia.
⁴ Department of Pharmacology and Therapy, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.
⁵ Department of Nutrition, Health Polytechnic of Gorontalo, Gorontalo 96135, Indonesia.
⁶ Department of Midwifery, Health Polytechnic of Palangka Raya, Palangka Raya 73111, Indonesia.

Abstract

Introduction: The current incidence of the novel coronavirus disease has shown only small reductions of cases and has become a major public health challenge. Development of effective vaccines against the virus is still being encouraged such as multi-epitope vaccines designed from the components of SARS-CoV-2 including its spike, nucleocapsid and ORF1a proteins. Since the addition of adjuvants including HABA protein and L7/L12 ribosomal are considered helpful to increase the effectiveness of the designed vaccine, we proposed to design multiepitope vaccines by two different adjuvants. Methods: We used the IEDB server to predict BCL and TCL epitopes that were characterized using online tools including VaxiJen, AllPred and IL-10 Prediction. The selected epitopes were further constructed into multiepitope vaccines. We also added two different adjuvants to the vaccine components in order to increase the effectiveness of the vaccines. The 3D-structured vaccines were built using trRosetta. They were further docked with different Toll-like-receptors (TLR 3, 4 and 8) and the entry receptor of SARS-CoV-2, ACE2 using ClusPro, PatchDock and refined by FireDock. All structures were visualized by USCF Chimera and PyMOL. Results: In this study, we succeeded in designing two different candidate vaccines by the addition of HABA protein and L7/L12 ribosomal as adjuvants. The two vaccines were almost equally good in terms of their physicochemical properties and characteristics. Likewise, their strong interactions with TLR3 4, 8 and ACE2 show the lowest energy level of both was estimated at more than -1,000. Interactions of vaccines with ACE2 and TLRs are essential for activation of immune responses and production of antibodies. Conclusion: The two designed and constructed multiepitope vaccine have good characteristics and may have the potential to activate humoral and cellular immune responses against SARS-CoV-2. Further research is worth considering to confirm the findings of this study.

Keywords: ACE2; Immunoinformatics; Multi-epitope vaccine candidate; SARS-COV-2.