In-silico prediction of B and T cell epitopes for the design of SARS-COV-2 immune surveillance tools and multi-subunit vaccines

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ABSTRACT

  • 1Mojadibe ET,
  • 2Malabi R ,
  • 3Selabe SG ,
  • 4Mampeule N ,
  • 5Sibiya M ,
  • 6Gededzha MP
  • 1Department of Virology, School of Medicine, Sefako Makgatho Health Sciences University
  • 2Centre for Nanostructures and Advanced Materials, Council for Scientific and Industrial Research, Pretoria
  • 3National Health Laboratory Services, Pretoria, South Africa.
  • 4Department of Immunology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
  • 5National Health Laboratory Services, Johannesburg, South Africa
  • 6Department of Virology, School of Medicine, Sefako Makgatho Health Sciences University

Background

The COVID-19 pandemic has necessitated the development of effective vaccines that address the genetic diversity of SARS-CoV-2 and its variants. Despite global vaccine rollout, disparities persist in protection against emerging variants, partly due to limited representation of genetically diverse populations, such as those in Africa. This study aims to bridge this gap by predicting B and T cell epitopes from SARS-CoV-2 that are both conserved across variants and compatible with HLA class I and II alleles in South African populations, aiming to support future vaccine design and immune surveillance tools to use in limited resource settings.

Method

Complete SARS-CoV-2 genome sequences from South Africa were downloaded from the GISAID database. Epitope predictions were conducted using NetMHCpan4.1, NetMHCIIpan4.0, and ABCpred, with further evaluation of antigenicity, immunogenicity, toxicity, and conservancy using VaxiJen, ToxinPred, and IEDB tools. Conservancy analysis across Alpha, Beta, Delta, and Omicron variants was performed to identify highly conserved epitopes. Predicted epitopes were assessed for binding affinity with HLA class I and II alleles reported in South Africa.

Result

The study identified highly conserved epitopes, particularly from ORF1ab and structural proteins, with strong antigenic and immunogenic properties. Epitopes such as YQPYRVVL (S protein) demonstrated high binding affinities to multiple HLA alleles. Accessory proteins like ORF3a also presented promising epitope candidates. Predicted epitopes were conserved across major variants.

Conclusion

This study highlights the importance of utilizing bioinformatics in identifying conserved and immunogenic SARS-CoV-2 epitopes with potential use in both vaccine development and diagnostic tool innovation. In resource-limited settings, such bioinformatics-guided strategies can help bridge diagnostic and immunological gaps, enabling region-specific immune profiling and guiding targeted public health responses. These findings will assist in the future development of multi-epitope diagnostics and vaccines tailored to African populations.
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PRESENTING AUTHOR

Mr. Edmond Mojadibe, BSc honours (Medical Sciences) Medical Virology

Student, Sefako Makgatho Health Sciences University (SMU)

Edmond Mojadibe is an MSc candidate with research focused on respiratory viral infections. As he continues to develop his expertise, he is driven by a desire to contribute to impactful research by engaging in collaborative scientific initiatives and pursuing innovative solutions that address pressing virological and immunological challenges.
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