Immunoinformatic Analysis of SARS-CoV-2 Nucleocapsid Protein and Identification of COVID-19 Vaccine Targets
- PMID: 33193414
- PMCID: PMC7655779
- DOI: 10.3389/fimmu.2020.587615
Immunoinformatic Analysis of SARS-CoV-2 Nucleocapsid Protein and Identification of COVID-19 Vaccine Targets
Abstract
COVID-19 is a worldwide emergency; therefore, there is a critical need for foundational knowledge about B and T cell responses to SARS-CoV-2 essential for vaccine development. However, little information is available defining which determinants of SARS-CoV-2 other than the spike glycoprotein are recognized by the host immune system. In this study, we focus on the SARS-CoV-2 nucleocapsid protein as a suitable candidate target for vaccine formulations. Major B and T cell epitopes of the SARS-CoV-2 N protein are predicted and resulting sequences compared with the homolog immunological domains of other coronaviruses that infect human beings. The most dominant of B cell epitope is located between 176-206 amino acids in the SRGGSQASSRSSSRSRNSSRNSTPGSSRGTS sequence. Further, we identify sequences which are predicted to bind multiple common MHC I and MHC II alleles. Most notably there is a region of potential T cell cross-reactivity within the SARS-CoV-2 N protein position 102-110 amino acids that traverses multiple human alpha and betacoronaviruses. Vaccination strategies designed to target these conserved epitope regions could generate immune responses that are cross-reactive across human coronaviruses, with potential to protect or modulate disease. Finally, these predictions can facilitate effective vaccine design against this high priority virus.
Keywords: B cells; Coronavirus Disease 2019; T cells; epitopes; nucleocapsid; severe acute respiratory syndrome coronavirus 2; vaccine.
Copyright © 2020 Oliveira, de Magalhães and Homan.
Figures
References
-
- Dahlke C, Heidepriem J, Kobbe R, Santer R, Koch T, Fathi A, et al. Distinct early IgA profile may determine severity of COVID-19 symptoms: an immunological case series. medRxiv (2020). 10.1101/2020.04.14.20059733 - DOI
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
Research Materials
Miscellaneous
