Immunodominant regions prediction of nucleocapsid protein for SARS-CoV-2 early diagnosis: a bioinformatics and immunoinformatics study

Yufeng Dai, Hongzhi Chen, Siqi Zhuang, Xiaojing Feng, Yiyuan Fang, Haoneng Tang, Ruchun Dai, Lingli Tang, Jun Liu, Tianmin Ma, Guangming Zhong

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

COVID-19 caused by SARS-CoV-2 is sweeping the world and posing serious health problems. Rapid and accurate detection along with timely isolation is the key to control the epidemic. Nucleic acid test and antibody-detection have been applied in the diagnosis of COVID-19, while both have their limitations. Comparatively, direct detection of viral antigens in clinical specimens is highly valuable for the early diagnosis of SARS-CoV-2. The nucleocapsid (N) protein is one of the predominantly expressed proteins with high immunogenicity during the early stages of infection. Here, we applied multiple bioinformatics servers to forecast the potential immunodominant regions derived from the N protein of SARS-CoV-2. Since the high homology of N protein between SARS-CoV-2 and SARS-CoV, we attempted to leverage existing SARS-CoV immunological studies to develop SARS-CoV-2 diagnostic antibodies. Finally, N229-269, N349-399, and N405-419 were predicted to be the potential immunodominant regions, which contain both predicted linear B-cell epitopes and murine MHC class II binding epitopes. These three regions exhibited good surface accessibility and hydrophilicity. All were forecasted to be non-allergen and non-toxic. The final construct was built based on the bioinformatics analysis, which could help to develop an antigen-capture system for the early diagnosis of SARS-CoV-2.

Original languageEnglish (US)
Pages (from-to)463-470
Number of pages8
JournalPathogens and Global Health
Volume114
Issue number8
DOIs
StatePublished - 2020

Keywords

  • COVID-19
  • SARS-CoV-2
  • antigen-capture diagnostics
  • linear B-cell epitopes
  • nucleocapsid protein

ASJC Scopus subject areas

  • Parasitology
  • Microbiology
  • Public Health, Environmental and Occupational Health
  • Infectious Diseases

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