nCoV

nCoV identifies candidate B- and T-cell epitopes in 2019-nCoV by leveraging the Immune Epitope Database and Analysis Resource (IEDB) and comparative homology with SARS-CoV to inform immune-target discovery.

Key Features:

• IEDB integration: Catalogs available epitope-related data from the Immune Epitope Database and Analysis Resource (IEDB).
• Comparative coronavirus data: Uses epitope data from other coronaviruses, particularly SARS-CoV, to inform analyses of 2019-nCoV.
• Homology-based region identification: Identifies specific regions in 2019-nCoV that are highly homologous to SARS-CoV sequences.
• Parallel prediction methods: Employs parallel bioinformatics prediction approaches to identify potential B- and T-cell epitopes.
• Convergence assessment: Evaluates convergence of independent methodologies to prioritize regions likely to serve as immune targets.

Scientific Applications:

• Vaccine candidate guidance: Informs selection of candidate epitopes for vaccine design against 2019-nCoV.
• Diagnostic target identification: Guides identification of epitope regions that may serve as diagnostic targets for COVID-19.
• Immune response characterization: Aids research into human B- and T-cell immune recognition of 2019-nCoV through comparative and predictive analyses.

Methodology:

Cataloging of IEDB epitope data from related coronaviruses (particularly SARS-CoV), comparative homology analysis to identify conserved regions in 2019-nCoV, and parallel bioinformatics predictions of B- and T-cell epitopes with assessment of result convergence.