A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2

By Alba Grifoni, John Sidney, Yun Zhang, Richard H. Scheuermann, Bjoern Peters, Alessandro Sette. Cell Host and Microbe, 2020

923 citations recorded by the source corpus.

Summary Effective countermeasures against the recent emergence and rapid expansion of the 2019 novel coronavirus (SARS-CoV-2) require the development of data and tools to understand and monitor its spread and immune responses to it. However, little information is available about the targets of immune responses to SARS-CoV-2. We used the Immune Epitope Database and Analysis Resource (IEDB) to catalog available data related to other coronaviruses. This includes SARS-CoV, which has high sequence similarity to SARS-CoV-2 and is the best-characterized coronavirus in terms of epitope responses. We identified multiple specific regions in SARS-CoV-2 that have high homology to the SARS-CoV virus. Parallel bioinformatic predictions identified a priori potential B and T cell epitopes for SARS-CoV-2. The independent identification of the same regions using two approaches reflects the high probability that these regions are promising targets for immune recognition of SARS-CoV-2. These predictions can facilitate effective vaccine design against this virus of high priority.

Subfields: Immunology, Infectious Diseases, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/28074a84a732f3f7de5a0bc9a8efa267cfb5b6eb

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Citations in the corpus

Two linear epitopes on the SARS-CoV-2 spike protein that elicit neutralising antibodies in COVID-19 patients (2020, background): “Six patients (2, 5, 6, 7, 8, 9) with sufficient amount of sera and good neutralising capacity were then selected for further characterisation.”
Emergence of genomic diversity and recurrent mutations in SARS-CoV-2 (2020, positive): “Interestingly, this region overlaps a putative immunogenic peptide predicted to result in both CD4+ and CD8+ T-cell reactivity (37).”
COVID-19 coronavirus vaccine design using reverse vaccinology and machine learning (2020, methodology): “SARS-CoV-2 were computationally predicted and evaluated by sequence homology analysis of SARS-CoV and MERS-CoV epitopes (48).”
Immunology of COVID-19: Current State of the Science (2020, positive): “Researchers have taken advantage of the genetic similarity between SARS-CoV-2 and SARS-CoV-1 and MERS-CoV and bioinformatics approaches to rapidly identify B and T cell potential epitopes in the S and other proteins, with many studies providing data regarding antigen presentation and antibody bindin”
Phenotype and kinetics of SARS-CoV-2-specific T cells in COVID-19 patients with acute respiratory distress syndrome (2020, methodology): “Here, we stimulated peripheral blood mononuclear cells (PBMC) from ten COVID-19 patients with ARDS, collected up to three weeks after admission to the intensive care unit (ICU), with MegaPools (MP) of overlapping or predictionbased peptides covering the SARS-CoV-2 proteome (11).”
Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals (2020, positive): “Two class I MPs were synthesized based on epitope predictions for those 12 most common HLA A and B alleles (Grifoni et al., 2020), which collectively encompass 628 predicted HLA class I CD8 T cell epitopes from the entire SARS-CoV-2 proteome (CD8 MP-A and MP-B).”