Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools

Marek Prachar,Daniel Bisgaard Steen-Jensen,Stephan Thorgrimsen,Frederik Otzen Bagger,Ole Winther,Erik Jurgons,Sune Justesen

doi:10.1038/s41598-020-77466-4

Abstract

The outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune response that leads to protection is highly dependent on presentation of epitopes to circulating T-cells via the HLA complex. SARS-CoV-2 is a large RNA virus and testing of all of its overlapping peptides in vitro to deconvolute an immune response is not feasible. Therefore HLA-binding prediction tools are often used to narrow down the number of peptides to test. We tested NetMHC suite tools' predictions by using an in vitro peptide-MHC stability assay. We assessed 777 peptides that were predicted to be good binders across 11 MHC alleles in a complex-stability assay and tested a selection of 19 epitope-HLA-binding prediction tools against the assay. In this investigation of potential SARS-CoV-2 epitopes we found that current prediction tools vary in performance when assessing binding stability, and they are highly dependent on the MHC allele in question. Designing a COVID-19 vaccine where only a few epitope targets are included is therefore a very challenging task. Here, we present 174 SARS-CoV-2 epitopes with high prediction binding scores, validated to bind stably to 11 HLA alleles. Our findings may contribute to the design of an efficacious vaccine against COVID-19.

Highlights

2019-nCoV (SARS-CoV-2) was first reported in Wuhan, China, on 31 December 2019, following a series of unexplained pneumonia cases[1]
To assess whether current peptide-HLA prediction tools could be suitable for identification of epitopes relevant in a vaccine against SARS-CoV-2, we tested binders predicted by the netMHC tools, using a new peptideMHC complex-stability assay NeoScreen on ten HLA class I alleles and one HLA class II allele
The overlap with peptides deposited in Immune Epitope Database (IEDB) clearly points out to cross-reactivity between SARS-CoV and SARS-CoV-2, this cross-reactivity has been described in a recent study showing that individuals infected with SARS retained long-lasting memory T cells reacting to the N protein of SARS-CoV, as well as N protein of SARS-CoV-240

Summary

Introduction

2019-nCoV (SARS-CoV-2) was first reported in Wuhan, China, on 31 December 2019, following a series of unexplained pneumonia cases[1]. Immune deconvolution to identify T cell epitopes will require initial filtering to assess which SARS-CoV-2-derived peptides are likely to bind a given HLA allele and to be presented on the surface of infected cells from where it can activate passing T cells. Several computational tools (a selection is presented in Table 1) have been developed that can predict the binding of peptides to HLA. These tools were trained using data from affinity assays[8], but more. Several tools are restricted in terms of which alleles are available for prediction, in particular for MHC class II This restriction is primarily determined by the availability of training data, for which the largest public collection is currently the Immune Epitope Database (IEDB)[13]. Most of the selected tools are periodically tested in the IEDB Automated Benchmark[35,36]

Methods

Results

Conclusion