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New Article in Scientific Reports:
Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools
We are delighted to announce that our latest research on COVID-19 vaccine candidate epitopes has just been published in Scientific Reports. In the article, we demonstrate that common peptide-MHC prediction tools vary dramatically in performance depending on the predicted allele.
The study reveals low performance for common prediction tools when benchmarked on the SARS-CoV-2 peptides assessed in our in vitro complex-stability platform. During the study, we identified 174 peptide epitopes, some of which have been either previously or recently deposited in the IEDB, showing the cross-reactivity between SARS-CoV and SARS-CoV-2.
The study was undertaken in collaboration with researchers at University of Copenhagen (Denmark), Copenhagen University Hospital (Denmark) and Intavis (Germany).
Study Workflow
We started out by translating the SARS-CoV-2 genome sequence to proteins, and we then used NetMHC suite tools to predict potential epitopes. We validated those candidates on our in vitro peptide-MHC stability assay platform, NeoScreen. In total, we assessed 777 viral peptides over 10 HLA class I alleles and 1 HLA class II allele.
We found 174 peptides that formed a stable complex with HLA, 98 of which were previously measured and deposited in IEDB either as 9-mers or as a substring of a longer peptide, 3 peptides were reported in recent studies but not deposited in the IEDB and the 73 remaining peptides are novel. We subsequently compared the performance of 19 peptide-MHC prediction tools using our measured data.
