Impact of glycan cloud on the B-cell epitope prediction of SARS-CoV-2 Spike protein

Abstract

The SARS-CoV-2 outbreak originated in China in late 2019 and has since spread to pandemic proportions. Diagnostics, therapeutics and vaccines are urgently needed. We model the trimeric Spike protein, including flexible loops and all N-glycosylation sites, in order to elucidate accessible epitopes for antibody-based diagnostics, therapeutics and vaccine development. Based on published experimental data, six homogeneous glycosylation patterns and two heterogeneous ones were used for the analysis. The glycan chains alter the accessible surface areas on the S-protein, impeding antibody-antigen recognition. In presence of glycan, epitopes on the S1 subunit, that notably contains the receptor binding domain, remain mostly accessible to antibodies while those present on the S2 subunit are predominantly inaccessible. We identify 28 B-cell epitopes in the Spike structure and group them as non-affected by the glycan cloud versus those which are strongly masked by the glycan cloud, resulting in a list of favourable epitopes as targets for vaccine development, antibody-based therapy and diagnostics.