Identifying and profiling structural similarities between Spike of SARS-CoV-2 and other viral or host proteins with Machaon

Abstract

Using protein structure to predict function, interactions, and evolutionary history is still an open challenge, with existing approaches relying extensively on protein homology and families. Here, we present Machaon, a new data-driven method combining orientation invariant metrics on phi-psi angles, inter-residue contacts and surface complexity. It can be readily applied on whole structures or segments—such as domains and binding sites. Machaon was applied on SARS-CoV-2 Spike monomers of native, Delta and Omicron variants and identified correlations with a wide range of viral proteins from close to distant taxonomy ranks, as well as host receptors, such as ACE2. The associated whole structures have: 32.7% and 38.5% sequence identities on protein secondary structure and gene coding region, 86% chemical and 22.1% protein tertiary structure similarities (median values, native Spike). Machaon’s meta-analysis revealed Spike’s relationships with biological processes such as ubiquitination and angiogenesis and highlighted different patterns in virus attachment among the studied variants. Available at: https://github.com/anastasiadoulab/machaon .