Computational analysis of the sequence-structure relation in SARS-CoV-2 spike protein using protein contact networks

Abstract

The structure of proteins impacts directly on the function they perform. Mutations in the primary sequence can provoke structural changes with consequent modification of functional properties. SARS-CoV-2 proteins have been extensively studied during the pandemic. This wide dataset, related to sequence and structure, has enabled joint sequence-structure analysis. In this work, we focus on the SARS-CoV-2 S (Spike) protein and the relations between sequence mutations and structure variations, in order to shed light on the structural changes stemming from the position of mutated amino acid residues in three different SARS-CoV-2 strains. We propose the use of protein contact network (PCN) formalism to: (i) obtain a global metric space and compare various molecular entities, (ii) give a structural explanation of the observed phenotype, and (iii) provide context dependent descriptors of single mutations. PCNs have been used to compare sequence and structure of the Alpha, Delta, and Omicron SARS-CoV-2 variants, and we found that omicron has a unique mutational pattern leading to different structural consequences from mutations of other strains. The non-random distribution of changes in network centrality along the chain has allowed to shed light on the structural (and functional) consequences of mutations.

Figure 1

Scheme of the PCN construction on the close conformation of SARS-CoV 2 spike protein (PDB code 6vyb): starting from the structure (upper left). it is possible to compute the distance matrix (lower left), then the adjacency matrix (lower right) and finally the PCN (upper right).

Figure 2

The x-axis of the Figure represents the distance of the sequences while the y-axis the distance of the structures. Each point represents the correlation of a pair sequence/structure. We report the wild type, alpha, delta and omicron variant and three structural conformations open, closed and complex.

Figure 3

The absolute values of eigenvector centrality (EC) variations relative to the three analysed strains are reported as box-plots. In terms of the changes it is evident that the position of Omicron is quite different from that of the other strains. The use of module values is crucial for a statistically significant result (F = 14.03, $p<$ 0.0001).