Objectives: the Covid-19 pandemic has been marked by sudden outbreaks of SARS-CoV-2 variants harboring mutations in both the N-terminal (NTD) and receptor binding (RBD) domains of the spike protein. The goal of this study was to predict the transmissibility of SARS-CoV-2 variants from genomic sequence data.

Methods: we used a target-based molecular modeling strategy combined with surface potential analysis of the NTD and RBD.

Results: we observed that both domains act synergistically to ensure optimal virus adhesion, which explains why most variants exhibit concomitant mutations in the RBD and in the NTD. Some mutation patterns affect the affinity of the spike protein for ACE-2. However, other patterns increase the electropositive surface of the spike, with determinant effects on the kinetics of virus adhesion to lipid raft gangliosides. Based on this new view of the structural dynamics of SARS-CoV-2 variants, we defined an index of transmissibility (T-index) calculated from kinetic and affinity parameters of coronavirus binding to host cells. The T-index is characteristic of each variant and predictive of its dissemination in animal and human populations.

Conclusions: the T-index can be used as a health monitoring strategy to anticipate future Covid-19 outbreaks due to the emergence of variants of concern.