The functional evolution of ACE2 receptor binding of Betacoronaviruses in the past, present, and uncertain future

Abstract

Comparative functional analysis of the dynamic interactions between various Betacoronavirus mutant strains and broadly utilized target proteins, is crucial for a more complete understanding of zoonotic spillovers of viruses that cause COVID-19. Here, we employ machine learning to replicate sets of nanosecond scale GPU accelerated molecular dynamics simulations to statistically compare and classify atom motions of these target proteins in both the presence and absence of different endemic and emergent strains of the viral receptor binding domain of the S spike glycoprotein.