A rigorous framework for detecting SARS-CoV-2 spike protein mutational ensemble from genomic and structural features (preprint)

ABSTRACT

The recent release of SARS-CoV-2 genomic data from several countries has provided clues into the potential antigenic drift of the coronavirus population. In particular, the genomic instability observed in the spike protein necessitates immediate action and further exploration in the context of viral-host interactions. Here we dynamically track 3,11,795 genome sequences of spike protein, which comprises 2,584 protein mutations. We reveal mutational genomic ensemble at different timing and geographies, that evolves on four distinct residues. In addition to the well-established N501 mutational cluster, we detect the presence of three novel clusters, namely A222, N439, and S477. The robust examination of structural features from 44 known cryo-EM structures showed that the virus is deploying many mutations within these clusters on structurally heterogeneous regions. One such dominant variant D614G was also simulated using molecular dynamics simulations and, as compared to wild-type, we found higher stability with human ACE2 receptor. There is also a significant overlap of mutational clusters on known epitopes, indicating putative interference with antibody binding. Thus, we propose that the resulting coaxility of mutational clusters is the most efficient feature of SARS-CoV-2 evolution and provides precise mutant combinations that can enable future vaccine re-positioning.