Insights on the evolution of Coronavirinae in general, and SARS-CoV-2 in particular, through innovative biocomputational resources

Abstract

The structural proteins of coronaviruses portray critical information to address issues of classification, assembly constraints, and evolutionary pathways involving host shifts. We compiled 173 complete protein sequences from isolates belonging to the four genera of the subfamily Coronavirinae. We calculate a single matrix of viral distance as a linear combination of protein distances. The minimum spanning tree (MST) connecting the individuals captures the structure of their similarities. The MST re-capitulates the known phylogeny of Coronovirinae. Hosts were mapped onto the MST and we found a non-trivial concordance between host phylogeny and viral proteomic distance. We also study the chimerism in our dataset through computational simulations. We found evidence that structural units coming from loosely related hosts hardly give rise to feasible chimeras in nature. This work offers a fresh way to analyze features of SARS-CoV-2 and related viruses.