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ABSTRACT The genomic deluge has pushed viral molecular evolution into a site-resolved era. For antigenically evolving viruses such as influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), dense genomic sampling now supports mutation-annotated phylogenies and per-site estimates of mutation and substitution processes. These data highlight strong effects of sequence context, genomic region, RNA structure, and protein-level constraints that are blurred by classic uniform substitution models. In parallel, accurate structure prediction and emerging structure-aware phylogenetic and machine-learning approaches provide practical ways to map mutations onto three-dimensional constraints, identify structurally plausible escape routes, and interpret evolutionary rate variation through solvent exposure, packing, stability, glycosylation, receptor-binding interfaces, and epitope geometry. Finally, antigenic cartography translates some forms of genetic change into an epidemiologically meaningful phenotype—antigenic distance—while predictive modeling increasingly enables sequence-to-antigenicity inference for variants that have not yet been tested experimentally. Here, we outline a practical framework linking sites, structure, and serology for viruses in which antigenic evolution is a major component of immune escape and lineage turnover; highlight why genetic and antigenic “clocks” can diverge; and discuss how integrating genomic surveillance data, phylogenetics, structural analysis, and predictive modeling could support more prospective variant assessment and improved vaccine and therapeutic design.
Översti et al. (Thu,) studied this question.