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arXiv · 2610.39662

AI-driven structural informatics reveals diverse glycosylation machinery across double-stranded DNA viruses

Lan Na
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Abstract

Glycosylation is widespread in biology and shapes molecular recognition, yet the diversity and biosynthetic organization of viral glycosyltransferases (GTs) remain poorly understood. Here we integrate structural-alphabet-guided searches and structure similarity networks with genomic-neighbourhood and biosynthetic gene cluster embedding analyses to examine viral GT-A proteins. This approach reveals extensive structural diversity overlooked by sequence-based annotation, including previously uncharacterized viral GT lineages. Most strikingly, we identified a jumbo-phage locus encoding five tandem glycosyltransferases alongside hydroxymethyl-pyrimidine biosynthetic and sulfation-associated enzymes, suggesting a previously unrecognized form of viral DNA modification involving a sulfated pentasaccharide. Beyond these examples, predicted saccharide-associated loci span divergent double-stranded DNA viruses, from giant viruses to tailed phages, and occupy multiple regions of the reference biosynthetic landscape. Together, our findings uncover an underappreciated repertoire of virus-encoded glycosylation machinery and suggest that viral glycan biosynthesis encompasses diverse molecular contexts and potential biological functions.

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Lan Na. 2026-10-29. AI-driven structural informatics reveals diverse glycosylation machinery across double-stranded DNA viruses. https://arxiv.org/abs/2610.39662

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