Authors
Margaret C Lunn-Halbert, Joel D Allen, Rohith Krishna, Anna Manchenko, Xinting Li, Edward D Lopatto, Jerome Pinkner, Carolina Moller, Woody Ahern, Johnny Mendoza, Alex Kang, Hannah Nguyen, Emily Joyce, Asim Bera, Scott J Hultgren, Evgeni Sokurenko, Max Crispin, David Baker, Neil P King
Published in
bioRxiv : the preprint server for biology. Oct 08, 2026. Epub Oct 08, 2026.
Abstract
N-linked glycans are ubiquitous post-translational modifications that mediate diverse biological processes, including cell signaling and adhesion, molecular recognition, and host-pathogen interactions. Despite their importance, N-linked glycans have largely remained beyond the reach of biomolecular design due to a lack of methods capable of jointly modeling glycans and protein structure. Here, we develop a general all-atom computational pipeline for creating de novo glycoproteins in which the amino acid sequence encodes both the location and composition of N-linked glycans. The method uses three-dimensional protein structure to tune glycan accessibility to processing enzymes in the eukaryotic secretory pathway. Systematic increases in steric restriction progressively reduced processing, shifting glycans from heterogeneous complex-type structures toward increasingly underprocessed oligomannose-type species resembling those found on many viral glycoproteins. Despite this programmed restriction, the resulting oligomannose glycans remained accessible for biological recognition, inhibiting uropathogenic Escherichia coli adhesion to human bladder cells and binding mannose-binding lectin. These results establish steric control of N-glycan processing as a genetically encodable design principle and extend computational protein design to functional glycoproteins with programmed composition.
PMID:
42926814
Bibliographic data and abstract were imported from PubMed on 25 Oct 2026.
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