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PreprintCC BYbioRxiv

Programming N-linked glycan composition through de novo protein design

7 more authors
  1. 1University of Washington

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.

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BibTeX
@misc{lunnhalbert2026programming,
  title = {{Programming N-linked glycan composition through de novo protein design}},
  author = {M. C. Lunn-Halbert and J. D. Allen and R. Krishna and A. Manchenko and X. Li and E. D. Lopatto and J. Pinkner and C. Moller and W. Ahern and J. Mendoza and A. Kang and H. Nguyen and E. Joyce and A. Bera and S. J. Hultgren and E. Sokurenko and M. Crispin and D. Baker and N. P. King},
  howpublished = {bioRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.07.757460},
  url = {https://www.biorxiv.org/content/10.64898/2026.10.07.757460v1},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - Programming N-linked glycan composition through de novo protein design
AU  - M. C. Lunn-Halbert
AU  - J. D. Allen
AU  - R. Krishna
AU  - A. Manchenko
AU  - X. Li
AU  - E. D. Lopatto
AU  - J. Pinkner
AU  - C. Moller
AU  - W. Ahern
AU  - J. Mendoza
AU  - A. Kang
AU  - H. Nguyen
AU  - E. Joyce
AU  - A. Bera
AU  - S. J. Hultgren
AU  - E. Sokurenko
AU  - M. Crispin
AU  - D. Baker
AU  - N. P. King
PY  - 2026
DA  - 2026/10/07
PB  - bioRxiv
DO  - 10.64898/2026.10.07.757460
UR  - https://www.biorxiv.org/content/10.64898/2026.10.07.757460v1
AB  - 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.
ER  -