Authors
Yu Liu, Saskia Pieters, Ganka Bineva-Todd, Mert Sagiroglugil, Sean A Burnap, Freya Hoddle, Anna Cioce, Andre Ohara, Sophie D Schmidt, Kevin Bruemmer, Carolyn R Bertozzi, Karen Polizzi, Weston B Struwe, Carme Rovira, Benjamin Schumann
Published in
Journal of the American Chemical Society. Jun 30, 2026. Epub Jun 30, 2026.
Abstract
Asparagine-linked protein glycosylation is among the most frequent modifications of proteins trafficking through the secretory pathway. These glycans are manufactured in an assembly line process, yielding a common precursor that is then subjected to individual modifications with different levels of complexity. An important biosynthetic modulator is the incorporation of N-acetylglucosamine (GlcNAc) at distinct positions in N-linked glycan biosynthesis, commencing with the activity of the glycosyltransferase MGAT1. While mapping of N-glycans to their corresponding protein attachment sites is generally possible, not much is known about the glycoprotein substrate choice for MGAT1 and related transferases. Analogs of GlcNAc with small bioorthogonal tags can be incorporated into N-glycans. However, due to the promiscuity of some GlcNAc transferases, incorporation is of little specificity toward individual positions. Here, we report an iterative bump-and-hole approach for the design of a bioorthogonal precision tool to study the activity of MGAT1 in mammalian cells. Structure-informed protein engineering abrogated the activity of MGAT1 toward the nucleotide-sugar UDP-GlcNAc while retaining activity toward bumped, azide-modified analogs. Kinetic and computational analyses using a neural network approach informed the synthesis of a tailored UDP-GlcNAc analog with preferential acceptance by the engineered enzyme. Following substrate biosynthesis, the strategy allowed selective incorporation of a chemical tag on MGAT1 substrate proteins in living mammalian cells with little background incorporation by other GlcNAc transferases. Our work expands the toolbox for glycan-based reporter compounds.
PMID:
42378460
Bibliographic data and abstract were imported from PubMed on 01 Jul 2026.
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