Glycosylation and Glycoproteins Research

This paper introduces SweetNet, a graph convolutional neural network for glycan sequence representation, showing it outperforms existing methods and predicts organismal traits and viral glycan-binding.

The paper models a hypo-N-glycosylation disorder in medaka fish, showing reduced N-glycan abundance and retinal degeneration, with mRNA rescue restoring viability.

The paper maps O-glycosylation sites on SARS-CoV-2 spike protein produced in insect and human cells, identifying 25 sites with distinct patterns between ectodomains and RBD.

This paper shows that excessive O-GlcNAcylation causes heart failure and sudden death in mice, while reducing it protects against cardiac stress.

OGP provides a comprehensive repository of O-glycoproteins and a prediction tool to facilitate O-glycosylation studies.

O-GlcNAcAtlas compiles experimentally identified O-GlcNAc sites and proteins, providing a curated database for functional and computational studies.

SugarPy enables glycoproteome analysis without glycan databases, validated on human breast milk and other organisms with uncommon glycans.

O-Pair Search identifies O-glycopeptides and localizes O-glycosites using collision- and electron-based dissociation spectra, improving speed and identification rates.

MSFragger-Glyco improves glycopeptide identification in N- and O-glycoproteomics data, increasing glycoPSMs and revealing new glycan trends.

The paper presents an integrated structural analysis of intestinal mucin MUC2, revealing the shared mechanism of polymer formation for mucosal barriers and blood clotting.

This paper introduces GalNAzMe, a monosaccharide probe that selectively labels O-GalNAc glycosylation in living cells, enabling detailed study of this cancer-relevant modification.

The paper presents two high-resolution structures of human ST6Gal I, one unliganded and one with CMP-Neu5Ac bound, revealing structural flexibility and substrate binding details.

This paper identifies two novel O-glycosylation modifications on bacterial flagellins catalyzed by Maf glycosyltransferases in Geobacillus kaustophilus and Clostridium botulinum.

GlypNirO automates quantitative glycoproteomic analysis by integrating Byonic and Proteome Discoverer outputs, identifying glycosylation changes in hepatocellular carcinoma as potential biomarkers.

The paper uses mass spectrometry to analyze post-translational modifications and glycans of SARS-CoV-2 spike protein and hACE2, revealing structural details relevant to virus-host interactions and vaccine development.

The paper identifies sialylation changes in mouse sperm during capacitation, showing that sialylation of ACO2 inhibits its activity, potentially driving the metabolic switch from oxidative phosphorylation to glycolysis.

The paper introduces GlyConnect Compozitor, a tool for visualizing and comparing glycan compositions to aid in selecting appropriate compositions for glycoproteomics analysis.

The paper evaluates normalization methods for glycomics data by assessing how well they enable accurate reconstruction of known glycosylation pathway reactions using Gaussian Graphical Models.

The paper resolves the paradox of glycan microheterogeneity by developing algorithmic compartments that convert inputs to unique outputs, and applies this to real glycan datasets.

This study investigates the role of ST3GAL4 in the interaction between Lassa virus GP-C and human LAMP1, identifying sialylated glycans as mediators of viral entry.

This study identifies site-specific changes in sialylation of N-linked glycoproteins in rat nerve terminals following brief depolarization.

The paper identifies off-target glycans formed during the engineering of Pichia pastoris to produce humanized N-glycans, highlighting challenges in achieving precise glycosylation control.

The paper introduces a method to chemically tag glycans in living cells using engineered glycosyltransferases to study glycan structure and biosynthesis.

The paper analyzes N-linked glycosylation sites in human glycoproteins and finds they are more prevalent in ordered regions than disordered regions, suggesting a functional trade-off between protein stability and flexibility.

The paper uses evolutionary analysis of GT-A fold sequences to identify core components and hypervariable loops contributing to catalytic diversity, and develops a machine learning classifier for donor specificity prediction.

The paper predicts O-glycosylation and phosphorylation sites on SARS-CoV-2 S1 protein to identify potential targets for inhibiting initial host cell binding.

This study investigates N-glycan biosynthesis in the dinoflagellate Breviolum minutum and shows that inhibiting Golgi processing reduces its colonization of the sea anemone Aiptasia.

The paper introduces a chemoenzymatic method to quantitatively analyze N-glycan types on glycoproteins, demonstrating its application in characterizing glycan heterogeneity in IgG1 and MCF7 cells.

The paper introduces a cell-free platform for assembling protein glycosylation pathways and demonstrates its use in creating vaccine proteins and antibody constant regions with specific glycan motifs.