Glycosylation and Glycoproteins Research

This paper introduces GlycoQL, a query language for glycan structure search, and demonstrates its use in analyzing SARS-CoV-2 spike protein glycosylation.

The paper develops sialoglycan-recognizing probes (SGRPs) to systematically study mammalian sialoglycome dynamics using established laboratory techniques.

This paper identifies JiangShi (JS), a Mucin-like protein in Drosophila, and shows its essential role in development through loss and over-production studies.

The paper shows that specific N-glycans regulate an extracellular adhesion complex involved in somatosensory dendrite patterning in C. elegans.

The paper identifies increased fucosylation patterns in saliva glycoproteins of lung cancer patients, suggesting potential for early diagnosis of lung adenocarcinoma.

CarboGrove integrates and analyzes glycan-array data from multiple sources to provide insights into glycan-binding specificities and support experimental and computational research.

The paper identifies genetic loci regulating glycosylation of transferrin and IgG, finding both shared and protein-specific associations and proposing tissue-specific transcription factor regulation.

This study shows that the schizophrenia-associated SLC39A8 variant A391T alters N-glycosylation in the mouse brain, affecting glycoproteins involved in schizophrenia-related pathways.

The paper introduces a method to accurately identify glycan compositions in glycopeptide spectra and control false discovery rates, integrating it into a computational pipeline for glycoproteomics analysis.

The paper analyzes glycosylation patterns in mouse brain regions and sexes, finding reduced complexity and minimal sex differences compared to plasma.

GlyNet predicts protein-glycan interactions with continuous relative binding strengths, outperforming classifiers and serving as a benchmark for quantitative glycobiology.

LectinOracle predicts lectin-glycan interactions using deep learning, showing agreement with literature and generalizing to new glycans and lectins.

GproDIA improves glycoproteomics by enabling accurate glycopeptide identification and quantification using DIA data with comprehensive statistical control.

This study identifies global determinants of lectin specificity by analyzing 221 physicochemical and geometric features of lectin-glycan interactions and demonstrates predictive modeling of glycan recognition.

This paper introduces a method to construct and analyze neoglycoproteins by systematically modifying glycosylation sites in proteins and assessing the effects of glycan addition.

This study analyzes fucose-containing glycan motifs across taxonomic kingdoms, identifying differences in fucose usage and its role in molecular mimicry and biological processes.

The paper shows that increased neuronal excitation leads to the formation of Golgi satellites in dendrites, which modify surface glycoproteins and impact neurotransmitter receptor function.

This study identifies elevated paucimannosidic and truncated N-glycans in the microbiota of pediatric ulcerative colitis patients compared to controls, suggesting a potential role for glycan metabolism in disease pathogenesis.

This paper introduces a mass binning glycoproteomics approach to explore prokaryotic protein glycosylation, revealing unique surface layer modulation in an anammox bacterium.

This paper predicts tissue-specific transcription factors and signaling pathways regulating glycan biosynthesis using multi-omics data across 29 cancer types.

This paper describes a workflow to improve glycan data interoperability between ChEBI, PubChem, and GlyGen by integrating and prioritizing glycan annotations.

Glycowork is a Python package for glycan data science and machine learning, offering tools for annotation, visualization, and analysis of glycan data.

The paper studies how two antibodies recognize the glycan antigen CA19-9 using crystallography and computational methods to improve antibody affinity.

The paper surveys fungal lectins through phylogenetic analysis and bioinformatics, identifying 33,485 putative lectin sequences across 1,223 fungal species.

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.