Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 7, 2026

Rapid Glyco-Qualitative Assessment of Recombinant Proteins Using a Fully Automated System
05:19

Rapid Glyco-Qualitative Assessment of Recombinant Proteins Using a Fully Automated System

Published on: June 28, 2024

LeGenD: High-throughput N-glycan profiling using explainable AI and lectin profiling.

Haining Li1, Angelo G Peralta2, Sanne Schoffelen3

  • 1Department of Bioengineering, University of California, San Diego, La Jolla, California, USA.

The Journal of Biological Chemistry
|June 5, 2026
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

High stability double Stokes-Mueller polarimetry under oblique incidence.

Optics express·2026
Same author

Systematic Mapping of Protein Interactions Underlying IL-2 Secretion in Human T Cells.

Analytical chemistry·2026
Same author

Cross-population validation of the TyG-ABSI index as a novel predictor for chronic obstructive pulmonary disease: an integrated analysis using logistic regression and explainable machine learning.

BMC pulmonary medicine·2026
Same author

Folding integrated all-paper photoelectrochemical immunoassay using annealed ZnO for point-of-care detection of ferritin.

Analytica chimica acta·2026
Same author

Early Birds and Thyroid Cancer: Unveiling the Link Between Morningness and Thyroid Cancer Risk Through Mendelian Randomization.

Brain and behavior·2026
Same author

Delineating the Transcriptional and Phenotypic Impact from Biotherapeutic Glycoengineering.

bioRxiv : the preprint server for biology·2026
Same journal

YhbO is a DJ-1 family glyoxalase and α-oxoaldehyde hydratase that confers resistance to reactive carbonyl stress (112).

The Journal of biological chemistry·2026
Same journal

ARMH3 acts as a central scaffold at the Golgi/TGN through interactions with Arl5, GBF1, and PI4KB.

The Journal of biological chemistry·2026
Same journal

PAX8 controls proximal tubule epithelial identity and stress response through epigenetic modification of distal regulatory elements.

The Journal of biological chemistry·2026
Same journal

Saturated cardiolipins are potent disruptors of inner mitochondrial membrane structure and function.

The Journal of biological chemistry·2026
Same journal

Phosphate release from myosin Va occurs after the initial powerstroke but before the secondary powerstroke associated with ADP-release.

The Journal of biological chemistry·2026
Same journal

Epigenetic silencing of miR-141 via core promoter methylation is associated with short-term bladder cancer progression.

The Journal of biological chemistry·2026
See all related articles
This summary is machine-generated.

A new AI platform called LeGenD uses lectin binding to predict N-glycan structures on proteins. This method offers a faster, cost-effective alternative for analyzing protein glycosylation patterns.

Area of Science:

  • Biochemistry
  • Glycobiology
  • Computational Biology

Background:

  • Protein glycosylation is crucial for biological functions, impacting areas from basic research to biopharmaceutical development.
  • Conventional glycan analysis methods face challenges in throughput and cost.
  • Lectins provide glycan epitope information but lack full structural details.

Purpose of the Study:

  • To develop an AI-driven platform, LeGenD, for predicting dominant N-glycan structures and their abundance on proteins.
  • To overcome limitations of existing glycan analysis techniques.

Main Methods:

  • LeGenD integrates lectin-binding patterns with artificial intelligence (AI) to predict N-glycan structures.
  • The model was trained on glycoprofiles from recombinant proteins produced in glycoengineered CHO cell lines.
Keywords:
AIbiotechnologyglycobiologyglycomicsmachine learning

More Related Videos

A Lectin HPLC Method to Enrich Selectively-glycosylated Peptides from Complex Biological Samples
20:23

A Lectin HPLC Method to Enrich Selectively-glycosylated Peptides from Complex Biological Samples

Published on: October 1, 2009

Related Experiment Videos

Last Updated: Jun 7, 2026

Rapid Glyco-Qualitative Assessment of Recombinant Proteins Using a Fully Automated System
05:19

Rapid Glyco-Qualitative Assessment of Recombinant Proteins Using a Fully Automated System

Published on: June 28, 2024

A Lectin HPLC Method to Enrich Selectively-glycosylated Peptides from Complex Biological Samples
20:23

A Lectin HPLC Method to Enrich Selectively-glycosylated Peptides from Complex Biological Samples

Published on: October 1, 2009

  • SHapley Additive exPlanations (SHAP) were used to identify key lectins for prediction.
  • Main Results:

    • LeGenD effectively predicts dominant glycosylation patterns on purified proteins.
    • The approach demonstrated high accuracy on independent test data.
    • Key lectins influencing glycoprofile predictions were identified.

    Conclusions:

    • LeGenD offers a novel, AI-based platform for analyzing protein glycosylation.
    • This approach provides an alternative to conventional methods, potentially complementing existing glycan analysis toolkits.