ArticleAnalytical chemistry2024
Boltzmann Model Predicts Glycan Structures from Lectin Binding.
Article in Analytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- LeGenD: High-throughput N-glycan profiling using explainable AI and lectin profiling.The Journal of biological chemistry · 2026Article
- Article
- LeGenD: determining N-glycoprofiles using an explainable AI-leveraged model with lectin profiling.bioRxiv : the preprint server for biology · 2024Article
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Authors and funding
3 authors.
Funding
Abstract
Glycans are complex oligosaccharides that are involved in many diseases and biological processes. Unfortunately, current methods for determining glycan composition and structure (glycan sequencing) are laborious and require a high level of expertise. Here, we assess the feasibility of sequencing glycans based on their lectin binding fingerprints. By training a Boltzmann model on lectin binding data, we predict the approximate structures of 88 ± 7% of N-glycans and 87 ± 13% of O-glycans in our test set. We show that our model generalizes well to the pharmaceutically relevant case of Chinese hamster ovary (CHO) cell glycans. We also analyze the motif specificity of a wide array of lectins and identify the most and least predictive lectins and glycan features. These results could help streamline glycoprotein research and be of use to anyone using lectins for glycobiology.
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