ArticleChem2021
Mucin-mimetic glycan arrays integrating machine learning for analyzing receptor pattern recognition by influenza A viruses.
Article in Chem, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed, 19 citations in OpenAlex.
- Molecularly Defined Glycocalyx Models Reveal ABJACS Au · 2025Article
- Phenylboronic Acid-Modified Polyethyleneimine: A Glycan-Targeting Anti-Biofilm Polymer for Inhibiting Bacterial Adhesion to Mucin and Enhancing Antibiotic Efficacy.ACS applied materials & interfaces · 2025Article
- The dawn of biophysical representations in computational immunology.QRB discovery · 2025Review
- Infection and the Glycome─New Insights into Host Response.ACS infectious diseases · 2024Review
- Significance of Artificial Intelligence in the Study of Virus-Host Cell Interactions.Biomolecules · 2024Review
- LeGenD: determining N-glycoprofiles using an explainable AI-leveraged model with lectin profiling.bioRxiv : the preprint server for biology · 2024Article
- Serum antibody screening using glycan arrays.Chemical Society reviews · 2024Review
- Article
- Article
- Application of bioanalytical and computational methods in decoding the roles of glycans in host-pathogen interactions.Current opinion in chemical biology · 2023Review
- Measuring the multifaceted roles of mucin-domain glycoproteins in cancer.Advances in cancer research · 2023Review
- Synthesis and biomedical applications of mucin mimic materials.Advanced drug delivery reviews · 2022Review
- LectinOracle: A Generalizable Deep Learning Model for Lectin-Glycan Binding Prediction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
Influenza A viruses (IAVs) exploit host glycans in airway mucosa for entry and infection. Detection of changes in IAV glycan-binding phenotype can provide early indication of transmissibility and infection potential. While zoonotic viruses are monitored for mutations, the influence of host glycan presentation on viral specificity remains obscured. Here, we describe an array platform which uses synthetic mimetics of mucin glycoproteins to model how receptor presentation and density in the mucinous glycocalyx may impact IAV recognition. H1N1 and H3N2 binding in arrays of α2,3- and α2,6-sialyllactose receptors confirmed their known sialic acid-binding specificities and revealed their different sensitivities to receptor presentation. Further, the transition of H1N1 from avian to mammalian cell culture improved the ability of the virus to recognize mucin-like displays of α2,6-sialic acid receptors. Support vector machine (SVM) learning efficiently characterized this shift in binding preference and may prove useful to study viral evolution to a new host.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.