High-precision glycan detectors using AI to spot disease-linked sugars
Official title: Rational design of high-specificity diagnostic reagents for detecting pathogenic glycoforms of aGal and NeuGc using AI/ML and multiscale modeling
Funded at University of Mississippi · NIH-11570017 · Data updated 2026-11-12
A grant to develop AI-guided, highly specific tools that detect disease-related glycans (áGal and NeuGc) in human samples to improve diagnostics and safe biologic therapies.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Mississippi NIH-funded |
| Lab location | 1 site (University, United States) |
| Project start | June 1, 2026 |
| Project end | May 31, 2030 |
| Funding year | 2026 |
| Award (this year) | $182,755 |
| NIH project number | 5P20GM130460-07 |
| Project ID | NIH-11570017 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are individuals at risk for red meat allergy or cancers where áGal and NeuGc glycoforms are relevant biomarkers, as well as patients who would benefit from improved diagnostic tests.
✕Less likely to help
Patients without conditions linked to áGal or NeuGc detection may not directly benefit from these reagents.
What this research studies
This project uses artificial intelligence and multiscale modeling to design reagents that bind very specifically to two glycans linked to disease and allergy. Researchers will map interaction energies to find where binding can be strongest, train a deep-learning model to create cyclic peptide binders with very high affinity, and adapt natural lectins for practical sensing. The work aims to produce reagents that are both sensitive and selective for áGal and NeuGc, improving diagnostic accuracy and patient safety. The outcomes could lead to better tests for red meat allergy and cancer-related glycan changes, with potential translation into clinical diagnostics. The study emphasizes iterative design, validation, and miniaturization to enable real-world diagnostic use.
Why it matters
Potential benefit: If successful, patients could benefit from more accurate, earlier, and safer diagnostics for allergies and glycan-related diseases.
How similar studies have gone: Previous work has shown promise in glycan detection with engineered binders, but this project advances toward nanomolar affinity and AI-guided design for higher specificity.
Where this research is happening
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University of Mississippi
University, United States Active
Researchers
- Principal investigator: Mishra, Sushil K — University of Mississippi
- Study coordinator: Mishra, Sushil K
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.