Understanding how molecules process information and adapt to changes
Official title: Revealing mechanisms of specificity and adaptability in molecular information processing through data-driven models
Funded at University of Chicago · NIH-11092163 · Data updated 2026-11-12
This study is looking at how proteins and antibodies learn to recognize and respond to different signals in our bodies, which could help create better treatments for diseases, especially through improved antibody therapies.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Chicago NIH-funded |
| Lab location | 1 site (Chicago, United States) |
| Project start | August 1, 2023 |
| Project end | May 31, 2028 |
| Funding year | 2025 |
| Award (this year) | $383,622 |
| NIH project number | 5R35GM151211-03 |
| Project ID | NIH-11092163 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for participation or benefit from this research include individuals with conditions that involve antibody responses, such as autoimmune diseases or infections.
✕Less likely to help
Patients with conditions unrelated to molecular signaling or antibody function may not receive any benefit from this research.
What this research studies
This research investigates how molecular systems, such as proteins and antibodies, recognize specific signals among many similar ones and adapt their responses over time. By developing predictive models that incorporate biophysics, information theory, and machine learning, the project aims to uncover the mechanisms behind molecular specificity and adaptability. Patients may benefit from insights gained in this research, particularly in the development of more effective antibody therapies and treatments for various diseases. The research will explore how these molecular systems can change their specificity in response to environmental signals.
Why it matters
Potential benefit: If successful, this research could lead to improved antibody therapies and better treatments for diseases that rely on molecular recognition.
How similar studies have gone: Other research has shown success in using machine learning and biophysical models to understand molecular interactions, indicating that this approach has potential for meaningful advancements.
Where this research is happening
-
University of Chicago
Chicago, United States Active
Researchers
- Principal investigator: Murugan, Arvind — University of Chicago
- Study coordinator: Murugan, Arvind
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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.