How cell enzymes called kinases change shape to control activity
Official title: Multiscale Modeling of Protein Kinase Structure, Catalysis and Allostery
Funded at University of Texas Arlington · NIH-11298330 · Data updated 2026-11-12
This work uses computer modeling, machine learning, and lab experiments to learn how protein kinases change shape and control cell signals, which could help people with cancers and metabolic disorders.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Texas Arlington NIH-funded |
| Lab location | 1 site (Arlington, United States) |
| Project start | September 15, 2019 |
| Project end | December 31, 2029 |
| Funding year | 2026 |
| Award (this year) | $341,712 |
| NIH project number | 2R01GM132481-05A1 |
| Project ID | NIH-11298330 on NIH RePORTER |
Who could benefit from this research
✓Could help
People with cancers, insulin resistance/diabetes, or other conditions tied to abnormal kinase signaling could ultimately benefit from therapies informed by this research.
✕Less likely to help
Patients whose conditions are unrelated to kinase signaling or do not involve these pathways are unlikely to see direct benefit from this specific work.
What this research studies
Researchers combine large-scale computer simulations with machine learning and targeted laboratory experiments to map the movements and regulatory switches of protein kinases such as AKT and AMP kinase. The team will connect small-scale chemical events at active sites to larger protein shape changes to show how dynamics tune enzyme activity. Experimental validation will be used alongside simulations to ensure the predicted mechanisms reflect real molecules. Findings aim to highlight precise regulatory sites that could guide development of better, more selective kinase-targeting therapies.
Why it matters
Potential benefit: If successful, this work could reveal new molecular targets and strategies for designing drugs that more precisely modulate kinase activity, potentially improving treatments for cancers, diabetes, and other kinase-linked diseases.
How similar studies have gone: Related computational and experimental studies have improved understanding of kinases, but this integrated multiscale simulation plus machine-learning approach to allostery is relatively novel.
Where this research is happening
-
University of Texas Arlington
Arlington, United States Active
Researchers
- Principal investigator: Nam, Kwangho — University of Texas Arlington
- Study coordinator: Nam, Kwangho
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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.