How changes in proteins can cause disease and drug resistance
Official title: Unraveling molecular and system-level mechanisms of human disease-associated protein mutations
Funded at Texas Engineering Experiment Station · NIH-11172452 · Data updated 2026-11-12
This project uses computer models, machine learning, and lab experiments to link protein-changing genetic variants to disease and treatment resistance for people with genetic conditions.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Texas Engineering Experiment Station NIH-funded |
| Lab location | 1 site (College Station, United States) |
| Project start | September 15, 2017 |
| Project end | August 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $396,002 |
| NIH project number | 5R35GM124952-07 |
| Project ID | NIH-11172452 on NIH RePORTER |
Who could benefit from this research
✓Could help
People with known or suspected protein-altering genetic variants, or those whose disease or drug resistance may be linked to such mutations, would be the most relevant candidates.
✕Less likely to help
Patients whose conditions are not related to genetic protein changes or who lack relevant genomic data are unlikely to see direct benefit from this work.
What this research studies
If you have a genetic condition, this work aims to trace how a single change in a protein can ripple through atoms, molecules, and cells to cause disease or make drugs stop working. The team combines physics-based protein design, large biobank genetic and health data, and machine learning to predict which mutations matter. Promising predictions will be tested in the lab to build clearer cause-and-effect links. The long-term goal is to turn those mechanistic insights into better diagnostics and targeted therapies.
Why it matters
Potential benefit: Could help create clearer genetic diagnoses and more precise treatments for people whose conditions are driven by protein-changing variants.
How similar studies have gone: Previous efforts combining computational predictions with laboratory tests have shown promise for some genes, but many variants remain uncharacterized and the approach is still being refined.
Where this research is happening
-
Texas Engineering Experiment Station
College Station, United States Active
Researchers
- Principal investigator: Shen, Yang — Texas Engineering Experiment Station
- Study coordinator: Shen, Yang
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.