Classifying protein structures using advanced AI methods
Official title: ECOD: Large scale classification of predicted and experimental protein structures
Funded at Ut Southwestern Medical Center · NIH-11088135 · Data updated 2026-11-12
This study is looking at how to better understand protein shapes and functions using both lab data and smart AI tools, which could eventually help us learn more about diseases linked to protein problems, benefiting patients in the long run.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Ut Southwestern Medical Center NIH-funded |
| Lab location | 1 site (Dallas, United States) |
| Project start | May 1, 2023 |
| Project end | April 30, 2027 |
| Funding year | 2025 |
| Award (this year) | $344,400 |
| NIH project number | 5R01GM147367-03 |
| Project ID | NIH-11088135 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for benefiting from this research include individuals with genetic disorders or diseases related to protein misfolding or malfunction.
✕Less likely to help
Patients with conditions unrelated to protein structures or functions may not receive direct benefits from this research.
What this research studies
This research focuses on classifying protein structures by leveraging both experimental data and advanced AI predictions. It aims to enhance the existing database of protein domains, known as ECOD, by integrating a vast number of predicted protein structures generated by cutting-edge technologies like AlphaFold. By doing so, the project seeks to provide a comprehensive understanding of protein functions and evolutionary relationships, which can be crucial for various biological applications. Patients may benefit indirectly as this research could lead to new insights in understanding diseases caused by protein malfunctions.
Why it matters
Potential benefit: If successful, this research could lead to improved understanding and treatment of diseases linked to protein dysfunction.
How similar studies have gone: Other research has shown success in utilizing AI for protein structure prediction, indicating a promising approach in this field.
Where this research is happening
-
Ut Southwestern Medical Center
Dallas, United States Active
Researchers
- Principal investigator: Schaeffer, Richard Dustin — Ut Southwestern Medical Center
- Study coordinator: Schaeffer, Richard Dustin
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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.