Creating new protein biosensors for detecting terpenes and terpenoids
Official title: Directed evolution of broadly fungible biosensors
Funded at University of Texas at Austin · NIH-10984472 · Data updated 2026-11-12
This study is working on creating new tools that can easily detect certain natural compounds called terpenes and terpenoids, which are useful in many industries and health applications, using smart computer techniques and special lab methods to make them more effective and accurate.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Texas at Austin NIH-funded |
| Lab location | 1 site (Austin, United States) |
| Project start | January 5, 2023 |
| Project end | November 30, 2026 |
| Funding year | 2025 |
| Award (this year) | $283,038 |
| NIH project number | 5R01GM146093-03 |
| Project ID | NIH-10984472 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals or organizations involved in industries that utilize terpenes and terpenoids, such as pharmaceuticals, agriculture, and biotechnology.
✕Less likely to help
Patients who are not involved in industries related to terpenes and terpenoids may not receive direct benefits from this research.
What this research studies
This research focuses on developing innovative protein biosensors that can detect a wide variety of terpenes and terpenoids, which are important compounds in many industrial and medical applications. The approach combines advanced computational methods with directed evolution techniques to create biosensors that are both sensitive and specific to these compounds. By leveraging machine learning tools, the researchers aim to enhance the functionality of these biosensors, making it easier to identify new ones that can respond to previously undetectable substances.
Why it matters
Potential benefit: If successful, this research could lead to the development of highly effective biosensors that improve detection methods for important biological and industrial compounds.
How similar studies have gone: Other research has shown promise in using directed evolution and computational methods to develop biosensors, indicating that this approach has potential for success.
Where this research is happening
-
University of Texas at Austin
Austin, United States Active
Researchers
- Principal investigator: Ellington, Andrew D — University of Texas at Austin
- Study coordinator: Ellington, Andrew D
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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.