Multiscale Modeling for Enzymes and Bioimaging Probes in Breast Cancer Research
Official title: Multiscale Modeling of Enzymatic Reactions and Bioimaging Probes
Funded at Brandeis University · NIH-11377293 · Data updated 2026-11-12
A Brandeis-led project uses advanced computer models and machine learning to simulate enzyme reactions and design bioimaging probes, with the goal of better understanding breast cancer biology.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Brandeis University NIH-funded |
| Lab location | 1 site (Waltham, United States) |
| Project start | June 1, 2024 |
| Project end | May 31, 2029 |
| Funding year | 2026 |
| Award (this year) | $381,405 |
| NIH project number | 5R35GM153297-04 |
| Project ID | NIH-11377293 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are individuals affected by breast cancer or related conditions who are involved in biomarker discovery, imaging research, or enzymology studies and may participate by providing samples or data in related projects.
✕Less likely to help
Direct patient participation is not a primary component of this grant; benefits are through future research tools and discoveries.
What this research studies
This project focuses on making powerful quantum and molecular simulations accessible to researchers studying enzymes and imaging probes. By combining machine-learning potentials with physics-based methods, the team aims to simulate enzyme reactions and predict how chromophores behave in imaging agents. The work centers on CRISPR-Cas protein systems as test cases and plans to validate new models against established physics-based benchmarks. If successful, these tools could speed up discoveries in cancer biology and imaging techniques. The grant supports development, testing, and dissemination of these methods to the wider community.
Why it matters
Potential benefit: Patients could benefit indirectly through faster development of targeted cancer therapies and improved imaging tools for diagnosis and monitoring.
How similar studies have gone: Precedents exist for successful integration of machine-learning potentials with quantum-mechanical models in enzymology and imaging research, though this multiscale approach is cutting-edge.
Where this research is happening
-
Brandeis University
Waltham, United States Active
Researchers
- Principal investigator: Shao, Yihan — Brandeis University
- Study coordinator: Shao, Yihan
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.