High-throughput, physics-based drug design using advanced free energy methods
Official title: Developing high-throughput free energy methods for small molecule, peptide, and protein design
Funded at University of New Mexico · NIH-11271500 · Data updated 2026-11-12
A computational program is being developed to rapidly design and optimize small molecules, peptides, and engineered proteins for cancer-related targets using advanced physics-based free energy calculations.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of New Mexico NIH-funded |
| Lab location | 1 site (Albuquerque, United States) |
| Project start | August 22, 2026 |
| Project end | May 31, 2031 |
| Funding year | 2026 |
| Award (this year) | $370,940 |
| NIH project number | 1R35GM162544-01 |
| Project ID | NIH-11271500 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates include patients with cancer or specific cancer subtypes that may be targeted by novel small molecules, peptides, or engineered proteins developed through this framework.
✕Less likely to help
Patients not eligible or unlikely to benefit are those not involved in drug development pipelines or whose cancer targets are not addressed by the project.
What this research studies
This project aims to speed up drug discovery by combining docking, pharmacophore mapping, and machine learning with new enhanced sampling methods. It will address the high computational cost of accurate free energy predictions so researchers can screen more candidates efficiently. The work focuses on cancer-related targets and seeks to produce a scalable framework that can generate reliable lead molecules for further testing. The team will integrate multisite dynamics to create MSlD++, enabling more throughput without sacrificing rigor.
Why it matters
Potential benefit: If successful, patients could benefit from faster identification of promising cancer therapies and more efficient use of experimental resources to bring effective drugs to clinical testing.
How similar studies have gone: Previous computational drug-design efforts have used similar tools, with growing evidence that physics-based methods can complement empirical screening.
Where this research is happening
-
University of New Mexico
Albuquerque, United States Active
Researchers
- Principal investigator: Liu, Xiaorong — University of New Mexico
- Study coordinator: Liu, Xiaorong
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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.