Unified toolkit to refine protein structures with AI help for drug design
Official title: Addressing Structural Disorder and Conformational Heterogeneity in Modern Therapeutic Modalities: A Unified X-ray/Cryo-EM QM/MM Ensemble Refinement Toolkit with Enhanced Density-Driven MD
Funded at Quantumbio, INC. · NIH-11418609 · Data updated 2026-11-12
A project at Quantumbio, Inc. aims to use AI-augmented methods to better refine protein structures and their flexible parts to improve drug discovery.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Quantumbio, INC. NIH-funded |
| Lab location | 1 site (State College, UNITED STATES) |
| Project start | September 30, 2025 |
| Project end | May 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $684,417 |
| NIH project number | 4R44GM163476-02 |
| Project ID | NIH-11418609 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are patients whose diseases could be targeted by drugs designed using refined structural information (e.g., protease inhibitors, kinase modulators, macrocyclic therapeutics).
✕Less likely to help
Patients unlikely to benefit are those not currently pursuing therapies related to structural drug design or those whose condition would not be influenced by improved structure-based design.
What this research studies
This project develops an integrated X-ray/Cryo-EM refinement workflow that uses quantum-mechanical/molecular-mechanics ensemble methods and enhanced density-driven molecular dynamics to better capture conformational diversity in protein–ligand complexes. By addressing missing residues and multiple binding modes, the work seeks to provide more accurate structural data that inform lead optimization. The team will combine experimental data with AI-assisted refinement to generate ensembles that reflect true biological flexibility, especially for challenging modalities like macrocycles and covalent inhibitors. The ultimate goal is to improve the reliability of structure-based drug design and AI structure predictions through higher-quality experimental inputs.
Why it matters
Potential benefit: If successful, patients could benefit from faster development of more precise and effective therapeutics guided by more accurate structural models.
How similar studies have gone: Previous ensemble refinement approaches have shown promise in better representing flexibility, but this project adds AI-driven enhancement and QM/MM integration for more accurate models.
Where this research is happening
-
Quantumbio, INC.
State College, United States Active
Researchers
- Principal investigator: Westerhoff, Lance M — Quantumbio, INC.
- Study coordinator: Westerhoff, Lance M
Related research
Other NIH-funded projects on the same topics.
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Improving drug discovery through advanced protein binding methods
This study is exploring a new way to help scientists design better medicines by understanding how proteins interact with other molecules, making it easier to find effective treatments for patients.
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.