This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) Project Grant award of $150,000 will support the University of Missouri System in developing novel deep learning-based "consistency models" to enable more efficient and long-duration molecular dynamics (MD) simulations of protein structures and dynamics. The central goal is to overcome the limitations of traditional MD simulations, which are constrained by small time steps and struggle to capture crucial long-time-scale protein behaviors like folding and aggregation. By integrating consistency models, this project aims to enable simulations at larger time steps without compromising physical accuracy, significantly accelerating the exploration of protein dynamics. The research will involve prototyping consistency models on simplified systems, optimizing the model architecture, and benchmarking the approach on complex protein systems. If successful, this project could advance scientific understanding and unlock new insights in fields like medicine, biotechnology, and materials science. The award period runs from August 1, 2025 to July 31, 2027.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $150.0k | 4/23/25 |