Openmm: scalable biomolecular modeling, simulation, and machine learning
Active Project Grant Awarded Last action
- Award ID
- R01GM140090
- Recipient
-
The Leland Stanford Junior University UEI HJD6G4D6TJY5
- Awarding agency
-
National Institute of General Medical Sciences
National Institutes of Health, Department of Health and Human Services
- Obligated
- $7,862,392
Award facts
- Assistance listing
- 93.859 Biomedical Research and Research Training
- Completion date 67% complete
- Originally
- Funding
-
- $6,840,435.00 Federal
- $1,021,957.00 Non-federal
- Place of performance
- Palo Alto, CA 94305, USA
Award details come from USAspending.gov.
Description
- Abstract
- Openmm [http://openmm.ORG] is the most widely-used open source GPU-accelerated framework for biomolecular modeling and simulation (>1300 citations, >270,000 downloads, >1M deployed instances). Its python API makes IT widely popular as both an application (for modelers) and a library (for developers), while its c/c++/fortran bindings enable major legacy simulation packages to use openmm to provide high performance on modern hardware. Openmm has been used for probing biological questions that leverage the $14B global investment in structural data from the PDB at multiple scales, from detailed studies of single disease proteins to superfamily-wide modeling studies and large-scale drug development efforts in industry and academia. Originally developed with NIH funding by the pande lab at stanford, we aim to fully transition toward a community governance and sustainable development model and extend its capabilities to ensure openmm can power the next decade of biomolecular research. To fully exploit the revolution in QM-level accuracy with machine-learning (ML) potentials, we will add plug-in support for ML models augmented by GPU-accelerated kernels, enabling transformative science with QM-level accuracy. To enable high-productivity development of new ML models with training dataset sizes approaching 100 million molecules, we will develop a python framework to enable openmm to be easily used within modern ML frameworks such as tensorflow and pytorch. Together with continued optimizations to exploit inexpensive gpus, these advances will power a transformation within biomolecular modeling and simulation, much as deep learning has transformed computer vision.
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| Amendment | $426,294 | $0 | |
| Original award | $426,294 | $426,294 |
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Subawards
| Subrecipient | Amount | Awarded |
|---|---|---|
| Universitat Pompeu Fabra CCT | $86,637 |
Quick answers
Who received award R01GM140090?
R01GM140090 was awarded to The Leland Stanford Junior University by National Institute of General Medical Sciences (National Institutes of Health) on July 1, 2021.
How much is award R01GM140090 worth?
$7,862,392 has been obligated on R01GM140090: $6,840,435 in federal funding and $1,021,957 in non-federal funding.
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