Securing sustainable funding to enable OpenMM to continue to power the next decade in biomolecular modeling and simulation

OpenMM is the most widely-used open source GPU-accelerated framework for biomolecular modeling and simulation. It has been cited more than 1300 times, downloaded over 280,000 times from conda-forge alone, and has run on more than one million distinct computers. 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 $16B 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 now 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, guided by the OpenMM Consortium. To fully exploit the revolution in QM-level accuracy with quantum machine-learning (QML) potentials, we also plan to add plug-in support for QML 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.

Recently, we applied for federal funding to realize this vision via a new NIH Focused Technology Research & Development R01 proposal, with strong support from the biomolecular simulation community. You can read the scientific components of the proposal we submitted here: [PDF]

We welcome your feedback on how OpenMM can continue to serve the needs of the biomolecular simulation community over the next decade and beyond!