We are excited to announce that the NIH Institute of General Medical Sciences has funded our Focused Technology Research & Development R01 proposal, enabling the Open Force Field Initiative to partner with the biopolymer force field community and extend our infrastructure and force fields to also cover biopolymers. This is a collaborative NIH grant, with $380K direct costs/year for four years shared over the five main academic sites (University of Colorado Boulder, Memorial Sloan Kettering Cancer Center, University of California, Irvine, University of California, San Diego, and University of California, Davis), and includes significant funded collaborations with the MolSSI QCArchive and the AMBER community (via David Cerutti at Rutgers). The submitted proposal text can be found here. We especially thank our partners who contributed letters in support of the proposal.

The NIH funding is synergistic to the existing industrial Open Force Field Consortium funding, which focuses on delivering small molecule force fields with systematic improvements to accuracy and coverage. The new NIH support will enable:

• Delivery of higher accuracy for protein-ligand binding free energies biomolecules through systematic construction of biopolymer force fields that will be compatible with OpenFF small molecules.
• Support for non-canonical amino and nucleic acids as well as covalently bound ligands.
• Better modeling of the interactions of proteins with organic polymers and solvents.
• Support for machine-learned potentials.
• Development of a Bayesian inference infrastructure to automate the selection of functional forms and parameter types that are most appropriate for matching a given set of experimental observables.

We look forward to working with the broader force field development community to help build on the extraordinary biomolecular force field work done so far. We plan on:

• Helping to port existing biomolecular force fields to our atom-type independent SMIRNOFF format
• Adding support for existing general biomolecular force fields to the Open Force Field format, so that other reserachers can use some or all of the Open Force Field tools to help in their parameterization work.
• Collaborating with other biomolecular force field developers to assemble sets of experimental and quantum mechanical data for future force field optimizations.
• Developing automated benchmarking frameworks for biophysical properties.

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