Grappa – a machine learned molecular mechanics force field
Leif Seute, Eric Hartmann, Jan Stühmer, Frauke Gräter
Abstract
-couplings. With its simple input features and high data-efficiency, Grappa is well suited for extensions to uncharted regions of chemical space, which we show on the example of peptide radicals. We demonstrate Grappa's transferability to macromolecules in MD simulations from a small fast-folding protein up to a whole virus particle. Our force field sets the stage for biomolecular simulations closer to chemical accuracy, but with the same computational cost as established protein force fields.
Topics & Concepts
Molecular mechanicsForce field (fiction)Field (mathematics)Computer scienceClassical mechanicsPhysicsArtificial intelligenceMolecular dynamicsQuantum mechanicsMathematicsPure mathematicsMachine Learning in Materials ScienceProtein Structure and DynamicsComputational Drug Discovery Methods