Biomolecular dynamics with machine-learned quantum-mechanical force fields trained on diverse chemical fragments
Oliver T. Unke, Martin Stöhr, Stefan Ganscha, Thomas Unterthiner, Hartmut Maennel, Sergii Kashubin, Daniel Ahlin, Michael Gastegger, Leonardo Medrano Sandonas, Joshua T. Berryman, Alexandre Tkatchenko, Klaus‐Robert Müller
Abstract
The GEMS method enables molecular dynamics simulations of large heterogeneous systems at ab initio quality.
Topics & Concepts
Dynamics (music)Molecular dynamicsQuantumAb initioQuantum chemicalComputer scienceQuality (philosophy)Force field (fiction)Statistical physicsChemical physicsBiological systemNanotechnologyPhysicsArtificial intelligenceMaterials scienceMoleculeQuantum mechanicsBiologyAcousticsMachine Learning in Materials ScienceProtein Structure and DynamicsAdvanced Electron Microscopy Techniques and Applications