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Q-Force: Quantum Mechanically Augmented Molecular Force Fields.

Selim SamiMaximilian F S J MengerShirin FarajiRia BroerRemco W A Havenith
Published in: Journal of chemical theory and computation (2021)
The quality of molecular dynamics simulations strongly depends on the accuracy of the underlying force fields (FFs) that determine all intra- and intermolecular interactions of the system. Commonly, transferable FF parameters are determined based on a representative set of small molecules. However, such an approach sacrifices accuracy in favor of generality. In this work, an open-source and automated toolkit named Q-Force is presented, which augments these transferable FFs with molecule-specific bonded parameters and atomic charges that are derived from quantum mechanical (QM) calculations. The molecular fragmentation procedure allows treatment of large molecules (>200 atoms) with a low computational cost. The generated Q-Force FFs can be used at the same computational cost as transferable FFs, but with improved accuracy: We demonstrate this for the vibrational properties on a set of small molecules and for the potential energy surface on a complex molecule (186 atoms) with photovoltaic applications. Overall, the accuracy, user-friendliness, and minimal computational overhead of the Q-Force protocol make it widely applicable for atomistic molecular dynamics simulations.
Keyphrases
  • molecular dynamics simulations
  • single molecule
  • molecular docking
  • molecular dynamics
  • randomized controlled trial
  • machine learning
  • deep learning
  • energy transfer
  • quality improvement
  • quantum dots
  • virtual reality