Implicit solvent approach based on generalized born and transferable graph neural_networks for molecular dynamics simulations special collection: machine learning hits molecular simulations

HIGHLIGHTS

• who: Paul Katzberger and colleagues from the Department of Chemistry and Applied Biosciences, ETH Zu00fcrich, Vladimir-Prelog-Weg, Zu00fcrich, Switzerland have published the research work: Implicit solvent approach based on generalized Born and transferable graph neural_networks for molecular dynamics simulations Special Collection: Machine Learning Hits Molecular Simulations, in the Journal: (JOURNAL)
• what: This approach provides good accuracy since it includes both short-range and long-range interactions. This free_energy contribution of the solvent is often described by a separation into a polar and a non-polar contribution. In a slightly adapted form, this approach has . . .
  

   

  

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