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Machine learning (ML) force fields are revolutionizing molecular dynamics (MD) simulations as they bypass the computational cost associated with ab initio methods but do not sacrifice accuracy in the process. In this work, the GPyTorch library is used to create Gaussian process regression (GPR) models that are interfaced with the next‐generation ML force field FFLUX. These models predict atomic properties...
This study addresses a comprehensive assessment of the interaction between chemical warfare agents (CWA) and acetylcholinesterase (AChE) systems, focus on the intriguing pnictogen‐bond interaction (PnB). Utilizing the crystallographic data from the Protein Data Bank pertaining to the AChE‐CWA complex involving Sarin (GB), Cyclosarin (GF), 2‐[fluoro(methyl)phosphoryl]oxy‐1,1‐dimethylcyclopentane (GP)...
Reinforcement learning (RL) methods have helped to define the state of the art in the field of modern artificial intelligence, mostly after the breakthrough involving AlphaGo and the discovery of novel algorithms. In this work, we present a RL method, based on Q‐learning, for the structural determination of adsorbate@substrate models in silico, where the minimization of the energy landscape resulting...