Enhanced Sampling Simulations on Transition-Metal-Catalyzed Organic Reactions:Zirconocene-Catalyzed Propylene Polymerization and Sharpless Epoxidation

The bond breaking and forming in chemical reactions is a typical rare event,which is one of the difficult problems in molecular dynamics simulations.Numerous enhanced sampling methods have been developed to extend the time scale covered by molecular simulations.However,the difficulties of obtaining appropriate collective variables from complicated reaction pathways and a controlled sampling over the desired phase space remain as challenges.Herein,we use MetaITS,which combines metadynamics and integrated tempered sampling,to increase the sampling efficiency for chemical reactions.Metadynamics with collective variables obtained by harmonic linear discriminant analysis can efficiently decrease the main energy barrier of chemical reaction.Meanwhile,integrated tempered sampling can enhance the exploration of other degrees of freedom.In this study,we applied the MetaITS method to two transition-metal-catalyzed organic reactions with complicated reaction coordinates.We simulated here a zirconocene-catalyzed propylene polymerization to investigate the regioselectivity and temperature effects.We also studied a Sharpless epoxidation reaction,for which both chiral products are observed through simulation.

SPONGE:A GPU-Accelerated Molecular Dynamics Package with Enhanced Sampling and AI-Driven Algorithms

SPONGE(Simulation Package tOward Next GEneration molecular modeling)is a software package for molecular dynamics(MD)simulation of solution and surface molecular systems.In this version of SPONGE,the all-atom potential energy functions used in AMBER MD packages are used by default and other all-atom/coarse-grained potential energy functions are also supported.SPONGE is designed to extend the timescale being approached in MD simulations by utilizing the latest CUDA-enabled graphical processing units(GPU)and adopting highly efficient enhanced sampling algorithms,such as integrated tempering,selective integrated tempering and enhanced sampling of reactive trajectories.It is highly modular and new algorithms and functions can be incorporated con veniently.Particularly,a specialized Python plugin can be easily used to perform the machine learning MD simulation with MindSpore,TensorFlow,PyTorch or other popular machine learning frameworks.Furthermore,a plugin of Finite-Element Method(FEM)is also available to handle metallic surface systems.All these advanced features increase the power of SPONGE for modeling and simulation of complex chemical and biological systems.