Gaussian Mixture Based Enhanced Sampling

Abstract

Many processes in chemistry and physics take place on timescales that cannot be explored using standard molecular dynamics simulations. This renders the use of enhanced sampling mandatory. Here we introduce an enhanced sampling method that is based on constructing a model probability density from which a bias potential is derived. The model relies on the fact that in a physical system most of the configurations visited can be grouped into isolated metastable islands. To each island we associate a distribution that is fitted to a Gaussian mixture. The different distributions are linearly combined together with coefficients that are computed self consistently. Remarkably, from this biased dynamics, rates of transition between different metastable states can be straightforwardly computed.

References in corpus (13)

• Canonical sampling through velocity-rescaling
• Escaping free-energy minima
• PLUMED 2: New feathers for an old bird
• From Metadynamics to Dynamics
• Rethinking Metadynamics: from bias potentials to probability distributions
• A Variational Approach to Enhanced Sampling and Free Energy Calculations
• Caliber based spectral gap optimization of order parameters (SGOOP) for sampling complex molecular systems
• A self-learning algorithm for biased molecular dynamics
• A variational conformational dynamics approach to the selection of collective variables in metadynamics
• Variationally Optimized Free Energy Flooding for Rate Calculation
• Making the best of a bad situation: a multiscale approach to free energy calculation
• Combining Metadynamics and Integrated Tempering Sampling
• Enhanced sampling of transition states

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• Water regulates the residence time of Benzamidine in Trypsin
• From enhanced sampling to reaction profiles
• Deep Learning Collective Variables from Transition Path Ensemble
• Deep learning the slow modes for rare events sampling
• A modified nudged elastic band algorithm with adaptive spring lengths
• A Sinking Approach to Explore Arbitrary Areas in Free Energy Landscapes
• Reweighted Jarzynski sampling: Acceleration of rare events and free energy calculation with a bias potential learned from nonequilibrium work
• Computing rates and understanding unbinding mechanism in host-guest systems
• Improving the Efficiency of Variationally Enhanced Sampling with Wavelet-Based Bias Potentials
• Global free energy landscapes as a smoothly joined collection of local maps