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Convergence to the fixed-node limit in deep variational Monte Carlo
Zeno Schätzle, Jan Hermann, Frank Noé
Variational quantum Monte Carlo (QMC) is an ab-initio method for solving the electronic Schrödinger equation that is exact in principle, but limited by the flexibility of the avail…
Coarse Graining Molecular Dynamics with Graph Neural Networks
Brooke E. Husic, Nicholas E. Charron, Dominik Lemm +9
Coarse graining enables the investigation of molecular dynamics for larger systems and at longer timescales than is possible at atomic resolution. However, a coarse graining model…
Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with a Kernel Approach
Jiang Wang, Stefan Chmiela, Klaus-Robert Müller +2
Gradient-domain machine learning (GDML) is an accurate and efficient approach to learn a molecular potential and associated force field based on the kernel ridge regression algorit…
Deep neural network solution of the electronic Schrödinger equation
Jan Hermann, Zeno Schätzle, Frank Noé
[New and updated results were published in Nature Chemistry, doi:10.1038/s41557-020-0544-y.] The electronic Schrödinger equation describes fundamental properties of molecules and m…
Hydrodynamic coupling for particle-based solvent-free membrane models
Mohsen Sadeghi, Frank Noé
The great challenge with biological membrane systems is the wide range of scales involved, from nanometers and picoseconds for individual lipids, to the micrometers and beyond mill…
Machine Learning of coarse-grained Molecular Dynamics Force Fields
Jiang Wang, Simon Olsson, Christoph Wehmeyer +5
Atomistic or ab-initio molecular dynamics simulations are widely used to predict thermodynamics and kinetics and relate them to molecular structure. A common approach to go beyond…
The mechanism of RNA base fraying: molecular dynamics simulations analyzed with core-set Markov state models
Giovanni Pinamonti, Fabian Paul, Frank Noé +2
The process of RNA base fraying (i.e. the transient opening of the termini of a helix) is involved in many aspects of RNA dynamics. We here use molecular dynamics simulations and M…
Predicting the kinetics of RNA oligonucleotides using Markov state models
Giovanni Pinamonti, Jianbo Zhao, David E. Condon +4
Nowadays different experimental techniques, such as single molecule or relaxation experiments, can provide dynamic properties of biomolecular systems, but the amount of detail obta…
Kinetic distance and kinetic maps from molecular dynamics simulation
Frank Noe, Cecilia Clementi
Characterizing macromolecular kinetics from molecular dynamics (MD) simulations requires a distance metric that can distinguish slowly-interconverting states. Here we build upon di…