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TorchMD: A deep learning framework for molecular simulations
Stefan Doerr, Maciej Majewsk, Adrià Pérez +5
Molecular dynamics simulations provide a mechanistic description of molecules by relying on empirical potentials. The quality and transferability of such potentials can be improved…
Machine learning for molecular simulation
Frank Noé, Alexandre Tkatchenko, Klaus-Robert Müller +1
Machine learning (ML) is transforming all areas of science. The complex and time-consuming calculations in molecular simulations are particularly suitable for a machine learning re…
Special Topic: Markov Models of Molecular Kinetics
Frank Noé, Edina Rosta
The Journal of Chemical Physics (JCP) article collection on Markov Models of Molecular Kinetics (MMMK) features recent advances developing and using Markov State Models (MSMs) in a…
Machine Learning for Molecular Dynamics on Long Timescales
Frank Noé
Molecular Dynamics (MD) simulation is widely used to analyze the properties of molecules and materials. Most practical applications, such as comparison with experimental measuremen…
Identification of kinetic order parameters for non-equilibrium dynamics
Fabian Paul, Hao Wu, Maximilian Vossel +2
A popular approach to analyze the dynamics of high-dimensional many-body systems, such as macromolecules, is to project the trajectories onto a space of slowly-varying collective v…
Reversible Interacting-Particle Reaction Dynamics
Christoph Fröhner, Frank Noé
Interacting-Particle Reaction Dynamics (iPRD) simulates the spatiotemporal evolution of particles that experience interaction forces and can react with one another. The combination…
Grand canonical diffusion-influenced reactions: a stochastic theory with applications to multiscale reaction-diffusion simulations
Mauricio J. del Razo, Hong Qian, Frank Noé
Smoluchowski-type models for diffusion-influenced reactions (A+B -> C) can be formulated within two frameworks: the probabilistic-based approach for a pair A, B of reacting particl…
MSM/RD: Coupling Markov state models of molecular kinetics with reaction-diffusion simulations
Manuel Dibak, Mauricio J. del Razo, David De Sancho +2
Molecular dynamics (MD) simulations can model the interactions between macromolecules with high spatiotemporal resolution but at a high computational cost. By combining high-throug…
An efficient multi-scale Green's Functions Reaction Dynamics scheme
Luigi Sbailò, Frank Noé
Molecular Dynamics - Green's Functions Reaction Dynamics (MD-GFRD) is a multiscale simulation method for particle dynamics or particle-based reaction-diffusion dynamics that is sui…
Estimation and uncertainty of reversible Markov models
Benjamin Trendelkamp-Schroer, Hao Wu, Fabian Paul +1
Reversibility is a key concept in Markov models and Master-equation models of molecular kinetics. The analysis and interpretation of the transition matrix encoding the kinetic prop…
Efficient estimation of rare-event kinetics
Benjamin Trendelkamp-Schroer, Frank Noe
The efficient calculation of rare-event kinetics in complex dynamical systems, such as the rate and pathways of ligand dissociation from a protein, is a generally unsolved problem.…
Projected and Hidden Markov Models for calculating kinetics and metastable states of complex molecules
Frank Noe, Hao Wu, Jan-Hendrik Prinz +1
Markov state models (MSMs) have been successful in computing metastable states, slow relaxation timescales and associated structural changes, and stationary or kinetic experimental…
Identification of slow molecular order parameters for Markov model construction
Guillermo Perez-Hernandez, Fabian Paul, Toni Giorgino +2
A goal in the kinetic characterization of a macromolecular system is the description of its slow relaxation processes, involving (i) identification of the structural changes involv…
Efficient Bayesian estimation of Markov model transition matrices with given stationary distribution
Benjamin Trendelkamp-Schroer, Frank Noe
Direct simulation of biomolecular dynamics in thermal equilibrium is challenging due to the metastable nature of conformation dynamics and the computational cost of molecular dynam…