Large-scale computational molecular models provide scientists a means to investigate the
effect of microscopic details on emergent mesoscopic behavior. Elucidating the relationship …

This Review illustrates the evaluation of permeability of lipid membranes from molecular
dynamics (MD) simulation primarily using water and oxygen as examples. Membrane …

Machine learning encompasses tools and algorithms that are now becoming popular in
almost all scientific and technological fields. This is true for molecular dynamics as well …

Coarse‐grained (CG) modeling is an invaluable tool for the study of polymers and other soft
matter systems due to the span of spatiotemporal scales that typify their physics and …

We extract the folding free energy landscape and the time-dependent friction function, the
two ingredients of the generalized Langevin equation (GLE), from explicit-water molecular …

We introduce a hybrid projection scheme that combines linear Mori projection and
conditional Zwanzig projection techniques and use it to derive a generalized Langevin …

For the simulations of polymeric systems, coarse‐grained (CG) molecular dynamics
simulations are computationally demanding not only because of their high computational …

The development of data-informed predictive models for dynamical systems is of
widespread interest in many disciplines. We present a unifying framework for blending …

We introduce a method to accurately and efficiently estimate the effective dynamics of
collective variables in molecular simulations. Such reduced dynamics play an essential role …

We present a data-driven approach to determine the memory kernel and random noise in
generalized Langevin equations. To facilitate practical implementations, we parameterize …