Enhanced sampling algorithms have emerged as powerful methods to extend the utility of
molecular dynamics simulations and allow the sampling of larger portions of the …

Unsupervised learning is becoming an essential tool to analyze the increasingly large
amounts of data produced by atomistic and molecular simulations, in material science, solid …

Enhancing sampling and analyzing simulations are central issues in molecular simulation.
Recently, we introduced PLUMED, an open-source plug-in that provides some of the most …

Metadynamics is an enhanced sampling method of great popularity, based on the on-the-fly
construction of a bias potential that is a function of a selected number of collective variables …

Since its inception nearly a half century ago, CHARMM has been playing a central role in
computational biochemistry and biophysics. Commensurate with the developments in …

Atomistic simulations play a central role in many fields of science. However, their usefulness
is often limited by the fact that many systems are characterized by several metastable states …

The ability of widely used sampling methods, such as molecular dynamics or Monte Carlo
simulations, to explore complex free energy landscapes is severely hampered by the …

We introduce a method to obtain one-dimensional collective variables for studying rarely
occurring transitions between two metastable states separated by a high free energy barrier …

The ever-increasing power of modern supercomputers, along with the availability of highly
scalable atomistic simulation codes, has begun to revolutionize predictive modeling of …

Molecular dynamics (MD) is the method of choice for understanding the structure, function,
and interactions of molecules. However, MD simulations are limited by the strong …