Well-tempered metadynamics: a smoothly converging and tunable free-energy method.

By Alessandro Barducci, Giovanni Bussi, Michele Parrinello. Physical Review Letters, 2008

2,243 citations recorded by the source corpus.

We present a method for determining the free-energy dependence on a selected number of collective variables using an adaptive bias. The formalism provides a unified description which has metadynamics and canonical sampling as limiting cases. Convergence and errors can be rigorously and easily controlled. The parameters of the simulation can be tuned so as to focus the computational effort only on the physically relevant regions of the order parameter space. The algorithm is tested on the reconstruction of an alanine dipeptide free-energy landscape.

Subfields: Atomic and Molecular Physics, and Optics, Condensed Matter Physics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/9fb9d52747b5937a31a67a76cd3d7a50ecbe1a82

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In Atomic and Molecular Physics, and Optics

In Condensed Matter Physics

In Molecular Biology

Citations in the corpus

Enhanced Sampling Methods for Molecular Dynamics Simulations [Article v1.0] (2022, background): “In Refs [369, 370], multiple windows (localized) umbrella sampling is used to bias some chosen CV while within each umbrella window, metadynamics is used to bias another set of CVs.”
Scalable molecular dynamics on CPU and GPU architectures with NAMD. (2020, methodology): “Among the widely used algorithms associated with geometric transformations that are available in Colvars are umbrella sampling 91,121 (US), metadynamics 92,122,123 (MtD), well-tempered metadynamics 124 (WT-MtD), and ABF 87,89 and its different variants 95,96,125,126 (see Fig.”