title: Efficient Sampling of High-Dimensional Free-Energy Landscapes with Parallel Bias Metadynamics.
abstract: Metadynamics accelerates sampling of molecular dynamics while reconstructing thermodynamic properties of selected descriptors of the system. Its main practical difficulty originates from the compromise between keeping the number of descriptors small for efficiently exploring their multidimensional free-energy landscape and biasing all of the slow motions of a process. Here we illustrate on a model system and on the tryptophan-cage miniprotein parallel bias metadynamics, a method that overcomes this issue by simultaneously applying multiple low-dimensional bias potentials.
authors.affiliation: Department of Chemical Engineering, University of Washington , Seattle, Washington 98195, United States.
authors.forename: Jim
authors.initials: J
authors.lastname: Pfaendtner
authors.affiliation: Department of Chemistry, University of Cambridge , Lensfield Road, Cambridge CB2 1EW, United Kingdom.
authors.forename: Massimiliano
authors.initials: M
authors.lastname: Bonomi
mesh_terms: D000465:Algorithms; D008954:Models, Biological; D056004:Molecular Dynamics Simulation; D013816:Thermodynamics; D014364:Tryptophan / Q000737:chemistry*
chemical_list: D014364:Tryptophan