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G.M. Torrie

Bio: G.M. Torrie is an academic researcher from University of Toronto. The author has contributed to research in topics: Hybrid Monte Carlo & Monte Carlo integration. The author has an hindex of 1, co-authored 1 publications receiving 4439 citations.

Papers
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TL;DR: In this paper, the authors describe the use of arbitrary sampling distributions chosen to facilitate the estimate of the free energy difference between a model system and some reference system, but the conventional Monte Carlo methods of obtaining such averages are inadequate for the free-energy case.

5,058 citations


Cited by
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TL;DR: NAMD as discussed by the authors is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems that scales to hundreds of processors on high-end parallel platforms, as well as tens of processors in low-cost commodity clusters, and also runs on individual desktop and laptop computers.
Abstract: NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temperature and pressure controls used. Features for steering the simulation across barriers and for calculating both alchemical and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Finally, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomolecular system, highlighting particular features of NAMD, for example, the Tcl scripting language. The article also provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the molecular graphics/sequence analysis software VMD and the grid computing/collaboratory software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu.

14,558 citations

Journal ArticleDOI
TL;DR: An improved and extended version of the coarse grained lipid model is presented, coined the MARTINI force field, based on the reproduction of partitioning free energies between polar and apolar phases of a large number of chemical compounds to reproduce the free energies of these chemical building blocks.
Abstract: We present an improved and extended version of our coarse grained lipid model. The new version, coined the MARTINI force field, is parametrized in a systematic way, based on the reproduction of partitioning free energies between polar and apolar phases of a large number of chemical compounds. To reproduce the free energies of these chemical building blocks, the number of possible interaction levels of the coarse-grained sites has increased compared to those of the previous model. Application of the new model to lipid bilayers shows an improved behavior in terms of the stress profile across the bilayer and the tendency to form pores. An extension of the force field now also allows the simulation of planar (ring) compounds, including sterols. Application to a bilayer/cholesterol system at various concentrations shows the typical cholesterol condensation effect similar to that observed in all atom representations.

4,580 citations

Journal ArticleDOI
TL;DR: This work presents PLUMED 2 here—a complete rewrite of the code in an object-oriented programming language (C++), which introduces greater flexibility and greater modularity, which both extends its core capabilities and makes it far easier to add new methods and CVs.

2,256 citations

Journal ArticleDOI
TL;DR: A method for determining the free-energy dependence on a selected number of collective variables using an adaptive bias and the formalism provides a unified description which has metadynamics and canonical sampling as limiting cases.
Abstract: 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.

2,174 citations