ELF: An Extended-Lagrangian Free Energy Calculation Module for Multiple Molecular Dynamics Engines,Journal of Chemical Information and Modeling

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ELF: An Extended-Lagrangian Free Energy Calculation Module for Multiple Molecular Dynamics Engines
Journal of Chemical Information and Modeling ( IF 5.6 ) Pub Date : 2018-06-06 00:00:00 , DOI: 10.1021/acs.jcim.8b00115
Haochuan Chen ₁ , Haohao Fu ₁ , Xueguang Shao _{1,

2,

3} , Christophe Chipot _{4,

5,

6} , Wensheng Cai _{1,

2}

Affiliation

Extended adaptive biasing force (eABF), a collective variable (CV)-based importance-sampling algorithm, has proven to be very robust and efficient compared with the original ABF algorithm. Its implementation in Colvars, a software addition to molecular dynamics (MD) engines, is, however, currently limited to NAMD and LAMMPS. To broaden the scope of eABF and its variants, like its generalized form (egABF), and make them available to other MD engines, e.g., GROMACS, AMBER, CP2K, and openMM, we present a PLUMED-based implementation, called extended-Lagrangian free energy calculation (ELF). This implementation can be used as a stand-alone gradient estimator for other CV-based sampling algorithms, such as temperature-accelerated MD (TAMD) and extended-Lagrangian metadynamics (MtD). ELF provides the end user with a convenient framework to help select the best-suited importance-sampling algorithm for a given application without any commitment to a particular MD engine.

中文翻译：

ELF：扩展的拉格朗日自由能计算模块，用于多个分子动力学引擎

与原始的ABF算法相比，扩展的自适应偏压力（eABF）是一种基于集体变量（CV）的重要性采样算法，已被证明非常强大和有效。但是，它在Colvars（分子动力学（MD）引擎的软件之外的软件）中的实现目前仅限于NAMD和LAMMPS。为了扩大eABF及其变体的范围，例如其广义形式（egABF），并使它们可用于其他MD引擎，例如GROMACS，AMBER，CP2K和openMM，我们提出了一种基于PLUMED的实现，称为扩展拉格朗日式自由能计算（ELF）。此实现可用作其他基于CV的采样算法（例如温度加速MD（TAMD）和扩展拉格朗日元动力学（MtD））的独立梯度估计器。

更新日期：2018-06-06

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