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Enhancing systematic motion in molecular dynamics simulation

机译:在分子动力学模拟中增强系统运动

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Molecular dynamics (MD) simulation is an important approach for conformational search. The conformational searching efficiency in MD simulation is greatly limited by the systematic conformational change or motion. We developed a new MD simulation method to enhance the conformational search efficiency through accelerating the systematic motion. In this work, we describe the theoretical basis and the simulation algorithm of this method for atomic systems. In this method, systematic motion is accelerated by a guiding force derived from a local free-energy surface defined for a system. Under certain approximations, the guiding forces can be estimated from the force information the system experienced in the past through a memory function, and these forces are used to guide the current motion in the same simulation. Therefore, this guiding force is called the self-guiding force and this kind of simulation is called the self-guided molecular dynamics (SGMD) simulation. We have performed detailed analysis of the characteristics of the SGMD in terms of energetic, structural, and dynamic properties with a Lennard-Jones argon system. In addition, we demonstrated the enhanced conformational search efficiency of the SGMD method through the ergodic measure and the crystallization of liquid argon.
机译:分子动力学(MD)模拟是构象搜索的重要方法。 MD仿真中的构象搜索效率受到系统构象变化或运动的极大限制。我们开发了一种新的MD仿真方法,通过加速系统运动来提高构象搜索效率。在本文中,我们描述了该方法在原子系统中的理论基础和仿真算法。在这种方法中,系统的运动通过来自为系统定义的局部自由能表面的导引力加速。在某些近似值下,可以通过记忆功能从系统过去所经历的力信息中估算出引导力,并且这些力在同一模拟中用于引导当前运动。因此,该引导力称为自引导力,这种模拟称为自引导分子动力学(SGMD)模拟。我们使用Lennard-Jones氩气系统对SGMD的特性进行了详细的分析,包括能量,结构和动态特性。此外,我们通过遍历测度和液氩结晶证明了SGMD方法的构象搜索效率提高。

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