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Driving torsion scans with wavefront propagation

机译:用波前传播驾驶扭转扫描

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The parameterization of torsional/dihedral angle potential energy terms is a crucial part of developing molecular mechanics force fields. Quantum mechanical (QM) methods are often used to provide samples of the potential energy surface (PES) for fitting the empirical parameters in these force field terms. To ensure that the sampled molecular configurations are thermodynamically feasible, constrained QM geometry optimizations are typically carried out, which relax the orthogonal degrees of freedom while fixing the target torsion angle(s) on a grid of values. However, the quality of results and computational cost are affected by various factors on a non-trivial PES, such as dependence on the chosen scan direction and the lack of efficient approaches to integrate results started from multiple initial guesses. In this paper, we propose a systematic and versatile workflow called TorsionDrive to generate energy-minimized structures on a grid of torsion constraints by means of a recursive wavefront propagation algorithm, which resolves the deficiencies of conventional scanning approaches and generates higher quality QM data for force field development. The capabilities of our method are presented for multi-dimensional scans and multiple initial guess structures, and an integration with the MolSSI QCArchive distributed computing ecosystem is described. The method is implemented in an open-source software package that is compatible with many QM software packages and energy minimization codes.
机译:扭转/二面角势能术语的参数化是显影分子力学力田的关键部分。量子机械(QM)方法通常用于提供势能表面(PE)的样品,用于在这些力场术语中拟合经验参数。为了确保采样的分子配置是热力学上可行的,通常进行约束的QM几何优化,该优化是在将目标扭转角度固定在值网格上的同时松弛正交的自由度。然而,结果和计算成本的质量受到非平凡PE上的各种因素的影响,例如对所选择的扫描方向的依赖性以及缺乏有效的方法来集成从多个初始猜测中开始的结果。在本文中,我们提出了一种称为TorSionDrive的系统和多功能的工作流程,通过递归波前传播算法在扭转约束网格上生成能量最小化结构,其解决了传统扫描方法的缺陷并产生了更高的力量QM数据现场发展。我们的方法的能力呈现用于多维扫描和多个初始猜测结构,并描述与MOLSI QCarrive分布式计算生态系统的集成。该方法在兼容许多QM软件包和能量最小化码中的开源软件包中实现。

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