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.

中文翻译：

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具有波前传播的驱动扭转扫描。

扭转/二面角势能项的参数化是发展分子力学力场的关键部分。量子力学（QM）方法通常用于提供势能面（PES）的样本，以适合这些力场项中的经验参数。为了确保所采样的分子构型在热力学上是可行的，通常会执行受约束的QM几何优化，该优化会放宽正交自由度，同时将目标扭转角固定在值网格上。但是，结果的质量和计算成本会受到非平凡PES上各种因素的影响，例如对所选扫描方向的依赖性以及缺乏从多个初始猜测开始的有效结果整合方法。在本文中，通过递归波前传播算法，TorsionDrive可以在扭转约束的网格上生成能量最小的结构，该算法可以解决常规扫描方法的不足，并可以生成更高质量的QM数据以进行力场开发。提出了我们方法的功能，可用于多维扫描和多个初始猜测结构，并描述了与MolSSI QCArchive分布式计算生态系统的集成。该方法在与许多QM软件包和能量最小化代码兼容的开源软件包中实现。