On-the-Fly Training of Atomistic Potentials for Flexible and Mechanically Interlocked Molecules.
On-the-Fly Training of Atomistic Potentials for Flexible and Mechanically Interlocked Molecules.
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柔性机械联锁分子原子势的动态训练
DOI：
10.1021/acs.jctc.1c00497
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发表时间：
2021
影响因子：
5.5
通讯作者：
S. Amirjalayer
中科院分区：
文献类型：
--
作者：
E. Kolodzeiski;S. Amirjalayer
机械互锁分子因其独特的能力而受到广泛关注，因为它们能够执行源自纠缠的明确运动，这对于人造分子机器的设计非常重要。基于力场 (FF) 的原子模拟提供了在分子水平上对此类架构的详细了解，使人们能够预测由此产生的功能。然而，可靠的 FF 的开发仍然具有挑战性且耗时，特别是对于具有大量不同构象异构体的轮烷等高动态和互锁结构。在目前的工作中，我们提出了一种即时训练（OTFT）算法。通过引导和非引导相空间采样，自动连续生成相关参考数据，并将其包含在基于群体交换遗传算法 (psGA) 的 FF 动态参数化中。 OTFT 方法提供了一种快速且自动化的 FF 参数化方案，并解决了因缺少相空间信息或需要大数据而引起的问题。我们证明了所开发的柔性分子 FF 在平衡和非平衡特性方面的高精度。最后，通过应用从头开始参数化 FF，在实验相关的时间尺度（约 1 μs）内进行分子动力学模拟，从而能够详细捕获结构评估并绘制自由能拓扑。因此，动态训练方法为自动化 FF 开发和热平衡内外现象的大规模研究奠定了坚实的基础。
Mechanically interlocked molecules have gained significant attention because of their unique ability to perform well-defined motions originating from their entanglement, which is important for the design of artificial molecular machines. Atomistic simulations based on force fields (FFs) provide detailed insights into such architectures at the molecular level enabling one to predict the resulting functionalities. However, the development of reliable FFs is still challenging and time-consuming, in particular for highly dynamic and interlocked structures such as rotaxanes, which exhibit a large number of different conformers. In the present work, we present an on-the-fly training (OTFT) algorithm. By a guided and nonguided phase space sampling, relevant reference data are automatically and continuously generated and included for the on-the-fly parametrization of the FF based on a population swapping genetic algorithm (psGA). The OTFT approach provides a fast and automated FF parametrization scheme and tackles problems caused by missing phase space information or the need for big data. We demonstrate the high accuracy of the developed FF for flexible molecules with respect to equilibrium and out-of-equilibrium properties. Finally, by applying the ab initio parametrized FF, molecular dynamic simulations were performed up to experimentally relevant time scales (ca. 1 μs) enabling capture in detail of the structural evaluation and mapping out of the free-energy topology. The on-the-fly training approach thus provides a strong foundation toward automated FF developments and large-scale investigations of phenomena in and out of thermal equilibrium.
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发表时间：
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期刊：
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影响因子：
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