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反应性分子动力学途径的自动发现与优化

Automated Discovery and Refinement of Reactive Molecular Dynamics Pathways.

作者信息

Wang Lee-Ping, McGibbon Robert T, Pande Vijay S, Martinez Todd J

机构信息

SLAC Linear Accelerator Laboratory , Menlo Park, California 94025, United States.

出版信息

J Chem Theory Comput. 2016 Feb 9;12(2):638-49. doi: 10.1021/acs.jctc.5b00830. Epub 2016 Jan 19.

Abstract

We describe a flexible and broadly applicable energy refinement method, "nebterpolation," for identifying and characterizing the reaction events in a molecular dynamics (MD) simulation. The new method is applicable to ab initio simulations with hundreds of atoms containing complex and multimolecular reaction events. A key aspect of nebterpolation is smoothing of the reactive MD trajectory in internal coordinates to initiate the search for the reaction path on the potential energy surface. We apply nebterpolation to analyze the reaction events in an ab initio nanoreactor simulation that discovers new molecules and mechanisms, including a C-C coupling pathway for glycolaldehyde synthesis. We find that the new method, which incorporates information from the MD trajectory that connects reactants with products, produces a dramatically distinct set of minimum energy paths compared to existing approaches that start from information for the reaction end points alone. The energy refinement method described here represents a key component of an emerging simulation paradigm where molecular dynamics simulations are applied to discover the possible reaction mechanisms.

摘要

我们描述了一种灵活且广泛适用的能量优化方法——“nebterpolation”,用于在分子动力学(MD)模拟中识别和表征反应事件。这种新方法适用于包含复杂多分子反应事件的数百个原子的从头算模拟。nebterpolation的一个关键方面是在内部坐标中对反应性MD轨迹进行平滑处理,以启动在势能面上寻找反应路径的搜索。我们应用nebterpolation来分析从头算纳米反应器模拟中的反应事件,该模拟发现了新的分子和机制,包括用于乙醇醛合成的C-C偶联途径。我们发现,与仅从反应终点信息出发的现有方法相比,这种结合了将反应物与产物连接起来的MD轨迹信息的新方法产生了一组截然不同的最小能量路径。这里描述的能量优化方法代表了一种新兴模拟范式的关键组成部分,即应用分子动力学模拟来发现可能的反应机制。

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