Automatic Proposal of Multistep Reaction Mechanisms using a Graph-Driven Search
Automatic Proposal of Multistep Reaction Mechanisms using a Graph-Driven Search
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DOI：
10.1021/acs.jpca.9b01014
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发表时间：
2019-04-18
影响因子：
2.9
通讯作者：
Habershon, Scott
中科院分区：
文献类型：
--
作者：
Ismail, Idil;Stuttaford-Fowler, Holly B. V. A.;Habershon, Scott
提出和测试机械假设是当代计算化学的关键应用之一。在大多数计算机理分析中，从反应物到产物的各个基本步骤是由用户基于所学的化学知识、直觉或与密切相关的化学反应的现有良好表征机制的比较而提出的。然而，现有化学知识的先决条件是自动（或“黑匣子”）机械生成和评估的障碍，并且它可能同时排除位于“标准”化学反应集之外的机械建议。在本文中，我们提出了一种简单的随机游走算法，用于搜索将定义的反应物结构转化为目标产物的基本化学反应集。我们的方法专门在分子连接矩阵的空间中运行，寻找一组化学上敏感的键合变化，将输入反应物和产物结构的连接矩阵连接起来。随后，我们将说明如何在图约束势的作用下生成每个基元反应的原子坐标，然后再通过量子化学计算进行进一步分析。我们的方法已成功用于一氧化碳氧化、水煤气变换反应和正己烷芳构化，所有这些均由 Pt 纳米粒子催化。
Proposing and testing mechanistic hypotheses stands as one of the key applications of contemporary computational chemistry. In the majority of computational mechanistic analyses, the individual elementary steps leading from reactants to products are proposed by the user, based on learned chemical knowledge, intuition, or comparison to an existing well-characterized mechanism for a closely related chemical reaction. However, the prerequisite of prior chemical knowledge is a barrier to automated (or "black box") mechanistic generation and assessment, and it may simultaneously preclude mechanistic proposals that lie outside the "standard" chemical reaction set. In this Article, we propose a simple random-walk algorithm that searches for the set of elementary chemical reactions that transform defined reactant structures into target products. Our approach operates exclusively in the space of molecular connectivity matrices, seeking the set of chemically sensible bonding changes that link connectivity matrices for input reactant and product structures. We subsequently illustrate how atomic coordinates for each elementary reaction can be generated under the action of a graph-restraining potential, prior to further analysis by quantum chemical calculations. Our approach is successfully demonstrated for carbon monoxide oxidation, the water-gas shift reaction, and n-hexane aromatization, all catalyzed by Pt nanoparticles.