启发式引导的反应机制探索
Heuristics-Guided Exploration of Reaction Mechanisms
摘要：
为了研究化学反应网络，必须有效和准确地确定所有相关的中间体和基元反应。这种网络的复杂性可能会迅速增长，特别是如果涉及可能引起无数副反应的反应性物种。如果没有自动化，对复杂反应机理的完整研究是乏味的，并且可能是不可行的。因此，只有化学反应网络的预期主导反应路径（例如，催化循环或酶级联）通常在实践中探索。在这里，我们提出了一个计算协议，以并行化和自动化的方式构建这样的网络。反应性复合物的分子结构是基于来自概念电子结构理论的启发式规则生成的，随后通过量子化学方法进行优化，以产生新兴反应网络的稳定中间体。然后自动检测该网络中可能根据某种结构相似性度量通过基元反应相关的中间体对，并对其进行自动搜索以寻找连接的过渡态。结果可视化为自动生成的网络图，从中可以获得复杂化学过程机理的全面图片，极大地方便了整个网络的分析。我们应用我们的协议Schrock二氮固定催化剂，研究催化氨生产的替代途径。
英文摘要：
For the investigation of chemical reaction networks, the efficient and accurate determination of all relevant intermediates and elementary reactions is mandatory. The complexity of such a network may grow rapidly, in particular if reactive species are involved that might cause a myriad of side reactions. Without automation, a complete investigation of complex reaction mechanisms is tedious and possibly unfeasible. Therefore, only the expected dominant reaction paths of a chemical reaction network (e.g., a catalytic cycle or an enzymatic cascade) are usually explored in practice. Here, we present a computational protocol that constructs such networks in a parallelized and automated manner. Molecular structures of reactive complexes are generated based on heuristic rules derived from conceptual electronic-structure theory and subsequently optimized by quantum chemical methods to produce stable intermediates of an emerging reaction network. Pairs of intermediates in this network that might be related by an elementary reaction according to some structural similarity measure are then automatically detected and subjected to an automated search for the connecting transition state. The results are visualized as an automatically generated network graph, from which a comprehensive picture of the mechanism of a complex chemical process can be obtained that greatly facilitates the analysis of the whole network. We apply our protocol to the Schrock dinitrogen-fixation catalyst to study alternative pathways of catalytic ammonia production.
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