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Issue 4, 2018
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Efficient prediction of reaction paths through molecular graph and reaction network analysis

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Abstract

Despite remarkable advances in computational chemistry, prediction of reaction mechanisms is still challenging, because investigating all possible reaction pathways is computationally prohibitive due to the high complexity of chemical space. A feasible strategy for efficient prediction is to utilize chemical heuristics. Here, we propose a novel approach to rapidly search reaction paths in a fully automated fashion by combining chemical theory and heuristics. A key idea of our method is to extract a minimal reaction network composed of only favorable reaction pathways from the complex chemical space through molecular graph and reaction network analysis. This can be done very efficiently by exploring the routes connecting reactants and products with minimum dissociation and formation of bonds. Finally, the resulting minimal network is subjected to quantum chemical calculations to determine kinetically the most favorable reaction path at the predictable accuracy. As example studies, our method was able to successfully find the accepted mechanisms of Claisen ester condensation and cobalt-catalyzed hydroformylation reactions.

Graphical abstract: Efficient prediction of reaction paths through molecular graph and reaction network analysis

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Publication details

The article was received on 18 Aug 2017, accepted on 11 Dec 2017 and first published on 12 Dec 2017


Article type: Edge Article
DOI: 10.1039/C7SC03628K
Citation: Chem. Sci., 2018,9, 825-835
  • Open access: Creative Commons BY license
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    Efficient prediction of reaction paths through molecular graph and reaction network analysis

    Y. Kim, J. W. Kim, Z. Kim and W. Y. Kim, Chem. Sci., 2018, 9, 825
    DOI: 10.1039/C7SC03628K

    This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Material from this article can be used in other publications provided that the correct acknowledgement is given with the reproduced material.

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