Efficient prediction of reaction paths through molecular graph and reaction network analysis

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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.
Publisher
ROYAL SOC CHEMISTRY
Issue Date
2018-01
Language
English
Article Type
Article
Keywords

POTENTIAL-ENERGY SURFACE; CHEMICAL-REACTION NETWORKS; REACTION-MECHANISMS; ORGANIC-SYNTHESIS; EQUILIBRIUM GEOMETRIES; TRANSITION STRUCTURES; DENSITY FUNCTIONALS; AUTOMATED DISCOVERY; REACTION DESIGN; REACTION STEPS

Citation

CHEMICAL SCIENCE, v.9, no.4, pp.825 - 835

ISSN
2041-6520
DOI
10.1039/c7sc03628k
URI
http://hdl.handle.net/10203/240217
Appears in Collection
CH-Journal Papers(저널논문)
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