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Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry
Author(s) -
Dmitrij Rappoport,
Cooper J. Galvin,
Dmitry Yu. Zubarev,
Alán AspuruGuzik
Publication year - 2014
Publication title -
journal of chemical theory and computation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.001
H-Index - 185
eISSN - 1549-9626
pISSN - 1549-9618
DOI - 10.1021/ct401004r
Subject(s) - heuristics , quantum chemical , autocatalysis , computer science , heuristic , chemical reaction , quantum , quantum chemistry , chemistry , chemical process , computational chemistry , molecule , biological system , nanotechnology , materials science , physics , quantum mechanics , organic chemistry , artificial intelligence , supramolecular chemistry , catalysis , biology , operating system
While structures and reactivities of many small molecules can be computed efficiently and accurately using quantum chemical methods, heuristic approaches remain essential for modeling complex structures and large-scale chemical systems. Here, we present a heuristics-aided quantum chemical methodology applicable to complex chemical reaction networks such as those arising in cell metabolism and prebiotic chemistry. Chemical heuristics offer an expedient way of traversing high-dimensional reactive potential energy surfaces and are combined here with quantum chemical structure optimizations, which yield the structures and energies of the reaction intermediates and products. Application of heuristics-aided quantum chemical methodology to the formose reaction reproduces the experimentally observed reaction products, major reaction pathways, and autocatalytic cycles.

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