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Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities
[Image: see text] Graph-based descriptors, such as bond-order matrices and adjacency matrices, offer a simple and compact way of categorizing molecular structures; furthermore, such descriptors can be readily used to catalog chemical reactions (i.e., bond-making and -breaking). As such, a number of...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9574932/ https://www.ncbi.nlm.nih.gov/pubmed/36190262 http://dx.doi.org/10.1021/acs.jpca.2c06408 |
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author | Ismail, Idil Chantreau Majerus, Raphael Habershon, Scott |
author_facet | Ismail, Idil Chantreau Majerus, Raphael Habershon, Scott |
author_sort | Ismail, Idil |
collection | PubMed |
description | [Image: see text] Graph-based descriptors, such as bond-order matrices and adjacency matrices, offer a simple and compact way of categorizing molecular structures; furthermore, such descriptors can be readily used to catalog chemical reactions (i.e., bond-making and -breaking). As such, a number of graph-based methodologies have been developed with the goal of automating the process of generating chemical reaction network models describing the possible mechanistic chemistry in a given set of reactant species. Here, we outline the evolution of these graph-based reaction discovery schemes, with particular emphasis on more recent methods incorporating graph-based methods with semiempirical and ab initio electronic structure calculations, minimum-energy path refinements, and transition state searches. Using representative examples from homogeneous catalysis and interstellar chemistry, we highlight how these schemes increasingly act as “virtual reaction vessels” for interrogating mechanistic questions. Finally, we highlight where challenges remain, including issues of chemical accuracy and calculation speeds, as well as the inherent challenge of dealing with the vast size of accessible chemical reaction space. |
format | Online Article Text |
id | pubmed-9574932 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-95749322022-10-18 Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities Ismail, Idil Chantreau Majerus, Raphael Habershon, Scott J Phys Chem A [Image: see text] Graph-based descriptors, such as bond-order matrices and adjacency matrices, offer a simple and compact way of categorizing molecular structures; furthermore, such descriptors can be readily used to catalog chemical reactions (i.e., bond-making and -breaking). As such, a number of graph-based methodologies have been developed with the goal of automating the process of generating chemical reaction network models describing the possible mechanistic chemistry in a given set of reactant species. Here, we outline the evolution of these graph-based reaction discovery schemes, with particular emphasis on more recent methods incorporating graph-based methods with semiempirical and ab initio electronic structure calculations, minimum-energy path refinements, and transition state searches. Using representative examples from homogeneous catalysis and interstellar chemistry, we highlight how these schemes increasingly act as “virtual reaction vessels” for interrogating mechanistic questions. Finally, we highlight where challenges remain, including issues of chemical accuracy and calculation speeds, as well as the inherent challenge of dealing with the vast size of accessible chemical reaction space. American Chemical Society 2022-10-03 2022-10-13 /pmc/articles/PMC9574932/ /pubmed/36190262 http://dx.doi.org/10.1021/acs.jpca.2c06408 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Ismail, Idil Chantreau Majerus, Raphael Habershon, Scott Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities |
title | Graph-Driven Reaction
Discovery: Progress, Challenges,
and Future Opportunities |
title_full | Graph-Driven Reaction
Discovery: Progress, Challenges,
and Future Opportunities |
title_fullStr | Graph-Driven Reaction
Discovery: Progress, Challenges,
and Future Opportunities |
title_full_unstemmed | Graph-Driven Reaction
Discovery: Progress, Challenges,
and Future Opportunities |
title_short | Graph-Driven Reaction
Discovery: Progress, Challenges,
and Future Opportunities |
title_sort | graph-driven reaction
discovery: progress, challenges,
and future opportunities |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9574932/ https://www.ncbi.nlm.nih.gov/pubmed/36190262 http://dx.doi.org/10.1021/acs.jpca.2c06408 |
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