Cargando…

The Impact of Computational Uncertainties on the Enantioselectivity Predictions: A Microkinetic Modeling of Ketone Transfer Hydrogenation with a Noyori‐type Mn‐diamine Catalyst

Selectivity control is one of the most important functions of a catalyst. In asymmetric catalysis the enantiomeric excess (e.e.) is a property of major interest, with a lot of effort dedicated to developing the most enantioselective catalyst, understanding the origin of selectivity, and predicting s...

Descripción completa

Detalles Bibliográficos
Autores principales: Krieger, Annika M., Pidko, Evgeny A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8453751/
https://www.ncbi.nlm.nih.gov/pubmed/34589158
http://dx.doi.org/10.1002/cctc.202100341
_version_ 1784570337991589888
author Krieger, Annika M.
Pidko, Evgeny A.
author_facet Krieger, Annika M.
Pidko, Evgeny A.
author_sort Krieger, Annika M.
collection PubMed
description Selectivity control is one of the most important functions of a catalyst. In asymmetric catalysis the enantiomeric excess (e.e.) is a property of major interest, with a lot of effort dedicated to developing the most enantioselective catalyst, understanding the origin of selectivity, and predicting stereoselectivity. Herein, we investigate the relationship between predicted selectivity and the uncertainties in the computed energetics of the catalytic reaction mechanism obtained by DFT calculations in a case study of catalytic asymmetric transfer hydrogenation (ATH) of ketones with an Mn‐diamine catalyst. Data obtained from our analysis of DFT data by microkinetic modeling is compared to results from experiment. We discuss the limitations of the conventional reductionist approach of e.e. estimation from assessing the enantiodetermining steps only. Our analysis shows that the energetics of other reaction steps in the reaction mechanism have a substantial impact on the predicted reaction selectivity. The uncertainty of DFT calculations within the commonly accepted energy ranges of chemical accuracy may reverse the predicted e.e. with the non‐enantiodetermining steps contributing to e.e. deviations of up to 25 %.
format Online
Article
Text
id pubmed-8453751
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-84537512021-09-27 The Impact of Computational Uncertainties on the Enantioselectivity Predictions: A Microkinetic Modeling of Ketone Transfer Hydrogenation with a Noyori‐type Mn‐diamine Catalyst Krieger, Annika M. Pidko, Evgeny A. ChemCatChem Full Papers Selectivity control is one of the most important functions of a catalyst. In asymmetric catalysis the enantiomeric excess (e.e.) is a property of major interest, with a lot of effort dedicated to developing the most enantioselective catalyst, understanding the origin of selectivity, and predicting stereoselectivity. Herein, we investigate the relationship between predicted selectivity and the uncertainties in the computed energetics of the catalytic reaction mechanism obtained by DFT calculations in a case study of catalytic asymmetric transfer hydrogenation (ATH) of ketones with an Mn‐diamine catalyst. Data obtained from our analysis of DFT data by microkinetic modeling is compared to results from experiment. We discuss the limitations of the conventional reductionist approach of e.e. estimation from assessing the enantiodetermining steps only. Our analysis shows that the energetics of other reaction steps in the reaction mechanism have a substantial impact on the predicted reaction selectivity. The uncertainty of DFT calculations within the commonly accepted energy ranges of chemical accuracy may reverse the predicted e.e. with the non‐enantiodetermining steps contributing to e.e. deviations of up to 25 %. John Wiley and Sons Inc. 2021-06-10 2021-08-06 /pmc/articles/PMC8453751/ /pubmed/34589158 http://dx.doi.org/10.1002/cctc.202100341 Text en © 2021 The Authors. ChemCatChem published by Wiley-VCH GmbH https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Full Papers
Krieger, Annika M.
Pidko, Evgeny A.
The Impact of Computational Uncertainties on the Enantioselectivity Predictions: A Microkinetic Modeling of Ketone Transfer Hydrogenation with a Noyori‐type Mn‐diamine Catalyst
title The Impact of Computational Uncertainties on the Enantioselectivity Predictions: A Microkinetic Modeling of Ketone Transfer Hydrogenation with a Noyori‐type Mn‐diamine Catalyst
title_full The Impact of Computational Uncertainties on the Enantioselectivity Predictions: A Microkinetic Modeling of Ketone Transfer Hydrogenation with a Noyori‐type Mn‐diamine Catalyst
title_fullStr The Impact of Computational Uncertainties on the Enantioselectivity Predictions: A Microkinetic Modeling of Ketone Transfer Hydrogenation with a Noyori‐type Mn‐diamine Catalyst
title_full_unstemmed The Impact of Computational Uncertainties on the Enantioselectivity Predictions: A Microkinetic Modeling of Ketone Transfer Hydrogenation with a Noyori‐type Mn‐diamine Catalyst
title_short The Impact of Computational Uncertainties on the Enantioselectivity Predictions: A Microkinetic Modeling of Ketone Transfer Hydrogenation with a Noyori‐type Mn‐diamine Catalyst
title_sort impact of computational uncertainties on the enantioselectivity predictions: a microkinetic modeling of ketone transfer hydrogenation with a noyori‐type mn‐diamine catalyst
topic Full Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8453751/
https://www.ncbi.nlm.nih.gov/pubmed/34589158
http://dx.doi.org/10.1002/cctc.202100341
work_keys_str_mv AT kriegerannikam theimpactofcomputationaluncertaintiesontheenantioselectivitypredictionsamicrokineticmodelingofketonetransferhydrogenationwithanoyoritypemndiaminecatalyst
AT pidkoevgenya theimpactofcomputationaluncertaintiesontheenantioselectivitypredictionsamicrokineticmodelingofketonetransferhydrogenationwithanoyoritypemndiaminecatalyst
AT kriegerannikam impactofcomputationaluncertaintiesontheenantioselectivitypredictionsamicrokineticmodelingofketonetransferhydrogenationwithanoyoritypemndiaminecatalyst
AT pidkoevgenya impactofcomputationaluncertaintiesontheenantioselectivitypredictionsamicrokineticmodelingofketonetransferhydrogenationwithanoyoritypemndiaminecatalyst