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Computational tools for the prediction of site- and regioselectivity of organic reactions

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Peer-reviewed

Repository URI

https://www.repository.cam.ac.uk/handle/1810/381230

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Primary Published version (3.24 MB)
 Bibliographic metadata (579.75 KB)
 Supporting information (17.74 MB)

Type

Article

Change log

Authors

Sigmund, Lukas M  ORCID logo  https://orcid.org/0000-0003-2667-2342
Assante, Michele  ORCID logo  https://orcid.org/0009-0007-3014-8662
Johansson, Magnus J  ORCID logo  https://orcid.org/0000-0002-0904-2835
Norrby, Per-Ola  ORCID logo  https://orcid.org/0000-0002-2419-0705
Jorner, Kjell  ORCID logo  https://orcid.org/0000-0002-4191-6790

Abstract

This article reviews computational tools for the prediction of the regio- and site-selectivity of organic reactions. It spans from quantum chemical procedures to deep learning models and showcases the application of the presented tools.

Description

Acknowledgements: L. M. S. and M. A. are part of the AstraZeneca PostDoc program and acknowledge its support. This publication was created as part of NCCR Catalysis (180544), a National Centre of Competence in Research funded by the Swiss National Science Foundation.


Publication status: Published

Keywords

3405 Organic Chemistry, 34 Chemical Sciences, Machine Learning and Artificial Intelligence, Networking and Information Technology R&D (NITRD)

Journal Title

Chemical Science

Conference Name

Journal ISSN

2041-6520
2041-6539

Volume Title

Publisher

Royal Society of Chemistry (RSC)

Publisher DOI

https://doi.org/10.1039/d5sc00541h

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Except where otherwised noted, this item's license is described as https://creativecommons.org/licenses/by/3.0/
Sponsorship
NCCR Catalysis (180544)
AstraZeneca Mölndal (Unassigned)

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