Issue 46, 2022

OSCAR: an extensive repository of chemically and functionally diverse organocatalysts

Abstract

The automated construction of datasets has become increasingly relevant in computational chemistry. While transition-metal catalysis has greatly benefitted from bottom-up or top-down strategies for the curation of organometallic complexes libraries, the field of organocatalysis is mostly dominated by case-by-case studies, with a lack of transferable data-driven tools that facilitate both the exploration of a wider range of catalyst space and the optimization of reaction properties. For these reasons, we introduce OSCAR, a repository of 4000 experimentally derived organocatalysts along with their corresponding building blocks and combinatorially enriched structures. We outline the fragment-based approach used for database generation and showcase the chemical diversity, in terms of functions and molecular properties, covered in OSCAR. The structures and corresponding stereoelectronic properties are publicly available (https://archive.materialscloud.org/record/2022.106) and constitute the starting point to build generative and predictive models for organocatalyst performance.

Graphical abstract: OSCAR: an extensive repository of chemically and functionally diverse organocatalysts

Supplementary files

Article information

Article type
Edge Article
Submitted
29 7月 2022
Accepted
24 10月 2022
First published
25 10月 2022
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2022,13, 13782-13794

OSCAR: an extensive repository of chemically and functionally diverse organocatalysts

S. Gallarati, P. van Gerwen, R. Laplaza, S. Vela, A. Fabrizio and C. Corminboeuf, Chem. Sci., 2022, 13, 13782 DOI: 10.1039/D2SC04251G

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