CatScore: evaluating asymmetric catalyst design at high efficiency-Reference-Cited by-同舟云学术

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CatScore: evaluating asymmetric catalyst design at high efficiency

Published:2024 Issue:8 Volume:3 Page:1624-1637
ISSN:2635-098X
Container-title:Digital Discovery
language:en
Short-container-title:Digital Discovery

Author:

Yan Bing¹^ORCID,Cho Kyunghyun¹

Affiliation:

1. Department of Computer Science, New York University, 60 5th Avenue, New York, NY 10011, USA

Abstract

We introduce CatScore, a learning-based evaluation metric tailored for asymmetric catalysis in organic chemistry. CatScore enables highly efficient and effective evaluation of diverse catalyst design models at both the instance and system levels.

Funder

Samsung Advanced Institute of Technology

National Science Foundation

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/DD/D4DD00114A

Reference44 articles.

1. Asymmetric Catalysis Special Feature Part I: Asymmetric catalysis: An enabling science

2. Organic synthesis provides opportunities to transform drug discovery

3. Copper Hydride-Catalyzed Enantioselective Olefin Hydromethylation

4. A unified machine-learning protocol for asymmetric catalysis as a proof of concept demonstration using asymmetric hydrogenation

5. Data-driven catalyst optimization for stereodivergent asymmetric synthesis by iridium/boron hybrid catalysis

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