PCA-Based Database Mining Enables the Discovery of Bacterial Carbene Transferases for Stereodivergent Cyclopropanation

Kato, Shunsuke; Takeuchi, Koki; Umeda, Kohei et al.

Angewandte Chemie - International Edition, 2026, 65(10), e26025

Number of Access:43（2026-06-02 04:51 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/104257

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Title
PCA-Based Database Mining Enables the Discovery of Bacterial Carbene Transferases for Stereodivergent Cyclopropanation
Creator
NRID
1000060909125 1000060909125
CreatorName
Kato, Shunsuke
CreatorName
Takeuchi, Koki
CreatorName
Umeda, Kohei
NRID
1000090891622 1000090891622
CreatorName
Kudo, Hisashi
NRID
1000020529606 1000020529606
CreatorName
Hasunuma, Tomohisa
NRID
1000020222226 1000020222226
ORCID
0000-0002-2215-935X 0000-0002-2215-935X
researchmap permalink
20190602_Sun 20190602_Sun
Scopus Author ID
55735983400 55735983400
CreatorName
Hayashi, Takashi
Subject
biocatalysis
database mining
enzyme discovery
hemoproteins
stereodivergent synthesis
Description
Kato S., Takeuchi K., Umeda K., et al. PCA-Based Database Mining Enables the Discovery of Bacterial Carbene Transferases for Stereodivergent Cyclopropanation. Angewandte Chemie - International Edition 65, e26025 (2026); https://doi.org/10.1002/anie.202526025.
Abstract
Protein engineering is a practical approach to providing enzymes with an “abiotic” catalytic activity. However, it remains difficult to explore the full diversity of natural sequence space through the engineering of a single specific protein. As an alternative to these protein engineering approaches, we here demonstrate a database mining approach using a principal component analysis (PCA)-based clustering method to facilitate the identification of promising enzyme candidates. As a proof of concept, we applied this method to the cyclopropanation of styrene, and the sequence space of bacterial globins in the database was extensively investigated. By screening 275 globins from 171 different organisms, we successfully discovered enzymes capable of catalyzing stereodivergent carbene transfer reactions. Furthermore, statistical analyses of sequence data allowed us to detect characteristic structural properties of these globins, which determine the unique stereoselectivity of cyclopropanation. While these bioinformatics tools have primarily been applied to predict enzymes’ natural biological functions, this study demonstrates their applicability to exploring enzyme candidates for abiotic reactions unrelated to their native biological activity. Given the increasing interest in biocatalytic applications beyond natural reactivity, this PCA-based mining approach provides a promising direction for expanding the functional diversity of biocatalysts.
Publisher
John Wiley and Sons Inc
Source Title
Angewandte Chemie - International Edition
Volume (Issue)
65(10)
Page
e26025
Date of Issued
2026-01-28
Language
English
Handle URL
https://hdl.handle.net/11094/104257
PISSN
14337851
eISSN
15213773
Relation.isIdenticalTo
DOI (Publisher Version)
https://doi.org/10.1002/anie.202526025
Access Rights
open access
CopyRight
This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
oaire:version
Version of Record
Category
学術雑誌論文 Journal Article