Enhanced stereodivergent evolution of carboxylesterase for efficient kinetic resolution of near-symmetric esters through machine learning.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
20 Oct 2024
20 Oct 2024
Historique:
received:
25
01
2024
accepted:
07
10
2024
medline:
21
10
2024
pubmed:
21
10
2024
entrez:
20
10
2024
Statut:
epublish
Résumé
Carboxylesterases serve as potent biocatalysts in the enantioselective synthesis of chiral carboxylic acids and esters. However, naturally occurring carboxylesterases exhibit limited enantioselectivity, particularly toward ethyl 3-cyclohexene-1-carboxylate (CHCE, S1), due to its nearly symmetric structure. While machine learning effectively expedites directed evolution, the lack of models for predicting the enantioselectivity for carboxylesterases has hindered progress, primarily due to challenges in obtaining high-quality training datasets. In this study, we devise a high-throughput method by coupling alcohol dehydrogenase to determine the apparent enantioselectivity of the carboxylesterase AcEst1 from Acinetobacter sp. JNU9335, generating a high-quality dataset. Leveraging seven features derived from biochemical considerations, we quantitively describe the steric, hydrophobic, hydrophilic, electrostatic, hydrogen bonding, and π-π interaction effects of residues within AcEst1. A robust gradient boosting regression tree model is trained to facilitate stereodivergent evolution, resulting in the enhanced enantioselectivity of AcEst1 toward S1. Through this approach, we successfully obtain two stereocomplementary variants, DR3 and DS6, demonstrating significantly increased and reversed enantioselectivity. Notably, DR3 and DS6 exhibit utility in the enantioselective hydrolysis of various symmetric esters. Comprehensive kinetic parameter analysis, molecular dynamics simulations, and QM/MM calculations offer insights into the kinetic and thermodynamic features underlying the manipulated enantioselectivity of DR3 and DS6.
Identifiants
pubmed: 39428434
doi: 10.1038/s41467-024-53191-8
pii: 10.1038/s41467-024-53191-8
doi:
Substances chimiques
Esters
0
Carboxylesterase
EC 3.1.1.1
Carboxylic Acids
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
9057Subventions
Organisme : National Natural Science Foundation of China (National Science Foundation of China)
ID : 22078127, 22378169
Informations de copyright
© 2024. The Author(s).
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