Derivatization-Assisted Lipase-Mediated Separation of Optically Pure α-Cyclopentylmandelic Acid Through Enhanced Substrate Recognition

α-Cyclopentylmandelic acid (CPMA) is a chiral α-hydroxycarboxylic acid valuable in pharmaceutical synthesis and asymmetric catalysis. However, it remains challenging to prepare with high optical purity due to its unique steric structure. This study established a chiral resolution strategy using derivatization-assisted lipase-catalyzed kinetic resolution to efficiently prepare optically pure CPMA. We employed acetoxyacetyl chloride derivatization to introduce a diester structure into CPMA that lipase recognizes efficiently and identified recombinant Cal B as the optimal catalyst through enzyme screening. Theoretical calculations suggested that the activity difference resulting from the derivatization strategy stems from spatial recognition rather than electronic effects; the significant difference in binding affinity between the R- and S-substrates provides the driving force for subsequent time-dependent separation. By controlling the reaction time, the (R)- and (S)-CPMA enantiomers could be selectively prepared. This achieved ee values exceeding 99.5% for both enantiomers, with isolated yields over 38% for each. Cal B was immobilized on an ESR carrier and retained good catalytic activity after 12 reuse cycles. The resulting (R)-CPMA was successfully used to synthesize sofpironium bromide, thereby validating the practical feasibility of this process. This strategy provides an effective, environmentally friendly enzymatic route to highly sterically hindered chiral α-hydroxycarboxylic acids.

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Journal
Molecules
Published
2026-09-17
DOI
https://doi.org/10.3390/molecules31183290
Primary Topic
Enzyme Catalysis and Immobilization
Type
article
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article

Derivatization-Assisted Lipase-Mediated Separation of Optically Pure α-Cyclopentylmandelic Acid Through Enhanced Substrate Recognition

Zhizhi Li, Xianwei Long, Qun Lu, Yuhao Zhao
Molecules
Enzyme Catalysis and Immobilization
article

Derivatization-Assisted Lipase-Mediated Separation of Optically Pure α-Cyclopentylmandelic Acid Through Enhanced Substrate Recognition

Zhizhi Li, Xianwei Long, Qun Lu, Yuhao Zhao
article en

Abstract

α-Cyclopentylmandelic acid (CPMA) is a chiral α-hydroxycarboxylic acid valuable in pharmaceutical synthesis and asymmetric catalysis. However, it remains challenging to prepare with high optical purity due to its unique steric structure. This study established a chiral resolution strategy using derivatization-assisted lipase-catalyzed kinetic resolution to efficiently prepare optically pure CPMA. We employed acetoxyacetyl chloride derivatization to introduce a diester structure into CPMA that lipase recognizes efficiently and identified recombinant Cal B as the optimal catalyst through enzyme screening. Theoretical calculations suggested that the activity difference resulting from the derivatization strategy stems from spatial recognition rather than electronic effects; the significant difference in binding affinity between the R- and S-substrates provides the driving force for subsequent time-dependent separation. By controlling the reaction time, the (R)- and (S)-CPMA enantiomers could be selectively prepared. This achieved ee values exceeding 99.5% for both enantiomers, with isolated yields over 38% for each. Cal B was immobilized on an ESR carrier and retained good catalytic activity after 12 reuse cycles. The resulting (R)-CPMA was successfully used to synthesize sofpironium bromide, thereby validating the practical feasibility of this process. This strategy provides an effective, environmentally friendly enzymatic route to highly sterically hindered chiral α-hydroxycarboxylic acids.

MoleculesVol. 31(18)
Southwest Jiaotong University (CN)
Life in Land
Openalex Percentile: Top 18%
Enzyme Catalysis and Immobilization
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Derivatization-Assisted Lipase-Mediated Separation of Optically Pure α-Cyclopentylmandelic Acid Through Enhanced Substrate Recognition — Zhizhi Li, Xianwei Long, et al. · Molecules (2026) | TGRS Research Map | TGRS