Gene mining-based identification of aldo–keto reductases for highly stereoselective reduction of bulky ketones

Chen Liang , Yao Nie , Xiaoqing Mu , Yan Xu

Bioresources and Bioprocessing ›› 2018, Vol. 5 ›› Issue (1) : 33

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Bioresources and Bioprocessing ›› 2018, Vol. 5 ›› Issue (1) : 33 DOI: 10.1186/s40643-018-0220-x
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Gene mining-based identification of aldo–keto reductases for highly stereoselective reduction of bulky ketones

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Abstract

Background

Aldo–keto reductase (AKR) or alcohol dehydrogenases (ADH)-mediated stereoselective reduction of prochiral carbonyl compounds is an efficient way of preparing single enantiomers of chiral alcohols. However, steric hindrance of substrate affects the catalytic performance of enzymes. The present study aims to discover and identify AKRs/ADHs capable of catalyzing highly stereoselective reduction of sterically hindered ketones.

Results

Five AKRs from different microorganisms (CaCR, ScCR, KmCR, CPR-C1, and CPR-C2) were identified through gene mining, and overexpressed in recombinant Escherichia coli BL21(DE3). The specific activity and stereoselectivity of the AKRs were further evaluated towards various ketoesters and heterocyclic ketones, which are sterically bulky and are valuable in industrial applications. Each purified enzyme exhibited catalytic activity to one or more of the tested substrates. Among the enzymes, ScCR showed a broader substrate spectrum compared to the others. Regarding Km values related to substrate association, we also provided insights into the specificity and preference of certain enzymes. Consequently, enantiopure (R)-methyl mandelate, ethyl (R)-mandelate, ethyl (R)-2-hydroxy-4-phenylbutyrate, and (S)-N-benzyl-3-pyrrolidinol (> 99%e.e.) were obtained through the identified AKRs.

Conclusion

The stereospecific AKRs were obtained through gene mining, which possesses the potential for application in the preparation of important optically active alcohols.

Keywords

Aldo–keto reductase / Carbonyl compound / Gene mining / Stereoselectivity / Substrate specificity

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Chen Liang, Yao Nie, Xiaoqing Mu, Yan Xu. Gene mining-based identification of aldo–keto reductases for highly stereoselective reduction of bulky ketones. Bioresources and Bioprocessing, 2018, 5(1): 33 DOI:10.1186/s40643-018-0220-x

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Funding

National Natural Science Foundation of China(21336009)

Natural Science Foundation of Jiangsu Province(BK20151124)

High-end Foreign Experts Recruitment Program(GDT20183200136)

National First-Class Discipline Program of Light Industry Technology and Engineering(LITE2018-09)

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