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Engineering of a Nucleoside 2′-Deoxyribosyltransferase for Efficient Catalysis of 5-Halogenated-2′-Deoxypyrimidine Nucleosides via Active-Site Channel Expansion

Journal 2026 · IF 3.5 · 发表于 2026 年 5 月 26 日
作者: Zhou Jianguo,Jiang Yanjun,He Ying,Ma Li,Yue Xiaoyang,Zhou Liya,Liu Guanhua,Zheng Xiaobing
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摘要

Nucleoside analogues play a crucial role in antiviral and anticancer drug synthesis. Owing to their high catalytic efficiency and substrate specificity, nucleoside 2′-deoxyribosyltransferases (NDTs) emerge as promising biocatalysts for nucleoside analogue synthesis. However, wild-type NDTs suffer from low yields in synthesizing halogen-substituted 2′-deoxypyrimidine nucleosides due to steric hindrance from halogen substituents in the active pocket and competitive product hydrolysis. Herein we identify an NDT from Bacillus haynesii ( Bh NDT) via sequence screening and introduce an E56T/D60A ( Bh NDT-M2) double mutation to disrupt the salt bridges and increase structural flexibility, thereby widening the active pocket and enhancing catalytic activity. The Bh NDT-M2 mutant displays markedly improved activity and efficiency for synthesizing 5-fluoro-2′-deoxyuridine (FdUrd), achieving 62% of yield under 20 mM substrate, which is twice that of the wild-type. In addition, we find that high substrate concentration can bring an unexpected inhibitory effect on hydrolytic side reactions, which further improve the catalytic performance of Bh NDT-M2, achieving a 55% yield of under 150 mM substrate. The Bh NDT-M2 also exhibits high substrate specificity toward a range of 2′-deoxypyrimidine nucleoside analogues. To facilitate practical applications, Bh NDT-M2 is immobilized onto an amino-functionalized resin, and the resulting immobilized enzyme shows excellent reusability, with only 20% loss of activity after eight cycles. Collectively, these properties establish Bh NDT-M2 as a promising biocatalyst and lay the foundation for large-scale nucleoside analogue synthesis. Graphical The alternative text for this image may have been generated using AI.