Machine learning gene mining method and phosphinothricin dehydrogenase mutant for amino translocation

US11781117B2 · kind B2 · utility

Assignee

• ZHEJIANG UNIVERSITY OF TECHNOLOGY · CN

Inventors

• Yaping Xue · Dongguan, CN
• Feng Cheng · Zhejiang, CN
• Dongyang Wu · Hangzhou City, CN
• Shuping Zou · Hangzhou City, CN
• Jianmiao Xu · Hangzhou City, CN
• Yuguo Zheng · Zhejiang, CN

Key dates

• Filing date: Oct 20, 2021
• Grant date: Oct 10, 2023
• Expiry date: Oct 20, 2041

Classification

• Technology area (CPC C): Chemistry; Metallurgy
• CPC primary: C12Y104/01004
• WIPO field: Biotechnology
• WIPO sector: Chemistry

Abstract

Disclosed are a machine learning gene mining method and a phosphinothricin dehydrogenase mutant for amino translocation. The phosphinothricin dehydrogenase mutant for amino translocation is obtained by mutation of a wild-type phosphinothricin dehydrogenase with an amino acid sequence as shown in SEQ ID No.2 at one of the following sites: (1) E263D-K134R-H96A-R290V; (2) E263D-K134R-H96A; (3) E263D-K134R; (4) E263D; (5) E263N; (6) E263C; and (7) E263G. The present invention utilizes the site-saturation mutagenesis technology to mutate a phosphinothricin dehydrogenase gene as shown in SEQ ID No. 1, finds that the 263rd, 134th, 290th and 290th positions are the key sites affecting enzyme activity and stereoselectivity, and obtains a mutant with enzyme activity and ee value much higher than those of the parent phosphinothricin dehydrogenase.