Structure- and Data-Driven Protein Engineering of Transaminases for Improving Activity and Stereoselectivity

Yu-Fei Ao1,2,3, Shuxin Pei4, Chao Xiang1

  • 1Department of Biotechnology and Enzyme Catalysis, Institute of Biochemistry, University of Greifswald, Felix-Hausdorff-Str. 4, 17487, Greifswald, Germany.

Summary

Researchers developed a machine learning model to predict amine transaminase (ATA) activity and stereoselectivity. This approach aids in engineering biocatalysts for chiral amine synthesis, overcoming data limitations.

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