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Rational assignment of key motifs for function guides in silico enzyme identification


Biocatalysis has emerged as a powerful alternative to traditional chemistry, especially for asymmetric synthesis. One key requirement during process development is the discovery of a biocatalyst with an appropriate enantiopreference and enantioselectivity, which can be achieved, for instance, by protein engineering or screening of metagenome libraries. We have developed an in silico strategy for a sequence-based prediction of substrate specificity and enantiopreference. First, we used rational protein design to predict key amino acid substitutions that indicate the desired activity. Then, we searched protein databases for proteins already carrying these mutations instead of constructing the corresponding mutants in the laboratory. This methodology exploits the fact that naturally evolved proteins have undergone selection over millions of years, which has resulted in highly optimized catalysts. Using this in silico approach, we have discovered 17 (R)-selective amine transaminases, which catalyzed the synthesis of several (R)-amines with excellent optical purity up to >99% enantiomeric excess.

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Figure 1: Strategies for protein engineering.
Figure 2: Identification of key amino acid motifs that allow prediction of function of PLP-dependent fold class IV proteins.
Figure 3: Characterization of the discovered (R)-selective amine transaminases.

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Authors and Affiliations



K.R. and U.T.B. initiated the project. M.H. designed the in silico strategy, devised the annotation algorithm and performed the database search and identification of the putative amine transaminases. M.H. expressed and confirmed amine transaminase activity and (R)-selectivity for the first three proteins. S.S. coordinated the comparative characterization of all proteins and performed cloning, expression, purification, data collection and data analysis. H.J. contributed to gene cloning, protein expression and activity measurements. U.T.B. and M.H. cowrote the paper, and all authors read and edited the manuscript.

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Correspondence to Uwe T Bornscheuer.

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Competing interests

Karen Robins is an employee of Lonza AG, which sponsored the research at Greifswald University.

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Supplementary Results, Supplementary Figures 1–7 and Supplementary Tables 1–5 (PDF 4808 kb)

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Höhne, M., Schätzle, S., Jochens, H. et al. Rational assignment of key motifs for function guides in silico enzyme identification. Nat Chem Biol 6, 807–813 (2010).

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