Kemp elimination catalysts by computational enzyme design

  • Röthlisberger D
  • Khersonsky O
  • Wollacott A
 et al. 
  • 968


    Mendeley users who have this article in their library.
  • 707


    Citations of this article.


The design of new enzymes for reactions not catalysed by naturally occurring biocatalysts is a challenge for protein engineering and is a critical test of our understanding of enzyme catalysis. Here we describe the computational design of eight enzymes that use two different catalytic motifs to catalyse the Kemp elimination—a model reaction for proton transfer from carbon—with measured rate enhancements of up to 10 5 and multiple turnovers. Mutational analysis confirms that catalysis depends on the computationally designed active sites, and a high-resolution crystal structure suggests that the designs have close to atomic accuracy. Application of in vitro evolution to enhance the computational designs produced a .200-fold increase in k cat /K m (k cat /K m of 2,600 M 21 s 21 and k cat /k uncat of .10 6). These results demonstrate the power of combining computational protein design with directed evolution for creating new enzymes, and we anticipate the creation of a wide range of useful new catalysts in the future. Naturally occurring enzymes are extraordinarily efficient catalysts 1 . They bind their substrates in a well-defined active site with precisely aligned catalytic residues to form highly active and selective catalysts for a wide range of chemical reactions under mild conditions. Nevertheless, many important synthetic reactions lack a naturally occurring enzymatic counterpart. Hence, the design of stable enzymes with new catalytic activities is of great practical interest, with potential applications in biotechnology, biomedicine and industrial processes. Furthermore, the computational design of new enzymes provides a stringent test of our understanding of how naturally occurring enzymes work. In the past several years, there has been exciting progress in designing new biocatalysts 2,3

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in


  • Daniela Röthlisberger

  • Olga Khersonsky

  • Andrew M. Wollacott

  • Lin Jiang

  • Jason DeChancie

  • Jamie Betker

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free