Active site plasticity of a computationally designed retro-aldolase enzyme

Richard Obexer, Sabine Studer, Lars Giger, Daniel M. Pinkas, Markus G. Grütter, David Baker, Donald Hilvert*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

20 Citations (Scopus)


RA110 is a computationally designed retro-aldolase enzyme that utilizes amine catalysis to convert 4-hydroxy-4-(6-methoxy-2-naphthyl)-2-butanone to 6-methoxy-2-naphthaldehyde and acetone. The original design accelerated substrate cleavage by a factor of 12 000 over background, and its activity was subsequently increased more than a thousand-fold by directed evolution. The X-ray structure of the evolved catalyst covalently modified with a 1,3-diketone inhibitor deviates substantially from the design model, however, with the ligand adopting a completely different orientation than predicted. Moreover, significant activity was maintained even after relocation of the reactive lysine within the apolar binding pocket. These results suggest that the success of the original design is not ascribable to atomically accurate molecular recognition, but rather to successful placement of a reactive lysine adjacent to an apolar binding pocket. Nevertheless, the stabilizing interactions observed at the active site of the evolved variant suggest that improvements in the precision of design calculations will afford enzymes with higher catalytic activities. What's that in your pocket? A computationally designed and experimentally optimized retro-aldolase enzyme utilizes amine catalysis for substrate cleavage. However, substantial differences between the original design model and experimental structure highlight the need for improved computational protocols. Generating catalysts with true enzyme-like activities will require more than simply placing a reactive lysine adjacent to a hydrophobic pocket.

Original languageEnglish
Pages (from-to)1043-1050
Number of pages8
Issue number4
Publication statusPublished - 1 Jan 2014


  • computational chemistry
  • enzyme catalysis
  • enzyme models
  • protein folding
  • structure-activity relationships


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