Enhancing the efficiency of directed evolution in focused enzyme libraries by the adaptive substituent reordering algorithm

Xiaojiang Feng, Joaquin Sanchis, Manfred T. Reetz, Herschel Rabitz

Research output: Contribution to journalArticle

34 Scopus citations

Abstract

Directed evolution is a broadly successful strategy for protein engineering in the quest to enhance the stereoselectivity, activity, and thermostability of enzymes. To increase the efficiency of directed evolution based on iterative saturation mutagenesis, the adaptive substituent reordering algorithm (ASRA) is introduced here as an alternative to traditional quantitative structure-activity relationship (QSAR) methods for identifying potential protein mutants with desired properties from minimal sampling of focused libraries. The operation of ASRA depends on identifying the underlying regularity of the protein property landscape, allowing it to make predictions without explicit knowledge of the structure-property relationships. In a proof-of-principle study, ASRA identified all or most of the best enantioselective mutants among the synthesized epoxide hydrolase from Aspergillus niger, in the absence of peptide seeds with high E-values. ASRA even revealed a laboratory error from irregularities of the reordered E-value landscape alone.

Original languageEnglish (US)
Pages (from-to)5646-5654
Number of pages9
JournalChemistry - A European Journal
Volume18
Issue number18
DOIs
StatePublished - Apr 27 2012

All Science Journal Classification (ASJC) codes

  • Catalysis
  • Organic Chemistry

Keywords

  • directed evolution
  • mutagenesis
  • optimization
  • protein engineering
  • structure-activity relationships

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