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Area of Science:

  • Biochemistry
  • Structural Biology
  • Bioinformatics

Background:

  • Catalytic promiscuity and de novo design enable novel enzyme activities.
  • Predicting enzyme function is crucial for biocatalyst development.

Purpose of the Study:

  • To develop and validate a structural bioinformatic method for predicting enzyme catalytic activities.
  • To identify novel enzymes with ene-reductase activity using this method.

Main Methods:

  • Developed a method to predict enzyme activity based on 3D functional group arrangements ('catalophores') in active sites.
  • Identified two candidate enzymes with predicted ene-reductase activity.
  • Compared predicted enzymes with known Old Yellow Enzyme family members using structural and biochemical analyses.

Main Results:

  • Identified two enzymes with promiscuous ene-reductase activity, despite distinct sequences and folds from known enzymes.
  • High-resolution crystal structures showed conserved substrate binding modes compared to Old Yellow Enzymes.
  • Biochemical data confirmed ene-reductase activity and revealed inverted stereoselectivity for certain substrates.

Conclusions:

  • The 'catalophore' method successfully predicts novel enzyme activities.
  • This approach can identify viable starting points for engineering new biocatalysts.
  • The identified enzymes represent novel ene-reductases with potential biotechnological applications.