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"Site and Mutation"-Specific Predictions Enable Minimal Directed Evolution Libraries.

Jeffrey C Moore, Agustina Rodriguez-Granillo, Alejandro Crespo

  • 1ATUM , 37950 Central Court , Newark , California 94560 , United States.

ACS Synthetic Biology
|May 22, 2018
PubMed
Summary
This summary is machine-generated.

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Predictive computational methods can accelerate enzyme evolution by identifying beneficial mutations. Focused libraries of less than 100 variants improved transaminase activity up to ninefold, despite some inactivating mutations.

Area of Science:

  • Biocatalysis
  • Protein Engineering
  • Directed Evolution

Background:

  • Traditional directed evolution relies on random mutagenesis, which is inefficient.
  • Sequence-based and structure-based methods identify

Purpose of the Study:

  • To evaluate the predictive power of sequence-based (Protein GPS) and structure-based (Bioluminate/MOE) methods for identifying specific beneficial amino acid substitutions.
  • To accelerate enzyme evolution by reducing library size and screening burden.

Main Methods:

  • Focused mutagenesis libraries were designed using sequence and structure-based predictions.
  • Libraries were limited to <100 variants containing specific amino acid substitutions.
  • Variants were screened for improved activity in ATA-117 R-selective transaminase evolution.
Keywords:
BioluminateMOEProtein GPSR-specific transaminase ATA-117directed evolutionin silico mutagenesis

Related Experiment Videos

Main Results:

  • 9% and 18% of predicted substitutions improved transaminase activity.
  • Sequence-based and structure-based methods predicted 30% and 45% inactivating mutations, respectively.
  • Combined mutations from each method yielded 7- and 9-fold increases in activity over wild-type.

Conclusions:

  • Sequence and structure-based methods can identify beneficial mutations for enzyme engineering.
  • Despite some inactivating predictions, focused libraries significantly accelerate the discovery of improved biocatalysts.
  • These methods offer a powerful strategy for rapid enzyme optimization.