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Area of Science:

  • Enzymology
  • Protein Engineering
  • Biocatalysis

Background:

  • Enzyme substrate specificity is crucial but challenging to understand and engineer at a molecular level.
  • D-amino acid oxidase (DAOx) from Rhodotorula gracilis serves as a model promiscuous enzyme for studying specificity.

Purpose of the Study:

  • To systematically map how mutations affect the substrate preferences of DAOx.
  • To identify mechanisms underlying specificity determination and guide enzyme engineering.

Main Methods:

  • Utilized enzyme proximity sequencing (EP-Seq) to generate ~40,000 sequence-phenotype pairs.
  • Assessed ~6,500 DAOx variants against five D-amino acid substrates with varying properties.

Main Results:

  • Identified substrate-specific mutations distributed across the enzyme structure.
  • Found active site mutations strongly shift specificity but reduce activity; distal mutations subtly modulate specificity with minimal activity loss.
  • Discovered allosteric hotspots influencing specificity and characterized variants with exclusive specificity or large preference changes (up to 230-fold).

Conclusions:

  • Established a powerful framework for decoding enzyme specificity using large-scale variant profiling.
  • Demonstrated that combining complementary mutations enhances substrate discrimination for rational biocatalyst design.
  • Provided foundational datasets for advancing AI-guided enzyme engineering.