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The first structure-function study of GH151 α-l-fucosidase uncovers new oligomerization pattern, active site complementation, and selective substrate specificity.

Terézia Koval'ováTomáš Koval'Jan StránskýPetr KolenkoJarmila DuškováLeona ŠvecováPatricie VodičkováVojtech SpiwokEva BenešováPetra LipovováJan Dohnalek
Published in: The FEBS journal (2022)
Fucosylated compounds are abundantly present in nature and are associated with many biological processes, therefore carrying great potential for use in medicine and biotechnology. Efficient ways to modify fucosylated compounds are still being developed. Promising results are provided by glycosyl hydrolases with transglycosylating activities, such as α-l-fucosidase isoenzyme 2 from Paenibacillus thiaminolyticus (family GH151 of Carbohydrate-Active enZYmes). Currently, there is no 3D structure representing this glycoside hydrolase family and only a few members have been investigated. Here, we present the first structure-function study of a GH151 member, providing the key insights into its specific oligomerization and active site properties. According to the crystal structure, small-angle X-ray scattering data and catalytic investigation, this enzyme functions as a tetramer of a new type and represents the second known case of active site complementation among all α-l-fucosidases. Mutation of the active site-complementing residue histidine 503 to alanine confirmed its influence on α-l-fucosidase activity and, specifically, on substrate binding. Several unique features of GH151 family α-l-fucosidases were revealed, including the oligomerization pattern, active site accessibility and complementation, and substrate selectivity. Some common properties of GH151 glycosyl hydrolases then would be the overall three-domain structure and conservation of the central domain loop 2 function, including its complementation role and the formation of the carbohydrate-binding platform in the active site vicinity.
Keyphrases
  • growth hormone
  • crystal structure
  • high resolution
  • structural basis
  • amino acid
  • high throughput
  • risk assessment
  • electronic health record
  • single cell
  • machine learning
  • data analysis