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Achieving Functionality Through Modular Build-up: Structure and Size Selection of Serine Oligopeptidases
Anna J Kiss-Szemán1, Veronika Harmat1,2, Dóra K Menyhárd3
1Laboratory of Structural Chemistry and Biology, Institute of Chemistry, Eotvos Lorand University, Budapest, Hungary.
Prolyl oligopeptidase family enzymes (S9 family) select substrates by size and specificity. Structural comparisons reveal key features for substrate selectivity and enzyme efficiency, aiding drug design for various diseases.
Area of Science:
- Biochemistry
- Enzymology
- Structural Biology
Background:
- Prolyl oligopeptidase family enzymes (S9 family) are serine proteases with unique structural and regulatory features.
- They hydrolyze oligopeptides smaller than 30 amino acids and are implicated in amnesia, schizophrenia, type 2 diabetes, and other diseases.
- Understanding their substrate selectivity is crucial for drug development.
Purpose of the Study:
- To elucidate the structural basis of substrate selectivity and efficiency in the S9 enzyme family.
- To identify key structural features governing substrate size selection and enzyme regulation.
- To provide a framework for predicting the structure and function of uncharacterized S9 family members.
Main Methods:
- Comparative structural analysis of various S9 family enzyme members.
- Identification of conserved and variable structural elements.
- Correlation of structural features with substrate specificity and enzyme activity.
Main Results:
- Two critical structural features influencing selectivity and efficiency were identified: domain interaction stability and beta-edge accessibility.
- Domain interactions are crucial for stabilizing the catalytic triad, and their disruption can lead to enzyme deactivation.
- Beta-edge accessibility guides multimerization, forming channels for size-based substrate selection.
Conclusions:
- Structural insights into S9 family enzymes explain their unique substrate size selection mechanism.
- These findings offer a basis for designing novel inhibitors targeting S9 enzymes for therapeutic purposes.
- The identified structural cornerstones can predict the multimeric state and selection strategy of unknown S9 family structures.
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