Wed, 05 Mar 2025
Seminar Series
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Dr Jeanine Amacher

Western Washington University

All Residues Considered: Specificity determinants in bacterial sortase enzymes

Wednesday, March 05, 2025
C9000 @ 3:30 p.m.

Host: Dr. Erika Plettner

 

Abstract


Sortases are cysteine transpeptidases located at the cell wall of Gram-positive bacteria. These enzymes are responsible for ligating proteins to the surface of these organisms. As such, they are an attractive target for novel antibiotic design. Sortases also see widespread use in protein engineering via sortase-mediated ligation (SML) applications, e.g., in the production of antibody/nanobody-drug conjugates, vaccines, insulin derivatives, etc. The first of this family discovered, the class A sortase from Staphylococcus aureus, is the gold standard for SML experiments. However, this enzyme is very specific for its L-P-X-T-G target motif (X = any amino acid) and while engineered variants show relatively higher catalytic efficiency than wild-type, it remains a relatively poor enzyme. Using protein biochemistry and structural biology, our lab investigates specificity determinants in sortase enzymes. We previously used X-ray crystallography, mutagenesis, biochemical assays, and molecular dynamics simulations to characterize the reaction of Streptococcus class A sortases, focused primarily on specificity-determining loops near the active site. This included a description of the mechanism by which certain sequences are alternatively cleaved by Streptococcus pyogenes sortase A, as well as preliminary work investigating the role of the transmembrane domain in the full-length enzyme. Furthermore, we expanded our position-specific investigations into class B sortases, specifically in understanding how the class B sortase from Bacillus anthracis requires positions beyond a canonical pentapeptide recognition motif for activity. For both classes A and B sortases, we revealed additional specificity determinants that greatly affect enzyme efficiency. Taken together, our data confirmed that a deeper understanding of substrate recognition in bacterial sortase enzymes can be used to inform next-generation tools for use in SML protein engineering.