An interaction between the transmembrane domains of Streptococcus pyogenes sortase A and its endogenous substrate M protein revealed by molecular dynamics simulations
Nathan G AveryiD, Elise F. Tahti, Paul Clinton SpiegeliD, John M. AntosiD, James McCartyiD, Jeanine F. AmacheriD
Abstract
Sortase enzymes are cysteine transpeptidases at the cell surface of gram-positive bacteria. Localized to distinct foci on the cell membrane, class A sortases (SrtAs) recognize a cell wall sorting signal (CWSS), and following cleavage at this specific binding motif, target proteins are ligated to precursors of the growing peptidoglycan layer. This activity of SrtA enzymes is utilized extensively in sortase-mediated ligation (SML) strategies, for a variety of protein engineering applications. Typically, engineered variants of SrtA are used for SML experiments considering the relatively low catalytic efficiency of this enzyme. Understandably, most biochemical studies are conducted with the isolated catalytic domain of SrtA enzymes from various bacteria, and the stereochemistry of the endogenous interaction between SrtA and substrate is not well understood. Here, we used AlphaFold2 to create a model of the full-length SrtA enzyme from Streptococcus pyogenes (spySrtA) with or without either a peptide substrate or a portion of M protein, a cellular target. We ran triplicate 500 ns molecular dynamics simulations for each model embedded in a lipid bilayer, which revealed several stereochemical features of this system. Contact map analyses revealed specific interactions between catalytic domain positions of spySrtA and the lipid bilayer, as well as between the enzyme and M protein residues outside the canonical LPXTG pentapeptide CWSS. We also characterized a potential transmembrane domain interaction between spySrtA and M protein that we predict orients and stabilizes substrate binding. Taken together, these interactions likely increase the catalytic efficiency of the enzyme for its substrates in vivo, and may provide important stereochemical insights for SML uses.
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