Matching Biochemical Reaction Kinetics to the Timescales of Life: Structural Determinants That Influence the Autodephosphorylation Rate of Response Regulator Proteins

Abstract

Summary In two-component regulatory systems, covalent phosphorylation typically activates the response regulator signaling protein and hydrolysis of the phosphoryl group reestablishes the inactive state. Despite highly conserved three-dimensional structures and active site features, the rates of catalytic autodephosphorylation for different response regulators vary by a factor of almost 106. Previous studies identified two variable active site residues, corresponding to Escherichia coli CheY residues 59 and 89, that modulate response regulator autodephosphorylation rates about 100-fold. Here, a set of five CheY mutants, which match other “model” response regulators (ArcA, CusR, DctD, FixJ, PhoB, or Spo0F) at variable active site positions corresponding to CheY residues 14, 59 and 89, were characterized functionally and structurally in an attempt to identify mechanisms that modulate autodephosphorylation rate. As expected, the autodephosphorylation rates of the CheY mutants were reduced six- to 40-fold relative to wild type CheY, but all still autodephosphorylated 12- to 80-fold faster than their respective model response regulators. Comparison of X-ray crystal structures of the five CheY mutants (complexed with the phosphoryl group analogue BeF3−) to wild type CheY or corresponding model response regulator structures gave strong evidence for steric obstruction of the phosphoryl group from the attacking water molecule as one mechanism to enhance phosphoryl group stability. Structural data also suggested that impeding the change of a response regulator from the active to inactive conformation might retard the autodephosphorylation reaction if the two processes are coupled, and that the residue at position '58' may contribute to rate modulation. A given combination of amino acids at positions '14', '59', and '89' adopted similar conformations regardless of protein context (CheY or model response regulator), suggesting that knowledge of residue identity may be sufficient to predict autodephosphorylation rate, and hence, the kinetics of the signaling response, in the response regulator family of proteins.

Sirt7 promotes adipogenesis in the mouse by inhibiting autocatalytic activation of Sirt1

“…8) and emphasize the role of posttranslational acetylation in the regulation of Sirt1 activity. Autocatalytic modifications of proteins are common and have been primarily described for kinases (30), acetyltransferases (31), and also for phosphatases (32) but not for deacetylases. An involvement of acetylation/deacetylation in the regulation of enzymatic activity of this class of proteins has mostly remained enigmatic, although acetylation of several protein deacetylases has been reported previously (33).…”

Probing kinase and phosphatase activities of two-component systems in vivo with concentration-dependent phosphorylation profiling

“…Apparently the success of modeling relies on the particular TCS fulfilling the model assumptions (see more discussions in SI Text). Many TCS activities displayed distinct differences, for instance, the rate of RR autodephosphorylation has been shown to range over six orders of magnitude (26). So great differences are expected for the vast number of TCSs; thus successful modeling requires careful examination of individual TCS behaviors.…”

Identification of Regions in the Receiver Domain of the ETHYLENE RESPONSE1 Ethylene Receptor of Arabidopsis Important for Functional Divergence

“…We also targeted amino acids in the C-terminal tail, which has been identified as a region that might be important in ETR1-protein interactions (Müller-Dieckmann et al, 1999) and is another region where there is high amino acid divergence. Finally, autodephosphorylation activity has been observed in receiver domains, and amino acids corresponding to Asn-618, Cys-661, and Asn-694 in ETR1 have been implicated as critical for this activity in other receiver domains (Pazy et al, 2009). We also homology modeled the receiver domains of ETR2 and EIN4 and compared these models to the crystal structure of the ETR1 receiver domain (Fig.…”