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Protein lysine methyltransferases (PKMTs) catalyze the methylation of lysine residues on many different cellular proteins. Despite extensive biochemical and structural studies, focusing on PKMT active site-peptide interactions, little is known regarding how PKMTs recognize globular substrates. To examine whether these enzymes recognize protein substrates through interactions that take place outside of the active site, we have measured SETD6 and SETD7 activity with both protein and peptide RelA substrate. We have utilized the MTase-Glo™ methyltransferase assay to measure the activity of SETD6 and SETD7 with the different RelA substrates and calculated the Michaelis-Menten (MM) parameters. We found an up to ∼12-fold increase in K M of the PKMTs activity with RelA peptide relative to the respective full-length protein, emphasizing the significantly higher PKMT-protein interaction affinity. Examination of SETD6 and SETD7 activity toward the same RelA substrates highlight the similarity in substrate recognition for both PKMTs. Our results show that the interaction affinity of SETD6 and SETD7 with RelA is enhanced through interactions that occur outside of the active site leading to higher catalytic efficiency and specificity. These interactions can significantly vary depending on the PKMT and the specific methylation site on RelA. Overall, our results underline that PKMTs can recognize their substrates through docking interactions that occur out of the active site-peptide region for enhancing their activity and specificity in the cellular environment. [ABSTRACT FROM AUTHOR]

We propose that the time course of an enzyme reaction following the Michaelis-Menten reaction mechanism can be conveniently described by a newly derived algebraic equation, which includes the Lambert Omega function. Following Northrop's ideas [ Anal. Biochem. 321 , 457–461, 1983], the integrated rate equation contains the Michaelis constant ( K M ) and the specificity number ( k S ≡ k cat / K M ) as adjustable parameters, but not the turnover number k cat . A modification of the usual global-fit approach involves a combinatorial treatment of nominal substrate concentrations being treated as fixed or alternately optimized model parameters. The newly proposed method is compared with the standard approach based on the “initial linear region” of the reaction progress curves, followed by nonlinear fit of initial rates to the hyperbolic Michaelis-Menten equation. A representative set of three chelation-enhanced fluorescence EGFR kinase substrates is used for experimental illustration. In one case, both data analysis methods (linear and nonlinear) produced identical results. However, in another test case, the standard method incorrectly reported a finite (50–70 μM) K M value, whereas the more rigorous global nonlinear fit shows that the K M is immeasurably high. [ABSTRACT FROM AUTHOR]