Improving the analysis of enzyme kinetics

Enzymes catalyze thousands of biochemical reactions and studying their operation is essential for understanding the chemistry of life. Elucidating the mechanism of enzyme-catalyzed reactions requires the analysis of experimental data to determine reaction rates under various conditions.

While the Michaelis–Menten kinetic equation works well for traditional single-site substrate reactions, DNA modifying enzymes acting on molecules with multiple substrate sites require a different approach. Barel, Reich, and Brown have previously come up with a theoretical framework to model and interpret the enzymatic turnover kinetics of two-site substrates, but the resulting equations were difficult to use in practice, due to the noise present in the experimental data.

Now, the same group of researchers have improved upon their previous model to make it more practical for interpreting real-world experiments. The present work takes the previously derived differential rate laws and integrates them to provide implicit time-dependent functions for the substrate and product concentrations, which are directly comparable to the raw experimental data. This approach lessens the impact of experimental uncertainties, or noise, and makes it feasible to interpret experiments that are not amenable to the original approach.

To demonstrate practical utility, they successfully analyzed data for DNA methylation by DNA adenine methyltransferase, which were impossible to analyze using the previous differential rate laws.

“Our work has provided a new tool for enzymologists to analyze their experimental data,” said author Frank Brown. “In particular, it should now be straightforward to extract information about both the processive and distributive aspects of enzyme turnover on multi-site substrates. This may prove important for studying the mechanisms of protein translocation along DNA.”

Source: “Integrated rate laws for processive and distributive enzymatic turnover,” by Itay Barel, Norbert O. Reich, and Frank L. H. Brown, The Journal of Chemical Physics (2019). The article can be accessed at http://doi.org/10.1063/1.5097576 .