Chemical Mapping Exposes the Importance of Active Site Interactions in Governing the Temperature Dependence of Enzyme Turnover

Abstract

Uncovering the role of global protein dynamics in enzyme turnover is needed to fully understand enzyme catalysis. Recently, we have demonstrated that the heat capacity of catalysis, Δ C P ‡ , can reveal links between the protein free energy landscape, global protein dynamics, and enzyme turnover, suggesting that subtle changes in molecular interactions at the active site can affect long-range protein dynamics and link to enzyme temperature activity. Here, we use a model promiscuous enzyme (glucose dehydrogenase from Sulfolobus solfataricus ) to chemically map how individual substrate interactions affect the temperature dependence of enzyme activity and the network of motions throughout the protein. Utilizing a combination of kinetics, red edge excitation shift (REES) spectroscopy, and computational simulation, we explore the complex relationship between enzyme–substrate interactions and the global dynamics of the protein. We find that changes in Δ C P ‡ and protein dynamics can be mapped to specific substrate–enzyme interactions. Our study reveals how subtle changes in substrate binding affect global changes in motion and flexibility extending throughout the protein.

Immobilization of Kluyveromyces lactis β‐Galactosidase on Meso‐macroporous Silica: Use of Infrared Spectroscopy to Rationalize the Catalytic Efficiency

“…The observed changes on the secondary structure by infrared spectroscopy (and hence the entire macromolecule) could act as a long‐range interference effect on the catalytic pocket. This is emphasized by the fact that localized interactions between the catalytic pocket and the bulk enzyme are essential in the enzyme bioactivity [28] …”

“…This is emphasized by the fact that localized interactions between the catalytic pocket and the bulk enzyme are essential in the enzyme bioactivity. [28] At last, the fact that a meso-macroporous silica carrier was used, pore filling constrains must be accounted for. It is erroneous to compare the bioactivity of adsorbed enzymes in non-porous and those adsorbed in porous silica materials.…”

N-linked glycosylation increases horse radish peroxidase rigidity leading to enhanced activity and stability

“…As in our previous work 32–35 , we therefore numerically modelled each of the spectra using a sum of two skewed Gaussians (Eq 1) as described recently for a de novo haem peroxidase 33 where fi is the measured fluorescence intensity, f max is the maximum emission intensity at wavelength , with a full width at half maximal of w and the ‘skewness’ was controlled by b . Fluorescence spectra were accurately modelled and deconvolved by fitting to such functions as demonstrated by elsewhere.…”

“…Fluorescence spectra were accurately modelled and deconvolved by fitting to such functions as demonstrated by elsewhere. [32][33][34][35] By fitting to a sum of two skewed Gaussians we were able to accurately model the spectral component attributable to tryptophan emission alone. From these models the centre of spectral mass (CSM) was extracted for each spectral component, which allowed quantification of changes in the structure of the fluorescence spectra,…”

“…As in our previous work [32][33][34][35] , we therefore numerically modelled each of the spectra using a sum of two skewed Gaussians (Eq 1) as described recently for a de novo haem peroxidase 33 𝑓𝑖 = 𝑓 ! "# exp (− ln 2) .…”