Does Urea Preferentially Interact with Amide Moieties or Nonpolar Sidechains? A Question Answered Through a Judicious Selection of Model Systems

Measuring the Thermal Unfolding of Lysozyme: A Critical Comparison of Differential Scanning Fluorimetry and Differential Scanning Calorimetry

The thermal unfolding of lysozyme in aqueous solution has been analyzed by (nano) differential scanning fluorimetry (nanoDSF) and differential scanning calorimetry (DSC). In addition, dynamic light scattering (DLS) acquired in parallel to the DSF measurements, was used to confirm that the change in hydrodynamic radius upon unfolding is rather small (RH,f =1.75 nm in the folded state; and RH,u=1.91 nm in the unfolded state). NanoDSF measurements were evaluated to characterize the folding/unfolding transition within the classical two-state folding model. The temperature of unfolding (Tm) is found to be the most robust quantity. The unfolding enthalpyΔ H u ${{\rm \Delta }{H}_{u}}$ and the change of specific heat were also obtained and errors in the range of 5-10 % and 30-50 % were determined, respectively. A comparison of thermodynamic parameters from nanoDSF and DSC measurements provides evidence for an increasing unfolding enthalpyΔ H u ${{\rm \Delta }{H}_{u}}$ with protein concentration. A comparison with data from literature suggests that a weak association in the folded state can lead to the observed change of the unfolding enthalpy. For Δcp significantly higher values is deduced from the analysis of temperature dependent nanoDSF measurements (10 kJ/(K mol)) as compare to DSC (3-5 kJ/(K mol)).

The Streptococcus phage protein paratox is an intrinsically disordered protein

The bacteriophage protein paratox (Prx) blocks quorum sensing in its streptococcal host by directly binding the signal receptor and transcription factor ComR. This reduces the ability of Streptococcus to uptake environmental DNA and protects phage DNA from damage by recombination. Past work characterizing the Prx:ComR molecular interaction revealed that paratox adopts a well-ordered globular fold when bound to ComR. However, solution-state biophysical measurements suggested that Prx may be conformationally dynamic. To address this discrepancy, we investigated the stability and dynamic properties of Prx in solution using circular dichroism, nuclear magnetic resonance, and several fluorescence-based protein folding assays. Our work shows that under dilute buffer conditions Prx is intrinsically disordered. We also show that the addition of kosmotropic salts or protein stabilizing osmolytes induces Prx folding. However, the solute stabilized fold is different from the conformation Prx adopts when it is bound to ComR. Furthermore, we have characterized Prx folding thermodynamics and folding kinetics through steady-state fluorescence and stopped flow kinetic measurements. Our results show that Prx is a highly dynamic protein in dilute solution, folding and refolding within the 10 ms timescale. Overall, our results demonstrate that the streptococcal phage protein Prx is an intrinsically disordered protein in a two-state equilibrium with a solute-stabilized folded form. Furthermore, the solute-stabilized fold is likely the predominant form of Prx in a solute-crowded bacterial cell. Finally, our work suggests that Prx binds and inhibits ComR, and thus quorum sensing in Streptococcus, by a combination of conformational selection and induced-fit binding mechanisms.

Computational Enzyme Redesign Enhances Tolerance to Denaturants for Peptide C-Terminal Amidation

The escalating demand for biocatalysts in pharmaceutical and biochemical applications underscores the critical imperative to enhance enzyme activity and durability under high denaturant concentrations. Nevertheless, the development of a practical computational redesign protocol for improving enzyme tolerance to denaturants is challenging due to the limitations of relying solely on model-driven approaches to adequately capture denaturant-enzyme interactions. In this study, we introduce an enzyme redesign strategy termed GRAPE_DA, which integrates multiple data-driven and model-driven computational methods to mitigate the sampling biases inherent in a single approach and comprehensively predict beneficial mutations on both the protein surface and backbone. To illustrate the methodology's effectiveness, we applied it to engineer a peptidylamidoglycolate lyase, resulting in a variant exhibiting up to a 24-fold increase in peptide C-terminal amidation activity under 2.5 M guanidine hydrochloride. We anticipate that this integrated engineering strategy will facilitate the development of enzymatic peptide synthesis and functionalization under denaturing conditions and highlight the role of engineering surface residues in governing protein stability.