Our understanding of how enzymes work is coloured by static structure depictions where the enzyme scaffold is presented as either immobile, or in equilibrium between well-defined static conformations. Proteins, however, exhibit a large degree of motion over a broad range of timescales and magnitudes and this is defined thermodynamically by the enzyme free energy landscape (FEL). The role and importance of enzyme motion is extremely contentious. Much of the challenge is in the experimental detection of so called 'conformational sampling' involved in enzyme turnover. Herein we apply combined pressure and temperature kinetics studies to elucidate the full suite of thermodynamic parameters defining an enzyme FEL as it relates to enzyme turnover. We find that the key thermodynamic parameters governing vibrational modes related to enzyme turnover are the isobaric expansivity term and the change in heat capacity for enzyme catalysis. Variation in the enzyme FEL affects these terms. Our analysis is supported by a range of biophysical and computational approaches that specifically capture information on protein vibrational modes and the FEL (all atom flexibility calculations, red edge excitation shift spectroscopy and viscosity studies) that provide independent evidence for our findings. Our data suggest that restricting the enzyme FEL may be a powerful strategy when attempting to rationally engineer enzymes, particularly to alter thermal activity. Moreover, we demonstrate how rational predictions can be made with a rapid computational approach.

Among the major challenges in the development of biopharmaceuticals are structural heterogeneity and aggregation. The development of a successful therapeutic monoclonal antibody (mAb) requires both a highly active and also stable molecule. Whilst a range of experimental (biophysical) approaches exist to track changes in stability of proteins, routine prediction of stability remains challenging. The fluorescence red edge excitation shift (REES) phenomenon is sensitive to a range of changes in protein structure. Based on recent work, we have found that quantifying the REES effect is extremely sensitive to changes in protein conformational state and dynamics. Given the extreme sensitivity, potentially this tool could provide a ‘fingerprint’ of the structure and stability of a protein, which would have applications in the discovery and development of biopharamceuticals. As such we have explored our hypothesis with a panel of therapeutic mAbs. We demonstrate that the quantified REES data show remarkable sensitivity, being able to discern between structurally identical antibodies and showing sensitivity to unfolding and aggregation. The approach works across a broad concentration range (μg –mg/ml) and is highly consistent. We show that the approach can be applied alongside traditional characterisation testing within the context of a forced degradation study (FDS). We demonstrate the approach is able to predict the stability of mAbs both in the short (hours), medium (days) and long-term (months). The approach benefits from low technical complexity, is rapid and uses instrumentation which exists in most biochemistry laboratories without modification.

Understanding how enzyme catalysis varies with temperature is key to understanding catalysis itself, and ultimately, how to tune temperature optima. Temperature dependence studies inform on the change in heat capacity during the reaction, Δ ‡ , and we have recently demonstrated that this can expose links between the protein free energy landscape and enzyme turnover. By quantifying Δ ‡ , we capture information on the changes to the distribution of vibrational frequencies during enzyme turnover. The primary experimental tool to probe the role of vibrational modes in a chemical/biological process is isotope effect measurements, since isotopic substitution primarily affects the frequency of vibrational modes at/local to the position of isotopic substitution. We have monitored the temperature dependence of a range of isotope effects on the turnover of a hyper-thermophilic glucose dehydrogenase. We find a progressive effect on the magnitude of Δ ‡ with increasing isotopic substitution of D-glucose. Our experimental findings, combined with molecular dynamics simulations and quantum mechanical calculations, demonstrate that Δ ‡ is sensitive to isotopic substitution. The magnitude of the change in Δ ‡ due to substrate isotopic substitution indicates that small changes in substrate vibrational modes are 'translated' into relatively large changes in the (distribution and/or magnitude of) enzyme vibrational modes along the reaction. Therefore, the data suggest that relatively small substrate isotopic changes are causing a significant change in the temperature dependence of enzymatic rates.

The potency and selectivity of a small molecule inhibitor are key parameters to assess during the early stages of drug discovery. In particular, it is very informative for characterizing compounds in a relevant cellular context in order to reveal potential off-target effects and drug efficacy. Activity-based probes are valuable tools for that purpose, however, obtaining cellular target engagement data in a high-throughput format has been particularly challenging. Here, we describe a new methodology named ABPP-HT (high-throughput-compatible activity-based protein profiling), implementing a semi-automated proteomic sample preparation workflow that increases the throughput capabilities of the classical ABPP workflow approximately ten times while preserving its enzyme profiling characteristics. Using a panel of deubiquitylating enzyme (DUB) inhibitors, we demonstrate the feasibility of ABPP-HT to provide compound selectivity profiles of endogenous DUBs in a cellular context at a fraction of time as compared to previous methodologies.

Here, we report a label-free gold nanoparticle-based single-molecule optical platform to study the immobilization, activity, and thermodynamics of single enzymes. The sensor uses plasmonic gold nanoparticles coupled to optical whispering gallery modes (WGMs) to probe enzyme conformational dynamics during turnover at a microsecond time resolution. Using a glucosidase enzyme as the model system, we explore the temperature dependence of the enzyme turnover at the single-molecule (SM) level. A recent physical model for understanding enzyme temperature dependencies (macromolecular rate theory; MMRT) has emerged as a powerful tool to study the relationship between enzyme turnover and thermodynamics. Using WGMs, SM enzyme measurements enable us to accurately track turnover as a function of conformational changes and therefore to quantitatively probe the key feature of the MMRT model, the activation heat capacity, at the ultimate level of SM. Our data shows that WGMs are extraordinarily sensitive to protein conformational change and can discern both multiple steps with turnover as well as microscopic conformational substates within those steps. The temperature dependence studies show that the MMRT model can be applied to a range of steps within turnover at the SM scale that is associated with conformational change. Our study validates the notion that MMRT captures differences in dynamics between states. The WGM sensors provide a platform for the quantitative analysis of SM activation heat capacity, applying MMRT to the label-free sensing of microsecond substates of active enzymes.

There is an increasing realization that structure-based drug design may show improved success by understanding the ensemble of conformations and sub-states accessible to an enzyme and how the environment affects this ensemble. Human monoamine oxidase B (MAO-B) catalyzes the oxidation of amines and is inhibited for the treatment of both Parkinson's disease and depression. Despite its clinical importance, its catalytic mechanism remains unclear and routes to drugging this target would be valuable. Evidence of a radical in either the transition state or resting state of MAO-B is present throughout the literature, and is suggested to be a flavin semiquinone, a tyrosyl radical or both. Here we see evidence of a resting state flavin semiquinone, via absorption redox studies and electron paramagnetic resonance, suggesting that the anionic semiquinone is biologically relevant. Based on enzyme kinetic studies, enzyme variants and molecular dynamics simulations we find evidence for the importance of the membrane environment in mediating the activity of MAO-B and that this mediation is related to the protein dynamics of MAO-B. Further, our MD simulations identify a hitherto undescribed entrance for substrate binding, membrane modulated substrate access, and indications for half-site reactivity: only one active site is accessible to binding at a time. Our study combines both experimental and computational evidence to illustrate the subtle interplay between enzyme activity, protein dynamics and the immediate membrane environment. Understanding key biomedical enzymes to this level of detail will be crucial to inform strategies (and binding sites) for rational drug design for these targets.

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.

α-Synuclein (α-syn) is associated with a range of diseases, including Parkinson disease. In disease, α-syn is known to aggregate and has the potential to be neurotoxic. The association between copper and α-syn results in the formation of stellate toxic oligomers that are highly toxic to cultured neurons. We further investigated the mechanism of toxicity of α-syn oligomers. Cells that overexpress α-syn showed increased susceptibility to the toxicity of the oligomers, while those that overexpressed β-syn showed increased resistance to the toxic oligomers. Elevated α-syn expression caused an increase in expression of the transcription factor Forkhead box O3a (FoxO3a). Inhibition of FoxO3a activity by the overexpression of DNA binding domain of FoxO3a resulted in significant protection from α-syn oligomer toxicity. Increased FoxO3a expression in cells was shown to be caused by increased ferrireductase activity and Fe(II) levels. These results suggest that α-syn increases FoxO3a expression as a result of its intrinsic ferrireductase activity. The results also suggest that FoxO3a plays a pivotal role in the toxicity of both Fe(II) and toxic α-syn species to neuronal cells.-Angelova, D. M., Jones, H. B. L., Brown, D. R. Levels of α- and β-synuclein regulate cellular susceptibility to toxicity from α-synuclein oligomers.