A complete thermodynamic analysis of enzyme turnover links the free energy landscape to enzyme catalysis

Cooperative Conformational Transitions Underpin the Activation Heat Capacity in the Temperature Dependence of Enzyme Catalysis

Many enzymes display non-Arrhenius behavior with curved Arrhenius plots in the absence of denaturation. There has been significant debate about the origin of this behavior and recently the role of the activation heat capacity (ΔCP⧧) has been widely discussed. If enzyme-catalyzed reactions occur with appreciable negative values of ΔCP⧧ (arising from narrowing of the conformational space along the reaction coordinate), then curved Arrhenius plots are a consequence. To investigate these phenomena in detail, we have collected high precision temperature-rate data over a wide temperature interval for a model glycosidase enzyme MalL, and a series of mutants that change the temperature-dependence of the enzyme-catalyzed rate. We use these data to test a range of models including macromolecular rate theory (MMRT) and an equilibrium model. In addition, we have performed extensive molecular dynamics (MD) simulations to characterize the conformational landscape traversed by MalL in the enzyme-substrate complex and an enzyme-transition state complex. We have crystallized the enzyme in a transition state-like conformation in the absence of a ligand and determined an X-ray crystal structure at very high resolution (1.10 Å). We show (using simulation) that this enzyme-transition state conformation has a more restricted conformational landscape than the wildtype enzyme. We coin the term "transition state-like conformation (TLC)" to apply to this state of the enzyme. Together, these results imply a cooperative conformational transition between an enzyme-substrate conformation (ES) and a transition-state-like conformation (TLC) that precedes the chemical step. We present a two-state model as an extension of MMRT (MMRT-2S) that describes the data along with a convenient approximation with linear temperature dependence of the activation heat capacity (MMRT-1L) that can be used where fewer data points are available. Our model rationalizes disparate behavior seen for MalL and previous results for a thermophilic alcohol dehydrogenase and is consistent with a raft of data for other enzymes. Our model can be used to characterize the conformational changes required for enzyme catalysis and provides insights into the role of cooperative conformational changes in transition state stabilization that are accompanied by changes in heat capacity for the system along the reaction coordinate. TLCs are likely to be of wide importance in understanding the temperature dependence of enzyme activity and other aspects of enzyme catalysis.

Red edge excitation shift spectroscopy is highly sensitive to tryptophan composition

Red edge excitation shift (REES) spectroscopy relies on the unique emission profiles of fluorophore-solvent interactions to profile protein molecular dynamics. Recently, we reported the use of REES to compare the stability of 32 polymorphic IgG antibodies natively containing tryptophan reporter fluorophores. Here, we expand on this work to investigate the sensitivity of REES to variations in tryptophan content using a subset of IgG3 antibodies containing arginine to tryptophan polymorphisms. Structural analysis revealed that the additional tryptophan residues were situated in highly solvated environments. Subsequently, REES showed clear differences in fluorescence emission profiles when compared with the unmutated variants, thereby limiting direct comparison of their structural dynamics. These findings highlight the exquisite sensitivity of REES to minor variations in protein structure and tryptophan composition.

Glycosylation increases active site rigidity leading to improved enzyme stability and turnover

Glycosylation is the most prevalent protein post-translational modification, with a quarter of glycosylated proteins having enzymatic properties. Yet, the full impact of glycosylation on the protein structure-function relationship, especially in enzymes, is still limited. Here, we show that glycosylation rigidifies the important commercial enzyme horseradish peroxidase (HRP), which in turn increases its turnover and stability. Circular dichroism spectroscopy revealed that glycosylation increased holo-HRP's thermal stability and promoted significant helical structure in the absence of haem (apo-HRP). Glycosylation also resulted in a 10-fold increase in enzymatic turnover towards o-phenylenediamine dihydrochloride when compared to its nonglycosylated form. Utilising a naturally occurring site-specific probe of active site flexibility (Trp117) in combination with red-edge excitation shift fluorescence spectroscopy, we found that glycosylation significantly rigidified the enzyme. In silico simulations confirmed that glycosylation largely decreased protein backbone flexibility, especially in regions close to the active site and the substrate access channel. Thus, our data show that glycosylation does not just have a passive effect on HRP stability but can exert long-range effects that mediate the 'native' enzyme's activity and stability through changes in inherent dynamics.

Constant domain polymorphisms influence monoclonal antibody stability and dynamics

The constant regions of clinical monoclonal antibodies are derived from a select number of allotypes found in IgG subclasses. Despite a long-term acknowledgment that this diversity may impact both antibody function and developability, there is a lack of data on the stability of variants carrying these mutations. Here, we generated a panel of IgG1, IgG2, and IgG3 antibodies with 32 unique constant region alleles and performed a systematic comparison of stability using red edge excitation shift (REES). This technique exploits the fluorescent properties of tryptophan residues to measure antibody structural dynamics which predict flexibility and the propensity to unfold. Our REES measurements revealed broad stability differences between subclasses with IgG3 possessing the poorest overall stability. Further interrogation of differences between variants within each subclass enabled the high-resolution profiling of individual allotype stabilities. Crucially, these observed differences were not found to be linked to N297-linked glycan heterogeneity. Our work demonstrates diverse stabilities (and dynamics) for a range of naturally occurring constant domain alleles and the utility of REES as a method for rapid and sensitive antibody stability profiling, requiring only laboratory spectrophotometry equipment.

Temperature-dependent hydrogen deuterium exchange shows impact of analog binding on adenosine deaminase flexibility but not embedded thermal networks

The analysis of hydrogen deuterium exchange by mass spectrometry as a function of temperature and mutation (TDHDX-MS) has emerged as a generic and efficient tool for the spatial resolution of protein networks that are proposed to function in the thermal activation of catalysis. In this work, we extend TDHDX from apo-enzyme structures to protein-ligand complexes. Using adenosine deaminase as a prototype, we compared the impacts of a substrate analog (1-deaza-adenosine or DAA) and a very tight-binding inhibitor/transition state analog (pentostatin) at single and multiple temperatures. At a single temperature, we observed different HDX-MS properties for the two ligands, as expected from their 10⁶-fold differences in strength of binding. By contrast, analogous patterns for TDHDX-MS emerge in the presence of both DAA and pentostatin, indicating similar impacts of either ligand on the enthalpic barriers for local protein unfolding. We extended TDHDX to a function-altering mutant of adenosine deaminase in the presence of pentostatin and revealed a protein thermal network that is highly similar to that previously reported for the apo-enzyme (Gao et al., 2020, JACS 142, 19936-19949). Finally, we discuss the differential impacts of pentostatin binding on overall protein flexibility vs. site-specific thermal transfer pathways in the context of models for substrate-induced changes to a distributed protein conformational landscape that act in synergy with embedded protein thermal networks to achieve efficient catalysis.

A Thermodynamic Model for Interpreting Tryptophan Excitation-Energy-Dependent Fluorescence Spectra Provides Insight Into Protein Conformational Sampling and Stability

It is now over 30 years since Demchenko and Ladokhin first posited the potential of the tryptophan red edge excitation shift (REES) effect to capture information on protein molecular dynamics. While there have been many key efforts in the intervening years, a biophysical thermodynamic model to quantify the relationship between the REES effect and protein flexibility has been lacking. Without such a model the full potential of the REES effect cannot be realized. Here, we present a thermodynamic model of the tryptophan REES effect that captures information on protein conformational flexibility, even with proteins containing multiple tryptophan residues. Our study incorporates exemplars at every scale, from tryptophan in solution, single tryptophan peptides, to multitryptophan proteins, with examples including a structurally disordered peptide, de novo designed enzyme, human regulatory protein, therapeutic monoclonal antibodies in active commercial development, and a mesophilic and hyperthermophilic enzyme. Combined, our model and data suggest a route forward for the experimental measurement of the protein REES effect and point to the potential for integrating biomolecular simulation with experimental data to yield novel insights.

Mapping Enzyme Landscapes by Time-Resolved Crystallography with Synchrotron and X-Ray Free Electron Laser Light

Directly observing enzyme catalysis in real time at the molecular level has been a long-standing goal of structural enzymology. Time-resolved serial crystallography methods at synchrotron and X-ray free electron laser (XFEL) sources have enabled researchers to follow enzyme catalysis and other nonequilibrium events at ambient conditions with unprecedented time resolution. X-ray crystallography provides detailed information about conformational heterogeneity and protein dynamics, which is enhanced when time-resolved approaches are used. This review outlines the ways in which information about the underlying energy landscape of a protein can be extracted from X-ray crystallographic data, with an emphasis on new developments in XFEL and synchrotron time-resolved crystallography. The emerging view of enzyme catalysis afforded by these techniques can be interpreted as enzymes moving on a time-dependent energy landscape. Some consequences of this view are discussed, including the proposal that irreversible enzymes or enzymes that use covalent catalytic mechanisms may commonly exhibit catalysis-activated motions. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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

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, ΔC _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 ΔC _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.

Evolution of dynamical networks enhances catalysis in a designer enzyme

Activation heat capacity is emerging as a crucial factor in enzyme thermoadaptation, as shown by the non-Arrhenius behaviour of many natural enzymes. However, its physical origin and relationship to the evolution of catalytic activity remain uncertain. Here we show that directed evolution of a computationally designed Kemp eliminase reshapes protein dynamics, which gives rise to an activation heat capacity absent in the original design. These changes buttress transition-state stabilization. Extensive molecular dynamics simulations show that evolution results in the closure of solvent-exposed loops and a better packing of the active site. Remarkably, this gives rise to a correlated dynamical network that involves the transition state and large parts of the protein. This network tightens the transition-state ensemble, which induces a negative activation heat capacity and non-linearity in the activity-temperature dependence. Our results have implications for understanding enzyme evolution and suggest that selectively targeting the conformational dynamics of the transition-state ensemble by design and evolution will expedite the creation of novel enzymes.

Rigidifying a De Novo Enzyme Increases Activity and Induces a Negative Activation Heat Capacity

Conformational sampling profoundly impacts the overall activity and temperature dependence of enzymes. Peroxidases have emerged as versatile platforms for high-value biocatalysis owing to their broad palette of potential biotransformations. Here, we explore the role of conformational sampling in mediating activity in the de novo peroxidase C45. We demonstrate that 2,2,2-triflouoroethanol (TFE) affects the equilibrium of enzyme conformational states, tending toward a more globally rigid structure. This is correlated with increases in both stability and activity. Notably, these effects are concomitant with the emergence of curvature in the temperature-activity profile, trading off activity gains at ambient temperature with losses at high temperatures. We apply macromolecular rate theory (MMRT) to understand enzyme temperature dependence data. These data point to an increase in protein rigidity associated with a difference in the distribution of protein dynamics between the ground and transition states. We compare the thermodynamics of the de novo enzyme activity to those of a natural peroxidase, horseradish peroxidase. We find that the native enzyme resembles the rigidified de novo enzyme in terms of the thermodynamics of enzyme catalysis and the putative distribution of protein dynamics between the ground and transition states. The addition of TFE apparently causes C45 to behave more like the natural enzyme. Our data suggest robust, generic strategies for improving biocatalytic activity by manipulating protein rigidity; for functional de novo protein catalysts in particular, this can provide more enzyme-like catalysts without further rational engineering, computational redesign, or directed evolution.

Biochemical and biophysical characterization of the OXA-48-like carbapenemase OXA-436

The crystal structure of the class D β-lactamase OXA-436 was solved to a resolution of 1.80 Å. Higher catalytic rates were found at higher temperatures for the clinically important antibiotic imipenem, indicating better adaptation of OXA-436 to its mesophilic host than OXA-48, which is believed to originate from an environmental source. Furthermore, based on the most populated conformations during 100 ns molecular-dynamics simulations, it is postulated that the modulation of activity involves conformational shifts of the α3-α4 and β5-β6 loops. While these changes overall do not cause clinically significant shifts in the resistance profile, they show that antibiotic-resistance enzymes exist in a continuum. It is believed that these seemingly neutral differences in the sequence exist on a path leading to significant changes in substrate selectivity.

Validating the CHARMM36m protein force field with LJ-PME reveals altered hydrogen bonding dynamics under elevated pressures

The pressure-temperature phase diagram is important to our understanding of the physics of biomolecules. Compared to studies on temperature effects, studies of the pressure dependence of protein dynamic are rather limited. Molecular dynamics (MD) simulations with fine-tuned force fields (FFs) offer a powerful tool to explore the influence of thermodynamic conditions on proteins. Here we evaluate the transferability of the CHARMM36m (C36m) protein force field at varied pressures compared with NMR data using ubiquitin as a model protein. The pressure dependences of J couplings for hydrogen bonds and order parameters for internal motion are in good agreement with experiment. We demonstrate that the C36m FF combined with the Lennard-Jones particle-mesh Ewald (LJ-PME) method is suitable for simulations in a wide range of temperature and pressure. As the ubiquitin remains stable up to 2500 bar, we identify the mobility and stability of different hydrogen bonds in response to pressure. Based on those results, C36m is expected to be applied to more proteins in the future to further investigate protein dynamics under elevated pressures.

Sensing Enzyme Activation Heat Capacity at the Single-Molecule Level Using Gold-Nanorod-Based Optical Whispering Gallery Modes

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.

Directed evolution of glycosyltransferase for enhanced efficiency of avermectin glucosylation

Avermectin, produced by Streptomyces avermitilis, is an active compound protective against nematodes, insects, and mites. However, its potential usage is limited by its low aqueous solubility. The uridine diphosphate (UDP)-glycosyltransferase (BLC) from Bacillus licheniformis synthesizes avermectin glycosides with improved water solubility and in vitro antinematodal activity. However, enzymatic glycosylation of avermectin by BLC is limited due to the low conversion rate of this reaction. Thus, improving BLC enzyme activity is necessary for mass production of avermectin glycosides for field application. In this study, the catalytic activity of BLC toward avermectin was enhanced via directed evolution. Three mutants from the BLC mutant library (R57H, V227A, and D252V) had specific glucosylation activity for avermectin 2.0-, 1.8-, and 1.5-fold higher, respectively, than wild-type BLC. Generation of combined mutations via site-directed mutagenesis led to even further enhancement of activity. The triple mutant, R57H/V227A/D252V, had the highest activity, 2.8-fold higher than that of wild-type BLC. The catalytic efficiencies (K_cat/K_m) of the best mutant (R57H/V227A/D252V) toward the substrates avermectin and UDP-glucose were improved by 2.71- and 2.29-fold, respectively, compared to those of wild-type BLC. Structural modeling analysis revealed that the free energy of the mutants was - 1.1 to - 7.1 kcal/mol lower than that of wild-type BLC, which was correlated with their improved activity. KEY POINTS: • Directed evolution improved the glucosylation activity of BLC toward avermectin. • Combinatorial site-directed mutagenesis led to further enhanced activity. • The mutants exhibited lower free energy values than wild-type BLC.

pH-Independent Heat Capacity Changes during Phosphorolysis Catalyzed by the Pyrimidine Nucleoside Phosphorylase from Geobacillus thermoglucosidasius

Enzyme-catalyzed reactions sometimes display curvature in their Eyring plots in the absence of denaturation, indicative of a change in activation heat capacity. However, the effects of pH and (de)protonation on this phenomenon have remained unexplored. Herein, we report a kinetic characterization of the thermophilic pyrimidine nucleoside phosphorylase from Geobacillus thermoglucosidasius across a two-dimensional working space covering 35 °C and 3 pH units with two substrates displaying different pK_a values. Our analysis revealed the presence of a measurable activation heat capacity change ΔC_p^⧧ in this reaction system, which showed no significant dependence on medium pH or substrate charge. Our results further describe the remarkable effects of a single halide substitution that has a minor influence on ΔC_p^⧧ but conveys a significant kinetic effect by decreasing the activation enthalpy, causing a >10-fold rate increase. Collectively, our results present an important piece in the understanding of enzymatic systems across multidimensional working spaces where the choice of reaction conditions can affect the rate, affinity, and thermodynamic phenomena independently of one another.

Red-Edge Excitation Shift Spectroscopy (REES): Application to Hidden Bound States of Ligands in Protein-Ligand Complexes

Ligand-protein binding is responsible for the vast majority of bio-molecular functions. Most experimental techniques examine the most populated ligand-bound state. The determination of less populated, intermediate, and transient bound states is experimentally challenging. However, hidden bound states are also important because these can strongly influence ligand binding and unbinding processes. Here, we explored the use of a classical optical spectroscopic technique, red-edge excitation shift spectroscopy (REES) to determine the number, population, and energetics associated with ligand-bound states in protein–ligand complexes. We describe a statistical mechanical model of a two-level fluorescent ligand located amongst a finite number of discrete protein microstates. We relate the progressive emission red shift with red-edge excitation to thermodynamic parameters underlying the protein–ligand free energy landscape and to photo-physical parameters relating to the fluorescent ligand. We applied the theoretical model to published red-edge excitation shift data from small molecule inhibitor–kinase complexes. The derived thermodynamic parameters allowed dissection of the energetic contribution of intermediate bound states to inhibitor–kinase interactions.

A critical perspective on Markov state model treatments of protein-protein association using coarse-grained simulations

Atomic-level information is essential to explain the specific interactions governing protein–protein recognition in terms of structure and dynamics. Of particular interest is a characterization of the time-dependent kinetic aspects of protein–protein association and dissociation. A powerful framework to characterize the dynamics of complex molecular systems is provided by Markov State Models (MSMs). The central idea is to construct a reduced stochastic model of the full system by defining a set of conformational featured microstates and determining the matrix of transition probabilities between them. While a MSM framework can sometimes be very effective, different combinations of input featurization and simulation methods can significantly affect the robustness and the quality of the information generated from MSMs in the context of protein association. Here, a systematic examination of a variety of MSMs methodologies is undertaken to clarify these issues. To circumvent the uncertainties caused by sampling issues, we use a simplified coarse-grained model of the barnase–barstar protein complex. A sensitivity analysis is proposed to identify the microstates of an MSM that contribute most to the error in conjunction with the transition-based reweighting analysis method for a more efficient and accurate MSM construction.

Monoclonal antibody stability can be usefully monitored using the excitation-energy-dependent fluorescence edge-shift

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. Such a tool would be useful in the discovery and development of biopharamceuticals and so 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). Most importantly, we demonstrate the approach is able to predict the stability of mAbs both in the short (hours), medium (days) and long-term (months). The quantified REES data will find immediate use in the biopharmaceutical industry in quality assurance, formulation and development. The approach benefits from low technical complexity, is rapid and uses instrumentation which exists in most biochemistry laboratories without modification.

Structure, dynamics and function of the evolutionarily changing biliverdin reductase B family

Biliverdin reductase B (BLVRB) family members are general flavin reductases critical in maintaining cellular redox with recent findings revealing that BLVRB alone can dictate cellular fate. However, as opposed to most enzymes, the BLVRB family remains enigmatic with an evolutionarily changing active site and unknown structural and functional consequences. Here, we applied a multi-faceted approach that combines X-ray crystallography, NMR and kinetics methods to elucidate the structural and functional basis of the evolutionarily changing BLVRB active site. Using a panel of three BLVRB isoforms (human, lemur and hyrax) and multiple human BLVRB mutants, our studies reveal a novel evolutionary mechanism where coenzyme 'clamps' formed by arginine side chains at two co-evolving positions within the active site serve to slow coenzyme release (Positions 14 and 78). We find that coenzyme release is further slowed by the weaker binding substrate, resulting in relatively slow turnover numbers. However, different BLVRB active sites imposed by either evolution or mutagenesis exhibit a surprising inverse relationship between coenzyme release and substrate turnover that is independent of the faster chemical step of hydride transfer also measured here. Collectively, our studies have elucidated the role of the evolutionarily changing BLVRB active site that serves to modulate coenzyme release and has revealed that coenzyme release is coupled to substrate turnover.

Novel insights in linking solvent relaxation dynamics and protein conformations utilizing red edge excitation shift approach

Protein hydration dynamics plays an important role in many physiological processes since protein fluctuations, slow solvation, and the dynamics of hydrating water are all intrinsically related. Red edge excitation shift (REES) is a unique and powerful wavelength-selective (i.e. excitation-energy dependent) fluorescence approach that can be used to directly monitor the environment-induced restriction and dynamics around a polar fluorophore in a complex biological system. This review is mainly focused on recent applications of REES and a novel analysis of REES data to monitor the structural dynamics, functionally relevant conformational transitions and to unmask the structural ensembles in proteins. In addition, the novel utility of REES in imaging protein aggregates in a cellular context is discussed. We believe that the enormous potential of REES approach showcased in this review will engage more researchers, particularly from life sciences.

Kramers’ Theory and the Dependence of Enzyme Dynamics on Trehalose-Mediated Viscosity

The disaccharide trehalose is accumulated in the cytoplasm of some organisms in response to harsh environmental conditions. Trehalose biosynthesis and accumulation are important for the survival of such organisms by protecting the structure and function of proteins and membranes. Trehalose affects the dynamics of proteins and water molecules in the bulk and the protein hydration shell. Enzyme catalysis and other processes dependent on protein dynamics are affected by the viscosity generated by trehalose, as described by the Kramers’ theory of rate reactions. Enzyme/protein stabilization by trehalose against thermal inactivation/unfolding is also explained by the viscosity mediated hindering of the thermally generated structural dynamics, as described by Kramers’ theory. The analysis of the relationship of viscosity–protein dynamics, and its effects on enzyme/protein function and other processes (thermal inactivation and unfolding/folding), is the focus of the present work regarding the disaccharide trehalose as the viscosity generating solute. Finally, trehalose is widely used (alone or in combination with other compounds) in the stabilization of enzymes in the laboratory and in biotechnological applications; hence, considering the effect of viscosity on catalysis and stability of enzymes may help to improve the results of trehalose in its diverse uses/applications.

Droplet-based optofluidic systems for measuring enzyme kinetics

The study of enzyme kinetics is of high significance in understanding metabolic networks in living cells and using enzymes in industrial applications. To gain insight into the catalytic mechanisms of enzymes, it is necessary to screen an enormous number of reaction conditions, a process that is typically laborious, time-consuming, and costly when using conventional measurement techniques. In recent times, droplet-based microfluidic systems have proved themselves to be of great utility in large-scale biological experimentation, since they consume a minimal sample, operate at high analytical throughput, are characterized by efficient mass and heat transfer, and offer high levels of integration and automation. The primary goal of this review is the introduction of novel microfluidic tools and detection methods for use in high-throughput and sensitive analysis of enzyme kinetics. The first part of this review focuses on introducing basic concepts of enzyme kinetics and describing most common microfluidic approaches, with a particular focus on segmented flow. Herein, the key advantages include accurate control over the flow behavior, efficient mass and heat transfer, multiplexing, and high-level integration with detection modalities. The second part describes the current state-of-the-art platforms for high-throughput and sensitive analysis of enzyme kinetics. In addition to our categorization of recent advances in measuring enzyme kinetics, we have endeavored to critically assess the limitations of each of these detection approaches and propose strategies to improve measurements in droplet-based microfluidics. Graphical abstract.

Exposing the Interplay Between Enzyme Turnover, Protein Dynamics, and the Membrane Environment in Monoamine Oxidase B

There is an increasing realization that structure-based drug design may show improved success by understanding the ensemble of conformations 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 the 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. On the basis of 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 and 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.

FoldX as Protein Engineering Tool: Better Than Random Based Approaches?

Improving protein stability is an important goal for basic research as well as for clinical and industrial applications but no commonly accepted and widely used strategy for efficient engineering is known. Beside random approaches like error prone PCR or physical techniques to stabilize proteins, e.g. by immobilization, in silico approaches are gaining more attention to apply target-oriented mutagenesis. In this review different algorithms for the prediction of beneficial mutation sites to enhance protein stability are summarized and the advantages and disadvantages of FoldX are highlighted. The question whether the prediction of mutation sites by the algorithm FoldX is more accurate than random based approaches is addressed.

Multiscale immobilized lipase for rapid separation and continuous catalysis

Enzyme–inorganic hybrid nanoflowers have drawn extensive research interest for enzyme immobilization owing to their enhanced enzymatic activity, high surface area, and excellent chemical stability.