Enhanced Diffusion of Catalytically Active Enzymes

A Cautionary Perspective on Hydrogel-Induced Concentration Gradient Generation for Studying Chemotaxis

The achievement of consistent and static chemical gradients is critically important in the study of diffusion and chemotaxis at the micro- and nanoscales. In this context, a number of groups have reported on hydrogel-based systems for generating concentration gradients. Here, we analyze the behavior of agarose and gelatin-based hydrogels in hybridization chambers of different heights. Our focus is on the issues that are caused by the presence of robust bulk fluid flows in such systems due to the solutes present in the hydrogel and/or the surrounding fluid. We describe the key insights derived from these experiments, offering practical guidelines for establishing gradients using hydrogel-based systems and make the community aware of different variables that can make the experiments nonreproducible and prone to misinterpretations.

Exploring Emergent Properties in Enzymatic Reaction Networks: Design and Control of Dynamic Functional Systems

The intricate and complex features of enzymatic reaction networks (ERNs) play a key role in the emergence and sustenance of life. Constructing such networks in vitro enables stepwise build up in complexity and introduces the opportunity to control enzymatic activity using physicochemical stimuli. Rational design and modulation of network motifs enable the engineering of artificial systems with emergent functionalities. Such functional systems are useful for a variety of reasons such as creating new-to-nature dynamic materials, producing value-added chemicals, constructing metabolic modules for synthetic cells, and even enabling molecular computation. In this review, we offer insights into the chemical characteristics of ERNs while also delving into their potential applications and associated challenges.

Open Questions of Chemically Powered Nano- and Micromotors

Chemically powered nano- and micromotors are microscopic devices that convert chemical energy into motion. Interest in these motors has grown over the past 20 years because they exhibit interesting collective behaviors and have found potential uses in biomedical and environmental applications. Understanding how these motors operate both individually and collectively and how environments affect their operation is of both fundamental and applied significance. However, there are still significant gaps in our knowledge. This Perspective highlights several open questions regarding the propulsion mechanisms of, interactions among, and impact of confinements on nano- and micromotors driven by self-generated chemical gradients. These questions are based on my own experience as an experimentalist. For each open question, I describe the problem and its significance, analyze the status-quo, identify the bottleneck problem, and propose potential solutions. An underlying theme for these questions is the interplay among reaction kinetics, physicochemical distributions, and fluid flows. Unraveling this interplay requires careful measurements as well as a close collaboration between experimentalists and theoreticians/numerical experts. The interdisciplinary nature of these challenges suggests that their solutions could bring new revelations and opportunities across disciplines such as colloidal sciences, material sciences, soft matter physics, robotics, and beyond.

Virus-like particles nanoreactors: from catalysis towards bio-applications

Virus-like particles (VLPs) are self-assembled supramolecular structures found in nature, often used for compartmentalization. Exploiting their inherent properties, including precise nanoscale structures, monodispersity, and high stability, these architectures have been widely used as nanocarriers to protect or enrich catalysts, facilitating catalytic reactions and avoiding interference from the bulk solutions. In this review, we summarize the current progress of virus-like particles (VLPs)-based nanoreactors. First, we briefly introduce the physicochemical properties of the most commonly used virus particles to understand their roles in catalytic reactions beyond the confined space. Next, we summarize the self-assembly of nanoreactors forming higher-order hierarchical structures, highlighting the emerging field of nanoreactors as artificial organelles and their potential biomedical applications. Finally, we discuss the current findings and future perspectives of VLPs-based nanoreactors.

SARS-CoV-2 proteases Mpro and PLpro: Design of inhibitors with predicted high potency and low mammalian toxicity using artificial neural networks, ligand-protein docking, molecular dynamics simulations, and ADMET calculations

The main (Mpro) and papain-like (PLpro) proteases are highly conserved viral proteins essential for replication of the COVID-19 virus, SARS-COV-2. Therefore, a logical plan for producing new drugs against this pathogen is to discover inhibitors of these enzymes. Accordingly, the goal of the present work was to devise a computational approach to design, characterize, and select compounds predicted to be potent dual inhibitors - effective against both Mpro and PLpro. The first step employed LigDream, an artificial neural network, to create a virtual ligand library. Ligands with computed ADMET profiles indicating drug-like properties and low mammalian toxicity were selected for further study. Initial docking of these ligands into the active sites of Mpro and PLpro was done with GOLD, and the highest-scoring ligands were redocked with AutoDock Vina to determine binding free energies (ΔG). Compounds 89-00, 89-07, 89-32, and 89-38 exhibited favorable ΔG values for Mpro (-7.6 to -8.7 kcal/mol) and PLpro (-9.1 to -9.7 kcal/mol). Global docking of selected compounds with the Mpro dimer identified prospective allosteric inhibitors 89-00, 89-27, and 89-40 (ΔG -8.2 to -8.9 kcal/mol). Molecular dynamics simulations performed on Mpro and PLpro active site complexes with the four top-scoring ligands from Vina demonstrated that the most stable complexes were formed with compounds 89-32 and 89-38. Overall, the present computational strategy generated new compounds with predicted drug-like characteristics, low mammalian toxicity, and high inhibitory potencies against both target proteases to form stable complexes. Further preclinical studies will be required to validate the in silico findings before the lead compounds could be considered for clinical trials.

Diffusion coefficient and power spectrum of active particles with a microscopically reversible mechanism of self-propelling

Catalytically active macromolecules are envisioned as key building blocks in development of artificial nanomotors. However, theory and experiments report conflicting findings regarding their dynamics. The lack of consensus is mostly caused by a limited understanding of specifics of self-propulsion mechanisms at the nanoscale. Here, we study a generic model of a self-propelled nanoparticle that does not rely on a particular mechanism. Instead, its main assumption is the fundamental symmetry of microscopic dynamics of chemical reactions: the principle of microscopic reversibility. Significant consequences of this assumption arise if we subject the particle to an action of an external time-periodic force. The particle diffusion coefficient is then enhanced compared to the unbiased dynamics. The enhancement can be controlled by the force amplitude and frequency. We also derive the power spectrum of particle trajectories. Among new effects stemming from the microscopic reversibility are the enhancement of the spectrum at all frequencies and sigmoid-shaped transitions and a peak at characteristic frequencies of rotational diffusion and external forcing. The microscopic reversibility is a generic property of a broad class of chemical reactions, therefore we expect that the presented results will motivate new experimental studies aimed at testing of our predictions. This could provide new insights into dynamics of catalytic macromolecules.

Regulating Spatial Localization and Reactivity Biasness of DNAzymes by Metal Ions and Oligonucleotides

Chemical gradient sensing behavior of catalytically active colloids and enzymes is an area of immense interest owing to their importance in understanding fundamental spatiotemporal complexity pattern in living systems and designing of dynamic materials. Herein, we have shown peroxidase activity of DNAzyme (G-quadruplex-hemin complex tagged in a micron-sized glass bead) can be modulated by metal ions and metal ion-binding oligonucleotides. Next we demonstrated both experimentally and theoretically that the localization and product formation ability of the DNAzyme containing particle remains biased to the more catalytically active zone where concentration of metal ion (Hg2+) inhibitor is low. Interestingly, this biased localization can be broken by introduction of Hg2+ binding oligonucleotide in the system. Additionally, macroscopically asymmetric catalytic product distributed zone has also been achieved on this process, showing possibility in regulation in autonomous spatially controlled chemical process. This demonstration of autonomous modulation of the localization pattern and spatially specific enhanced product forming ability of DNAzymes will further enable in designing of responsive nucleic acid-based motile materials and surfaces.

Study Enhanced Enzyme Diffusion with High-Speed Single Nanoparticle Rotational and Translational Tracking

Catalytic enzymes exhibiting enhanced motion have drawn extensive attention over the past decade; nevertheless, little is known about the effect on the environment induced by enzymes. Herein, we studied the active urease system by simultaneously monitoring the diffusion of single anisotropic gold nanorods (AuNRs) with high speed dark-field imaging. We found both the translational and the rotational diffusion coefficients of AuNRs were enhanced but with inconsistent degrees, indicating the catalytic reaction had a minor effect on the physiochemical properties of the environment according to the Stokes-Einstein equation. With the increase of substrate concentration, the diffusion of AuNRs showed increased spatial but decreased temporal heterogeneity. Additionally, high speed imaging revealed AuNRs could experience intermittent ballistic motion for tens of milliseconds. These results imply inhomogeneous distribution of enzymes in free solution induced by active enzymatic reactions.

Enzyme Purification Improves the Enzyme Loading, Self-Propulsion, and Endurance Performance of Micromotors

Enzyme-powered micro- and nanomotors make use of biocatalysis to self-propel in aqueous media and hold immense promise for active and targeted drug delivery. Most (if not all) of these micro- and nanomotors described to date are fabricated using a commercially available enzyme, despite claims that some commercial preparations may not have a sufficiently high degree of purity for downstream applications. In this study, the purity of a commercial urease, an enzyme frequently used to power the motion of micro- and nanomotors, was evaluated and found to be impure. After separating the hexameric urease from the protein impurities by size-exclusion chromatography, the hexameric urease was subsequently characterized and used to functionalize hollow silica microcapsules. Micromotors loaded with purified urease were found to be 2.5 times more motile than the same micromotors loaded with unpurified urease, reaching average speeds of 5.5 μm/s. After comparing a number of parameters, such as enzyme distribution, protein loading, and motor reusability, between micromotors functionalized with purified vs unpurified urease, it was concluded that protein purification was essential for optimal performance of the enzyme-powered micromotor.

Enhanced diffusivity in microscopically reversible active matter

The physics of self-propelled objects at the nanoscale is a rapidly developing research field where recent experiments have focused on the motion of individual catalytic enzymes. Contrary to the experimental advancements, theoretical understanding of the possible self-propulsion mechanisms at these scales is limited. A particularly puzzling question concerns the origins of the reportedly high diffusivities of the individual enzymes. Here we start with the fundamental principle of microscopic reversibility (MR) of chemical reactions powering self-propulsion and demonstrate that MR can lead to an increase of the particle mobility and of the short- and long-time diffusion coefficients as compared to dynamics where MR is neglected. Furthermore, the derived diffusion coefficients are enhanced due to the action of an external force. These results can shed new light on interpretations of the measured diffusivities and help to test the relevance of MR for the active motion of individual nanoswimmers.

Displacement Statistics of Unhindered Single Molecules Show no Enhanced Diffusion in Enzymatic Reactions

Recent studies have sparked debate over whether catalytic reactions enhance the diffusion coefficients D of enzymes. Through high statistics of the transient (600 μs) displacements of unhindered single molecules freely diffusing in common buffers, we here quantify D for four enzymes under catalytic turnovers. We thus formulate how ∼ ±1% precisions may be achieved for D, and show no changes in diffusivity for catalase, urease, aldolase, and alkaline phosphatase under the application of wide concentration ranges of substrates. Our single-molecule approach thus overcomes potential limitations and artifacts underscored by recent studies to show no enhanced diffusion in enzymatic reactions.

Molecular Diffusivity of Click Reaction Components: The Diffusion Enhancement Question

Micrometer-sized objects are widely known to exhibit chemically driven motility in systems away from equilibrium. Experimental observation of reaction-induced motility or enhancement in diffusivity at the much shorter length scale of small molecules is, however, still a matter of debate. Here, we investigate the molecular diffusivity of reactants, catalyst, and product of a model reaction, the copper-catalyzed azide-alkyne cycloaddition click reaction, and develop new NMR diffusion approaches that allow the probing of reaction-induced diffusion enhancement in nanosized molecular systems with higher accuracy than the state of the art. Following two different approaches that enable the accounting of time-dependent concentration changes during NMR experiments, we closely monitored the diffusion coefficient of reaction components during the reaction. The reaction components showed distinct changes in the diffusivity: while the two reactants underwent a time-dependent decrease in their diffusivity, the diffusion coefficient of the product gradually increased and the catalyst showed only slight diffusion enhancement within the range expected for reaction-induced sample heating. The decrease in diffusion coefficient of the alkyne, one of the two reactants of click reaction, was not reproduced during its copper coordination when the second reactant, azide, was absent. Our results do not support the catalysis-induced diffusion enhancement of the components of the click reaction and, instead, point to the role of a relatively large intermediate species within the reaction cycle with diffusivity lower than that of both the reactants and product molecule.

Trade-off between carbohydrates and metal ions regulates the chemotactic directionality of alkaline phosphatase

The role of the Hofmeister interaction in governing the chemotactic behavior of alkaline phosphatase in the presence of carbohydrate and metal ion gradients has been established.

Dependence of diffusion in Escherichia coli cytoplasm on protein size, environmental conditions, and cell growth

Inside prokaryotic cells, passive translational diffusion typically limits the rates with which cytoplasmic proteins can reach their locations. Diffusion is thus fundamental to most cellular processes, but the understanding of protein mobility in the highly crowded and non-homogeneous environment of a bacterial cell is still limited. Here, we investigated the mobility of a large set of proteins in the cytoplasm of Escherichia coli, by employing fluorescence correlation spectroscopy (FCS) combined with simulations and theoretical modeling. We conclude that cytoplasmic protein mobility could be well described by Brownian diffusion in the confined geometry of the bacterial cell and at the high viscosity imposed by macromolecular crowding. We observed similar size dependence of protein diffusion for the majority of tested proteins, whether native or foreign to E. coli. For the faster-diffusing proteins, this size dependence is well consistent with the Stokes-Einstein relation once taking into account the specific dumbbell shape of protein fusions. Pronounced subdiffusion and hindered mobility are only observed for proteins with extensive interactions within the cytoplasm. Finally, while protein diffusion becomes markedly faster in actively growing cells, at high temperature, or upon treatment with rifampicin, and slower at high osmolarity, all of these perturbations affect proteins of different sizes in the same proportions, which could thus be described as changes of a well-defined cytoplasmic viscosity.

A simple theory for molecular chemotaxis driven by specific binding interactions

Recent experiments have suggested that enzymes and other small molecules chemotax toward their substrates. However, the physical forces driving this chemotaxis are currently debated. In this work, we consider a simple thermodynamic theory for molecular chemotaxis that is based on the McMillan-Mayer theory of dilute solutions and Schellman's theory for macromolecular binding. Even in the absence of direct interactions, the chemical binding equilibrium introduces a coupling term into the relevant free energy, which then reduces the chemical potential of both enzymes and their substrates. Assuming a local thermodynamic equilibrium, this binding contribution to the chemical potential generates an effective thermodynamic force that promotes chemotaxis by driving each solute toward its binding partner. Our numerical simulations demonstrate that, although small, this thermodynamic force is qualitatively consistent with several experimental studies. Thus, our study may provide additional insight into the role of the thermodynamic binding free energy for molecular chemotaxis.

Relative Diffusivities of Bound and Unbound Protein Can Control Chemotactic Directionality

Enzyme-based systems have been shown to undergo chemotactic motion in response to their substrate gradient. This phenomenon has been exploited to direct the motion of enzymes and enzyme-attached particles to specific locations in space. Here, we propose a new kinetic model to analyze the directional movement of an ensemble of protein molecules in response to a gradient of the ligand. We also formulate a separate model to probe the motion of enzyme molecules in response to a gradient of the substrate under catalytic conditions. The only input for the new enzymatic model is the Michaelis-Menten constant which is the relevant measurable constant for enzymatic reactions. We show how our model differs from previously proposed models in a significant manner. For both binding and catalytic reactions, a net movement up the ligand/substrate gradient is predicted when the diffusivity of the ligand/substrate-bound protein is lower than that of the unbound protein (positive chemotaxis). Conversely, movement down the ligand/substrate gradient is expected when the diffusivity of the ligand/substrate-bound protein is higher than that of the unbound protein (negative chemotaxis). However, there is no net movement of protein/enzyme when the diffusivities of the bound and free species are equal. The work underscores the critical importance of measuring the diffusivity of the bound protein and comparing it with that of the free protein.

Pnictogen-Bonding Catalysis and Transport Combined: Polyether Transporters Made In Situ

The combination of catalysis and transport across lipid bilayer membranes promises directional access to a solvent-free and structured nanospace that could accelerate, modulate, and, at best, enable new chemical reactions. To elaborate on these expectations, anion transport and catalysis with pnictogen and tetrel bonds are combined with polyether cascade cyclizations into bioinspired cation transporters. Characterized separately, synergistic anion and cation transporters of very high activity are identified. Combined for catalysis in membranes, cascade cyclizations are found to occur with a formal rate enhancement beyond one million compared to bulk solution and product formation is detected in situ as an increase in transport activity. With this operational system in place, intriguing perspectives open up to exploit all aspects of this unique nanospace for important chemical transformations.

Enzyme aggregation and fragmentation induced by catalysis relevant species

It is usually assumed that enzymes retain their native structure during catalysis. However, the aggregation and fragmentation of proteins can be difficult to detect and sometimes conclusions are drawn based on the assumption that the protein is in its native form. We have examined three model enzymes, alkaline phosphatase (AkP), hexokinase (HK) and glucose oxidase (GOx). We find that these enzymes aggregate or fragment after addition of chemical species directly related to their catalysis. We used several independent techniques to study this behavior. Specifically, we found that glucose oxidase and hexokinase fragment in the presence of D-glucose but not L-glucose, while hexokinase aggregates in the presence of Mg²⁺ ion and either ATP or ADP at low pH. Alkaline phosphatase aggregates in the presence of Zn²⁺ ion and inorganic phosphate. The aggregation of hexokinase and alkaline phosphatase does not appear to attenuate their catalytic activity. Our study indicates that specific multimeric structures of native enzymes may not be retained during catalysis and suggests pathways for different enzymes to associate or separate over the course of substrate turnover.

Active, Yet Little Mobility: Asymmetric Decomposition of H2O2 Is Not Sufficient in Propelling Catalytic Micromotors

A popular principle in designing chemical micromachines is to take advantage of asymmetric chemical reactions such as the catalytic decomposition of H₂O₂. Contrary to intuition, we use Janus micromotors half-coated with platinum (Pt) or catalase as an example to show that this ingredient is not sufficient in powering a micromotor into self-propulsion. In particular, by annealing a thin Pt film on a SiO₂ microsphere, the resulting microsphere half-decorated with discrete Pt nanoparticles swims ∼80% more slowly than its unannealed counterpart in H₂O₂, even though they both catalytically produce comparable amounts of oxygen. Similarly, SiO₂ microspheres half-functionalized with the enzyme catalase show negligible self-propulsion despite high catalytic activity toward decomposing H₂O₂. In addition to highlighting how surface morphology of a catalytic cap enables/disables a chemical micromotor, this study offers a refreshed perspective in understanding how chemistry powers nano- and microscopic objects (or not): our results are consistent with a self-electrophoresis mechanism that emphasizes the electrochemical decomposition of H₂O₂ over nonelectrochemical pathways. More broadly, our finding is a critical piece of the puzzle in understanding and designing nano- and micromachines, in developing capable model systems of active colloids, and in relating enzymes to active matter.

Single-particle diffusional fingerprinting: A machine-learning framework for quantitative analysis of heterogeneous diffusion

Single-particle tracking (SPT) analysis of individual biomolecules is an indispensable tool for extracting quantitative information from dynamic biological processes, but often requires some a priori knowledge of the system. Here we present “single-particle diffusional fingerprinting,” a more general approach for extraction of diffusional patterns in SPT independently of the biological system. This method extracts a set of descriptive features for each SPT trajectory, which are ranked upon classification to yield mechanistic insights for the species under comparison. We demonstrate its capacity to yield a dictionary of diffusional traits across multiple systems (e.g., lipases hydrolyzing fat, transcription factors diffusing in cells, and nanoparticles in mucus), supporting its use on multiple biological phenomena (e.g., drug delivery, receptor dynamics, and virology).

Single-particle tracking (SPT) is a key tool for quantitative analysis of dynamic biological processes and has provided unprecedented insights into a wide range of systems such as receptor localization, enzyme propulsion, bacteria motility, and drug nanocarrier delivery. The inherently complex diffusion in such biological systems can vary drastically both in time and across systems, consequently imposing considerable analytical challenges, and currently requires an a priori knowledge of the system. Here we introduce a method for SPT data analysis, processing, and classification, which we term “diffusional fingerprinting.” This method allows for dissecting the features that underlie diffusional behavior and establishing molecular identity, regardless of the underlying diffusion type. The method operates by isolating 17 descriptive features for each observed motion trajectory and generating a diffusional map of all features for each type of particle. Precise classification of the diffusing particle identity is then obtained by training a simple logistic regression model. A linear discriminant analysis generates a feature ranking that outputs the main differences among diffusional features, providing key mechanistic insights. Fingerprinting operates by both training on and predicting experimental data, without the need for pretraining on simulated data. We found this approach to work across a wide range of simulated and experimentally diverse systems, such as tracked lipases on fat substrates, transcription factors diffusing in cells, and nanoparticles diffusing in mucus. This flexibility ultimately supports diffusional fingerprinting’s utility as a universal paradigm for SPT diffusional analysis and prediction.

Chemically-powered swimming and diffusion in the microscopic world

The past decade has seen intriguing reports and heated debates concerning the chemically-driven enhanced motion of objects ranging from small molecules to millimetre-size synthetic robots. These objects, in solutions in which chemical reactions were occurring, were observed to diffuse (spread non-directionally) or swim (move directionally) at rates exceeding those expected from Brownian motion alone. The debates have focused on whether observed enhancement is an experimental artefact or a real phenomenon. If the latter were true, then we would also need to explain how the chemical energy is converted into mechanical work. In this Perspective, we summarize and discuss recent observations and theories of active diffusion and swimming. Notably, the chemomechanical coupling and magnitude of diffusion enhancement are strongly size-dependent and should vanish as the size of the swimmers approaches the molecular scale. We evaluate the reliability of common techniques to measure diffusion coefficients and finish by considering the potential applications and chemical to mechanical energy conversion efficiencies of typical nanoswimmers and microswimmers.

Interconnectivity between Surface Reactivity and Self-Assembly of Kemp Elimination Catalyzing Nanorods

Understanding the fundamental facts behind dynamicity of catalytic processes has been a longstanding quest across disciplines. Herein, we report self-assembly of catalytically active gold nanorods that can be regulated by tuning its reactivity towards a proton transfer reaction at different pH. Unlike substrate-induced templating and co-operativity, the enhanced aggregation rate is due to alteration of catalytic surface charge only during reactivity as negatively charged transition state of reactant (5-nitrobenzisoxazole) is formed on positively charged nanorod while undergoing a concerted E2-pathway. Herein, enhanced diffusivity during catalytic processes might also act as an additional contributing factor. Furthermore, we have also shown that nanosized hydrophobic cavities of clustered nanorods can also efficiently accelerate the rate of an aromatic nucleophilic substitution reaction, which also demonstrates a catalytic phenomenon that can lead to cascading of other reactions where substrates and products of the starting reactions are not directly involved.

Comment on “Boosted molecular mobility during common chemical reactions”

The apparent “boosted mobility” observed by Wang et al. (Reports, 31 July 2020, p. 537) is the result of a known artifact. When signal intensities are changing during a nuclear magnetic resonance (NMR) diffusion measurement for reasons other than diffusion, the use of monotonically increasing gradient amplitudes produces erroneous diffusion coefficients. We show that no boosted molecular mobility is observed when shuffled gradient amplitudes are applied.

Single-molecule diffusometry reveals no catalysis-induced diffusion enhancement of alkaline phosphatase as proposed by FCS experiments

Recent experiments have suggested that the energy released by a chemical reaction can propel its enzyme catalyst (for example, alkaline phosphatase). However, this topic remains controversial, partially due to the indirect and ensemble nature of existing measurements. Here, we used recently developed single-molecule approaches to monitor directly the motions of individual proteins in aqueous solution and find that single alkaline phosphatase enzymes do not diffuse faster under catalysis. Instead, we demonstrate that interactions between the fluorescent dye and the enzyme’s substrate can produce the signature of apparent diffusion enhancement in fluorescence correlation spectroscopy, the standard ensemble assay currently used to study enzyme diffusion and indicate that single-molecule approaches provide a more robust means to investigate diffusion at the nanoscale.

Theoretical and experimental observations that catalysis enhances the diffusion of enzymes have generated exciting implications about nanoscale energy flow, molecular chemotaxis, and self-powered nanomachines. However, contradictory claims on the origin, magnitude, and consequence of this phenomenon continue to arise. To date, experimental observations of catalysis-enhanced enzyme diffusion have relied almost exclusively on fluorescence correlation spectroscopy (FCS), a technique that provides only indirect, ensemble-averaged measurements of diffusion behavior. Here, using an anti-Brownian electrokinetic (ABEL) trap and in-solution single-particle tracking, we show that catalysis does not increase the diffusion of alkaline phosphatase (ALP) at the single-molecule level, in sharp contrast to the ∼20% enhancement seen in parallel FCS experiments using p-nitrophenyl phosphate (pNPP) as substrate. Combining comprehensive FCS controls, ABEL trap, surface-based single-molecule fluorescence, and Monte Carlo simulations, we establish that pNPP-induced dye blinking at the ∼10-ms timescale is responsible for the apparent diffusion enhancement seen in FCS. Our observations urge a crucial revisit of various experimental findings and theoretical models––including those of our own––in the field, and indicate that in-solution single-particle tracking and ABEL trap are more reliable means to investigate diffusion phenomena at the nanoscale.

The 2020 motile active matter roadmap

Activity and autonomous motion are fundamental in living and engineering systems. This has stimulated the new field of 'active matter' in recent years, which focuses on the physical aspects of propulsion mechanisms, and on motility-induced emergent collective behavior of a larger number of identical agents. The scale of agents ranges from nanomotors and microswimmers, to cells, fish, birds, and people. Inspired by biological microswimmers, various designs of autonomous synthetic nano- and micromachines have been proposed. Such machines provide the basis for multifunctional, highly responsive, intelligent (artificial) active materials, which exhibit emergent behavior and the ability to perform tasks in response to external stimuli. A major challenge for understanding and designing active matter is their inherent nonequilibrium nature due to persistent energy consumption, which invalidates equilibrium concepts such as free energy, detailed balance, and time-reversal symmetry. Unraveling, predicting, and controlling the behavior of active matter is a truly interdisciplinary endeavor at the interface of biology, chemistry, ecology, engineering, mathematics, and physics. The vast complexity of phenomena and mechanisms involved in the self-organization and dynamics of motile active matter comprises a major challenge. Hence, to advance, and eventually reach a comprehensive understanding, this important research area requires a concerted, synergetic approach of the various disciplines. The 2020 motile active matter roadmap of Journal of Physics: Condensed Matter addresses the current state of the art of the field and provides guidance for both students as well as established scientists in their efforts to advance this fascinating area.

Interaction of enzymes with lignocellulosic materials: causes, mechanism and influencing factors

For the production of biofuel (bioethanol), enzymatic adsorption onto a lignocellulosic biomass surface is a prior condition for the enzymatic hydrolysis process to occur. Lignocellulosic substances are mainly composed of cellulose, hemicellulose and lignin. The polysaccharide matrix (cellulose and hemicellulose) is capable of producing bioethanol. Therefore, lignin is removed or its concentration is reduced from the adsorption substrates by pretreatments. Selected enzymes are used for the production of reducing sugars from cellulosic materials, which in turn are converted to bioethanol. Adsorption of enzymes onto the substrate surface is a complicated process. A large number of research have been performed on the adsorption process, but little has been done to understand the mechanism of adsorption process. This article reviews the mechanisms of adsorption of enzymes onto the biomass surfaces. A conceptual adsorption mechanism is presented which will fill the gaps in literature and help researchers and industry to use adsorption more efficiently. The process of enzymatic adsorption starts with the reciprocal interplay of enzymes and substrates and ends with the establishment of molecular and cellular binding. The kinetics of an enzymatic reaction is almost the same as that of a characteristic chemical catalytic reaction. The influencing factors discussed in detail are: surface characteristics of the participating materials, the environmental factors, such as the associated flow conditions, temperature, concentration, etc. Pretreatment of lignocellulosic materials and optimum range of shear force and temperature for getting better results of adsorption are recommended.

Shear viscosity of two-state enzyme solutions

We discuss the shear viscosity of a Newtonian solution of catalytic enzymes and substrate molecules. The enzyme is modeled as a two-state dimer consisting of two spherical domains connected with an elastic spring. The enzymatic conformational dynamics is induced by the substrate binding and such a process is represented by an additional elastic spring. Employing the Boltzmann distribution weighted by the waiting times of enzymatic species in each catalytic cycle, we obtain the shear viscosity of dilute enzyme solutions as a function of substrate concentration and its physical properties. The substrate affinity distinguishes between fast and slow enzymes, and the corresponding viscosity expressions are obtained. Furthermore, we connect the obtained viscosity with the diffusion coefficient of a tracer particle in enzyme solutions.

Enhanced Diffusion and Chemotaxis of Enzymes

Many enzymes appear to diffuse faster in the presence of substrate and to drift either up or down a concentration gradient of their substrate. Observations of these phenomena, termed enhanced enzyme diffusion (EED) and enzyme chemotaxis, respectively, lead to a novel view of enzymes as active matter. Enzyme chemotaxis and EED may be important in biology and could have practical applications in biotechnology and nanotechnology. They are also of considerable biophysical interest; indeed, their physical mechanisms are still quite uncertain. This review provides an analytic summary of experimental studies of these phenomena and of the mechanisms that have been proposed to explain them and offers a perspective on future directions for the field.

Robustness of FCS (Fluorescence Correlation Spectroscopy) with Quenchers Present

Inspired by recent publications doubtful of the FCS technique, we scrutinize how irreversible ("static") and reversible ("dynamic") quenching can influence the interpretation of such data. Textbook presentations often emphasize only how to analyze data in extremes, the absence of quenching or the presence of substantial quenching. Here, we consider intermediate cases where the assessment of photophysics (static quenching, blinking-like triplet-state relaxation) influence on autocorrelation curves can be delicate if dye-labeled objects diffuse on comparably rapid time scales. We used the amino acid, tryptophan, as the quencher. As our example of small-molecule dye that diffuses rapidly, we mix the quencher with the fluorescence dye, Alexa 488. The translational diffusion coefficient, inferred from fit to the standard one-component Fickian diffusion model, speeds up without the loss of quality of fit, but quenching is reflected in the fact that the data become exceptionally noisy. This reflects the bidisperse population of quenched and unquenched dyes when the time scales overlap between the processes of translational diffusion, quenching, and blinking. As our example of the large-molecule dye-labeled object that diffuses relatively slowly, we mixed the quencher with dye-labeled BSA, bovine serum albumin. Diffusion, static quenching, and blinking time scales are now separated. In spite of quenching contribution to the autocorrelation function when the delay time is relatively short, the inferred translational diffusion coefficient now depends weakly on the presence of a quencher. We conclude that when the diffusing molecule is substantially slower to diffuse than the time scale of photophysical processes of the fluorescent dye to which it is attached, the influence of quenching is self-evident and the FCS autocorrelation curves give an appropriate diffusion coefficient if correct fitting functions are chosen in the analysis.

Enzyme-Powered Gated Mesoporous Silica Nanomotors for On-Command Intracellular Payload Delivery

The introduction of stimuli-responsive cargo release capabilities on self-propelled micro- and nanomotors holds enormous potential in a number of applications in the biomedical field. Herein, we report the preparation of mesoporous silica nanoparticles gated with pH-responsive supramolecular nanovalves and equipped with urease enzymes which act as chemical engines to power the nanomotors. The nanoparticles are loaded with different cargo molecules ([Ru(bpy)₃]Cl₂ (bpy = 2,2'-bipyridine) or doxorubicin), grafted with benzimidazole groups on the outer surface, and capped by the formation of inclusion complexes between benzimidazole and cyclodextrin-modified urease. The nanomotor exhibits enhanced Brownian motion in the presence of urea. Moreover, no cargo is released at neutral pH, even in the presence of the biofuel urea, due to the blockage of the pores by the bulky benzimidazole:cyclodextrin-urease caps. Cargo delivery is only triggered on-command at acidic pH due to the protonation of benzimidazole groups, the dethreading of the supramolecular nanovalves, and the subsequent uncapping of the nanoparticles. Studies with HeLa cells indicate that the presence of biofuel urea enhances nanoparticle internalization and both [Ru(bpy)₃]Cl₂ or doxorubicin intracellular release due to the acidity of lysosomal compartments. Gated enzyme-powered nanomotors shown here display some of the requirements for ideal drug delivery carriers such as the capacity to self-propel and the ability to "sense" the environment and deliver the payload on demand in response to predefined stimuli.