Free-Energy Landscape of Enzyme Catalysis

Wide transition-state ensemble as key component for enzyme catalysis

Transition-state (TS) theory has provided the theoretical framework to explain the enormous rate accelerations of chemical reactions by enzymes. Given that proteins display large ensembles of conformations, unique TSs would pose a huge entropic bottleneck for enzyme catalysis. To shed light on this question, we studied the nature of the enzymatic TS for the phosphoryl-transfer step in adenylate kinase by quantum-mechanics/molecular-mechanics calculations. We find a structurally wide set of energetically equivalent configurations that lie along the reaction coordinate and hence a broad transition-state ensemble (TSE). A conformationally delocalized ensemble, including asymmetric TSs, is rooted in the macroscopic nature of the enzyme. The computational results are buttressed by enzyme kinetics experiments that confirm the decrease of the entropy of activation predicted from such wide TSE. TSEs as a key for efficient enzyme catalysis further boosts a unifying concept for protein folding and conformational transitions underlying protein function.

Computational insights in repurposing a cardiovascular drug for Alzheimer's disease: the role of aromatic amino acids in stabilizing the drug through π-π stacking interaction

Alzheimer's disease (AD) is a neurological condition that worsens over time and causes linguistic difficulties, cognitive decline, and memory loss. Since AD is a complicated, multifaceted illness, it is critical to identify drugs to combat this degenerative condition. Histone deacetylase 2 (HDAC2) represents a promising epigenetic target for neurodegenerative diseases. So, for this study, we chose HDAC2 as the targeted protein. Repurposing drugs has many advantages, including reduced costs and high profits. There is a lower probability of malfunction because the unique drug candidate has previously completed numerous investigations. In this study, we have taken 58 clinically approved food and drug administration (FDA) drugs utilized in clinical trials for AD. Molecular docking was carried out for the 58 compounds. The telmisartan drug has the highest binding score of -9.4 kcal mol-1. The angiotensin II receptor blocker (ARB) telmisartan has demonstrated some promise in AD research as of the last update in January 2022. However, its exact significance in treating or preventing AD is still being studied. Molecular dynamics (MD) and molecular mechanics with generalized born and surface area solvation (MM-GBSA)/interaction entropy (IE) calculations were carried out to study the structural stability of the complexes. Umbrella sampling (US) techniques are a cutting-edge drug development method to understand more about the interactions between protein and ligand. π-π stacking interactions play a major role in helping the ligand to bind in the zinc bounding domain of the protein. From these analyses, we conclude that telmisartan, which is a cardiovascular drug, is more potent than the other drugs to treat AD. The anti-inflammatory, neuroprotective, and blood-brain barrier-crossing qualities of telmisartan make it a promising therapeutic agent for AD; however, more research, including larger clinical trials, is needed to determine the drug's precise role in treating AD.

Conformational Modulation of a Mobile Loop Controls Catalysis in the (βα)8-Barrel Enzyme of Histidine Biosynthesis HisF

The overall significance of loop motions for enzymatic activity is generally accepted. However, it has largely remained unclear whether and how such motions can control different steps of catalysis. We have studied this problem on the example of the mobile active site β1α1-loop (loop1) of the (βα)8-barrel enzyme HisF, which is the cyclase subunit of imidazole glycerol phosphate synthase. Loop1 variants containing single mutations of conserved amino acids showed drastically reduced rates for the turnover of the substrates N'-[(5'-phosphoribulosyl) formimino]-5-aminoimidazole-4-carboxamide ribonucleotide (PrFAR) and ammonia to the products imidazole glycerol phosphate (ImGP) and 5-aminoimidazole-4-carboxamide-ribotide (AICAR). A comprehensive mechanistic analysis including stopped-flow kinetics, X-ray crystallography, NMR spectroscopy, and molecular dynamics simulations detected three conformations of loop1 (open, detached, closed) whose populations differed between wild-type HisF and functionally affected loop1 variants. Transient stopped-flow kinetic experiments demonstrated that wt-HisF binds PrFAR by an induced-fit mechanism whereas catalytically impaired loop1 variants bind PrFAR by a simple two-state mechanism. Our findings suggest that PrFAR-induced formation of the closed conformation of loop1 brings active site residues in a productive orientation for chemical turnover, which we show to be the rate-limiting step of HisF catalysis. After the cyclase reaction, the closed loop conformation is destabilized, which favors the formation of detached and open conformations and hence facilitates the release of the products ImGP and AICAR. Our data demonstrate how different conformations of active site loops contribute to different catalytic steps, a finding that is presumably of broad relevance for the reaction mechanisms of (βα)8-barrel enzymes and beyond.

Changes in an enzyme ensemble during catalysis observed by high-resolution XFEL crystallography

Enzymes populate ensembles of structures necessary for catalysis that are difficult to experimentally characterize. We use time-resolved mix-and-inject serial crystallography at an x-ray free electron laser to observe catalysis in a designed mutant isocyanide hydratase (ICH) enzyme that enhances sampling of important minor conformations. The active site exists in a mixture of conformations, and formation of the thioimidate intermediate selects for catalytically competent substates. The influence of cysteine ionization on the ICH ensemble is validated by determining structures of the enzyme at multiple pH values. Large molecular dynamics simulations in crystallo and time-resolved electron density maps show that Asp17 ionizes during catalysis and causes conformational changes that propagate across the dimer, permitting water to enter the active site for intermediate hydrolysis. ICH exhibits a tight coupling between ionization of active site residues and catalysis-activated protein motions, exemplifying a mechanism of electrostatic control of enzyme dynamics.

Computational remodeling of an enzyme conformational landscape for altered substrate selectivity

Structural plasticity of enzymes dictates their function. Yet, our ability to rationally remodel enzyme conformational landscapes to tailor catalytic properties remains limited. Here, we report a computational procedure for tuning conformational landscapes that is based on multistate design of hinge-mediated domain motions. Using this method, we redesign the conformational landscape of a natural aminotransferase to preferentially stabilize a less populated but reactive conformation and thereby increase catalytic efficiency with a non-native substrate, resulting in altered substrate selectivity. Steady-state kinetics of designed variants reveals activity increases with the non-native substrate of approximately 100-fold and selectivity switches of up to 1900-fold. Structural analyses by room-temperature X-ray crystallography and multitemperature nuclear magnetic resonance spectroscopy confirm that conformational equilibria favor the target conformation. Our computational approach opens the door to targeted alterations of conformational states and equilibria, which should facilitate the design of biocatalysts with customized activity and selectivity.

Changes in an Enzyme Ensemble During Catalysis Observed by High Resolution XFEL Crystallography

Enzymes populate ensembles of structures with intrinsically different catalytic proficiencies that are difficult to experimentally characterize. We use time-resolved mix-and-inject serial crystallography (MISC) at an X-ray free electron laser (XFEL) to observe catalysis in a designed mutant (G150T) isocyanide hydratase (ICH) enzyme that enhances sampling of important minor conformations. The active site exists in a mixture of conformations and formation of the thioimidate catalytic intermediate selects for catalytically competent substates. A prior proposal for active site cysteine charge-coupled conformational changes in ICH is validated by determining structures of the enzyme over a range of pH values. A combination of large molecular dynamics simulations of the enzyme in crystallo and time-resolved electron density maps shows that ionization of the general acid Asp17 during catalysis causes additional conformational changes that propagate across the dimer interface, connecting the two active sites. These ionization-linked changes in the ICH conformational ensemble permit water to enter the active site in a location that is poised for intermediate hydrolysis. ICH exhibits a tight coupling between ionization of active site residues and catalysis-activated protein motions, exemplifying a mechanism of electrostatic control of enzyme dynamics.

Refinement of multiconformer ensemble models from multi-temperature X-ray diffraction data

Conformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363 K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca2+ binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships.

Decoupling of catalysis and transition state analog binding from mutations throughout a phosphatase revealed by high-throughput enzymology

Using high-throughput microfluidic enzyme kinetics (HT-MEK), we measured over 9,000 inhibition curves detailing impacts of 1,004 single-site mutations throughout the alkaline phosphatase PafA on binding affinity for two transition state analogs (TSAs), vanadate and tungstate. As predicted by catalytic models invoking transition state complementary, mutations to active site and active-site-contacting residues had highly similar impacts on catalysis and TSA binding. Unexpectedly, most mutations to more distal residues that reduced catalysis had little or no impact on TSA binding and many even increased tungstate affinity. These disparate effects can be accounted for by a model in which distal mutations alter the enzyme's conformational landscape, increasing the occupancy of microstates that are catalytically less effective but better able to accommodate larger transition state analogs. In support of this ensemble model, glycine substitutions (rather than valine) were more likely to increase tungstate affinity (but not more likely to impact catalysis), presumably due to increased conformational flexibility that allows previously disfavored microstates to increase in occupancy. These results indicate that residues throughout an enzyme provide specificity for the transition state and discriminate against analogs that are larger only by tenths of an Ångström. Thus, engineering enzymes that rival the most powerful natural enzymes will likely require consideration of distal residues that shape the enzyme's conformational landscape and fine-tune active-site residues. Biologically, the evolution of extensive communication between the active site and remote residues to aid catalysis may have provided the foundation for allostery to make it a highly evolvable trait.

Refinement of Multiconformer Ensemble Models from Multi-temperature X-ray Diffraction Data

Conformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca2+ binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships.

Structural evolution of Delta lineage of SARS-CoV-2

One of the main obstacles in prevention and treatment of COVID-19 is the rapid evolution of the SARS-CoV-2 Spike protein. Given that Spike is the main target of common treatments of COVID-19, mutations occurring at this virulent factor can affect the effectiveness of treatments. The B.1.617.2 lineage of SARS-CoV-2, being characterized by many Spike mutations inside and outside of its receptor-binding domain (RBD), shows high infectivity and relative resistance to existing cures. Here, utilizing a wide range of computational biology approaches, such as immunoinformatics, molecular dynamics (MD), analysis of intrinsically disordered regions (IDRs), protein-protein interaction analyses, residue scanning, and free energy calculations, we examine the structural and biological attributes of the B.1.617.2 Spike protein. Furthermore, the antibody design protocol of Rosetta was implemented for evaluation the stability and affinity improvement of the Bamlanivimab (LY-CoV55) antibody, which is not capable of interactions with the B.1.617.2 Spike. We observed that the detected mutations in the Spike of the B1.617.2 variant of concern can cause extensive structural changes compatible with the described variation in immunogenicity, secondary and tertiary structure, oligomerization potency, Furin cleavability, and drug targetability. Compared to the Spike of Wuhan lineage, the B.1.617.2 Spike is more stable and binds to the Angiotensin-converting enzyme 2 (ACE2) with higher affinity.

The Inhibitory Mechanism of 7H-Pyrrolo[2,3-d]pyrimidine Derivatives as Inhibitors of P21-Activated Kinase 4 through Molecular Dynamics Simulation

The overexpression of p21-activated kinase 4 (PAK4) is associated with a variety of cancers. In this paper, the binding modes and inhibitory mechanisms of four 7H-pyrrolo[2,3-d]pyrimidine competitive inhibitors of PAK4 were investigated at the molecular level, mainly using molecular dynamics simulations and binding free energy calculations. The results show that the inhibitors had strong interactions with the hinge region, the β-sheets, and the residues with charged side chains around the 4-substituent. The terminal amino group of the inhibitor 5n was different from the other three, which could cause the enhancement of hydrogen bonds or electrostatic interactions formed with the surrounding residues. Thus, inhibitor 5n had the strongest inhibition capacity. The different halogen atoms on the 2-substituents of the inhibitors 5h, 5g, and 5e caused differences in the positions of the 2-benzene rings and affected the interactions of the hinge region. It also affected to some extent the orientations of the 4-imino groups and consequently their affinities for the surrounding charged residues. The combined results lead to the weakest inhibitory capacity of inhibitor 5e.

DHFR Mutants Modulate Their Synchronized Dynamics with the Substrate by Shifting Hydrogen Bond Occupancies

Antibiotic resistance is a global health problem in which mutations occurring in functional proteins render drugs ineffective. The working mechanisms of the arising mutants are seldom apparent; a methodology to decipher these mechanisms systematically would render devising therapies to control the arising mutational pathways possible. Here we utilize C_α-C_β bond vector relaxations obtained from moderate length MD trajectories to determine conduits for functionality of the resistance conferring mutants of Escherichia coli dihydrofolate reductase. We find that the whole enzyme is synchronized to the motions of the substrate, irrespective of the mutation introducing gain-of-function or loss-of function. The total coordination of the motions suggests changes in the hydrogen bond dynamics with respect to the wild type as a possible route to determine and classify the mode-of-action of individual mutants. As a result, nine trimethoprim-resistant point mutations arising frequently in evolution experiments are categorized. One group of mutants that display the largest occurrence (L28R, W30G) work directly by modifying the dihydrofolate binding region. Conversely, W30R works indirectly by the formation of the E139-R30 salt bridge which releases energy resulting from tight binding by distorting the binding cavity. A third group (D27E, F153S, I94L) arising as single, resistance invoking mutants in evolution experiment trajectories allosterically and dynamically affects a hydrogen bonding motif formed at residues 59-69-71 which in turn modifies the binding site dynamics. The final group (I5F, A26T, R98P) consists of those mutants that have properties most similar to the wild type; these only appear after one of the other mutants is fixed on the protein structure and therefore display clear epistasis. Thus, we show that the binding event is governed by the entire enzyme dynamics while the binding site residues play gating roles. The adjustments made in the total enzyme in response to point mutations are what make quantifying and pinpointing their effect a hard problem. Here, we show that hydrogen bond dynamics recorded on sub-μs time scales provide the necessary fingerprints to decipher the various mechanisms at play.

Insight into the Inhibitory Mechanism of Aryl Formyl Piperidine Derivatives on Monoacylglycerol Lipase through Molecular Dynamics Simulations

Monoacylglycerol lipase (MAGL) can regulate the endocannabinoid system and thus becomes a target of antidepressant drugs. In this paper, molecular docking and molecular dynamics simulations, combined with binding free energy calculation, were employed to investigate the inhibitory mechanism and binding modes of four aryl formyl piperidine derivative inhibitors with different 1-substituents to MAGL. The results showed that in the four systems, the main four regions where the enzyme bound to the inhibitor included around the head aromatic ring, the head carbonyl oxygen, the tail amide bond, and the tail benzene ring. The significant conformational changes in the more flexible lid domain of the enzyme were caused by 1-substituted group differences of inhibitors and resulted in different degrees of flipping in the tail of the inhibitor. The flipping led to a different direction of the tail amide bond and made a greater variation in its interaction with some of the charged residues in the enzyme, which further contributed to a different swing of the tail benzene ring. If the swing is large enough, it can weaken the binding strength of the head carbonyl oxygen to its nearby residues, and even the whole inhibitor with the enzyme so that the inhibition decreases.

Strong and Reversible Covalent Double Network Hydrogel Based on Force-Coupled Enzymatic Reactions

Biological load-bearing tissues are strong, tough, and recoverable under periodic mechanical loads. However, such features have rarely been achieved simultaneously in the same synthetic hydrogels. Here, we use a force-coupled enzymatic reaction to tune a strong covalent peptide linkage to a reversible bond. Based on this concept we engineered double network hydrogels that combine high mechanical strength and reversible mechanical recovery in the same hydrogels. Specifically, we found that a peptide ligase, sortase A, can promote the proteolysis of peptides under force. The peptide bond can be re-ligated by the same enzyme in the absence of force. This allows the sacrificial network in the double-network hydrogels to be ruptured and rebuilt reversibly. Our results demonstrate a general approach for precisely controlling the mechanical and dynamic properties of hydrogels at the molecular level.

Hydride Transfer Mechanism of Enzymatic Sugar Nucleotide C2 Epimerization Probed with a Loose-Fit CDP-Glucose Substrate

Transient oxidation–reduction through hydride transfer with tightly bound NAD coenzyme is used by a large class of sugar nucleotide epimerases to promote configurational inversion of carbon stereocenters in carbohydrate substrates. A requirement for the epimerases to coordinate hydride abstraction and re-addition with substrate rotation in the binding pocket poses a challenge for dynamical protein conformational selection linked to enzyme catalysis. Here, we studied the thermophilic C2 epimerase from Thermodesulfatator atlanticus (TaCPa2E) in combination with a slow CDP-glucose substrate (k_cat ≈ 1.0 min^–1; 60 °C) to explore the sensitivity of the enzymatic hydride transfer toward environmental fluctuations affected by temperature (20–80 °C). We determined noncompetitive primary kinetic isotope effects (KIE) due to ²H at the glucose C2 and showed that a normal KIE on the k_cat (^Dk_cat) reflects isotope sensitivity of the hydrogen abstraction to enzyme-NAD⁺ in a rate-limiting transient oxidation. The ^Dk_cat peaked at 40 °C was 6.1 and decreased to 2.1 at low (20 °C) and 3.3 at high temperature (80 °C). The temperature profiles for k_cat with the ¹H and ²H substrate showed a decrease in the rate below a dynamically important breakpoint (∼40 °C), suggesting an equilibrium shift to an impaired conformational landscape relevant for catalysis in the low-temperature region. Full Marcus-like model fits of the rate and KIE profiles provided evidence for a high-temperature reaction via low-frequency conformational sampling associated with a broad distribution of hydride donor–acceptor distances (long-distance population centered at 3.31 ± 0.02 Å), only poorly suitable for quantum mechanical tunneling. Collectively, dynamical characteristics of TaCPa2E-catalyzed hydride transfer during transient oxidation of CDP-glucose reveal important analogies to mechanistically simpler enzymes such as alcohol dehydrogenase and dihydrofolate reductase. A loose-fit substrate (in TaCPa2E) resembles structural variants of these enzymes by extensive dynamical sampling to balance conformational flexibility and catalytic efficiency.

Structural dynamics support electrostatic interactions in the active site of Adenylate Kinase

Electrostatic preorganization as well as structural and dynamic heterogeneity are often used to rationalize the remarkable catalytic efficiency of enzymes. However, they are often presented as incompatible because the generation of permanent electrostatic effects implies that the protein structure remains rigid. Here, we use a metric, electric fields, that can treat electrostatic contributions and dynamics effects on equal footing, for a unique perspective on enzymatic catalysis. We find that the residues that contribute the most to electrostatic interactions with the substrate in the active site of Adenylate Kinase (our working example) are also the most flexible residues. Further, entropy-tuning mutations raise flexibility at the picosecond timescale where more conformations can be visited on short time periods, thereby softening the sharp heterogeneity normally visible at the microsecond timescale.

Heterogeneity in Protein Folding and Unfolding Reactions

Proteins have dynamic structures that undergo chain motions on time scales spanning from picoseconds to seconds. Resolving the resultant conformational heterogeneity is essential for gaining accurate insight into fundamental mechanistic aspects of the protein folding reaction. The use of high-resolution structural probes, sensitive to population distributions, has begun to enable the resolution of site-specific conformational heterogeneity at different stages of the folding reaction. Different states populated during protein folding, including the unfolded state, collapsed intermediate states, and even the native state, are found to possess significant conformational heterogeneity. Heterogeneity in protein folding and unfolding reactions originates from the reduced cooperativity of various kinds of physicochemical interactions between various structural elements of a protein, and between a protein and solvent. Heterogeneity may arise because of functional or evolutionary constraints. Conformational substates within the unfolded state and the collapsed intermediates that exchange at rates slower than the subsequent folding steps give rise to heterogeneity on the protein folding pathways. Multiple folding pathways are likely to represent distinct sequences of structure formation. Insight into the nature of the energy barriers separating different conformational states populated during (un)folding can also be obtained by resolving heterogeneity.

Experimental mapping of short-wavelength phonons in proteins

Phonons are quasi-particles, observed as lattice vibrations in periodic materials, that often dampen in the presence of structural perturbations. Nevertheless, phonon-like collective excitations exist in highly complex systems, such as proteins, although the origin of such collective motions has remained elusive. Here we present a picture of temperature and hydration dependence of collective excitations in green fluorescent protein (GFP) obtained by inelastic neutron scattering. Our results provide evidence that such excitations can be used as a measure of flexibility/softness and are possibly associated with the protein’s activity. Moreover, we show that the hydration water in GFP interferes with the phonon propagation pathway, enhancing the structural rigidity and stability of GFP.

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Quantum phenomena in biology have long fascinated people around the world

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This work presents a direct experimental observation of phonons, the quantum vibrations in a protein

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The collective excitations or phonons in proteins were detected by utilizing inelastic neutron scattering technique at Oak Ridge National Laboratory

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Our results illustrate the flexibility-activity relationship in proteins by mapping the temperature and hydration dependence of these collective excitations

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.

Analytical and functional aspects of protein-ligand interactions: Beyond induced fit and conformational selection

Ligand-dependent changes in protein conformation are foundational to biology. Historical mechanistic models for substrate-specific proteins are induced fit (IF) and conformational selection (CS), which invoke a change in protein conformation after ligand binds or before ligand binds, respectively. These mechanisms have important, but rarely discussed, functional relevance because IF vs. CS can differentially affect a protein's substrate specificity or promiscuity, and its regulatory properties. The modern view of proteins as conformational ensembles in both ligand free and bound states, together with the realization that most proteins exhibit some substrate promiscuity, demands a deeper interpretation of the historical models and provides an opportunity to improve mechanistic analyses. Here we describe alternative analytical strategies for distinguishing the historical models, including the more complex expanded versions of IF and CS. Functional implications of the different models are described. We provide an alternative perspective based on protein ensembles interacting with ligand ensembles that clarifies how a single protein can 'apparently' exploit different mechanisms for different ligands. Mechanistic information about protein ensembles can be optimized when they are probed with multiple ligands.

Molecular Mechanism of Methanol Inhibition in CALB-Catalyzed Alcoholysis: Analyzing Molecular Dynamics Simulations by a Markov State Model

Lipases are widely used enzymes that catalyze hydrolysis and alcoholysis of fatty acid esters. At high concentrations of small alcohols such as methanol or ethanol, many lipases are inhibited by the substrate. The molecular basis of the inhibition of Candida antarctica lipase B (CALB) by methanol was investigated by unbiased molecular dynamics (MD) simulations, and the substrate binding kinetics was analyzed by Markov state models (MSMs). The modeled fluxes of productive methanol binding at concentrations between 50 mM and 5.5 M were in good agreement with the experimental activity profile of CALB, with a peak at 300 mM. The kinetic and structural analysis uncovered the molecular basis of CALB inhibition. Beyond 300 mM, the kinetic bottleneck results from crowding of methanol in the substrate access channel, which is caused by the gradual formation of methanol patches close to Leu140 (helix α5), Leu278, and Ile285 (helix α10) at a distance of 4-5 Å from the active site. Our findings demonstrate the usefulness of unbiased MD simulations to study enzyme-substrate interactions at realistic substrate concentrations and the feasibility of scale-bridging by an MSM analysis to derive kinetic information.

Out-of-Equilibrium Biophysical Chemistry: The Case for Multidimensional, Integrated Single-Molecule Approaches

Out-of-equilibrium processes are ubiquitous across living organisms and all structural hierarchies of life. At the molecular scale, out-of-equilibrium processes (for example, enzyme catalysis, gene regulation, and motor protein functions) cause biological macromolecules to sample an ensemble of conformations over a wide range of time scales. Quantifying and conceptualizing the structure–dynamics to function relationship is challenging because continuously evolving multidimensional energy landscapes are necessary to describe nonequilibrium biological processes in biological macromolecules. In this perspective, we explore the challenges associated with state-of-the-art experimental techniques to understanding biological macromolecular function. We argue that it is time to revisit how we probe and model functional out-of-equilibrium biomolecular dynamics. We suggest that developing integrated single-molecule multiparametric force–fluorescence instruments and using advanced molecular dynamics simulations to study out-of-equilibrium biomolecules will provide a path towards understanding the principles of and mechanisms behind the structure–dynamics to function paradigm in biological macromolecules.

Accounting for the instantaneous disorder in the enzyme-substrate Michaelis complex to calculate the Gibbs free energy barrier of an enzyme reaction

Many enzyme reactions present instantaneous disorder. These dynamic fluctuations in the enzyme-substrate Michaelis complexes generate a wide range of energy barriers that cannot be experimentally observed, but that determine the measured kinetics of the reaction. These individual energy barriers can be calculated using QM/MM methods, but then the problem is how to deal with this dispersion of energy barriers to provide kinetic information. So far, the most usual procedure has implied the so-called exponential average of the energy barriers. In this paper, we discuss the foundations of this method, and we use the free energy perturbation theory to derive an alternative equation to get the Gibbs free energy barrier of the enzyme reaction. In addition, we propose a practical way to implement it. We have chosen four enzyme reactions as examples. In particular, we have studied the hydrolysis of a glycosidic bond catalyzed by the enzyme Thermus thermophilus β-glycosidase, and the mutant Y284P Ttb-gly, and the hydrogen abstraction reactions from C13 and C7 of arachidonic acid catalyzed by the enzyme rabbit 15-lipoxygenase-1.

Unifying Catalysis Framework to Dissect Proteasomal Degradation Paradigms

Diverging from traditional target inhibition, proteasomal protein degradation approaches have emerged as novel therapeutic modalities that embody distinct pharmacological profiles and can access previously undrugged targets. Small molecule degraders have the potential to catalytically destroy target proteins at substoichiometric concentrations, thus lowering administered doses and extending pharmacological effects. With this mechanistic premise, research efforts have advanced the development of small molecule degraders that benefit from stable and increased affinity ternary complexes. However, a holistic framework that evaluates different degradation modes from a catalytic perspective, including focusing on kinetically favored degradation mechanisms, is lacking. In this Outlook, we introduce the concept of an induced cooperativity spectrum as a unifying framework to mechanistically understand catalytic degradation profiles. This framework is bolstered by key examples of published molecular degraders extending from molecular glues to bivalent degraders. Critically, we discuss remaining challenges and future opportunities in drug discovery to rationally design and phenotypically screen for efficient degraders.

Correlated Motions in Structural Biology

Correlated motions in proteins arising from the collective movements of residues have long been proposed to be fundamentally important to key properties of proteins, from allostery and catalysis to evolvability. Recent breakthroughs in structural biology have made it possible to capture proteins undergoing complex conformational changes, yet intrinsic correlated motions within a conformation remain one of the least understood facets of protein structure. For many decades, the analysis of total X-ray scattering held the promise of animating crystal structures with correlated motions. With recent advances in both X-ray detectors and data interpretation methods, this long-held promise can now be met. In this Perspective, we will introduce how correlated motions are captured in total scattering and provide guidelines for the collection, interpretation, and validation of data. As structural biology continues to push the boundaries, we see an opportunity to gain atomistic insight into correlated motions using total scattering as a bridge between theory and experiment.

Quantum Sensing of Electron Transfer Pathways in Natural Photosynthesis Using Time-Resolved High-Field Electron Paramagnetic Resonance/Electron-Nuclear Double Resonance Spectroscopy

Photosynthetic integral membrane reaction center (RC) proteins capture and convert sunlight into chemical energy via efficient charge separation achieved through a series of rapid, photoinitiated electron transfer steps. These fast electron transfers create an entangled spin qubit (radical) pair that contains detailed information about the weak magnetic interactions, structure, and dynamics of localized protein environments involved in charge separation events. Herein, we investigate how these entangled electron spin qubits interact with nuclear spins of the protein environment using the high spectral resolution of 130 GHz electron paramagnetic resonance (EPR) and electron-nuclear double resonance (ENDOR). Spectroscopic interrogation enabled the observation and probing of protons located in the electron transfer pathway between the membrane-spanning electron pair P⁺Q_A^- (where P⁺ is the primary donor, a special pair of bacteriochlorophylls, and Q_A is the primary quinone acceptor) in the bacterial RC. Spectroscopic analysis reveals hydrogen-bonding interactions involved in regulating the route that light-induced electrons travel through the RC protein during charge separation.

Enzyme free energy profiles: Can substrate binding be nonspontaneous? Can ground state interactions enhance catalysis?

Two influential enzymological theories were proposed in the late 1970s - that catalytic power stems only from transition state stabilization, while ground state interactions are either irrelevant or inhibitory; and enzyme substrate binding is nonspontaneous at low substrate concentrations ([S]₀ << K_m). I show here that ground state destabilization can be a very effective source of catalytic power, especially at high substrate concentrations, and enzyme-substrate binding thermodynamics are independent of initial substrate concentration. Binding free energy ranges from negative (spontaneous) under pre-steady state conditions up to a maximum of zero at steady state. Nonspontaneous binding can only occur under standard state conditions when c° is defined to be less than K_m.

Biomolecular QM/MM Simulations: What Are Some of the "Burning Issues"?

QM/MM simulations have become an indispensable tool in many chemical and biochemical investigations. Considering the tremendous degree of success, including recognition by a 2013 Nobel Prize in Chemistry, are there still "burning challenges" in QM/MM methods, especially for biomolecular systems? In this short Perspective, we discuss several issues that we believe greatly impact the robustness and quantitative applicability of QM/MM simulations to many, if not all, biomolecules. We highlight these issues with observations and relevant advances from recent studies in our group and others in the field. Despite such limited scope, we hope the discussions are of general interest and will stimulate additional developments that help push the field forward in meaningful directions.

Catalytic Principles from Natural Enzymes and Translational Design Strategies for Synthetic Catalysts

As biocatalysts, enzymes are characterized by their high catalytic efficiency and strong specificity but are relatively fragile by requiring narrow and specific reactive conditions for activity. Synthetic catalysts offer an opportunity for more chemical versatility operating over a wider range of conditions but currently do not reach the remarkable performance of natural enzymes. Here we consider some new design strategies based on the contributions of nonlocal electric fields and thermodynamic fluctuations to both improve the catalytic step and turnover for rate acceleration in arbitrary synthetic catalysts through bioinspired studies of natural enzymes. With a focus on the enzyme as a whole catalytic construct, we illustrate the translational impact of natural enzyme principles to synthetic enzymes, supramolecular capsules, and electrocatalytic surfaces.

Acceleration of catalysis in dihydrofolate reductase by transient, site-specific photothermal excitation

We have studied the role of protein dynamics in chemical catalysis in the enzyme dihydrofolate reductase (DHFR), using a pump-probe method that employs pulsed-laser photothermal heating of a gold nanoparticle (AuNP) to directly excite a local region of the protein structure and transient absorbance to probe the effect on enzyme activity. Enzyme activity is accelerated by pulsed-laser excitation when the AuNP is attached close to a network of coupled motions in DHFR (on the FG loop, containing residues 116-132, or on a nearby alpha helix). No rate acceleration is observed when the AuNP is attached away from the network (distal mutant and His-tagged mutant) with pulsed excitation, or for any attachment site with continuous wave excitation. We interpret these results within an energy landscape model in which transient, site-specific addition of energy to the enzyme speeds up the search for reactive conformations by activating motions that facilitate this search.

Kinetic Evidence for an Induced Fit Mechanism in the Binding of the Substrate Camphor by Cytochrome P450cam

Bacterial cytochrome P450 (P450) 101A1 (P450cam) has served as a prototype among the P450 enzymes and has high catalytic activity towards its cognate substrate, camphor. X-ray crystallography and NMR and IR spectroscopy have demonstrated the existence of multiple conformations of many P450s, including P450cam. Kinetic studies have indicated that substrate binding to several P450s is dominated by a conformational selection process, in which the substrate binds an individual conformer(s) of the unliganded enzyme. P450cam was found to differ in that binding of the substrate camphor is dominated by an induced fit mechanism, in which the enzyme binds camphor and then changes conformation, as evidenced by the equivalence of binding eigenvalues observed when varying both camphor and P450cam concentrations. The accessory protein putidaredoxin had no effect on substrate binding. Estimation of the rate of dissociation of the P450cam·camphor complex (15 s-1) and fitting of the data yield a minimal kinetic mechanism in which camphor binds (1.5 × 107 M-1 s-1) and the initial P450cam•camphor complex undergoes a reversible equilibrium (k forward 112 s-1, k reverse 28 s-1) to a final complex. This induced fit mechanism differs from those reported for several mammalian P450s and bacterial P450BM-3, indicative of the diversity of how P450s recognize multiple substrates. However, similar behavior was not observed with the alternate substrates (+)-α-pinene and 2-adamantanone, which probably utilize a conformational selection process.

Enzyme dynamics: Looking beyond a single structure

Conventional understanding of how enzymes function strongly emphasizes the role of structure. However, increasing evidence clearly indicates that enzymes do not remain fixed or operate exclusively in or close to their native structure. Different parts of the enzyme (from individual residues to full domains) undergo concerted motions on a wide range of time-scales, including that of the catalyzed reaction. Information obtained on these internal motions and conformational fluctuations has so far uncovered and explained many aspects of enzyme mechanisms, which could not have been understood from a single structure alone. Although there is wide interest in understanding enzyme dynamics and its role in catalysis, several challenges remain. In addition to technical difficulties, the vast majority of investigations are performed in dilute aqueous solutions, where conditions are significantly different than the cellular milieu where a large number of enzymes operate. In this review, we discuss recent developments, several challenges as well as opportunities related to this topic. The benefits of considering dynamics as an integral part of the enzyme function can also enable new means of biocatalysis, engineering enzymes for industrial and medicinal applications.

Hydrogen deuterium exchange defines catalytically linked regions of protein flexibility in the catechol O-methyltransferase reaction

Human catechol O-methyltransferase (COMT) has emerged as a model for understanding enzyme-catalyzed methyl transfer from S-adenosylmethionine (AdoMet) to small-molecule catecholate acceptors. Mutation of a single residue (tyrosine 68) behind the methyl-bearing sulfonium of AdoMet was previously shown to impair COMT activity by interfering with methyl donor-acceptor compaction within the activated ground state of the wild type enzyme [J. Zhang, H. J. Kulik, T. J. Martinez, J. P. Klinman, Proc. Natl. Acad. Sci. U.S.A. 112, 7954-7959 (2015)]. This predicts the involvement of spatially defined protein dynamical effects that further tune the donor/acceptor distance and geometry as well as the electrostatics of the reactants. Here, we present a hydrogen/deuterium exchange (HDX)-mass spectrometric study of wild type and mutant COMT, comparing temperature dependences of HDX against corresponding kinetic and cofactor binding parameters. The data show that the impaired Tyr68Ala mutant displays similar breaks in Arrhenius plots of both kinetic and HDX properties that are absent in the wild type enzyme. The spatial resolution of HDX below a break point of 15-20 °C indicates changes in flexibility across ∼40% of the protein structure that is confined primarily to the periphery of the AdoMet binding site. Above 20 °C, Tyr68Ala behaves more like WT in HDX, but its rate and enthalpic barrier remain significantly altered. The impairment of catalysis by Tyr68Ala can be understood in the context of a mutationally induced alteration in protein motions that becomes manifest along and perpendicular to the primary group transfer coordinate.

Methylene Oxidation of Alkyl Sulfates by Cytochrome P450BM-3 and a Role for Conformational Selection in Substrate Recognition

Cytochrome P450_BM-3 (P450_BM-3) is a flavoprotein reductase-heme fusion protein from the bacterium Bacillus megaterium that has been well-characterized in many biophysical aspects. Although the enzyme is known to catalyze the hydroxylation of medium and long-chain fatty acids at high rates, no definitive physiological function has been associated with this process in the organism other than a possible protective role. We found that P450_BM-3 rapidly hydroxylates alkyl sulfates, particularly those with 12-16 carbons (i.e., including dodecyl sulfate) in a similar manner to the fatty acids. The products were characterized as primarily ω-1 hydroxylated alkyl sulfates (plus some ω-2 and ω-3 hydroxylation products), and some further oxidation to dihydroxy and keto derivatives also occurred. Binding of the alkyl sulfates to P450_BM-3 converted the iron from the low-spin to high-spin form in a saturable manner, consistent with the catalytic results. Rates of binding decreased as a function of increasing concentration of dodecyl sulfate or the fatty acid myristate. This pattern is consistent with a binding model involving multiple events and with conformational selection (equilibrium of the unbound enzyme prior to binding) instead of an induced fit mechanism. Neither C-H bond-breaking nor product release was found to be rate-limiting in the oxidation of lauric acid. The conformational selection results rationalize some known crystal structures of P450_BM-3 and can help explain the flexibility of P450_BM-3 and engineered forms in accepting a great variety of substrates.

Reaction mechanism of nucleoside 2'-deoxyribosyltransferases: free-energy landscape supports an oxocarbenium ion as the reaction intermediate

Insight into the catalytic mechanism of Lactobacillus leichmannii nucleoside 2'-deoxyribosyltransferase (LlNDT) has been gained by calculating a quantum mechanics-molecular mechanics (QM/MM) free-energy landscape of the reaction within the enzyme active site. Our results support an oxocarbenium species as the reaction intermediate and thus an SN1 reaction mechanism in this family of bacterial enzymes. Our mechanistic proposal is validated by comparing experimental kinetic data on the impact of the single amino acid replacements Tyr7, Glu98 and Met125 with Ala, Asp and Ala/norLeu, respectively, and accounts for the specificity shown by this enzyme on a non-natural substrate. This work broadens our understanding of enzymatic C-N bond cleavage and C-N bond formation.

A protocol to obtain multidimensional quantum tunneling corrections derived from QM(DFT)/MM calculations for an enzyme reaction

The multidimensional small-curvature tunneling (SCT) method with Electrostatic Embedding calculations is a compromise between an accessible computational cost and the attainment of an accurate enough estimation of tunneling for an enzyme reaction.

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.

Detecting and Characterizing the Kinetic Activation of Thermal Networks in Proteins: Thermal Transfer from a Distal, Solvent-Exposed Loop to the Active Site in Soybean Lipoxygenase

The rate-limiting chemical reaction catalyzed by soybean lipoxygenase (SLO) involves quantum mechanical tunneling of a hydrogen atom from substrate to its active site ferric-hydroxide cofactor. SLO has emerged as a prototypical system for linking the thermal activation of a protein scaffold to the efficiency of active site chemistry. Significantly, hydrogen-deuterium exchange-mass spectrometry (HDX-MS) experiments on wild type and mutant forms of SLO have uncovered trends in the enthalpic barriers for HDX within a solvent-exposed loop (positions 317-334) that correlate well with trends in the corresponding enthalpic barriers for kcat. A model for this behavior posits that collisions between water and loop 317-334 initiate thermal activation at the protein surface that is then propagated 15-34 Å inward toward the reactive carbon of substrate in proximity to the iron catalyst. In this study, we have prepared protein samples containing cysteine residues either at the tip of the loop 317-334 (Q322C) or on a control loop, 586-603 (S596C). Chemical modification of cysteines with the fluorophore 6-bromoacetyl-2-dimethylaminonaphthalene (Badan, BD) provides site-specific probes for the measurement of fluorescence relaxation lifetimes and Stokes shift decays as a function of temperature. Computational studies indicate that surface water structure is likely to be largely preserved in each sample. While both loops exhibit temperature-independent fluorescence relaxation lifetimes as do the Stokes shifts for S596C-BD, the activation enthalpy for the nanosecond solvent reorganization at Q322C-BD (Ea(ksolv) = 2.8(0.9) kcal/mol)) approximates the enthalpy of activation for catalytic C-H activation (Ea(kcat) = 2.3(0.4) kcal/mol). This study establishes and validates the methodology for measuring rates of rapid local motions at the protein/solvent interface of SLO. These new findings, when combined with previously published correlations between protein motions and the rate-limiting hydride transfer in a thermophilic alcohol dehydrogenase, provide experimental evidence for thermally induced "protein quakes" as the origin of enthalpic barriers in catalysis.

Numerical optimization of probiotic Ayran production based on whey containing transglutaminase and Aloe vera gel

The purpose of this study was to optimize the functional properties of probiotic Ayran. Two-level fractional factorial design with four center points was used to investigate the effect of five independent variables including, reconstructed whey protein (70-90% of milk), salt (0.5-1 g/100 g), Aloe vera gel (0-30 g/100 g), transglutaminase enzyme (0-14 unit/100 g) and storage time (1-21 days). The viability of Lactobacillus acidophilus La-5 and other physicochemical properties such as pH, acidity, viscosity, sedimentation, and color were modeled and then optimized using desirability function method. Results showed that reconstructed whey protein and Aloe vera gel significantly affected the viability of L. acidophilus La-5 and other physicochemical properties (p < 0.05). The viability of L. acidophilus La-5 and viscosity decreased by increasing of whey protein percentage from 70 to 90. Maximum L. acidophilus La-5 count was observed in samples with a minimum level of whey protein and maximum level of Aloe vera gel. Milk replacement with whey protein up to 90% caused to decrease acidity and viscosity significantly but sedimentation increased (p < 0.05). Optimum condition for production of functional Ayran determined as follow: Aloe vera gel concentration: 25.7%, reconstructed whey protein: 70%, salt: 0.58% and transglutaminase enzyme: 5 unit/100 mL.

Human cytochrome P450 enzymes bind drugs and other substrates mainly through conformational-selection modes

Cytochrome P450 (P450) enzymes are major catalysts involved in the oxidations of most drugs, steroids, carcinogens, fat-soluble vitamins, and natural products. The binding of substrates to some of the 57 human P450s and other mammalian P450s is more complex than a two-state system and has been proposed to involve mechanisms such as multiple ligand occupancy, induced-fit, and conformational-selection. Here, we used kinetic analysis of binding with multiple concentrations of substrates and computational modeling of these data to discern possible binding modes of several human P450s. We observed that P450 2D6 binds its ligand rolapitant in a mechanism involving conformational-selection. P450 4A11 bound the substrate lauric acid via conformational-selection, as did P450 2C8 with palmitic acid. Binding of the steroid progesterone to P450 21A2 was also best described by a conformational-selection model. Hexyl isonicotinate binding to P450 2E1 could be described by either a conformational-selection or an induced-fit model. Simulation of the binding of the ligands midazolam, bromocriptine, testosterone, and ketoconazole to P450 3A4 was consistent with an induced-fit or a conformational-selection model, but the concentration dependence of binding rates for varying both P450 3A4 and midazolam concentrations revealed discordance in the parameters, indicative of conformational-selection. Binding of the P450s 2C8, 2D6, 3A4, 4A11, and 21A2 was best described by conformational-selection, and P450 2E1 appeared to fit either mode. These findings highlight the complexity of human P450-substrate interactions and that conformational-selection is a dominant feature of many of these interactions.

Computational insights into the different catalytic activities of CYP3A4 and CYP3A5 toward schisantherin E

The cytochromes CYP3A4 and CYP3A5 share 84% sequence identity, but they exhibit different catalytic activities toward some substrates. Schisantherin E (SE) was recently identified as a selective substrate of CYP3A5, which exhibited catalytic efficiency that was more than 23 times higher than CYP3A4. At present, however, the structural determinants responsible for the different catalytic activities of the two enzymes toward SE have not been fully understood. In this study, a combination of molecular docking, molecular dynamic simulations, and binding free energy calculation was performed on the CYP3A4/CYP3A5-SE systems to investigate the issue. The results demonstrate that Ser119 in CYP3A4 and Glu374 in CYP3A5 formed direct hydrogen bonding with SE, respectively. Additionally, one water molecule located between the B-C loop and the I helix mediated different hydrogen-bonding networks between CYP3A4/3A5 and SE. The residue differences (Phe/Leu108 and Leu/Phe210) triggered the distinct conformational changes of the Phe-cluster residues, especially Phe213 and Phe215, which formed stronger hydrophobic interactions with SE in CYP3A5. The calculated binding free energies were consistent with the experimental results.

Why the Energy Landscape of Barnase Is Hierarchical

We have used NMR and computational methods to characterize the dynamics of the ribonuclease barnase over a wide range of timescales in free and inhibitor-bound states. Using temperature- and denaturant-dependent measurements of chemical shift, we show that barnase undergoes frequent and highly populated hinge bending. Using relaxation dispersion, we characterize a slower and less populated motion with a rate of 750 ± 200 s⁻¹, involving residues around the lip of the active site, which occurs in both free and bound states and therefore suggests conformational selection. Normal mode calculations characterize correlated hinge bending motions on a very rapid timescale. These three measurements are combined with previous measurements and molecular dynamics calculations on barnase to characterize its dynamic landscape on timescales from picoseconds to milliseconds and length scales from 0.1 to 2.5 nm. We show that barnase has two different large-scale fluctuations: one on a timescale of 10⁻⁹−10⁻⁶ s that has no free energy barrier and is a hinge bending that is determined by the architecture of the protein; and one on a timescale of milliseconds (i.e., 750 s⁻¹) that has a significant free energy barrier and starts from a partially hinge-bent conformation. These two motions can be described as hierarchical, in that the more highly populated faster motion provides a platform for the slower (less probable) motion. The implications are discussed. The use of temperature and denaturant is suggested as a simple and general way to characterize motions on the intermediate ns-μs timescale.

A Biophysical Perspective on Enzyme Catalysis

Even after a century of investigation, our understanding of how enzymes work remains far from complete. In particular, several factors that enable enzymes to achieve high catalytic efficiencies remain only poorly understood. A number of theories have been developed, which propose or reaffirm that enzymes work as structural scaffolds, serving to bring together and properly orient the participants so that the reaction can proceed; therefore, leading to enzymes being viewed as only passive participants in the catalyzed reaction. A growing body of evidence shows that enzymes are not rigid structures but are constantly undergoing a wide range of internal motions and conformational fluctuations. In this Perspective, on the basis of studies from our group, we discuss the emerging biophysical model of enzyme catalysis that provides a detailed understanding of the interconnection among internal protein motions, conformational substates, enzyme mechanisms, and the catalytic efficiency of enzymes. For a number of enzymes, networks of conserved residues that extend from the surface of the enzyme all the way to the active site have been discovered. These networks are hypothesized to serve as pathways of energy transfer that enables thermodynamical coupling of the surrounding solvent with enzyme catalysis and play a role in promoting enzyme function. Additionally, the role of enzyme structure and electrostatic effects has been well acknowledged for quite some time. Collectively, the recent knowledge gained about enzyme mechanisms suggests that the conventional paradigm of enzyme structure encoding function is incomplete and needs to be extended to structure encodes dynamics, and together these enzyme features encode function including catalytic rate acceleration.

Single-Molecule Studies of Allosteric Inhibition of Individual Enzyme on a DNA Origami Reactor

Unraveling the conformational changes of enzymes together with inhibition kinetics during an enzymatic reaction has great potential in screening therapeutic candidates; however, it remains challenging due to the transient nature of each intermediate step. We report our study on the noncompetitive inhibition of horseradish peroxidase with single-turnover resolution using single-molecule fluorescence microscopy. By introducing DNA origami as an addressable nanoreactor, we observe the coexistence of nascent-formed fluorescent product on both catalytic and docking sites. We further propose a single-molecule kinetic model to reveal the interplay between product generation and noncompetitive inhibition and find three distinct inhibitor releasing pathways. Moreover, the kinetic isotope effect experiment indicates a strong correlation between catalytic and docking sites, suggesting an allosteric conformational change in noncompetitive inhibition. A memory effect is also observed. This work provides an in-depth understanding of the correlation between enzyme behavior and enzymatic conformational fluctuation, substrate conversion, and product releasing pathway and kinetics.