Illuminating the mechanistic roles of enzyme conformational dynamics

Toward the Prediction of Binding Events in Very Flexible, Allosteric, Multidomain Proteins

Knowledge of the structures formed by proteins and small molecules is key to understand the molecular principles of chemotherapy and for designing new and more effective drugs. During the early stage of a drug discovery program, it is customary to predict ligand-protein complexes in silico, particularly when screening large compound databases. While virtual screening based on molecular docking is widely used for this purpose, it generally fails in mimicking binding events associated with large conformational changes in the protein, particularly when the latter involve multiple domains. In this work, we describe a new methodology to generate bound-like conformations of very flexible and allosteric proteins bearing multiple binding sites by exploiting only information on the unbound structure and the putative binding sites. The protocol is validated on the paradigm enzyme adenylate kinase, for which we generated a significant fraction of bound-like structures. A fraction of these conformations, employed in ensemble-docking calculations, allowed to find native-like poses of substrates and inhibitors (binding to the active form of the enzyme), as well as catalytically incompetent analogs (binding the inactive form). Our protocol provides a general framework for the generation of bound-like conformations of challenging drug targets that are suitable to host different ligands, demonstrating high sensitivity to the fine chemical details that regulate protein's activity. We foresee applications in virtual screening, in the prediction of the impact of amino acid mutations on structure and dynamics, and in protein engineering.

Interplay between conformational dynamics and substrate binding regulates enzymatic activity: a single-molecule FRET study

Proteins often harness extensive motions of domains and subunits to promote their function. Deciphering how these movements impact activity is key for understanding life's molecular machinery. The enzyme adenylate kinase is an intriguing example for this relationship; it ensures efficient catalysis by large-scale domain motions that lead to the enclosure of the bound substrates ATP and AMP. Surprisingly, the enzyme is activated by urea, a compound commonly acting as a denaturant. We utilize this phenomenon to decipher the involvement of conformational dynamics in the mechanism of action of the enzyme. Combining single-molecule FRET spectroscopy and enzymatic activity studies, we find that urea promotes the open conformation of the enzyme, aiding the proper positioning of the substrates. Further, urea decreases AMP affinity, paradoxically facilitating a more efficient progression towards the catalytically active complex. These results allow us to define a complete kinetic scheme that includes the open/close transitions of the enzyme and to unravel the important interplay between conformational dynamics and chemical steps, a general property of enzymes. State-of-the-art tools, such as single-molecule fluorescence spectroscopy, offer new insights into how enzymes balance different conformations to regulate activity.

Allostery can convert binding free energies into concerted domain motions in enzymes

Enzymatic mechanisms are typically inferred from structural data. However, understanding enzymes require unravelling the intricate dynamic interplay between dynamics, conformational substates, and multiple protein structures. Here, we use single-molecule nanopore analysis to investigate the catalytic conformational changes of adenylate kinase (AK), an enzyme that catalyzes the interconversion of various adenosine phosphates (ATP, ADP, and AMP). Kinetic analysis validated by hidden Markov models unravels the details of domain motions during catalysis. Our findings reveal that allosteric interactions between ligands and cofactor enable converting binding energies into directional conformational changes of the two catalytic domains of AK. These coordinated motions emerged to control the exact sequence of ligand binding and the affinity for the three different substrates, thereby guiding the reactants along the reaction coordinates. Interestingly, we find that about 10% of enzymes show altered allosteric regulation and ligand affinities, indicating that a subset of enzymes folds in alternative catalytically active forms. Since molecules or proteins might be able to selectively stabilize one of the folds, this observation suggests an evolutionary path for allostery in enzymes. In AK, this complex catalytic framework has likely emerged to prevent futile ATP/ADP hydrolysis and to regulate the enzyme for different energy needs of the cell.

Predicting binding events in very flexible, allosteric, multi-domain proteins

Knowledge of the structures formed by proteins and small molecules is key to understand the molecular principles of chemotherapy and for designing new and more effective drugs. During the early stage of a drug discovery program, it is customary to predict ligand-protein complexes in silico, particularly when screening large compound databases. While virtual screening based on molecular docking is widely used for this purpose, it generally fails in mimicking binding events associated with large conformational changes in the protein, particularly when the latter involve multiple domains. In this work, we describe a new methodology to generate bound-like conformations of very flexible and allosteric proteins bearing multiple binding sites by exploiting only information on the unbound structure and the putative binding sites. The protocol is validated on the paradigm enzyme adenylate kinase, for which we generated a significant fraction of bound-like structures. A fraction of these conformations, employed in ensemble-docking calculations, allowed to find native-like poses of substrates and inhibitors (binding to the active form of the enzyme), as well as catalytically incompetent analogs (binding the inactive form). Our protocol provides a general framework for the generation of bound-like conformations of challenging drug targets that are suitable to host different ligands, demonstrating high sensitivity to the fine chemical details that regulate protein's activity. We foresee applications in virtual screening, in the prediction of the impact of amino acid mutations on structure and dynamics, and in protein engineering.

Evolutionary-Scale Enzymology Enables Biochemical Constant Prediction Across a Multi-Peaked Catalytic Landscape

Quantitatively mapping enzyme sequence-catalysis landscapes remains a critical challenge in understanding enzyme function, evolution, and design. Here, we expand an emerging microfluidic platform to measure catalytic constants-k cat and K M-for hundreds of diverse naturally occurring sequences and mutants of the model enzyme Adenylate Kinase (ADK). This enables us to dissect the sequence-catalysis landscape's topology, navigability, and mechanistic underpinnings, revealing distinct catalytic peaks organized by structural motifs. These results challenge long-standing hypotheses in enzyme adaptation, demonstrating that thermophilic enzymes are not slower than their mesophilic counterparts. Combining the rich representations of protein sequences provided by deep-learning models with our custom high-throughput kinetic data yields semi-supervised models that significantly outperform existing models at predicting catalytic parameters of naturally occurring ADK sequences. Our work demonstrates a promising strategy for dissecting sequence-catalysis landscapes across enzymatic evolution and building family-specific models capable of accurately predicting catalytic constants, opening new avenues for enzyme engineering and functional prediction.

Optical scattering methods for the label-free analysis of single biomolecules

Single-molecule techniques to analyze proteins and other biomolecules involving labels and tethers have allowed for new understanding of the underlying biophysics; however, the impact of perturbation from the labels and tethers has recently been shown to be significant in several cases. New approaches are emerging to measure single proteins through light scattering without the need for labels and ideally without tethers. Here, the approaches of interference scattering, plasmonic scattering, microcavity sensing, nanoaperture optical tweezing, and variants are described and compared. The application of these approaches to sizing, oligomerization, interactions, conformational dynamics, diffusion, and vibrational mode analysis is described. With early commercial successes, these approaches are poised to have an impact in the field of single-molecule biophysics.

Enzyme activation by urea reveals the interplay between conformational dynamics and substrate binding: a single-molecule FRET study

Proteins often harness extensive motions of domains and subunits to promote their function. Deciphering how these movements impact activity is key for understanding life's molecular machinery. The enzyme adenylate kinase is an intriguing example for this relationship; it ensures efficient catalysis by large-scale domain motions that lead to the enclosure of the bound substrates ATP and AMP. At high concentrations, AMP also operates as an allosteric inhibitor of the protein. Surprisingly, the enzyme is activated by urea, a compound commonly acting as a denaturant. Combining single-molecule FRET spectroscopy and enzymatic activity studies, we find that urea interferes with two key mechanisms that contribute to enzyme efficacy. First, urea promotes the open conformation of the enzyme, aiding the proper positioning of the substrates. Second, urea decreases AMP affinity, paradoxically facilitating a more efficient progression towards the catalytically active complex. These results signify the important interplay between conformational dynamics and chemical steps, including binding, in the activity of enzymes. State-of-the-art tools, such as single-molecule fluorescence spectroscopy, offer new insights into how enzymes balance different conformations to regulate activity.

Magnesium induced structural reorganization in the active site of adenylate kinase

Phosphoryl transfer is a fundamental reaction in cellular signaling and metabolism that requires Mg2+ as an essential cofactor. While the primary function of Mg2+ is electrostatic activation of substrates, such as ATP, the full spectrum of catalytic mechanisms exerted by Mg2+ is not known. In this study, we integrate structural biology methods, molecular dynamic (MD) simulations, phylogeny, and enzymology assays to provide molecular insights into Mg2+-dependent structural reorganization in the active site of the metabolic enzyme adenylate kinase. Our results demonstrate that Mg2+ induces a conformational rearrangement of the substrates (ATP and ADP), resulting in a 30° adjustment of the angle essential for reversible phosphoryl transfer, thereby optimizing it for catalysis. MD simulations revealed transitions between conformational substates that link the fluctuation of the angle to large-scale enzyme dynamics. The findings contribute detailed insight into Mg2+ activation of enzymes and may be relevant for reversible and irreversible phosphoryl transfer reactions.

NMR and Single-Molecule FRET Insights into Fast Protein Motions and Their Relation to Function

Proteins often undergo large-scale conformational transitions, in which secondary and tertiary structure elements (loops, helices, and domains) change their structures or their positions with respect to each other. Simple considerations suggest that such dynamics should be relatively fast, but the functional cycles of many proteins are often relatively slow. Sophisticated experimental methods are starting to tackle this dichotomy and shed light on the contribution of large-scale conformational dynamics to protein function. In this review, we focus on the contribution of single-molecule Förster resonance energy transfer and nuclear magnetic resonance (NMR) spectroscopies to the study of conformational dynamics. We briefly describe the state of the art in each of these techniques and then point out their similarities and differences, as well as the relative strengths and weaknesses of each. Several case studies, in which the connection between fast conformational dynamics and slower function has been demonstrated, are then introduced and discussed. These examples include both enzymes and large protein machines, some of which have been studied by both NMR and fluorescence spectroscopies.

CDK2 and CDK4: Cell Cycle Functions Evolve Distinct, Catalysis-Competent Conformations, Offering Drug Targets

Cyclin-dependent kinases (CDKs), particularly CDK4 and CDK2, are crucial for cell cycle progression from the Gap 1 (G1) to the Synthesis (S) phase by phosphorylating targets such as the Retinoblastoma Protein (Rb). CDK4, paired with cyclin-D, operates in the long G1 phase, while CDK2 with cyclin-E, manages the brief G1-to-S transition, enabling DNA replication. Aberrant CDK signaling leads to uncontrolled cell proliferation, which is a hallmark of cancer. Exactly how they accomplish their catalytic phosphorylation actions with distinct efficiencies poses the fundamental, albeit overlooked question. Here we combined available experimental data and modeling of the active complexes to establish their conformational functional landscapes to explain how the two cyclin/CDK complexes differentially populate their catalytically competent states for cell cycle progression. Our premise is that CDK catalytic efficiencies could be more important for cell cycle progression than the cyclin-CDK biochemical binding specificity and that efficiency is likely the prime determinant of cell cycle progression. We observe that CDK4 is more dynamic than CDK2 in the ATP binding site, the regulatory spine, and the interaction with its cyclin partner. The N-terminus of cyclin-D acts as an allosteric regulator of the activation loop and the ATP-binding site in CDK4. Integrated with a suite of experimental data, we suggest that the CDK4 complex is less capable of remaining in the active catalytically competent conformation, and may have a lower catalytic efficiency than CDK2, befitting their cell cycle time scales, and point to critical residues and motifs that drive their differences. Our mechanistic landscape may apply broadly to kinases, and we propose two drug design strategies: (i) allosteric Inhibition by conformational stabilization for targeting allosteric CDK4 regulation by cyclin-D, and (ii) dynamic entropy-optimized targeting which leverages the dynamic, entropic aspects of CDK4 to optimize drug binding efficacy.

Synthesis, kinetic studies, and QSAR of dinucleoside polyphosphate derivatives as human AK1 inhibitors

Adenylate kinase (AK) plays a crucial role in the metabolic monitoring of cellular adenine nucleotide homeostasis by catalyzing the reversible transfer of a phosphate group between ATP and AMP, yielding two ADP molecules. By regulating the nucleotide levels and energy metabolism, the enzyme is considered a disease modifier and potential therapeutic target for various human diseases, including malignancies and inflammatory and neurodegenerative disorders. However, lacking approved drugs targeting AK hinders broad studies on this enzyme's pathological importance and therapeutic potential. In this work, we determined the effect of a series of dinucleoside polyphosphate derivatives, commercially available (11 compounds) and newly synthesized (8 compounds), on the catalytic activity of human adenylate kinase isoenzyme 1 (hAK1). The tested compounds belonged to the following groups: (1) diadenosine polyphosphates with different phosphate chain lengths, (2) base-modified derivatives, and (3) phosphate-modified derivatives. We found that all the investigated compounds inhibited the catalytic activity of hAK1, yet with different efficiencies. Three dinucleoside polyphosphates showed IC50 values below 1 µM, and the most significant inhibitory effect was observed for P1-(5'-adenosyl) P5-(5'-adenosyl) pentaphosphate (Ap5A). To understand the observed differences in the inhibition efficiency of the tested dinucleoside polyphosphates, the molecular docking of these compounds to hAK1 was performed. Finally, we conducted a quantitative structure-activity relationship (QSAR) analysis to establish a computational prediction model for hAK1 modulators. Two PLS-regression-based models were built using kinetic data obtained from the AK1 activity analysis performed in both directions of the enzymatic reaction. Model 1 (AMP and ATP synthesis) had a good prediction power (R2 = 0.931, Q2 = 0.854, and MAE = 0.286), while Model 2 (ADP synthesis) exhibited a moderate quality (R2 = 0.913, Q2 = 0.848, and MAE = 0.370). These studies can help better understand the interactions between dinucleoside polyphosphates and adenylate kinase to attain more effective and selective inhibitors in the future.

Subdomain dynamics enable chemical chain reactions in non-ribosomal peptide synthetases

Many peptide-derived natural products are produced by non-ribosomal peptide synthetases (NRPSs) in an assembly-line fashion. Each amino acid is coupled to a designated peptidyl carrier protein (PCP) through two distinct reactions catalysed sequentially by the single active site of the adenylation domain (A-domain). Accumulating evidence suggests that large-amplitude structural changes occur in different NRPS states; yet how these molecular machines orchestrate such biochemical sequences has remained elusive. Here, using single-molecule Förster resonance energy transfer, we show that the A-domain of gramicidin S synthetase I adopts structurally extended and functionally obligatory conformations for alternating between adenylation and thioester-formation structures during enzymatic cycles. Complementary biochemical, computational and small-angle X-ray scattering studies reveal interconversion among these three conformations as intrinsic and hierarchical where intra-A-domain organizations propagate to remodel inter-A-PCP didomain configurations during catalysis. The tight kinetic coupling between structural transitions and enzymatic transformations is quantified, and how the gramicidin S synthetase I A-domain utilizes its inherent conformational dynamics to drive directional biosynthesis with a flexibly linked PCP domain is revealed.

Trajectory Statistical Learning of the Potential Mean of Force and Diffusion Coefficient from Molecular Dynamics Simulations

Central to studying the conformational changes of a complex protein is understanding the dynamics and energetics involved. Phenomenologically, structural dynamics can be formulated using an overdamped Langevin model along an observable, e.g., the distance between two residues in the protein. The Langevin model is specified by the deterministic force (the potential of mean force, PMF) and stochastic force (characterized by the diffusion coefficient, D). It is therefore of great interest to be able to extract both PMF and D from an observable time series but under the same computational framework. Here, we approach this challenge in molecular dynamics (MD) simulations by treating it as a missing-data Bayesian estimation problem. An important distinction in our methodology is that the entire MD trajectory, as opposed to the individual data elements, is used as the statistical variable in Bayesian imputation. This idea is implemented through an eigen-decomposition procedure for a time-symmetrized Fokker-Planck equation, followed by maximizing the likelihood for parameter estimation. The mathematical expressions for the functional derivatives used in learning PMF and D also provide new physical insights for the manner by which the information on both the deterministic and stochastic forces is encoded in the dynamics data. An all-atom MD simulation of a nontrivial biomolecule case is used to illustrate the application of this approach. We show that, interestingly, the results of trajectory statistical learning can motivate new order parameters for an improved description of the kinetic bottlenecks in conformational changes. Complementing purely data-driven or black-box methods, this work underscores the advantages of physics-based machine learning in gaining chemical insights from quantitative parameter estimation.

Elucidating Dynamics of Adenylate Kinase from Enzyme Opening to Ligand Release

This study explores ligand-driven conformational changes in adenylate kinase (AK), which is known for its open-to-close conformational transitions upon ligand binding and release. By utilizing string free energy simulations, we determine the free energy profiles for both enzyme opening and ligand release and compare them with profiles from the apoenzyme. Results reveal a three-step ligand release process, which initiates with the opening of the adenosine triphosphate-binding subdomain (ATP lid), followed by ligand release and concomitant opening of the adenosine monophosphate-binding subdomain (AMP lid). The ligands then transition to nonspecific positions before complete dissociation. In these processes, the first step is energetically driven by ATP lid opening, whereas the second step is driven by ATP release. In contrast, the AMP lid opening and its ligand release make minor contributions to the total free energy for enzyme opening. Regarding the ligand binding mechanism, our results suggest that AMP lid closure occurs via an induced-fit mechanism triggered by AMP binding, whereas ATP lid closure follows conformational selection. This difference in the closure mechanisms provides an explanation with implications for the debate on ligand-driven conformational changes of AK. Additionally, we determine an X-ray structure of an AK variant that exhibits significant rearrangements in the stacking of catalytic arginines, explaining its reduced catalytic activity. In the context of apoenzyme opening, the sequence of events is different. Here, the AMP lid opens first while the ATP lid remains closed, and the free energy associated with ATP lid opening varies with orientation, aligning with the reported AK opening and closing rate heterogeneity. Finally, this study, in conjunction with our previous research, provides a comprehensive view of the intricate interplay between various structural elements, ligands, and catalytic residues that collectively contribute to the robust catalytic power of the enzyme.

Ratcheting synthesis

Synthetic chemistry has traditionally relied on reactions between reactants of high chemical potential and transformations that proceed energetically downhill to either a global or local minimum (thermodynamic or kinetic control). Catalysts can be used to manipulate kinetic control, lowering activation energies to influence reaction outcomes. However, such chemistry is still constrained by the shape of one-dimensional reaction coordinates. Coupling synthesis to an orthogonal energy input can allow ratcheting of chemical reaction outcomes, reminiscent of the ways that molecular machines ratchet random thermal motion to bias conformational dynamics. This fundamentally distinct approach to synthesis allows multi-dimensional potential energy surfaces to be navigated, enabling reaction outcomes that cannot be achieved under conventional kinetic or thermodynamic control. In this Review, we discuss how ratcheted synthesis is ubiquitous throughout biology and consider how chemists might harness ratchet mechanisms to accelerate catalysis, drive chemical reactions uphill and programme complex reaction sequences.

Substrate Positioning Dynamics Involves a Non-Electrostatic Component to Mediate Catalysis

Substrate positioning dynamics (SPD) orients the substrate in the active site, thereby influencing catalytic efficiency. However, it remains unknown whether SPD effects originate primarily from electrostatic perturbation inside the enzyme or can independently mediate catalysis with a significant non-electrostatic component. In this work, we investigated how the non-electrostatic component of SPD affects transition state (TS) stabilization. Using high-throughput enzyme modeling, we selected Kemp eliminase variants with similar electrostatics inside the enzyme but significantly different SPD. The kinetic parameters of these mutants were experimentally characterized. We observed a valley-shaped, two-segment linear correlation between the TS stabilization free energy (converted from kinetic parameters) and substrate positioning index (a metric to quantify SPD). The energy varies by approximately 2 kcal/mol. Favorable SPD was observed for the distal mutant R154W, increasing the proportion of reactive conformations and leading to the lowest activation free energy. These results indicate the substantial contribution of the non-electrostatic component of SPD to enzyme catalytic efficiency.

The case for an oxidopyrylium intermediate in the mechanism of quercetin dioxygenases

The quercetin dioxygenases (QDOs) are unusual metalloenzymes in that they display ring-opening dioxygenase activity with several different first-row transition metal ions which do not undergo redox changes during turnover. The QDOs are also unique in that the substrate binds as an η1-flavonolate rather than the η2 -bidentate mode seen in all reported model complexes. The flavonol substrates were early examples of excited state intramolecular proton transfer (ESIPT) phenomena, in which photoexcitation causes an H-atom exchange between the adjacent hydroxyl and ketone, generating an oxidopyrylium emissive state. These oxidopyryliums undergo ring-opening dioxygenations analogous to the enzymatic reactions. Our hypothesis is that lability of the divalent metal ion may allow access to a reactive oxidopyrylium intermediate via coordination switching from the oxy to ketone position, which allows reaction with O2. In this report, we use a straight-forward methylation strategy to generate a panel of flavonol and thioflavonol derivatives modeling several η1- and η2-coordination modes. Methylation of 3-hydroxythioflavone generates an air stable η1 hydroxopyrylium salt, which undergoes rapid ring-opening dioxygenation by deprotonation or photoexcitation. By comparison, the η1-methoxyflavonol does not react with O2 under any condition. We find that any of the studied flavonol derivatives, η1 or η2, which demonstrates ESIPT-like oxidopyrylium emissions undergo QDO-like ring-opening reactions with dioxygen. The implications of these results concerning the mechanism of QDOs and related dioxygenases is discussed.

Transition Time Determination of Single-Molecule FRET Trajectories via Wasserstein Distance Analysis in Steady-State Variations in smFRET (WAVE)

Many biological molecules respond to external stimuli that can cause their conformational states to shift from one steady state to another. Single-molecule FRET (Fluorescence Resonance Energy Transfer) is of particular interest to not only define the steady-state conformational ensemble usually averaged out in the ensemble of molecules but also characterize the dynamics of biomolecules. To study steady-state transitions, i.e., non-equilibrium transitions, a data analysis methodology is necessary to analyze single-molecule FRET photon trajectories, which contain mixtures of contributions from two steady-state statuses and include non-equilibrium transitions. In this study, we introduce a novel methodology called WAVE (Wasserstein distance Analysis in steady-state Variations in smFRET) to detect and locate non-equilibrium transition positions in FRET trajectories. Our method first utilizes a combined STaSI-HMM (Stepwise Transitions with State Inference Hidden Markov Model) algorithm to convert the original FRET trajectories into discretized trajectories. We then apply Maximum Wasserstein Distance analysis to differentiate the FRET state compositions of the fitting trajectories before and after the non-equilibrium transition. Forward and backward algorithms, based on the Minimum Description Length (MDL) principle, are used to find the refined positions of the non-equilibrium transitions. This methodology allows us to observe changes in experimental conditions in chromophore-tagged biomolecules or vice versa.

Insights into Enzymatic Catalysis from Binding and Hydrolysis of Diadenosine Tetraphosphate by E. coli Adenylate Kinase

Adenylate kinases play a crucial role in cellular energy homeostasis through the interconversion of ATP, AMP, and ADP in all living organisms. Here, we explore how adenylate kinase (AdK) from Escherichia coli interacts with diadenosine tetraphosphate (AP4A), a putative alarmone associated with transcriptional regulation, stress, and DNA damage response. From a combination of EPR and NMR spectroscopy together with X-ray crystallography, we found that AdK interacts with AP4A with two distinct modes that occur on disparate time scales. First, AdK dynamically interconverts between open and closed states with equal weights in the presence of AP4A. On a much slower time scale, AdK hydrolyses AP4A, and we suggest that the dynamically accessed substrate-bound open AdK conformation enables this hydrolytic activity. The partitioning of the enzyme into open and closed states is discussed in relation to a recently proposed linkage between active site dynamics and collective conformational dynamics.

Perspective: How Fast Dynamics Affect Slow Function in Protein Machines

Internal motions in proteins take place on a broad range of time- and space-scales. The potential roles of these dynamics in the biochemical functions of proteins have intrigued biophysicists for many years, and multiple mechanisms to couple motions to function have been proposed. Some of these mechanisms have relied on equilibrium concepts. For example, the modulation of dynamics was proposed to change the entropy of a protein, hence affecting processes such as binding. This so-called dynamic allostery scenario has been demonstrated in several recent experiments. Perhaps even more intriguing may be models that involve out-of-equilibrium operation, which by necessity require the input of energy. We discuss several recent experimental studies that expose such potential mechanisms for coupling dynamics and function. In Brownian ratchets, for example, directional motion is promoted by switching a protein between two free energy surfaces. An additional example involves the effect of microsecond domain-closure dynamics of an enzyme on its much slower chemical cycle. These observations lead us to propose a novel two-time-scale paradigm for the activity of protein machines: fast equilibrium fluctuations take place on the microsecond-millisecond time scale, while on a slower time scale, free energy is invested in order to push the system out of equilibrium and drive functional transitions. Motions on the two time scales affect each other and are essential for the overall function of these machines.

Allosteric communication between ligand binding domains modulates substrate inhibition in adenylate kinase

Enzymes play a vital role in life processes; they control chemical reactions and allow functional cycles to be synchronized. Many enzymes harness large-scale motions of their domains to achieve tremendous catalytic prowess and high selectivity for specific substrates. One outstanding example is provided by the three-domain enzyme adenylate kinase (AK), which catalyzes phosphotransfer between ATP to AMP. Here we study the phenomenon of substrate inhibition by AMP and its correlation with domain motions. Using single-molecule FRET spectroscopy, we show that AMP does not block access to the ATP binding site, neither by competitive binding to the ATP cognate site nor by directly closing the LID domain. Instead, inhibitory concentrations of AMP lead to a faster and more cooperative domain closure by ATP, leading in turn to an increased population of the closed state. The effect of AMP binding can be modulated through mutations throughout the structure of the enzyme, as shown by the screening of an extensive AK mutant library. The mutation of multiple conserved residues reduces substrate inhibition, suggesting that substrate inhibition is an evolutionary well conserved feature in AK. Combining these insights, we developed a model that explains the complex activity of AK, particularly substrate inhibition, based on the experimentally observed opening and closing rates. Notably, the model indicates that the catalytic power is affected by the microsecond balance between the open and closed states of the enzyme. Our findings highlight the crucial role of protein motions in enzymatic activity.

Mutation of a distal gating residue modulates NADH binding in NADH:Quinone oxidoreductase from Pseudomonas aeruginosa PAO1

Enzymes require flexible regions to adopt multiple conformations during catalysis. The mobile regions of enzymes include gates that modulate the passage of molecules in and out of the enzyme's active site. The enzyme PA1024 from Pseudomonas aeruginosa PA01 is a recently discovered flavin-dependent NADH:quinone oxidoreductase (NQO, EC 1.6.5.9). Q80 in loop 3 (residues 75-86) of NQO is ∼15 Å away from the flavin and creates a gate that seals the active site through a hydrogen bond with Y261 upon NADH binding. In this study, we mutated Q80 to glycine, leucine, or glutamate to investigate the mechanistic significance of distal residue Q80 in NADH binding in the active site of NQO. The UV-visible absorption spectrum reveals that the mutation of Q80 minimally affects the protein microenvironment surrounding the flavin. The anaerobic reductive half-reaction of the NQO-mutants yields a ≥25-fold increase in the Kd value for NADH compared to the WT enzyme. However, we determined that the kred value was similar in the Q80G, Q80L, and wildtype enzymes and only ∼25% smaller in the Q80E enzyme. Steady-state kinetics with NQO-mutants and NQO-WT at varying concentrations of NADH and 1,4-benzoquinone establish a ≤5-fold decrease in the kcat/KNADH value. Moreover, there is no significant difference in the kcat/KBQ (∼1 × 106 M-1s-1) and kcat (∼24 s-1) values in NQO-mutants and NQO-WT. These results are consistent with the distal residue Q80 being mechanistically essential for NADH binding to NQO with minimal effect on the quinone binding to the enzyme and hydride transfer from NADH to flavin.

Mechanistic Basis for a Connection between the Catalytic Step and Slow Opening Dynamics of Adenylate Kinase

Escherichia coli adenylate kinase (AdK) is a small, monomeric enzyme that synchronizes the catalytic step with the enzyme's conformational dynamics to optimize a phosphoryl transfer reaction and the subsequent release of the product. Guided by experimental measurements of low catalytic activity in seven single-point mutation AdK variants (K13Q, R36A, R88A, R123A, R156K, R167A, and D158A), we utilized classical mechanical simulations to probe mutant dynamics linked to product release, and quantum mechanical and molecular mechanical calculations to compute a free energy barrier for the catalytic event. The goal was to establish a mechanistic connection between the two activities. Our calculations of the free energy barriers in AdK variants were in line with those from experiments, and conformational dynamics consistently demonstrated an enhanced tendency toward enzyme opening. This indicates that the catalytic residues in the wild-type AdK serve a dual role in this enzyme's function─one to lower the energy barrier for the phosphoryl transfer reaction and another to delay enzyme opening, maintaining it in a catalytically active, closed conformation for long enough to enable the subsequent chemical step. Our study also discovers that while each catalytic residue individually contributes to facilitating the catalysis, R36, R123, R156, R167, and D158 are organized in a tightly coordinated interaction network and collectively modulate AdK's conformational transitions. Unlike the existing notion of product release being rate-limiting, our results suggest a mechanistic interconnection between the chemical step and the enzyme's conformational dynamics acting as the bottleneck of the catalytic process. Our results also suggest that the enzyme's active site has evolved to optimize the chemical reaction step while slowing down the overall opening dynamics of the enzyme.

Protein dynamics: The future is bright and complicated!

Biological life depends on motion, and this manifests itself in proteins that display motion over a formidable range of time scales spanning from femtoseconds vibrations of atoms at enzymatic transition states, all the way to slow domain motions occurring on micro to milliseconds. An outstanding challenge in contemporary biophysics and structural biology is a quantitative understanding of the linkages among protein structure, dynamics, and function. These linkages are becoming increasingly explorable due to conceptual and methodological advances. In this Perspective article, we will point toward future directions of the field of protein dynamics with an emphasis on enzymes. Research questions in the field are becoming increasingly complex such as the mechanistic understanding of high-order interaction networks in allosteric signal propagation through a protein matrix, or the connection between local and collective motions. In analogy to the solution to the "protein folding problem," we argue that the way forward to understanding these and other important questions lies in the successful integration of experiment and computation, while utilizing the present rapid expansion of sequence and structure space. Looking forward, the future is bright, and we are in a period where we are on the doorstep to, at least in part, comprehend the importance of dynamics for biological function.

Role of Repeated Conformational Transitions in Substrate Binding of Adenylate Kinase

The catalytic cycle of the enzyme adenylate kinase involves large conformational motions between open and closed states. A previous single-molecule experiment showed that substrate binding tends to accelerate both the opening and the closing rates and that a single turnover event often involves multiple rounds of conformational switching. In this work, we showed that the repeated conformational transitions of adenylate kinase are essential for the relaxation of incorrectly bound substrates into the catalytically competent conformation by combining all-atom and coarse-grained molecular simulations. In addition, free energy calculations based on all-atom and coarse-grained models demonstrated that the enzyme with incorrectly bound substrates has much a lower free energy barrier for domain opening compared to that with the correct substrate conformation, which may explain the the acceleration of the domain opening rate by substrate binding. The results of this work provide mechanistic understanding to previous experimental observations and shed light onto the interplay between conformational dynamics and enzyme catalysis.

Frustration and the Kinetic Repartitioning Mechanism of Substrate Inhibition in Enzyme Catalysis

Substrate inhibition, whereby enzymatic activity decreases with excess substrate after reaching a maximum turnover rate, is among the most elusive phenomena in enzymatic catalysis. Here, based on a dynamic energy landscape model, we investigate the underlying mechanism by performing molecular simulations and frustration analysis for a model enzyme adenylate kinase (AdK), which catalyzes the phosphoryl transfer reaction ATP + AMP ⇋ ADP + ADP. Intriguingly, these reveal a kinetic repartitioning mechanism of substrate inhibition, whereby excess substrate AMP suppresses the population of an energetically frustrated, but kinetically activated, catalytic pathway going through a substrate (ATP)-product (ADP) cobound complex with steric incompatibility. Such a frustrated pathway plays a crucial role in facilitating the bottleneck product ADP release, and its suppression by excess substrate AMP leads to a slow down of product release and overall turnover. The simulation results directly demonstrate that substrate inhibition arises from the rate-limiting product-release step, instead of the steps for populating the catalytically competent complex as often suggested in previous works. Furthermore, there is a tight interplay between the enzyme conformational equilibrium and the extent of substrate inhibition. Mutations biasing to more closed conformations tend to enhance substrate inhibition. We also characterized the key features of single-molecule enzyme kinetics with substrate inhibition effect. We propose that the above molecular mechanism of substrate inhibition may be relevant to other multisubstrate enzymes in which product release is the bottleneck step.

Machine learning/molecular dynamic protein structure prediction approach to investigate the protein conformational ensemble

Proteins exist in several different conformations. These structural changes are often associated with fluctuations at the residue level. Recent findings show that co-evolutionary analysis coupled with machine-learning techniques improves the precision by providing quantitative distance predictions between pairs of residues. The predicted statistical distance distribution from Multi Sequence Analysis reveals the presence of different local maxima suggesting the flexibility of key residue pairs. Here we investigate the ability of the residue-residue distance prediction to provide insights into the protein conformational ensemble. We combine deep learning approaches with mechanistic modeling to a set of proteins that experimentally showed conformational changes. The predicted protein models were filtered based on energy scores, RMSD clustering, and the centroids selected as the lowest energy structure per cluster. These models were compared to the experimental-Molecular Dynamics (MD) relaxed structure by analyzing the backbone residue torsional distribution and the sidechain orientations. Our pipeline allows to retrieve the experimental structural dynamics experimentally represented by different X-ray conformations for the same sequence as well the conformational space observed with the MD simulations. We show the potential correlation between the experimental structure dynamics and the predicted model ensemble demonstrating the susceptibility of the current state-of-the-art methods in protein folding and dynamics prediction and pointing out the areas of improvement.

Elucidating the mechanisms underlying protein conformational switching using NMR spectroscopy

How proteins switch between various ligand-free and ligand-bound structures has been a key biophysical question ever since the postulation of the Monod-Wyman-Changeux and Koshland-Nemethy-Filmer models over six decades ago. The ability of NMR spectroscopy to provide structural and kinetic information on biomolecular conformational exchange places it in a unique position as an analytical tool to interrogate the mechanisms of biological processes such as protein folding and biomolecular complex formation. In addition, recent methodological developments in the areas of saturation transfer and relaxation dispersion have expanded the scope of NMR for probing the mechanics of transitions in systems where one or more states constituting the exchange process are sparsely populated and 'invisible' in NMR spectra. In this review, we highlight some of the strategies available from NMR spectroscopy for examining the nature of multi-site conformational exchange, using five case studies that have employed NMR, either in isolation, or in conjunction with other biophysical tools.

AK2 is an AMP-sensing negative regulator of BRAF in tumorigenesis

The RAS-BRAF signaling is a major pathway of cell proliferation and their mutations are frequently found in human cancers. Adenylate kinase 2 (AK2), which modulates balance of adenine nucleotide pool, has been implicated in cell death and cell proliferation independently of its enzyme activity. Recently, the role of AK2 in tumorigenesis was in part elucidated in some cancer types including lung adenocarcinoma and breast cancer, but the underlying mechanism is not clear. Here, we show that AK2 is a BRAF-suppressor. In in vitro assays and cell model, AK2 interacted with BRAF and inhibited BRAF activity and downstream ERK phosphorylation. Energy-deprived conditions in cell model and the addition of AMP to cell lysates strengthened the AK2-BRAF interaction, suggesting that AK2 is involved in the regulation of BRAF activity in response to cell metabolic state. AMP facilitated the AK2-BRAF complex formation through binding to AK2. In a panel of HCC cell lines, AK2 expression was inversely correlated with ERK/MAPK activation, and AK2-knockdown or -knockout increased BRAF activity and promoted cell proliferation. Tumors from HCC patients showed low-AK2 protein expression and increased ERK activation compared to non-tumor tissues and the downregulation of AK2 was also verified by two microarray datasets (TCGA-LIHC and GSE14520). Moreover, AK2/BRAF interaction was abrogated by RAS activation in in vitro assay and cell model and in a mouse model of HRAS^G12V-driven HCC, and AK2 ablation promoted tumor growth and BRAF activity. AK2 also bound to BRAF inhibitor-insensitive BRAF mutants and attenuated their activities. These findings indicate that AK2 monitoring cellular AMP levels is indeed a negative regulator of BRAF, linking the metabolic status to tumor growth.

Structure-mechanics statistical learning uncovers mechanical relay in proteins

A protein's adaptive response to its substrates is one of the key questions driving molecular physics and physical chemistry. This work employs the recently developed structure-mechanics statistical learning method to establish a mechanical perspective. Specifically, by mapping all-atom molecular dynamics simulations onto the spring parameters of a backbone-side-chain elastic network model, the chemical moiety specific force constants (or mechanical rigidity) are used to assemble the rigidity graph, which is the matrix of inter-residue coupling strength. Using the S1A protease and the PDZ3 signaling domain as examples, chains of spatially contiguous residues are found to exhibit prominent changes in their mechanical rigidity upon substrate binding or dissociation. Such a mechanical-relay picture thus provides a mechanistic underpinning for conformational changes, long-range communication, and inter-domain allostery in both proteins, where the responsive mechanical hotspots are mostly residues having important biological functions or significant mutation sensitivity.

Protein residues exhibit specific routes of mechanical relay as the adaptive responses to substrate binding or dissociation. On such physically contiguous connections, residues experience prominent changes in their coupling strengths.

Structure determination of high-energy states in a dynamic protein ensemble

Macromolecular function frequently requires that proteins change conformation into high-energy states1-4. However, methods for solving the structures of these functionally essential, lowly populated states are lacking. Here we develop a method for high-resolution structure determination of minorly populated states by coupling NMR spectroscopy-derived pseudocontact shifts5 (PCSs) with Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion6 (PCS-CPMG). Our approach additionally defines the corresponding kinetics and thermodynamics of high-energy excursions, thereby characterizing the entire free-energy landscape. Using a large set of simulated data for adenylate kinase (Adk), calmodulin and Src kinase, we find that high-energy PCSs accurately determine high-energy structures (with a root mean squared deviation of less than 3.5 angström). Applying our methodology to Adk during catalysis, we find that the high-energy excursion involves surprisingly small openings of the AMP and ATP lids. This previously unresolved high-energy structure solves a longstanding controversy about conformational interconversions that are rate-limiting for catalysis. Primed for either substrate binding or product release, the high-energy structure of Adk suggests a two-step mechanism combining conformational selection to this state, followed by an induced-fit step into a fully closed state for catalysis of the phosphoryl-transfer reaction. Unlike other methods for resolving high-energy states, such as cryo-electron microscopy and X-ray crystallography, our solution PCS-CPMG approach excels in cases involving domain rearrangements of smaller systems (less than 60 kDa) and populations as low as 0.5%, and enables the simultaneous determination of protein structure, kinetics and thermodynamics while proteins perform their function.

Theory and Analysis of Single-Molecule FRET Experiments

Inter-dye distances and conformational dynamics can be studied using single-molecule FRET measurements. We consider two approaches to analyze sequences of photons with recorded photon colors and arrival times. The first approach is based on FRET efficiency histograms obtained from binned photon sequences. The experimental histograms are compared with the theoretical histograms obtained using the joint distribution of acceptor and donor photons or the Gaussian approximation. In the second approach, a photon sequence is analyzed without binning. The parameters of a model describing conformational dynamics are found by maximizing the appropriate likelihood function. The first approach is simpler, while the second one is more accurate, especially when the population of species is small and transition rates are fast. The likelihood-based analysis as well as the recoloring method has the advantage that diffusion of molecules through the laser focus can be rigorously handled.

Analysis of changes of cavity volumes in predefined directions of protein motions and cavity flexibility

Dynamics of protein cavities associated with protein fluctuations and conformational plasticity is essential for their biological function. NMR ensembles, molecular dynamics (MD) simulations, and normal mode analysis (NMA) provide appropriate frameworks to explore functionally relevant protein dynamics and cavity changes relationships. Within this context, we have recently developed analysis of null areas (ANA), an efficient method to calculate cavity volumes. ANA is based on a combination of algorithms that guarantees its robustness against numerical differentiations. This is a unique feature with respect to other methods. Herein, we present an updated and improved version that expands it use to quantify changes in cavity features, like volume and flexibility, due to protein structural distortions performed on predefined biologically relevant directions, for example, directions of largest contribution to protein fluctuations (principal component analysis [PCA modes]) obtained by MD simulations or ensembles of NMR structures, collective NMA modes or any other direction of motion associated with specific conformational changes. A web page has been developed where its facilities are explained in detail. First, we show that ANA can be useful to explore gradual changes of cavity volume and flexibility associated with protein ligand binding. Secondly, we perform a comparison study of the extent of variability between protein backbone structural distortions, and changes in cavity volumes and flexibilities evaluated for an ensemble of NMR active and inactive conformers of the epidermal growth factor receptor structures. Finally, we compare changes in size and flexibility between sets of NMR structures for different homologous chains of dynein.

Physics of biomolecular recognition and conformational dynamics

Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.

Tracking the ATP-binding response in adenylate kinase in real time

The biological function of proteins is critically dependent on dynamics inherent to the native structure. Such structural dynamics obey a predefined order and temporal timing to execute the specific reaction. Determination of the cooperativity of key structural rearrangements requires monitoring protein reactions in real time. In this work, we used time-resolved x-ray solution scattering (TR-XSS) to visualize structural changes in the Escherichia coli adenylate kinase (AdK) enzyme upon laser-induced activation of a protected ATP substrate. A 4.3-ms transient intermediate showed partial closing of both the ATP- and AMP-binding domains, which indicates a cooperative closing mechanism. The ATP-binding domain also showed local unfolding and breaking of an Arg¹³¹-Asp¹⁴⁶ salt bridge. Nuclear magnetic resonance spectroscopy data identified similar unfolding in an Arg¹³¹Ala AdK mutant, which refolded in a closed, substrate-binding conformation. The observed structural dynamics agree with a “cracking mechanism” proposed to underlie global structural transformation, such as allostery, in proteins.

Explore Protein Conformational Space With Variational Autoencoder

Molecular dynamics (MD) simulations have been actively used in the study of protein structure and function. However, extensive sampling in the protein conformational space requires large computational resources and takes a prohibitive amount of time. In this study, we demonstrated that variational autoencoders (VAEs), a type of deep learning model, can be employed to explore the conformational space of a protein through MD simulations. VAEs are shown to be superior to autoencoders (AEs) through a benchmark study, with low deviation between the training and decoded conformations. Moreover, we show that the learned latent space in the VAE can be used to generate unsampled protein conformations. Additional simulations starting from these generated conformations accelerated the sampling process and explored hidden spaces in the conformational landscape.

Molecular and Spectroscopic Characterization of Green and Red Cyanine Fluorophores from the Alexa Fluor and AF Series*

The use of fluorescence techniques has an enormous impact on various research fields including imaging, biochemical assays, DNA-sequencing and medical technologies. This has been facilitated by the development of numerous commercial dyes with optimized photophysical and chemical properties. Often, however, information about the chemical structures of dyes and the attached linkers used for bioconjugation remain a well-kept secret. This can lead to problems for research applications where knowledge of the dye structure is necessary to predict or understand (unwanted) dye-target interactions, or to establish structural models of the dye-target complex. Using a combination of optical spectroscopy, mass spectrometry, NMR spectroscopy and molecular dynamics simulations, we here investigate the molecular structures and spectroscopic properties of dyes from the Alexa Fluor (Alexa Fluor 555 and 647) and AF series (AF555, AF647, AFD647). Based on available data and published structures of the AF and Cy dyes, we propose a structure for Alexa Fluor 555 and refine that of AF555. We also resolve conflicting reports on the linker composition of Alexa Fluor 647 maleimide. We also conducted a comprehensive comparison between Alexa Fluor and AF dyes by continuous-wave absorption and emission spectroscopy, quantum yield determination, fluorescence lifetime and anisotropy spectroscopy of free and protein-attached dyes. All these data support the idea that Alexa Fluor and AF dyes have a cyanine core and are a derivative of Cy3 and Cy5. In addition, we compared Alexa Fluor 555 and Alexa Fluor 647 to their structural homologs AF555 and AF(D)647 in single-molecule FRET applications. Both pairs showed excellent performance in solution-based smFRET experiments using alternating laser excitation. Minor differences in apparent dye-protein interactions were investigated by molecular dynamics simulations. Our findings clearly demonstrate that the AF-fluorophores are an attractive alternative to Alexa- and Cy-dyes in smFRET studies or other fluorescence applications.

Impacts of mutations on dynamic allostery of adenylate kinase

Escherichia coli adenylate kinase (AK) is composed of CORE domain and two branch domains: LID and AMP-binding domain (AMPbd). AK exhibits considerable allostery in a reversible phosphoryl transfer reaction, which is largely attributed to the relative motion of LID and AMPbd with respect to CORE. Such an allosteric conformational change is also evident in the absence of ligands. Recent studies showed that the mutations in branch domains can adjust dynamic allostery and alter the substrate affinity and enzyme activity. In this work, we use all-atom molecular dynamics simulation to study the impacts of mutations in branch domains on AK's dynamic allostery by comparing two double mutants, i.e., LID mutant (Val135Gly, Val142Gly) and AMPbd mutant (Ala37Gly, Ala55Gly), with wild-type. Two mutants undergo considerable conformational fluctuation and exhibit deviation from the initially extended apo state to more compact structures. The LID domain in the LID mutant adjusts its relative position and firmly adheres to CORE. More strikingly, AMPbd mutations affect the relative positions of both the AMPbd domain and remote LID domain. Both domains undergo considerable movement, especially the inherent hinge swing motion of the flexible LID domain. In both mutants, the mutations can enhance the inter-domain interaction. The results about the conformation change of AK in both mutants are in line with the experiment of AK's affinity and activity. As revealed by our findings, the flexibility of branch domains and their inherent motions, especially LID domain, is highly relevant to dynamic allostery in the AK system.

Understanding enzyme behavior in a crowded scenario through modulation in activity, conformation and dynamics

Macromolecular crowding, inside the physiological interior, modulates the energy landscape of biological macromolecules in multiple ways. Amongst these, enzymes occupy a special place and hence understanding the function of the same in the crowded interior is of utmost importance. In this study, we have investigated the manner in which the multidomain enzyme, AK3L1 (PDB ID: 1ZD8), an isoform of adenylate kinase, has its features affected in presence of commonly used crowders (PEG 8, Dextran 40, Dextran 70, and Ficoll 70). Michaelis Menten plots reveal that the crowders in general enhance the activity of the enzyme, with the K_m and V_max values showing significant variations. Ficoll 70, induced the maximum activity for AK3L1 at 100 g/L, beyond which the activity reduced. Ensemble FRET studies were performed to provide insights into the relative domain (LID and CORE) displacements in presence of the crowders. Solvation studies reveal that the protein matrix surrounding the probe CPM (7-diethylamino-3-(4-maleimido-phenyl)-4-methylcoumarin) gets restricted in presence of the crowders, with Ficoll 70 providing the maximum rigidity, the same being linked to the decrease in the activity of the enzyme. Through our multipronged approach, we have observed a distinct correlation between domain displacement, enzyme activity and associated dynamics. Thus, keeping in mind the complex nature of enzyme activity and the surrounding bath of dense soup that the biological entity remains immersed in, indeed more such approaches need to be undertaken to have a better grasp of the "enzymes in the crowd".

Dynamic Connection between Enzymatic Catalysis and Collective Protein Motions

Enzymes employ a wide range of protein motions to achieve efficient catalysis of chemical reactions. While the role of collective protein motions in substrate binding, product release, and regulation of enzymatic activity is generally understood, their roles in catalytic steps per se remain uncertain. Here, molecular dynamics simulations, enzyme kinetics, X-ray crystallography, and nuclear magnetic resonance spectroscopy are combined to elucidate the catalytic mechanism of adenylate kinase and to delineate the roles of catalytic residues in catalysis and the conformational change in the enzyme. This study reveals that the motions in the active site, which occur on a time scale of picoseconds to nanoseconds, link the catalytic reaction to the slow conformational dynamics of the enzyme by modulating the free energy landscapes of subdomain motions. In particular, substantial conformational rearrangement occurs in the active site following the catalytic reaction. This rearrangement not only affects the reaction barrier but also promotes a more open conformation of the enzyme after the reaction, which then results in an accelerated opening of the enzyme compared to that of the reactant state. The results illustrate a linkage between enzymatic catalysis and collective protein motions, whereby the disparate time scales between the two processes are bridged by a cascade of intermediate-scale motion of catalytic residues modulating the free energy landscapes of the catalytic and conformational change processes.

ABEL-FRET: tether-free single-molecule FRET with hydrodynamic profiling

Single-molecule Förster resonance energy transfer (smFRET) has become a versatile and widespread method to probe nanoscale conformation and dynamics. However, current experimental modalities often resort to molecule immobilization for long observation times and do not always approach the resolution limit of FRET-based nanoscale metrology. Here we present ABEL-FRET, an immobilization-free platform for smFRET measurements with ultrahigh resolving power in FRET efficiency. Importantly, single-molecule diffusivity is used to provide additional size and shape information for hydrodynamic profiling of individual molecules, which, together with the concurrently measured intramolecular conformation through FRET, enables a holistic and dynamic view of biomolecules and their complexes.

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

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

Coarse-Grained Modeling of Multiple Pathways in Conformational Transitions of Multi-Domain Proteins

Large-scale conformational transitions in multi-domain proteins are often essential for their functions. To investigate the transitions, it is necessary to explore multiple potential pathways, which involve different intermediate structures. Here, we present a multi-basin (MB) coarse-grained (CG) structure-based Go̅ model for describing transitions in proteins with more than two moving domains. This model is an extension of our dual-basin Go̅ model in which system-dependent parameters are determined systematically using the multistate Bennett acceptance ratio method. In the MB Go̅ model for multi-domain proteins, we assume that intermediate structures may have partial inter-domain native contacts. This approach allows us to search multiple transition pathways that involve distinct intermediate structures using the CG molecular dynamics (MD) simulations. We apply this scheme to an enzyme, adenylate kinase (AdK), which has three major domains and can move along two different pathways. Using the optimized mixing parameters for each pathway, AdK shows frequent transitions between the Open, Closed, and the intermediate basins and samples a wide variety of conformations within each basin. The explored multiple transition pathways could be compared with experimental data and examined in more detail by atomistic MD simulations.

FRET-based dynamic structural biology: Challenges, perspectives and an appeal for open-science practices

Single-molecule FRET (smFRET) has become a mainstream technique for studying biomolecular structural dynamics. The rapid and wide adoption of smFRET experiments by an ever-increasing number of groups has generated significant progress in sample preparation, measurement procedures, data analysis, algorithms and documentation. Several labs that employ smFRET approaches have joined forces to inform the smFRET community about streamlining how to perform experiments and analyze results for obtaining quantitative information on biomolecular structure and dynamics. The recent efforts include blind tests to assess the accuracy and the precision of smFRET experiments among different labs using various procedures. These multi-lab studies have led to the development of smFRET procedures and documentation, which are important when submitting entries into the archiving system for integrative structure models, PDB-Dev. This position paper describes the current 'state of the art' from different perspectives, points to unresolved methodological issues for quantitative structural studies, provides a set of 'soft recommendations' about which an emerging consensus exists, and lists openly available resources for newcomers and seasoned practitioners. To make further progress, we strongly encourage 'open science' practices.

Rational Design of Adenylate Kinase Thermostability through Coevolution and Sequence Divergence Analysis

Protein engineering is actively pursued in industrial and laboratory settings for high thermostability. Among the many protein engineering methods, rational design by bioinformatics provides theoretical guidance without time-consuming experimental screenings. However, most rational design methods either rely on protein tertiary structure information or have limited accuracies. We proposed a primary-sequence-based algorithm for increasing the heat resistance of a protein while maintaining its functions. Using adenylate kinase (ADK) family as a model system, this method identified a series of amino acid sites closely related to thermostability. Single- and double-point mutants constructed based on this method increase the thermal denaturation temperature of the mesophilic Escherichia coli (E. coli) ADK by 5.5 and 8.3 °C, respectively, while preserving most of the catalytic function at ambient temperatures. Additionally, the constructed mutants have improved enzymatic activity at higher temperature.

Crystal structure of adenylate kinase from an extremophilic archaeon Aeropyrum pernix with ATP and AMP

The crystal structure of an adenylate kinase from an extremophilic archaeon Aeropyrum pernix was determined in complex with full ligands, ATP-Mg2+ and AMP, at a resolution of 2.0 Å. The protein forms a trimer as found for other adenylate kinases from archaea. Interestingly, the reacting three atoms, two phosphorus and one oxygen atoms, were located almost in line, supporting the SN2 nucleophilic substitution reaction mechanism. Based on the crystal structure obtained, the reaction coordinate was estimated by the quantum mechanics calculations combined with molecular dynamics. It was found that the reaction undergoes two energy barriers; the steps for breaking the bond between the oxygen and γ-phosphorus atoms of ATP to produce a phosphoryl fragment and creating the bond between the phosphoryl fragment and the oxygen atom of the β-phosphate group of ADP. The reaction coordinate analysis also suggested the role of amino-acid residues for the catalysis of adenylate kinase.

Exploring Large Domain Motions in Proteins Using Atomistic Molecular Dynamics with Enhanced Conformational Sampling

Conformational transitions in multidomain proteins are essential for biological functions. The Apo conformations are typically open and flexible, while the Holo states form more compact conformations stabilized by protein-ligand interactions. Unfortunately, the atomically detailed mechanisms for such open-closed conformational changes are difficult to be accessed experimentally as well as computationally. To simulate the transitions using atomistic molecular dynamics (MD) simulations, efficient conformational sampling algorithms are required. In this work, we propose a new approach based on generalized replica-exchange with solute tempering (gREST) for exploring the open-closed conformational changes in multidomain proteins. Wherein, selected surface charged residues in a target protein are defined as the solute region in gREST simulation and the solute temperatures are different in replicas and exchanged between them to enhance the domain motions. This approach is called gREST selected surface charged residues (gREST_SSCR) and is applied to the Apo and Holo states of ribose binding protein (RBP) in solution. The conformational spaces sampled with gREST_SSCR are much wider than those with the conventional MD, sampling open-closed conformational changes while maintaining RBP domains’ stability. The free-energy landscapes of RBP in the Apo and Holo states are drawn along with twist and hinge angles of the two moving domains. The inter-domain salt-bridges that are not observed in the experimental structures are also important in the intermediate states during the conformational changes.

How fast are the motions of tertiary-structure elements in proteins?

Protein motions occur on multiple time and distance scales. Large-scale motions of protein tertiary-structure elements, i.e., domains, are particularly intriguing as they are essential for the catalytic activity of many enzymes and for the functional cycles of protein machines and motors. Theoretical estimates suggest that domain motions should be very fast, occurring on the nanosecond or microsecond time scales. Indeed, free-energy barriers for domain motions are likely to involve salt bridges, which can break in microseconds. Experimental methods that can directly probe domain motions on fast time scales have appeared only in recent years. This Perspective discusses briefly some of these techniques, including nuclear magnetic resonance and single-molecule fluorescence spectroscopies. We introduce a few recent studies that demonstrate ultrafast domain motions and discuss their potential roles. Particularly surprising is the observation of tertiary-structure element dynamics that are much faster than the functional cycles in some protein machines. These swift motions can be rationalized on a case-by-case basis. For example, fast domain closure in multi-substrate enzymes may be utilized to optimize relative substrate orientation. Whether a large mismatch in time scales of conformational dynamics vs functional cycles is a general design principle in proteins remains to be determined.

Double-Well Ultra-Coarse-Grained Model to Describe Protein Conformational Transitions

The double-well model is usually used to describe the conformational transition between two states of a protein. Since conformational changes usually occur within a relatively large time scale, coarse-grained models are often used to accelerate the dynamic process due to their inexpensive computational cost. In this work, we develop a double-well ultra-coarse-grained (DW-UCG) model to describe the conformational transitions of the adenylate kinase, glutamine-binding protein, and lactoferrin. The coarse-grained simulation results show that the DW-UCG model of adenylate kinase captures the crucial intermediate states in the LID-closing and NMP-closing pathways, reflecting the key secondary structural changes in the conformational transition. A comparison of the different DW-UCG models of adenylate kinase indicates that an appropriate choice of bead resolution could generate the free energy landscape that is comparable to that from the residue-based model. The coarse-grained simulations for the glutamine-binding protein and lactoferrin also demonstrate that the DW-UCG model is valid in reproducing the correct two-state behavior for their functional study, which indicates the potential application of the DW-UCG model in investigating the mechanism of conformational changes of large proteins.

Molecular dynamics simulations of two GH74 endo-processive xyloglucanases and the mutated variants to understand better the mechanism of the enzyme action

BACKGROUND

GH74 xyloglucanases are composed of two separate domains connected by two unstructured peptides. Previously, a hypothesis was made that the movement of domains may affect the enzyme mechanism of catalysis.

METHODS

The molecular dynamics (MD) simulations of endo-processive xyloglucanases from Paenibacillus odorifer (PoGH74_cat) and Myceliophthora thermophila (MtXeg74A) were carried out.

RESULTS

MD simulations for both enzymes in complex with XXLG and XGXXLG oligosaccharides confirmed the possibility of domain movement. In the case of MtXeg74A, changes in the distances between C_α atoms of aromatic residues involved in xyloglucan binding in -3 and +3 subsites of the active site cleft and those of selected residues on the opposite side of the cleft reached values up to 10-12 Å. For PoGH74_cat the conformational changes were less pronounced. In MtXeg74A variants, the deletion of loop 1, which partially closes the entrance to the cleft, and the additional double mutation of two Trp residues in +3 and +5 subsites caused the enhanced mobility of the XGXXLG and also induced changes in topography of the cleft.

CONCLUSIONS

These findings demonstrate the possibility of existence of GH74 xyloglucanases in a more open and more closed enzyme conformation. The enzyme in an open conformation may more easily accommodate the branched polysaccharide, while its transition to the closed conformation, together with loop 1 function, should aid processivity.

GENERAL SIGNIFICANCE

Our results provide an insight into a mechanism of action of GH74 xyloglucanases and may be useful for discussing the catalytic mechanisms of glycoside hydrolases from other families.