Keep on moving: discovering and perturbing the conformational dynamics of enzymes

Innovative Strategies in X-ray Crystallography for Exploring Structural Dynamics and Reaction Mechanisms in Metabolic Disorders

Enzymes are crucial in metabolic processes, and their dysfunction can lead to severe metabolic disorders. Structural biology, particularly X-ray crystallography, has advanced our understanding of these diseases by providing 3D structures of pathological enzymes. However, traditional X-ray crystallography faces limitations, such as difficulties in obtaining suitable protein crystals and studying protein dynamics. X-ray free-electron lasers (XFELs) have revolutionized this field with their bright and brief X-ray pulses, providing high-resolution structures of radiation-sensitive and hard-to-crystallize proteins. XFELs also enable the study of protein dynamics through room temperature structures and time-resolved serial femtosecond crystallography, offering comprehensive insights into the molecular mechanisms of metabolic diseases. Understanding these dynamics is vital for developing effective therapies. This review highlights the contributions of protein dynamics studies using XFELs and synchrotrons to metabolic disorder research and their application in designing better therapies. It also discusses G protein-coupled receptors (GPCRs), which, though not enzymes, play key roles in regulating physiological systems and are implicated in many metabolic disorders.

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.

Probability Density Reweighting of High-Temperature Molecular Dynamics

Molecular dynamics (MD) simulation is a popular method for elucidating the structures and functions of biomolecules. However, exploring the conformational space, especially for large systems with slow transitions, often requires enhanced sampling methods. Although conducting MD at high temperatures provides a straightforward approach, resulting conformational ensembles diverge significantly from those at low temperatures. To address this discrepancy, we propose a novel probability density-based reweighting (PDR) method. PDR exhibits robust performance across four distinct systems, including a miniprotein, a cyclic peptide, a protein loop, and a protein-peptide complex. It accurately restores the conformational distributions at high temperatures to those at low temperatures. Additionally, we apply PDR to reweight previously studied high-T MD simulations of 12 protein-peptide complexes, enabling a comprehensive investigation of the conformational space of protein-peptide complexes.

MatchMaps: non-isomorphous difference maps for X-ray crystallography

Conformational change mediates the biological functions of macromolecules. Crystallographic measurements can map these changes with extraordinary sensitivity as a function of mutations, ligands and time. A popular method for detecting structural differences between crystallographic data sets is the isomorphous difference map. These maps combine the phases of a chosen reference state with the observed changes in structure factor amplitudes to yield a map of changes in electron density. Such maps are much more sensitive to conformational change than structure refinement is, and are unbiased in the sense that observed differences do not depend on refinement of the perturbed state. However, even modest changes in unit-cell properties can render isomorphous difference maps useless. This is unnecessary. Described here is a generalized procedure for calculating observed difference maps that retains the high sensitivity to conformational change and avoids structure refinement of the perturbed state. This procedure is implemented in an open-source Python package, MatchMaps, that can be run in any software environment supporting PHENIX [Liebschner et al. (2019). Acta Cryst. D75, 861-877] and CCP4 [Agirre et al. (2023). Acta Cryst. D79, 449-461]. Worked examples show that MatchMaps 'rescues' observed difference electron-density maps for poorly isomorphous crystals, corrects artifacts in nominally isomorphous difference maps, and extends to detecting differences across copies within the asymmetric unit or across altogether different crystal forms.

Unusual catalytic strategy by non-heme Fe(ii)/2-oxoglutarate-dependent aspartyl hydroxylase AspH

Biocatalytic C-H oxidation reactions are of important synthetic utility, provide a sustainable route for selective synthesis of important organic molecules, and are an integral part of fundamental cell processes. The multidomain non-heme Fe(ii)/2-oxoglutarate (2OG) dependent oxygenase AspH catalyzes stereoselective (3R)-hydroxylation of aspartyl- and asparaginyl-residues. Unusually, compared to other 2OG hydroxylases, crystallography has shown that AspH lacks the carboxylate residue of the characteristic two-His-one-Asp/Glu Fe-binding triad. Instead, AspH has a water molecule that coordinates Fe(ii) in the coordination position usually occupied by the Asp/Glu carboxylate. Molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) studies reveal that the iron coordinating water is stabilized by hydrogen bonding with a second coordination sphere (SCS) carboxylate residue Asp721, an arrangement that helps maintain the six coordinated Fe(ii) distorted octahedral coordination geometry and enable catalysis. AspH catalysis follows a dioxygen activation-hydrogen atom transfer (HAT)-rebound hydroxylation mechanism, unusually exhibiting higher activation energy for rebound hydroxylation than for HAT, indicating that the rebound step may be rate-limiting. The HAT step, along with substrate positioning modulated by the non-covalent interactions with SCS residues (Arg688, Arg686, Lys666, Asp721, and Gln664), are essential in determining stereoselectivity, which likely proceeds with retention of configuration. The tetratricopeptide repeat (TPR) domain of AspH influences substrate binding and manifests dynamic motions during catalysis, an observation of interest with respect to other 2OG oxygenases with TPR domains. The results provide unique insights into how non-heme Fe(ii) oxygenases can effectively catalyze stereoselective hydroxylation using only two enzyme-derived Fe-ligating residues, potentially guiding enzyme engineering for stereoselective biocatalysis, thus advancing the development of non-heme Fe(ii) based biomimetic C-H oxidation catalysts, and supporting the proposal that the 2OG oxygenase superfamily may be larger than once perceived.

Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering

Enzymes can be engineered at the level of their amino acid sequences to optimize key properties such as expression, stability, substrate range, and catalytic efficiency-or even to unlock new catalytic activities not found in nature. Because the search space of possible proteins is vast, enzyme engineering usually involves discovering an enzyme starting point that has some level of the desired activity followed by directed evolution to improve its "fitness" for a desired application. Recently, machine learning (ML) has emerged as a powerful tool to complement this empirical process. ML models can contribute to (1) starting point discovery by functional annotation of known protein sequences or generating novel protein sequences with desired functions and (2) navigating protein fitness landscapes for fitness optimization by learning mappings between protein sequences and their associated fitness values. In this Outlook, we explain how ML complements enzyme engineering and discuss its future potential to unlock improved engineering outcomes.

MatchMaps: Non-isomorphous difference maps for X-ray crystallography

Conformational change mediates the biological functions of macromolecules. Crystallographic measurements can map these changes with extraordinary sensitivity as a function of mutations, ligands, and time. The isomorphous difference map remains the gold standard for detecting structural differences between datasets. Isomorphous difference maps combine the phases of a chosen reference state with the observed changes in structure factor amplitudes to yield a map of changes in electron density. Such maps are much more sensitive to conformational change than structure refinement is, and are unbiased in the sense that observed differences do not depend on refinement of the perturbed state. However, even minute changes in unit cell properties can render isomorphous difference maps useless. This is unnecessary. Here we describe a generalized procedure for calculating observed difference maps that retains the high sensitivity to conformational change and avoids structure refinement of the perturbed state. We have implemented this procedure in an open-source python package, MatchMaps, that can be run in any software environment supporting PHENIX and CCP4. Through examples, we show that MatchMaps "rescues" observed difference electron density maps for poorly-isomorphous crystals, corrects artifacts in nominally isomorphous difference maps, and extends to detecting differences across copies within the asymmetric unit, or across altogether different crystal forms.

High-resolution double vision of the allosteric phosphatase PTP1B

Protein tyrosine phosphatase 1B (PTP1B) plays important roles in cellular homeostasis and is a highly validated therapeutic target for multiple human ailments, including diabetes, obesity and breast cancer. However, much remains to be learned about how conformational changes may convey information through the structure of PTP1B to enable allosteric regulation by ligands or functional responses to mutations. High-resolution X-ray crystallography can offer unique windows into protein conformational ensembles, but comparison of even high-resolution structures is often complicated by differences between data sets, including non-isomorphism. Here, the highest resolution crystal structure of apo wild-type (WT) PTP1B to date is presented out of a total of ∼350 PTP1B structures in the PDB. This structure is in a crystal form that is rare for PTP1B, with two unique copies of the protein that exhibit distinct patterns of conformational heterogeneity, allowing a controlled comparison of local disorder across the two chains within the same asymmetric unit. The conformational differences between these chains are interrogated in the apo structure and between several recently reported high-resolution ligand-bound structures. Electron-density maps in a high-resolution structure of a recently reported activating double mutant are also examined, and unmodeled alternate conformations in the mutant structure are discovered that coincide with regions of enhanced conformational heterogeneity in the new WT structure. These results validate the notion that these mutations operate by enhancing local dynamics, and suggest a latent susceptibility to such changes in the WT enzyme. Together, these new data and analysis provide a detailed view of the conformational ensemble of PTP1B and highlight the utility of high-resolution crystallography for elucidating conformational heterogeneity with potential relevance for function.

Mapping protein dynamics at high spatial resolution with temperature-jump X-ray crystallography

Understanding and controlling protein motion at atomic resolution is a hallmark challenge for structural biologists and protein engineers because conformational dynamics are essential for complex functions such as enzyme catalysis and allosteric regulation. Time-resolved crystallography offers a window into protein motions, yet without a universal perturbation to initiate conformational changes the method has been limited in scope. Here we couple a solvent-based temperature jump with time-resolved crystallography to visualize structural motions in lysozyme, a dynamic enzyme. We observed widespread atomic vibrations on the nanosecond timescale, which evolve on the submillisecond timescale into localized structural fluctuations that are coupled to the active site. An orthogonal perturbation to the enzyme, inhibitor binding, altered these dynamics by blocking key motions that allow energy to dissipate from vibrations into functional movements linked to the catalytic cycle. Because temperature jump is a universal method for perturbing molecular motion, the method demonstrated here is broadly applicable for studying protein dynamics.

Loop dynamics and the evolution of enzyme activity

In the early 2000s, Tawfik presented his 'New View' on enzyme evolution, highlighting the role of conformational plasticity in expanding the functional diversity of limited repertoires of sequences. This view is gaining increasing traction with increasing evidence of the importance of conformational dynamics in both natural and laboratory evolution of enzymes. The past years have seen several elegant examples of harnessing conformational (particularly loop) dynamics to successfully manipulate protein function. This Review revisits flexible loops as critical participants in regulating enzyme activity. We showcase several systems of particular interest: triosephosphate isomerase barrel proteins, protein tyrosine phosphatases and β-lactamases, while briefly discussing other systems in which loop dynamics are important for selectivity and turnover. We then discuss the implications for engineering, presenting examples of successful loop manipulation in either improving catalytic efficiency, or changing selectivity completely. Overall, it is becoming clearer that mimicking nature by manipulating the conformational dynamics of key protein loops is a powerful method of tailoring enzyme activity, without needing to target active-site residues.

Conformational exchange divergence along the evolutionary pathway of eosinophil-associated ribonucleases

The evolutionary role of conformational exchange in the emergence and preservation of function within structural homologs remains elusive. While protein engineering has revealed the importance of flexibility in function, productive modulation of atomic-scale dynamics has only been achieved on a finite number of distinct folds. Allosteric control of unique members within dynamically diverse structural families requires a better appreciation of exchange phenomena. Here, we examined the functional and structural role of conformational exchange within eosinophil-associated ribonucleases. Biological and catalytic activity of various EARs was performed in parallel to mapping their conformational behavior on multiple timescales using NMR and computational analyses. Despite functional conservation and conformational seclusion to a specific domain, we show that EARs can display similar or distinct motional profiles, implying divergence rather than conservation of flexibility. Comparing progressively more distant enzymes should unravel how this subfamily has evolved new functions and/or altered their behavior at the molecular level.

Evolutionary conservation of protein dynamics: insights from all-atom molecular dynamics simulations of 'peptidase' domain of Spt16

Protein function is encoded in its sequence, manifested in its three-dimensional structure, and facilitated by its dynamics. Studies have suggested that protein structures with higher sequence similarity could have more similar patterns of dynamics. However, such studies of protein dynamics within and across protein families typically rely on coarse-grained models, or approximate metrics like crystallographic B-factors. This study uses µs scale molecular dynamics (MD) simulations to explore the conservation of dynamics among homologs of ∼50 kDa N-terminal module of Spt16 (Spt16N). Spt16N from Saccharomyces cerevisiae (Sc-Spt16N) and three of its homologs with 30-40% sequence identities were available in the PDB. To make our data-set more comprehensive, the crystal structure of an additional homolog (62% sequence identity with Sc-Spt16N) was solved at 1.7 Å resolution. Cumulative MD simulations of 6 µs were carried out on these Spt16N structures and on two additional protein structures with varying degrees of similarity to it. The simulations revealed that correlation in patterns of backbone fluctuations vary linearly with sequence identity. This trend could not be inferred using crystallographic B-factors. Further, normal mode analysis suggested a similar pattern of inter-domain (inter-lobe) motions not only among Spt16N homologs, but also in the M24 peptidase structure. On the other hand, MD simulation results highlighted conserved motions that were found unique for Spt16N protein, this along with electrostatics trends shed light on functional aspects of Spt16N.Communicated by Ramaswamy H. Sarma.

Slow protein dynamics probed by time-resolved oscillation crystallography at room temperature

The development of serial crystallography over the last decade at XFELs and synchrotrons has produced a renaissance in room-temperature macromolecular crystallography (RT-MX), and fostered many technical and methodological breakthroughs designed to study phenomena occurring in proteins on the picosecond-to-second timescale. However, there are components of protein dynamics that occur in much slower regimes, of which the study could readily benefit from state-of-the-art RT-MX. Here, the room-temperature structural study of the relaxation of a reaction intermediate at a synchrotron, exploiting a handful of single crystals, is described. The intermediate in question is formed in microseconds during the photoreaction of the LOV2 domain of phototropin 2 from Arabidopsis thaliana, which then decays in minutes. This work monitored its relaxation in the dark using a fast-readout EIGER X 4M detector to record several complete oscillation X-ray diffraction datasets, each of 1.2 s total exposure time, at different time points in the relaxation process. Coupled with in crystallo UV-Vis absorption spectroscopy, this RT-MX approach allowed the authors to follow the relaxation of the photoadduct, a thio-ether covalent bond between the chromophore and a cysteine residue. Unexpectedly, the return of the chromophore to its spectroscopic ground state is followed by medium-scale protein rearrangements that trigger a crystal phase transition and hinder the full recovery of the structural ground state of the protein. In addition to suggesting a hitherto unexpected role of a conserved tryptophan residue in the regulation of the photocycle of LOV2, this work provides a basis for performing routine time-resolved protein crystallography experiments at synchrotrons for phenomena occurring on the second-to-hour timescale.

Mutagenic Activation of Glutathione Peroxidase-4: Approaches toward Rational Design of Allosteric Drugs

Glutathione peroxidase 4 (GPX4) reduces lipid hydroperoxides in lipid membranes, effectively inhibiting iron-dependent cell death or ferroptosis. The upregulation of the enzyme by the mutations at residues D21 and D23 has been suggested to be associated with higher protein activity, which confers more protection against neurodegenerative diseases such as Alzheimer's, Parkinson's, and Huntington's diseases. Therefore, it has become an attractive target for treating and preventing neurodegenerative diseases. However, identifying means of mimicking the beneficial effects of these mutations distant from the active site constitutes a formidable challenge in moving toward therapeutics. In this study, we explore using molecular dynamics simulations to computationally map the conformational and energetic landscape of the wild-type GPX4 protein and three mutant variants to identify the allosteric networks of the enzyme. We present the conformational dynamic profile providing the desired signature behavior of the enzyme. We also discuss the implications of these findings for drug design efforts.

Molecular Insights into the Intrinsic Dynamics and Their Roles During Catalysis in Pin1 Peptidyl-prolyl Isomerase

Proteins are intrinsically dynamic and change conformations over a wide range of time scales. While the conformational dynamics have been realized to be important for protein functions, e.g., in activity-stability trade-offs, how they play a role during enzyme catalysis has been of debate over decades. By studying Pin1 peptidyl-prolyl isomerase using extensive molecular dynamics simulations, here we discuss how the slow intrinsic dynamics of Pin1 observed in the NMR relaxation dispersion experiment occur and couple to isomerization reactions in molecular detail. In particular, we analyze the angular correlation functions of the backbone N-H bonds and find that slow conformational transitions occur at about the 3₁₀ helix in the apo state. These events at the helical region further affect the residues at about the ligand binding site. Unfolding of this helix leads to a tight hydrogen bond between the helical region and the ligand binding loop, thus forming a stable coiled structure. The helical and coiled structures are found to be characteristic of the Pin1-ligand complex with the ligand in the trans and cis states, respectively. These results indicate that the changes in the slow dynamics of Pin1 by the isomerization reaction occur via the shift in populations of the helical and coiled states, where the balance is dependent on the ligand isomerization states.

Rebuilding the lid region from conformational and dynamic features to engineering applications of lipase in foods: Current status and future prospects

The applications of lipases in esterification, amidation, and transesterification have broadened their potential in the production of fine compounds with high cumulative values. Mostly, the catalytic triad of lipases is covered by either one or two mobile peptides called the "lid" that control the substrate channel to the catalytic center. The lid holds unique conformational allostery via interfacial activation to regulate the dynamics and catalytic functions of lipases, thereby highlighting its importance in redesigning these enzymes for industrial applications. The structural characteristic of lipase, the dynamics of lids, and the roles of lid in lipase catalysis were summarized, providing opportunities for rebuilding lid region by biotechniques (e.g., metagenomic technology and protein engineering) and enzyme immobilization. The review focused on the advantages and disadvantages of strategies rebuilding the lid region. The main shortcomings of biotechnologies on lid rebuilding were discussed such as negative effects on lipase (e.g., a decrease of activity). Additionally, the main shortcomings (e.g., enzyme desorption at high temperatre) in immobilization on hydrophobic supports via interfacial action were presented. Solutions to the mentioned problems were proposed by combinations of computational design with biotechnologies, and improvements of lipase immobilization (e.g., immobilization protocols and support design). Finally, the review provides future perspectives about designing hyperfunctional lipases as biocatalysts in the food industry based on lid conformation and dynamics.

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.

Enhanced sampling without borders: on global biasing functions and how to reweight them

Molecular dynamics (MD) simulations are a powerful tool to follow the time evolution of biomolecular motions in atomistic resolution. However, the high computational demand of these simulations limits the timescales of motions that can be observed. To resolve this issue, so called enhanced sampling techniques are developed, which extend conventional MD algorithms to speed up the simulation process. Here, we focus on techniques that apply global biasing functions. We provide a broad overview of established enhanced sampling methods and promising new advances. As the ultimate goal is to retrieve unbiased information from biased ensembles, we also discuss benefits and limitations of common reweighting schemes. In addition to concisely summarizing critical assumptions and implications, we highlight the general application opportunities as well as uncertainties of global enhanced sampling.

Structural Dynamics of the Functional Nonameric Type III Translocase Export Gate

Type III protein secretion is widespread in Gram-negative pathogens. It comprises the injectisome with a surface-exposed needle and an inner membrane translocase. The translocase contains the SctRSTU export channel enveloped by the export gate subunit SctV that binds chaperone/exported clients and forms a putative ante-chamber. We probed the assembly, function, structure and dynamics of SctV from enteropathogenic E. coli (EPEC). In both EPEC and E. coli lab strains, SctV forms peripheral oligomeric clusters that are detergent-extracted as homo-nonamers. Membrane-embedded SctV₉ is necessary and sufficient to act as a receptor for different chaperone/exported protein pairs with distinct C-domain binding sites that are essential for secretion. Negative staining electron microscopy revealed that peptidisc-reconstituted His-SctV₉ forms a tripartite particle of ∼22 nm with a N-terminal domain connected by a short linker to a C-domain ring structure with a ∼5 nm-wide inner opening. The isolated C-domain ring was resolved with cryo-EM at 3.1 Å and structurally compared to other SctV homologues. Its four sub-domains undergo a three-stage "pinching" motion. Hydrogen-deuterium exchange mass spectrometry revealed this to involve dynamic and rigid hinges and a hyper-flexible sub-domain that flips out of the ring periphery and binds chaperones on and between adjacent protomers. These motions are coincident with local conformational changes at the pore surface and ring entry mouth that may also be modulated by the ATPase inner stalk. We propose that the intrinsic dynamics of the SctV protomer are modulated by chaperones and the ATPase and could affect allosterically the other subunits of the nonameric ring during secretion.

Energy penalties enhance flexible receptor docking in a model cavity

Protein flexibility remains a major challenge in library docking because of difficulties in sampling conformational ensembles with accurate probabilities. Here, we use the model cavity site of T4 lysozyme L99A to test flexible receptor docking with energy penalties from molecular dynamics (MD) simulations. Crystallography with larger and smaller ligands indicates that this cavity can adopt three major conformations: open, intermediate, and closed. Since smaller ligands typically bind better to the cavity site, we anticipate an energy penalty for the cavity opening. To estimate its magnitude, we calculate conformational preferences from MD simulations. We find that including a penalty term is essential for retrospective ligand enrichment; otherwise, high-energy states dominate the docking. We then prospectively docked a library of over 900,000 compounds for new molecules binding to each conformational state. Absent a penalty term, the open conformation dominated the docking results; inclusion of this term led to a balanced sampling of ligands against each state. High ranked molecules were experimentally tested by Tm upshift and X-ray crystallography. From 33 selected molecules, we identified 18 ligands and determined 13 crystal structures. Most interesting were those bound to the open cavity, where the buried site opens to bulk solvent. Here, highly unusual ligands for this cavity had been predicted, including large ligands with polar tails; these were confirmed both by binding and by crystallography. In docking, incorporating protein flexibility with thermodynamic weightings may thus access new ligand chemotypes. The MD approach to accessing and, crucially, weighting such alternative states may find general applicability.

Temperature-Dependent Low-Frequency Modes in the Active Site of Bovine Carbonic Anhydrase II Probed by 2D-IR Spectroscopy

Enzyme catalysis achieves tremendous rate accelerations. Enzyme reaction centers provide a constraint geometry that preferentially binds an activated form of the substrate and thus lowers the energy barrier. However, this transition state picture neglects the flexibility of proteins and its role in enzymatic catalysis. Especially for proton transfer reactions, it has been suggested that motions of the protein modulate the donor-acceptor distance and prepare a tunneling-ready state. We report the detection of frequency fluctuations of an azide anion (N₃^-) bound in the active site of the protein carbonic anhydrase II, where a low-frequency mode of the protein has been proposed to facilitate proton transfer over two water molecules during the catalyzed reaction. 2D-IR spectroscopy resolves an underdamped low-frequency mode at about 1 THz (30 cm^-1). We find its frequency to be viscosity- and temperature-dependent and to decrease by 6 cm^-1 between 230 and 320 K, reporting the softening of the mode's potential.

A Minireview on Temperature Dependent Protein Conformational Sampling

In this minireview we discuss the role of the more subtle conformational change-protein conformational sampling and connect it to the classic relationship of protein structure and function. The theory of pre-existing functional states of protein are discussed in context of alternate protein conformational sampling. Last, we discuss how temperature, ligand binding and mutations affect the protein conformational sampling mode which is linked to the protein function regulation. The review includes several protein systems that showed temperature dependent protein conformational sampling. We also specifically included two enzyme systems, thermophilic alcohol dehydrogenase (ht-ADH) and thermolysin which we previously studied when discussing temperature dependent protein conformational sampling.

Bcl-xL Dynamics under the Lens of Protein Structure Networks

Understanding the finely orchestrated interactions leading to or preventing programmed cell death (apoptosis) is of utmost importance in cancer research because the failure of these systems could eventually lead to the onset of the disease. In this regard, the maintenance of a delicate balance between the promoters and inhibitors of mitochondrial apoptosis is crucial, as demonstrated by the interplay among the Bcl-2 family members. In particular, B-cell lymphoma extra-large (Bcl-x_L) is a target of interest due to the forefront role of its dysfunctions in cancer development. Bcl-x_L prevents apoptosis by binding both the pro-apoptotic BH3-only proteins, like PUMA, and the noncanonical partners, such as p53, at different sites. An allosteric communication between the BH3-only protein binding pocket and the p53 binding site, mediating the release of p53 from Bcl-x_L upon PUMA binding, has been postulated and supported by nuclear magnetic resonance and other biophysical data. The molecular details of this mechanism, especially at the residue level, remain unclear. In this work, we investigated the distal communication between these two sites in Bcl-x_L in its free state and when bound to PUMA. We also evaluated how missense mutations of Bcl-x_L found in cancer samples might impair this communication and therefore the allosteric mechanism. We employed all-atom explicit solvent microsecond molecular dynamics simulations, analyzed through a Protein Structure Network approach and integrated with calculations of changes in free energies upon cancer-related mutations identified by genomics studies. We found a subset of candidate residues responsible for both maintaining protein stability and for conveying structural information between the two binding sites and hypothesized possible communication routes between specific residues at both sites.

A nexus of intrinsic dynamics underlies translocase priming

The cytoplasmic ATPase SecA and the membrane-embedded SecYEG channel assemble to form the Sec translocase. How this interaction primes and catalytically activates the translocase remains unclear. We show that priming exploits a nexus of intrinsic dynamics in SecA. Using atomistic simulations, smFRET, and HDX-MS, we reveal multiple dynamic islands that cross-talk with domain and quaternary motions. These dynamic elements are functionally important and conserved. Central to the nexus is a slender stem through which rotation of the preprotein clamp of SecA is biased by ATPase domain motions between open and closed clamping states. An H-bonded framework covering most of SecA enables multi-tier dynamics and conformational alterations with minimal energy input. As a result, cognate ligands select preexisting conformations and alter local dynamics to regulate catalytic activity and clamp motions. These events prime the translocase for high-affinity reception of non-folded preprotein clients. Dynamics nexuses are likely universal and essential in multi-liganded proteins.

Non-Coordinative Binding of O2 at the Active Center of a Copper-Dependent Enzyme

Molecular oxygen (O₂ ) is a sustainable oxidation reagent. O₂ is strongly oxidizing but kinetically stable and its final reaction product is water. For these reasons learning how to activate O₂ and how to steer its reactivity along desired reaction pathways is a longstanding challenge in chemical research.^[1] Activation of ground-state diradical O₂ can occur either via conversion to singlet oxygen or by one-electron reduction to superoxide. Many enzymes facilitate activation of O₂ by direct fomation of a metal-oxygen coordination complex concomitant with inner sphere electron transfer. The formylglycine generating enzyme (FGE) is an unusual mononuclear copper enzyme that appears to follow a different strategy. Atomic-resolution crystal structures of the precatalytic complex of FGE demonstrate that this enzyme binds O₂ juxtaposed, but not coordinated to the catalytic Cu^I . Isostructural complexes that contain Ag^I instead of Cu^I or nitric oxide instead of O₂ confirm that formation of the initial oxygenated complex of FGE does not depend on redox activity. A stepwise mechanism that decouples binding and activation of O₂ is unprecedented for metal-dependent oxidases, but is reminiscent of flavin-dependent enzymes.

Extension of an Atom-Atom Dispersion Function to Halogen Bonds and Its Use for Rational Design of Drugs and Biocatalysts

A dispersion function Das in the form of a damped atom-atom asymptotic expansion fitted to ab initio dispersion energies from symmetry-adapted perturbation theory was improved and extended to systems containing heavier halogen atoms. To illustrate its performance, the revised Das function was implemented in the multipole first-order electrostatic and second-order dispersion (MED) scoring model. The extension has allowed applications to a much larger set of biocomplexes than it was possible with the original Das. A reasonable correlation between MED and experimentally determined inhibitory activities was achieved in a number of test cases, including structures featuring nonphysically shortened intermonomer distances, which constitute a particular challenge for binding strength predictions. Since the MED model is also computationally efficient, it can be used for reliable and rapid assessment of the ligand affinity or multidimensional scanning of amino acid side-chain conformations in the process of rational design of novel drugs or biocatalysts.

A Single-Point Mutation in d-Arginine Dehydrogenase Unlocks a Transient Conformational State Resulting in Altered Cofactor Reactivity

Proteins are inherently dynamic, and proper enzyme function relies on conformational flexibility. In this study, we demonstrated how an active site residue changes an enzyme's reactivity by modulating fluctuations between conformational states. Replacement of tyrosine 249 (Y249) with phenylalanine in the active site of the flavin-dependent d-arginine dehydrogenase yielded an enzyme with both an active yellow FAD (Y249F-y) and an inactive chemically modified green FAD, identified as 6-OH-FAD (Y249F-g) through various spectroscopic techniques. Structural investigation of Y249F-g and Y249F-y variants by comparison to the wild-type enzyme showed no differences in the overall protein structure and fold. A closer observation of the active site of the Y249F-y enzyme revealed an alternative conformation for some active site residues and the flavin cofactor. Molecular dynamics simulations probed the alternate conformations observed in the Y249F-y enzyme structure and showed that the enzyme variant with FAD samples a metastable conformational state, not available to the wild-type enzyme. Hybrid quantum/molecular mechanical calculations identified differences in flavin electronics between the wild type and the alternate conformation of the Y249F-y enzyme. The computational studies further indicated that the alternate conformation in the Y249F-y enzyme is responsible for the higher spin density at the C6 atom of flavin, which is consistent with the formation of 6-OH-FAD in the variant enzyme. The observations in this study are consistent with an alternate conformational space that results in fine-tuning the microenvironment around a versatile cofactor playing a critical role in enzyme function.

A mechanistic view of enzyme evolution

New enzyme functions often evolve through the recruitment and optimization of latent promiscuous activities. How do mutations alter the molecular architecture of enzymes to enhance their activities? Can we infer general mechanisms that are common to most enzymes, or does each enzyme require a unique optimization process? The ability to predict the location and type of mutations necessary to enhance an enzyme's activity is critical to protein engineering and rational design. In this review, via the detailed examination of recent studies that have shed new light on the molecular changes underlying the optimization of enzyme function, we provide a mechanistic perspective of enzyme evolution. We first present a global survey of the prevalence of activity-enhancing mutations and their distribution within protein structures. We then delve into the molecular solutions that mediate functional optimization, specifically highlighting several common mechanisms that have been observed across multiple examples. As distinct protein sequences encounter different evolutionary bottlenecks, different mechanisms are likely to emerge along evolutionary trajectories toward improved function. Identifying the specific mechanism(s) that need to be improved upon, and tailoring our engineering efforts to each sequence, may considerably improve our chances to succeed in generating highly efficient catalysts in the future.

Driving Protein Conformational Cycles in Physiology and Disease: "Frustrated" Amino Acid Interaction Networks Define Dynamic Energy Landscapes: Amino Acid Interaction Networks Change Progressively Along Alpha Tryptophan Synthase's Catalytic Cycle

A general framework by which dynamic interactions within a protein will promote the necessary series of structural changes, or "conformational cycle," required for function is proposed. It is suggested that the free-energy landscape of a protein is biased toward this conformational cycle. Fluctuations into higher energy, although thermally accessible, conformations drive the conformational cycle forward. The amino acid interaction network is defined as those intraprotein interactions that contribute most to the free-energy landscape. Some network connections are consistent in every structural state, while others periodically change their interaction strength according to the conformational cycle. It is reviewed here that structural transitions change these periodic network connections, which then predisposes the protein toward the next set of network changes, and hence the next structural change. These concepts are illustrated by recent work on tryptophan synthase. Disruption of these dynamic connections may lead to aberrant protein function and disease states.

Harnessing Conformational Plasticity to Generate Designer Enzymes

Recent years have witnessed an explosion of interest in understanding the role of conformational dynamics both in the evolution of new enzymatic activities from existing enzymes and in facilitating the emergence of enzymatic activity de novo on scaffolds that were previously non-catalytic. There are also an increasing number of examples in the literature of targeted engineering of conformational dynamics being successfully used to alter enzyme selectivity and activity. Despite the obvious importance of conformational dynamics to both enzyme function and evolvability, many (although not all) computational design approaches still focus either on pure sequence-based approaches or on using structures with limited flexibility to guide the design. However, there exist a wide variety of computational approaches that can be (re)purposed to introduce conformational dynamics as a key consideration in the design process. Coupled with laboratory evolution and more conventional existing sequence- and structure-based approaches, these techniques provide powerful tools for greatly expanding the protein engineering toolkit. This Perspective provides an overview of evolutionary studies that have dissected the role of conformational dynamics in facilitating the emergence of novel enzymes, as well as advances in computational approaches that allow one to target conformational dynamics as part of enzyme design. Harnessing conformational dynamics in engineering studies is a powerful paradigm with which to engineer the next generation of designer biocatalysts.

Long fluorescence lifetime triangulenium dyes in imaging and fluorescence polarization assay

The development of new fluorescent dyes-new fluorochromes-has a large potential to improve the established methods in enzymology, by empowering both detection capability and the scope of the individual method. Unfortunately, there are huge barriers when adopting new improved fluorescent dyes in established methods. The dyes have to be generally available, protocols for labeling and analysis must be in place, and the field has to be aware how the new improved dye can enhance their method of choice. In this chapter, we will address these issues for the triangulenium dyes. A class of dyes that has a long fluorescence lifetime and emission in the red. A unique combination that opens up new possibilities for the study of protein rotational motion, when developing fluorescence polarization (FP) assays, and for all time-resolved imaging or analysis platforms. To make these dyes generally available, the features of the long fluorescence lifetime triangulenium dyes are described and an optimized labelling protocol are reported.

In Silico Strategies in Tuberculosis Drug Discovery

Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel TB drugs. Discovering new and more potent antibiotics that target novel TB protein targets is an attractive strategy towards controlling the global TB epidemic. In silico strategies can be applied at multiple stages of the drug discovery paradigm to expedite the identification of novel anti-TB therapeutics. In this paper, we discuss the current TB treatment, emergence of drug resistance, and the effective application of computational tools to the different stages of TB drug discovery when combined with traditional biochemical methods. We will also highlight the strengths and points of improvement in in silico TB drug discovery research, as well as possible future perspectives in this field.

Active Site-Induced Evolutionary Constraints Follow Fold Polarity Principles in Soluble Globular Enzymes

A recent analysis of evolutionary rates in >500 globular soluble enzymes revealed pervasive conservation gradients toward catalytic residues. By looking at amino acid preference profiles rather than evolutionary rates in the same data set, we quantified the effects of active sites on site-specific constraints for physicochemical traits. We found that conservation gradients respond to constraints for polarity, hydrophobicity, flexibility, rigidity and structure in ways consistent with fold polarity principles; while sites far from active sites seem to experience no physicochemical constraint, rather being highly variable and favoring amino acids of low metabolic cost. Globally, our results highlight that amino acid variation contains finer information about protein structure than usually regarded in evolutionary models, and that this information is retrievable automatically with simple fits. We propose that analyses of the kind presented here incorporated into models of protein evolution should allow for better description of the physical chemistry that underlies molecular evolution.

The ATP-bound conformation of the Mre11-Rad50 complex is essential for Tel1/ATM activation

Activation of the checkpoint protein Tel1 requires the Mre11–Rad50–Xrs2 (MRX) complex, which recruits Tel1 at DNA double-strand breaks (DSBs) through direct interaction between Tel1 and Xrs2. However, in vitro Tel1 activation by MRX requires ATP binding to Rad50, suggesting a role also for the MR subcomplex in Tel1 activation. Here we describe two separation-of-functions alleles, mre11-S499P and rad50-A78T, which we show to specifically affect Tel1 activation without impairing MRX functions in DSB repair. Both Mre11-S499P and Rad50-A78T reduce Tel1–MRX interaction leading to poor Tel1 association at DSBs and consequent loss of Tel1 activation. The Mre11-S499P variant reduces Mre11–Rad50 interaction, suggesting an important role for MR complex formation in Tel1 activation. Molecular dynamics simulations show that the wild type MR subcomplex bound to ATP lingers in a tightly ‘closed’ conformation, while ADP presence leads to the destabilization of Rad50 dimer and of Mre11–Rad50 association, both events being required for MR conformational transition to an open state. By contrast, MR^A78T undertakes complex opening even if Rad50 is bound to ATP, indicating that defective Tel1 activation caused by MR^A78T results from destabilization of the ATP-bound conformational state.

Chokepoints in Mechanical Coupling Associated with Allosteric Proteins: The Pyruvate Kinase Example

Although the critical role of allostery in controlling enzymatic processes is well appreciated, there is a current dearth in our understanding of its underlying mechanisms, including communication between binding sites. One potential key aspect of intersite communication is the mechanical coupling between residues in a protein. Here, we introduce a graph-based computational approach to investigate the mechanical coupling between distant parts of a protein, highlighting effective pathways via which protein motion can transfer energy between sites. In this method, each residue is treated as a node on a weighted, undirected graph, in which the edges are defined by locally correlated motions of those residues and weighted by the strength of the correlation. The method was validated against experimental data on allosteric regulation in the human liver pyruvate kinase as obtained from full-protein alanine-scanning mutagenesis (systematic mutation) studies, as well as computational data on two G-protein-coupled receptors. The method provides semiquantitative information on the regulatory importance of specific structural elements. It is shown that these elements are key for the mechanical coupling between distant parts of the protein by providing effective pathways for energy transfer. It is also shown that, although there are a multitude of energy transfer pathways between distant parts of a protein, these pathways share a few common nodes that represent effective "chokepoints" for the communication.

Beyond the Second Coordination Sphere: Engineering Dirhodium Artificial Metalloenzymes To Enable Protein Control of Transition Metal Catalysis

Transition metal catalysis is a powerful tool for chemical synthesis, a standard by which understanding of elementary chemical processes can be measured, and a source of awe for those who simply appreciate the difficulty of cleaving and forming chemical bonds. Each of these statements is amplified in cases where the transition metal catalyst controls the selectivity of a chemical reaction. Enantioselective catalysis is a challenging but well-established phenomenon, and regio- or site-selective catalysis is increasingly common. On the other hand, transition-metal-catalyzed reactions are typically conducted under highly optimized conditions. Rigorous exclusion of air and water is common, and it is taken for granted that only a single substrate (of a particular class) will be present in a reaction, a desired site selectivity can be achieved by installing a directing group, and undesired reactivity can be blocked with protecting groups. These are all reasonable synthetic strategies, but they also highlight limits to catalyst control. The utility of transition metal catalysis could be greatly expanded if catalysts possessed the ability to regulate which molecules they encounter and the relative orientation of those molecules. The rapid and widespread adoption of stoichiometric bioorthogonal reactions illustrates the utility of robust reactions that proceed with high selectivity and specificity under mild reaction conditions. Expanding this capability beyond preprogrammed substrate pairs via catalyst control could therefore have an enormous impact on molecular science. Many metalloenzymes exhibit this level of catalyst control, and directed evolution can be used to rapidly improve the catalytic properties of these systems. On the other hand, the range of reactions catalyzed by enzymes is limited relative to that developed by chemists. The possibility of imparting enzyme-like activity, selectivity, and evolvability to reactions catalyzed by synthetic transition metal complexes has inspired the creation of artificial metalloenzymes (ArMs). The increasing levels of catalyst control exhibited by ArMs developed to date suggest that these systems could constitute a powerful platform for bioorthogonal transition metal catalysis and for selective catalysis in general. This Account outlines the development of a new class of ArMs based on a prolyl oligopeptidase (POP) scaffold. Studies conducted on POP ArMs containing a covalently linked dirhodium cofactor have shown that POP can impart enantioselectivity to a range of dirhodium-catalyzed reactions, increase reaction rates, and improve the specificity for reaction of dirhodium carbene intermediates with targeted organic substrates over components of cell lysate, including bulk water. Several design features of these ArMs enabled their evolution via random mutagenesis, which revealed that mutations throughout the POP scaffold, beyond the second sphere of the dirhodium cofactor, were important for ArM activity and selectivity. While it was anticipated that the POP scaffold would be capable of encapsulating and thus controlling the selectivity of bulky cofactors, molecular dynamics studies also suggest that POP conformational dynamics plays a role in its unique efficacy. These advances in scaffold selection, bioconjugation, and evolution form the basis of our ongoing efforts to control transition metal reactivity using protein scaffolds with the goal of enabling unique synthetic capabilities, including bioorthogonal catalysis.

Peptide-Based Catalysts Reach the Outer Sphere through Remote Desymmetrization and Atroposelectivity

Nature’s catalytic machinery has provided endless inspiration for chemists. While the enzymatic ideal has yet to be fully realized, the field has made tremendous strides toward synthetic, small-molecule catalysts for a wide array of transformations, often drawing upon biological concepts in their design. One strategy that has been particularly influenced by enzymology is peptide catalysis, wherein oligopeptides are implemented as chiral catalysts in synthetically relevant reactions. The fundamental goal has been to mimic enzymatic active sites by taking advantage of secondary structures that allow for multifunctional activation of substrates within a framework of significantly reduced molecular complexity.

Our group has now been studying peptide-based catalysis for over two decades. At the outset, there were many reasons to be concerned that general contributions might not be possible. Precedents existed, including the Juliá–Colonna epoxidations mediated by helical oligopeptides, among others. However, we sought to explore whether peptide catalysts could find broad applications in organic synthesis despite what was expected to be their principal liability: conformational flexibility. Over time, we have been able to identify peptidic catalysts for a variety of site- and enantioselective transformations ranging from hydroxyl group and arene functionalizations to redox and C–C bond forming reactions. The peptides often exhibited excellent catalytic activities, in many cases enabling never-before-seen patterns of selectivity. Recent studies even suggest that, in certain situations, the conformational flexibility of these catalysts may be advantageous for asymmetric induction.

In the course of our studies, opportunities to employ peptide-based catalysis to solve long-standing and stereochemically intriguing problems in asymmetric synthesis presented themselves. For example, we have found that peptides provide exceptional enantiotopic group differentiation in catalytic desymmetrization reactions. Early results with symmetrical polyol substrates, such as myo-inositols and glycerols, eventually spurred the development of remote desymmetrizations of diarylmethanes, in which the enantiotopic groups are separated from the prochiral center by ∼6 Å and from one another by nearly 1 nm. Various hydroxyl group functionalizations and electrophilic brominations, as well as C–C, C–O, and C–N cross-coupling reactions using peptidic ligands on copper(I) have now been developed within this reaction archetype. Additionally, the preponderance of axially chiral, atropisomeric compounds as ligands, organocatalysts, and pharmacophores encouraged us to employ peptides as atroposelective catalysts. We have developed peptide-catalyzed brominations of pharmaceutically relevant biaryl, non-biaryl, and hetero-biaryl atropisomers that take advantage of dynamic kinetic resolution schemes. These projects have vastly expanded the reach of our original hypotheses and raised new questions about peptide-based catalysts and the extent to which they might mimic enzymes.

Herein, we recount the development and optimization of these stereochemically complex reactions, with a particular focus on structural and mechanistic aspects of the peptide-based catalysts that make them well-suited for their respective functions. The ability of these peptides to address important yet fundamentally challenging issues in asymmetric catalysis, combined with their modularity and ease-of-synthesis, make them primed for future use in organic synthesis.

Hydrogen Bonds: Simple after All?

Hydrogen bonds play integral roles in biological structure, function, and conformational dynamics and are fundamental to life as it has evolved on Earth. However, our understanding of these fundamental and ubiquitous interactions has seemed fractured and incomplete, and it has been difficult to extract generalities and principles about hydrogen bonds despite thousands of papers published on this topic, perhaps in part because of the expanse of this subject and the density of studies. Fortunately, recent hydrogen bond proposals, discussions, and debates have stimulated new tests and models and have led to a remarkably simple picture of the structure of hydrogen bonds. This knowledge also provides clarity concerning hydrogen bond energetics, limiting and simplifying the factors that need be considered. Herein we recount the advances that have led to this simpler view of hydrogen bond structure, dynamics, and energetics. A quantitative predictive model for hydrogen bond length can now be broadly and deeply applied to evaluate current proposals and to uncover structural features of proteins, their conformational restraints, and their correlated motions. In contrast, a quantitative energetic description of molecular recognition and catalysis by proteins remains an important ongoing challenge, although our improved understanding of hydrogen bonds may aid in testing predictions from current and future models. We close by codifying our current state of understanding into five "Rules for Hydrogen Bonding" that may provide a foundation for understanding and teaching about these vital interactions and for building toward a deeper understanding of hydrogen bond energetics.

Engineered control of enzyme structural dynamics and function

Enzymes undergo a range of internal motions from local, active site fluctuations to large-scale, global conformational changes. These motions are often important for enzyme function, including in ligand binding and dissociation and even preparing the active site for chemical catalysis. Protein engineering efforts have been directed towards manipulating enzyme structural dynamics and conformational changes, including targeting specific amino acid interactions and creation of chimeric enzymes with new regulatory functions. Post-translational covalent modification can provide an additional level of enzyme control. These studies have not only provided insights into the functional role of protein motions, but they offer opportunities to create stimulus-responsive enzymes. These enzymes can be engineered to respond to a number of external stimuli, including light, pH, and the presence of novel allosteric modulators. Altogether, the ability to engineer and control enzyme structural dynamics can provide new tools for biotechnology and medicine.

Inferring joint sequence-structural determinants of protein functional specificity

Residues responsible for allostery, cooperativity, and other subtle but functionally important interactions remain difficult to detect. To aid such detection, we employ statistical inference based on the assumption that residues distinguishing a protein subgroup from evolutionarily divergent subgroups often constitute an interacting functional network. We identify such networks with the aid of two measures of statistical significance. One measure aids identification of divergent subgroups based on distinguishing residue patterns. For each subgroup, a second measure identifies structural interactions involving pattern residues. Such interactions are derived either from atomic coordinates or from Direct Coupling Analysis scores, used as surrogates for structural distances. Applying this approach to N-acetyltransferases, P-loop GTPases, RNA helicases, synaptojanin-superfamily phosphatases and nucleases, and thymine/uracil DNA glycosylases yielded results congruent with biochemical understanding of these proteins, and also revealed striking sequence-structural features overlooked by other methods. These and similar analyses can aid the design of drugs targeting allosteric sites.

Origins of Enzyme Catalysis: Experimental Findings for C-H Activation, New Models, and Their Relevance to Prevailing Theoretical Constructs

The physical basis for enzymatic rate accelerations is a subject of great fundamental interest and of direct relevance to areas that include the de novo design of green catalysts and the pursuit of new drug regimens. Extensive investigations of C-H activating systems have provided considerable insight into the relationship between an enzyme's overall structure and the catalytic chemistry at its active site. This Perspective highlights recent experimental data for two members of distinct, yet iconic C-H activation enzyme classes, lipoxygenases and prokaryotic alcohol dehydrogenases. The data necessitate a reformulation of the dominant textbook definition of biological catalysis. A multidimensional model emerges that incorporates a range of protein motions that can be parsed into a combination of global stochastic conformational thermal fluctuations and local donor-acceptor distance sampling. These motions are needed to achieve a high degree of precision with regard to internuclear distances, geometries, and charges within the active site. The available model also suggests a physical framework for understanding the empirical enthalpic barrier in enzyme-catalyzed processes. We conclude by addressing the often conflicting interface between computational and experimental chemists, emphasizing the need for computation to predict experimental results in advance of their measurement.

Dependence of prevalence of contiguous pathways in proteins on structural complexity

Allostery is a regulatory mechanism in proteins where an effector molecule binds distal from an active site to modulate its activity. Allosteric signaling may occur via a continuous path of residues linking the active and allosteric sites, which has been suggested by large conformational changes evident in crystal structures. An alternate possibility is that the signal occurs in the realm of ensemble dynamics via an energy landscape change. While the latter was first proposed on theoretical grounds, increasing evidence suggests that such a control mechanism is plausible. A major difficulty for testing the two methods is the ability to definitively determine that a residue is directly involved in allosteric signal transduction. Statistical Coupling Analysis (SCA) is a method that has been successful at predicting pathways, and experimental tests involving mutagenesis or domain substitution provide the best available evidence of signaling pathways. However, ascertaining energetic pathways which need not be contiguous is far more difficult. To date, simple estimates of the statistical significance of a pathway in a protein remain to be established. The focus of this work is to estimate such benchmarks for the statistical significance of contiguous pathways for the null model of selecting residues at random. We found that when 20% of residues in proteins are randomly selected, contiguous pathways at the 6 Å cutoff level were found with success rates of 51% in PDZ, 30% in p53, and 3% in MutS. The results suggest that the significance of pathways may have system specific factors involved. Furthermore, the possible existence of false positives for contiguous pathways implies that signaling could be occurring via alternate routes including those consistent with the energetic landscape model.

Shuffling Active Site Substate Populations Affects Catalytic Activity: The Case of Glucose Oxidase

Glucose oxidase has wide applications in the pharmaceutical, chemical, and food industries. Many recent studies have enhanced key properties of this enzyme using directed evolution, yet without being able to reveal why these mutations are actually beneficial. This work presents a synergistic combination of experimental and computational methods, indicating how mutations, even when distant from the active site, positively affect glucose oxidase catalysis. We have determined the crystal structures of glucose oxidase mutants containing molecular oxygen in the active site. The catalytically important His516 residue has been previously shown to be flexible in the wild-type enzyme. The molecular dynamics simulations performed in this work allow us to quantify this floppiness, revealing that His516 exists in two states: catalytic and noncatalytic. The relative populations of these two substates are almost identical in the wild-type enzyme, with His516 readily shuffling between them. In the glucose oxidase mutants, on the other hand, the mutations enrich the catalytic His516 conformation and reduce the flexibility of this residue, leading to an enhancement in their catalytic efficiency. This study stresses the benefit of active site preorganization with respect to enzyme conversion rates by reducing molecular reorientation needs. We further suggest that the computational approach based on Hamiltonian replica exchange molecular dynamics, used in this study, may be a general approach to screening in silico for improved enzyme variants involving flexible catalytic residues.

Orchestrated Domain Movement in Catalysis by Cytochrome P450 Reductase

NADPH-cytochrome P450 reductase is a multi-domain redox enzyme which is a key component of the P450 mono-oxygenase drug-metabolizing system. We report studies of the conformational equilibrium of this enzyme using small-angle neutron scattering, under conditions where we are able to control the redox state of the enzyme precisely. Different redox states have a profound effect on domain orientation in the enzyme and we analyse the data in terms of a two-state equilibrium between compact and extended conformations. The effects of ionic strength show that the presence of a greater proportion of the extended form leads to an enhanced ability to transfer electrons to cytochrome c. Domain motion is intrinsically linked to the functionality of the enzyme, and we can define the position of the conformational equilibrium for individual steps in the catalytic cycle.

In Silico Studies of Small Molecule Interactions with Enzymes Reveal Aspects of Catalytic Function

Small molecules, such as solvent, substrate, and cofactor molecules, are key players in enzyme catalysis. Computational methods are powerful tools for exploring the dynamics and thermodynamics of these small molecules as they participate in or contribute to enzymatic processes. In-depth knowledge of how small molecule interactions and dynamics influence protein conformational dynamics and function is critical for progress in the field of enzyme catalysis. Although numerous computational studies have focused on enzyme-substrate complexes to gain insight into catalytic mechanisms, transition states and reaction rates, the dynamics of solvents, substrates, and cofactors are generally less well studied. Also, solvent dynamics within the biomolecular solvation layer play an important part in enzyme catalysis, but a full understanding of its role is hampered by its complexity. Moreover, passive substrate transport has been identified in certain enzymes, and the underlying principles of molecular recognition are an area of active investigation. Enzymes are highly dynamic entities that undergo different conformational changes, which range from side chain rearrangement of a residue to larger-scale conformational dynamics involving domains. These events may happen nearby or far away from the catalytic site, and may occur on different time scales, yet many are related to biological and catalytic function. Computational studies, primarily molecular dynamics (MD) simulations, provide atomistic-level insight and site-specific information on small molecule interactions, and their role in conformational pre-reorganization and dynamics in enzyme catalysis. The review is focused on MD simulation studies of small molecule interactions and dynamics to characterize and comprehend protein dynamics and function in catalyzed reactions. Experimental and theoretical methods available to complement and expand insight from MD simulations are discussed briefly.