Visualizing transiently associated catalytic domains in assembly-line biosynthesis using cryo-electron microscopy.

While cryo-electron microscopy (cryo-EM) has revolutionized the structure determination of supramolecular protein complexes that are refractory to structure determination by X-ray crystallography, structure determination by cryo-EM can nonetheless be complicated by excessive conformational flexibility or structural heterogeneity resulting from weak or transient protein-protein association. Since such transient complexes are often critical for function, specialized approaches must be employed for the determination of meaningful structure-function relationships. Here, we outline examples in which transient protein-protein interactions have been visualized successfully by cryo-EM in the biosynthesis of fatty acids, polyketides, and terpenes. These studies demonstrate the utility of chemical crosslinking to stabilize transient protein-protein complexes for cryo-EM structural analysis, as well as the use of partial signal subtraction and localized reconstruction to extract useful structural information out of cryo-EM data collected from inherently dynamic systems. While these approaches do not always yield atomic resolution insights on protein-protein interactions, they nonetheless enable direct experimental observation of complexes in assembly-line biosynthesis that would otherwise be too fleeting for structural analysis.

Words of advice: teaching enzyme kinetics.

Enzymology is concerned with the study of enzyme structure, function, regulation and kinetics. It is an interdisciplinary subject that can be treated as an exclusive sphere of exhaustive inquiry within mathematical, physico-chemical and biological sciences. Hence, teaching of enzymology, in general, and enzyme kinetics, in particular, should be undertaken in an interdisciplinary manner for a holistic appreciation of this subject. Further, analogous examples from everyday life should form an integral component of the teaching for an intuitive grasp of the subject matter. Furthermore, simulation-based appreciation of enzyme kinetics should be preferred over simplifying assumptions and approximations of traditional enzyme kinetics teaching. In this Words of Advice, I outline the domain depth of enzymology across the various disciplines and provide initial ideas on how appropriate analogies can provide firm insights into the subject. Further, I demonstrate how an intuitive feel for the subject can help not only in grasping abstract concepts but also extending it in experimental design and subsequent interpretation. Use of simulations in grasping complex concepts is also advocated given the advantages this medium offers over traditional approaches involving images and molecular models. Furthermore, I discuss the merits of incorporating the historical backdrop of major discoveries in enzymological teaching. We, at AstraZeneca, have experimented with this approach with the desired outcome of generating interest in the subject from people practising diverse disciplines.

Asymmetric dynamic coupling promotes alternative evolutionary pathways in an enzyme dimer.

The importance of dynamic factors in enzyme evolution is gaining recognition. Here we study how the evolution of a new enzymatic activity exploits conformational tinkering and demonstrate that conversion of a dimeric phosphotriesterase to an arylesterase in Pseudomonas diminuta is accompanied by structural divergence between the two subunits. Deviations in loop conformations increase with promiscuity, leading to functionally distinct states, while they decrease during specialisation for the new function. We show that opposite loop movements in the two subunits are due to a dynamic coupling with the dimer interface, the importance of which is also corroborated by the co-evolution of the loop and interface residues. These results illuminate how protein dynamics promotes conformational heterogeneity in a dimeric enzyme, leading to alternative evolutionary pathways for the emergence of a new function.

Multiplex enzyme activity imaging by MALDI-IMS of substrate library conversions.

Enzymes are fundamental to biological processes and involved in most pathologies. Here we demonstrate the concept of simultaneously mapping multiple enzyme activities (EA) by applying enzyme substrate libraries to tissue sections and analyzing their conversion by matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS). To that end, we spray-applied a solution of 20 naturally derived peptides that are known substrates for proteases, kinases, and phosphatases to zinc-fixed paraffin tissue sections of mouse kidneys. After enzyme conversion for 5 to 120 min at 37 °C and matrix application, the tissue sections were imaged by MALDI-IMS. We could image incubation time-dependently 16 of the applied substrates with differing signal intensities and 12 masses of expected products. Utilizing inherent enzyme amplification, EA-IMS can become a powerful tool to locally study multiple, potentially even lowly expressed, enzyme activities, networks, and their pharmaceutical modulation. Differences in the substrate detectability highlight the need for future optimizations.

In Vitro Light-Up Visualization of a Subunit-Specific Enzyme by an AIE Probe via Restriction of Single Molecular Motion.

Enzymes contain several subunits to maintain different biological functions. However, it remains a great challenge for specific discrimination of one subunit over another. Toward this end, the fluorescent probe TPEMA is now presented for highly specific detection of the B subunit of cytosolic creatine (CK) kinase isoenzyme (CK-B). Owing to its aggregation-induced emission property, TPEMA shows highly boosted emission toward CK-B with a fast response time and very low interference from other analytes, including the M subunit of CK (CK-M). With the aid of a Job plot assay, ITC assay and molecular dynamics simulation, it was directly confirmed that the remarkably enhanced fluorescence of TPEMA in the presence of CK-B results from the restriction of single molecular motion in the cavity. Selective wash-free fluorescence imaging of CK-B in macrophages under different treatments was successfully demonstrated.

Characterizing and Predicting Protein Hinges for Mechanistic Insight.

The functioning of proteins requires highly specific dynamics, which depend critically on the details of how amino acids are packed. Hinge motions are the most common type of large motion, typified by the opening and closing of enzymes around their substrates. The packing and geometries of residues are characterized here by graph theory. This characterization is sufficient to enable reliable hinge predictions from a single static structure, and notably, this can be from either the open or the closed form of a structure. This new method to identify hinges within protein structures is called PACKMAN. The predicted hinges are validated by using permutation tests on B-factors. Hinge prediction results are compared against lists of manually curated hinge residues, and the results suggest that PACKMAN is robust enough to reproduce the known conformational changes and is able to predict hinge regions equally well from either the open or the closed forms of a protein. A group of 167 protein pairs with open and closed structures has been investigated Examples are shown for several additional proteins, including Zika virus nonstructured (NS) proteins where there are 6 hinge regions in the NS5 protein, 5 hinge regions in the NS2B bound in the NS3 protease complex and 5 hinges in the NS3- helicase protein. Results obtained from this method can be important for generating conformational ensembles of protein targets for drug design. PACKMAN is freely accessible at (https://PACKMAN.bb.iastate.edu/).

Mix-and-inject XFEL crystallography reveals gated conformational dynamics during enzyme catalysis.

How changes in enzyme structure and dynamics facilitate passage along the reaction coordinate is a fundamental unanswered question. Here, we use time-resolved mix-and-inject serial crystallography (MISC) at an X-ray free electron laser (XFEL), ambient-temperature X-ray crystallography, computer simulations, and enzyme kinetics to characterize how covalent catalysis modulates isocyanide hydratase (ICH) conformational dynamics throughout its catalytic cycle. We visualize this previously hypothetical reaction mechanism, directly observing formation of a thioimidate covalent intermediate in ICH microcrystals during catalysis. ICH exhibits a concerted helical displacement upon active-site cysteine modification that is gated by changes in hydrogen bond strength between the cysteine thiolate and the backbone amide of the highly strained Ile152 residue. These catalysis-activated motions permit water entry into the ICH active site for intermediate hydrolysis. Mutations at a Gly residue (Gly150) that modulate helical mobility reduce ICH catalytic turnover and alter its pre-steady-state kinetic behavior, establishing that helical mobility is important for ICH catalytic efficiency. These results demonstrate that MISC can capture otherwise elusive aspects of enzyme mechanism and dynamics in microcrystalline samples, resolving long-standing questions about the connection between nonequilibrium protein motions and enzyme catalysis.

Evolution of a highly active and enantiospecific metalloenzyme from short peptides.

Primordial sequence signatures in modern proteins imply ancestral origins tracing back to simple peptides. Although short peptides seldom adopt unique folds, metal ions might have templated their assembly into higher-order structures in early evolution and imparted useful chemical reactivity. Recapitulating such a biogenetic scenario, we have combined design and laboratory evolution to transform a zinc-binding peptide into a globular enzyme capable of accelerating ester cleavage with exacting enantiospecificity and high catalytic efficiency (k cat/K M ~ 106 M-1 s-1). The simultaneous optimization of structure and function in a naïve peptide scaffold not only illustrates a plausible enzyme evolutionary pathway from the distant past to the present but also proffers exciting future opportunities for enzyme design and engineering.

Defying the activity-stability trade-off in enzymes: taking advantage of entropy to enhance activity and thermostability.

The biotechnological applications of enzymes are limited due to the activity-stability trade-off, which implies that an increase in activity is accompanied by a concomitant decrease in protein stability. This premise is based on thermally adapted homologous enzymes where cold-adapted enzymes show high intrinsic activity linked to enhanced thermolability. In contrast, thermophilic enzymes show low activity around ambient temperatures. Nevertheless, genetically and chemically modified enzymes are beginning to show that the activity-stability trade-off can be overcome. In this review, the origin of the activity-stability trade-off, the thermodynamic basis for enhanced activity and stability, and various approaches for escaping the activity-stability trade-off are discussed. The role of entropy in enhancing both the activity and the stability of enzymes is highlighted with a special emphasis placed on the involvement of solvent water molecules. This review is concluded with suggestions for further research, which underscores the implications of these findings in the context of productivity curves, the Daniel-Danson equilibrium model, catalytic antibodies, and life on cold planets.

Normal Modes Expose Active Sites in Enzymes.

Accurate prediction of active sites is an important tool in bioinformatics. Here we present an improved structure based technique to expose active sites that is based on large changes of solvent accessibility accompanying normal mode dynamics. The technique which detects EXPOsure of active SITes through normal modEs is named EXPOSITE. The technique is trained using a small 133 enzyme dataset and tested using a large 845 enzyme dataset, both with known active site residues. EXPOSITE is also tested in a benchmark protein ligand dataset (PLD) comprising 48 proteins with and without bound ligands. EXPOSITE is shown to successfully locate the active site in most instances, and is found to be more accurate than other structure-based techniques. Interestingly, in several instances, the active site does not correspond to the largest pocket. EXPOSITE is advantageous due to its high precision and paves the way for structure based prediction of active site in enzymes.

NMR Methods to Study Dynamic Allostery.

Nuclear magnetic resonance (NMR) spectroscopy provides a unique toolbox of experimental probes for studying dynamic processes on a wide range of timescales, ranging from picoseconds to milliseconds and beyond. Along with NMR hardware developments, recent methodological advancements have enabled the characterization of allosteric proteins at unprecedented detail, revealing intriguing aspects of allosteric mechanisms and increasing the proportion of the conformational ensemble that can be observed by experiment. Here, we present an overview of NMR spectroscopic methods for characterizing equilibrium fluctuations in free and bound states of allosteric proteins that have been most influential in the field. By combining NMR experimental approaches with molecular simulations, atomistic-level descriptions of the mechanisms by which allosteric phenomena take place are now within reach.

Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication.

Allostery is one of the pervasive mechanisms through which proteins in living systems carry out enzymatic activity, cell signaling, and metabolism control. Effective modeling of the protein function regulation requires a synthesis of the thermodynamic and structural views of allostery. We present here a structure-based statistical mechanical model of allostery, allowing one to observe causality of communication between regulatory and functional sites, and to estimate per residue free energy changes. Based on the consideration of ligand free and ligand bound systems in the context of a harmonic model, corresponding sets of characteristic normal modes are obtained and used as inputs for an allosteric potential. This potential quantifies the mean work exerted on a residue due to the local motion of its neighbors. Subsequently, in a statistical mechanical framework the entropic contribution to allosteric free energy of a residue is directly calculated from the comparison of conformational ensembles in the ligand free and ligand bound systems. As a result, this method provides a systematic approach for analyzing the energetics of allosteric communication based on a single structure. The feasibility of the approach was tested on a variety of allosteric proteins, heterogeneous in terms of size, topology and degree of oligomerization. The allosteric free energy calculations show the diversity of ways and complexity of scenarios existing in the phenomenology of allosteric causality and communication. The presented model is a step forward in developing the computational techniques aimed at detecting allosteric sites and obtaining the discriminative power between agonistic and antagonistic effectors, which are among the major goals in allosteric drug design.

Artificial neural networks for dihedral angles prediction in enzyme loops: a novel approach.

Structure prediction of proteins is considered a limiting step and determining factor in drug development and in the introduction of new therapies. Since the 3D structures of proteins determine their functionalities, prediction of dihedral angles remains an open and important problem in bioinformatics, as well as a major step in discovering tertiary structures. This work presents a method that predicts values of the dihedral angles φ and ψ for enzyme loops based on data derived from amino acid sequences. The prediction of dihedral angles is implemented through a neural network based mining mechanism. The amino acid sequence data represents 6342 enzyme loop chains with 18,882 residues. The initial neural network input was a selection of 115 features and the outputs were the predicted dihedral angles φ and ψ. The simulation results yielded a 0.64 Pearson's correlation coefficient. After feature selection through determining insignificant features, the input feature vector size was reduced to 45, while maintaining close to identical performance.

Fluorescein-5-isothiocyanate-conjugated protein-directed synthesis of gold nanoclusters for fluorescent ratiometric sensing of an enzyme-substrate system.

This study describes the synthesis of a dual emission probe for the fluorescent ratiometric sensing of hydrogen peroxide (H2O2), enzyme activity, and environmental pH change. Green-emitting fluorescein-5-isothiocyanate (FITC) was conjugated to the amino groups of bovine serum albumin (BSA). This FITC-conjugated BSA acted as a template for the synthesis of red-emitting gold nanoclusters (AuNCs) under alkaline conditions. Under single wavelength excitation, FITC/BSA-stabilized AuNCs (FITC/BSA-AuNCs) emitted fluorescence at 525 and 670nm, which are sensitive to changes in solution pH and H2O2 concentration, respectively. The effective fluorescence quenching of AuNCs by H2O2 enabled FITC/BSA-AuNCs to ratiometrically detect the H2O2 product-related enzyme system and its inhibition, including glucose oxidase-catalyzed oxidation of glucose, acetylcholinesterase/choline oxidase-mediated hydrolysis and oxidation of acetylcholine, and paraoxon-induced inhibition of acetylcholinesterase activity. When pH-insensitive AuNCs were used as an internal standard, FITC/BSA-AuNCs offered a sensitive and reversible ratiometric sensing of a 0.1-pH unit change in the pH range 5.0-8.5. The pH-induced change in FITC fluorescence enabled FITC/BSA-AuNCs to detect an ammonia product-related enzyme system. This was exemplified with the determination of urea in plasma by urease-mediated hydrolysis of urea.

Repurposing TRASH: emergence of the enzyme organomercurial lyase from a non-catalytic zinc finger scaffold.

The mercury resistance pathway enzyme organomercurial lyase (MerB) catalyzes the conversion of organomercurials to ionic mercury (Hg(2+)). Here, we provide evidence for the emergence of this enzyme from a TRASH-like, non-enzymatic, treble-clef zinc finger ancestor by domain duplication and fusion. Surprisingly, the structure-stabilizing metal-binding core of the treble-clef appears to have been repurposed in evolution to serve a catalytic role. Novel enzymatic functions are believed to have evolved from ancestral generalist catalytic scaffolds or from already specialized enzymes with catalytic promiscuity. The emergence of MerB from a zinc finger ancestor serves as a rare example of how a novel enzyme may emerge from a non-catalytic scaffold with a related binding function.

Enzyme molecules in solitary confinement.

Large arrays of homogeneous microwells each defining a femtoliter volume are a versatile platform for monitoring the substrate turnover of many individual enzyme molecules in parallel. The high degree of parallelization enables the analysis of a statistically representative enzyme population. Enclosing individual enzyme molecules in microwells does not require any surface immobilization step and enables the kinetic investigation of enzymes free in solution. This review describes various microwell array formats and explores their applications for the detection and investigation of single enzyme molecules. The development of new fabrication techniques and sensitive detection methods drives the field of single molecule enzymology. Here, we introduce recent progress in single enzyme molecule analysis in microwell arrays and discuss the challenges and opportunities.

The natural history of biocatalytic mechanisms.

Phylogenomic analysis of the occurrence and abundance of protein domains in proteomes has recently showed that the α/ß architecture is probably the oldest fold design. This holds important implications for the origins of biochemistry. Here we explore structure-function relationships addressing the use of chemical mechanisms by ancestral enzymes. We test the hypothesis that the oldest folds used the most mechanisms. We start by tracing biocatalytic mechanisms operating in metabolic enzymes along a phylogenetic timeline of the first appearance of homologous superfamilies of protein domain structures from CATH. A total of 335 enzyme reactions were retrieved from MACiE and were mapped over fold age. We define a mechanistic step type as one of the 51 mechanistic annotations given in MACiE, and each step of each of the 335 mechanisms was described using one or more of these annotations. We find that the first two folds, the P-loop containing nucleotide triphosphate hydrolase and the NAD(P)-binding Rossmann-like homologous superfamilies, were α/ß architectures responsible for introducing 35% (18/51) of the known mechanistic step types. We find that these two oldest structures in the phylogenomic analysis of protein domains introduced many mechanistic step types that were later combinatorially spread in catalytic history. The most common mechanistic step types included fundamental building blocks of enzyme chemistry: "Proton transfer," "Bimolecular nucleophilic addition," "Bimolecular nucleophilic substitution," and "Unimolecular elimination by the conjugate base." They were associated with the most ancestral fold structure typical of P-loop containing nucleotide triphosphate hydrolases. Over half of the mechanistic step types were introduced in the evolutionary timeline before the appearance of structures specific to diversified organisms, during a period of architectural diversification. The other half unfolded gradually after organismal diversification and during a period that spanned ∼2 billion years of evolutionary history.