The interdigitating loop of the enolase superfamily as a specificity binding determinant or 'flying buttress'

Constructing an artificial in vitro multi-enzyme cascade pathway to convert glycerol and CO2 into L-aspartic acid

Developing utilization technologies for biomass resources, exploring their applications in the fields of energy and chemical engineering, holds significant importance for promoting sustainable development and constructing a green, low-carbon society. In this study, we designed a non-natural in vitro multi-enzyme system for converting glycerol and CO2 into L-aspartic acid (L-Asp). The coupled system utilized eight enzymes, including alditol oxidase (ALDO), catalase-peroxidase (CAT), lactaldehyde dehydrogenase (ALDH), glycerate 2-kinase (GK), phosphopyruvate hydratase (PPH), phosphoenolpyruvate carboxylase (PPC), L-aspartate dehydrogenase (ASPD), and polyphosphate kinase (PPK), to convert the raw materials into L-Asp in one-pot coupled with NADH and ATP regeneration. Under optimal reaction conditions, 18.6 mM of L-Asp could be produced within 2.0 h at a total enzyme addition of 4.85 mg/mL, demonstrating the high efficiency and productivity characteristics of the designed system. Our technological application provides new insights and methods for the development of biomass resource utilization technologies.

Supramolecular Regulation of Catalytic Activity in Molecularly Responsive Catalysts

Some enzymes switch between an open form and a closed form. We report a molecularly tuned catalyst that accommodates a substrate and a signal molecule simultaneously. Binding of the signal molecule helps direct the reactive group of the substrate to the catalytic group and enhances the catalytic activity. Subtle structural changes in either the substrate or the signal molecule are readily detected. The switching mechanism also allows the catalytic reaction to be turned on and off reversibly by specific molecular signals.

The Birth of Genomic Enzymology: Discovery of the Mechanistically Diverse Enolase Superfamily

Enzymes are categorized into superfamilies by sequence, structural, and mechanistic similarities. The evolutionary implications can be profound. Until the mid-1990s, the approach was fragmented largely due to limited sequence and structural data. However, in 1996, Babbitt et al. published a paper in Biochemistry that demonstrated the potential power of mechanistically diverse superfamilies to identify common ancestry, predict function, and, in some cases, predict specificity. This Perspective describes the findings of the original work and reviews the current understanding of structure and mechanism in the founding family members. The outcomes of the genomic enzymology approach have reached far beyond the functional assignment of members of the enolase superfamily, inspiring the study of superfamilies and the adoption of sequence similarity networks and genome context and yielding fundamental insights into enzyme evolution.

Racemases and epimerases operating through a 1,1-proton transfer mechanism: reactivity, mechanism and inhibition

Racemases and epimerases catalyse changes in the stereochemical configurations of chiral centres and are of interest as model enzymes and as biotechnological tools. They also occupy pivotal positions within metabolic pathways and, hence, many of them are important drug targets. This review summarises the catalytic mechanisms of PLP-dependent, enolase family and cofactor-independent racemases and epimerases operating by a deprotonation/reprotonation (1,1-proton transfer) mechanism and methods for measuring their catalytic activity. Strategies for inhibiting these enzymes are reviewed, as are specific examples of inhibitors. Rational design of inhibitors based on substrates has been extensively explored but there is considerable scope for development of transition-state mimics and covalent inhibitors and for the identification of inhibitors by high-throughput, fragment and virtual screening approaches. The increasing availability of enzyme structures obtained using X-ray crystallography will facilitate development of inhibitors by rational design and fragment screening, whilst protein models will facilitate development of transition-state mimics.

Protein Flexibility and Stiffness Enable Efficient Enzymatic Catalysis

The enormous rate accelerations observed for many enzyme catalysts are due to strong stabilizing interactions between the protein and reaction transition state. The defining property of these catalysts is their specificity for binding the transition state with a much higher affinity than substrate. Experimental results are presented which show that the phosphodianion-binding energy of phosphate monoester substrates is used to drive conversion of their protein catalysts from flexible and entropically rich ground states to stiff and catalytically active Michaelis complexes. These results are generalized to other enzyme-catalyzed reactions. The existence of many enzymes in flexible, entropically rich, and inactive ground states provides a mechanism for utilization of ligand-binding energy to mold these catalysts into stiff and active forms. This reduces the substrate-binding energy expressed at the Michaelis complex, while enabling the full and specific expression of large transition-state binding energies. Evidence is presented that the complexity of enzyme conformational changes increases with increases in the enzymatic rate acceleration. The requirement that a large fraction of the total substrate-binding energy be utilized to drive conformational changes of floppy enzymes is proposed to favor the selection and evolution of protein folds with multiple flexible unstructured loops, such as the TIM-barrel fold. The effect of protein motions on the kinetic parameters for enzymes that undergo ligand-driven conformational changes is considered. The results of computational studies to model the complex ligand-driven conformational change in catalysis by triosephosphate isomerase are presented.

A platform for chemical modification of mandelate racemase: characterization of the C92S/C264S and γ-thialysine 166 variants

Mandelate racemase (MR) serves as a paradigm for our understanding of enzyme-catalyzed deprotonation of a carbon acid substrate. To facilitate structure-function studies on MR using non-natural amino acid substitutions, we engineered the Cys92Ser/Cys264Ser variant (dmMR) as a platform for introducing Cys residues at specific locations for subsequent covalent modification. While the highly reactive thiol of Cys furnishes a site for chemical modification, site-specificity requires that other Cys residues be non-reactive or replaced by a non-reactive amino acid, especially if chemical modification is conducted under denaturing conditions. The catalytic efficiency of dmMR is reduced only ~2-fold relative to wild-type MR, making dmMR a viable platform for the site-specific introduction of Cys. As an example, the inactive Lys166Cys variant of dmMR was treated with ethylenimine under denaturing conditions to replace the Brønsted acid-base catalyst Lys 166 with the non-natural amino acid γ-thialysine. Comparison of the pH-activity profiles of dmMR and the active γ-thialysine variant revealed a reduction in the pKa for the side chain amino group of ~0.4 units for the latter variant. Unlike wild-type MR for which diffusion is partially rate-limiting, dmMR and the γ-thialysine variant showed no dependence on the solvent viscosity suggesting that the chemical step is fully rate-limiting.

Identification of differentially regulated deceitful proteins in SH-SY5Y cells engineered with Tet-regulated protein expression system

Tetracycline regulated protein expression in mammalian cells is a powerful tool to predict the physiological function, cellular localization, and stability of a protein. In addition, to predict metabolic networks affected by the expression of wild-type or mutant forms of proteins, researchers generally produce a single mammalian cell clone that can express the protein of interest under tetracycline control and study the changes occurring in overall proteome before and after expression of a protein of interest. One limitation of tetracycline regulated clonal cell creation, however, is that it sometimes creates clones with changed protein levels even without the expression of the protein of interest due to the nonspecific insertion of the gene encoding the protein of interest into the genome or disruption of a metabolic pathway due to insertional silencing or activation. The aim of this study was to demonstrate the limitation of tetracycline regulated gene expression by creating clonal cell lines expressing the wild-type or the mutant forms of Fat mass and obesity-associated protein. Comparative proteome analysis of the protein extracts by two-dimensional gel electrophoresis coupled to MALDI-TOF/TOF revealed the presence of eight proteins subjected to differential regulation even in the absence of induction. The identified proteins were 14-3-3 protein Epsilon, Vimentin, Heterogeneous nuclear ribonucleoprotein K, Tubulin beta-2C chain, Heat shock protein HSP 90-alpha, Heat shock protein HSP 90-beta, Alpha-enolase, TATA-binding protein-associated factor 2N. An ultimate care should be taken to prevent reporting of deceitful proteins generated from studies utilizing tetracycline regulated gene expression systems.

Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence-Function Space and Genome Context to Discover Novel Functions

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of “genomic enzymology” web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence–function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems.

A Paradigm for CH Bond Cleavage: Structural and Functional Aspects of Transition State Stabilization by Mandelate Racemase

Mandelate racemase (MR) from Pseudomonas putida catalyzes the Mg²⁺-dependent, 1,1-proton transfer reaction that racemizes (R)- and (S)-mandelate. MR shares a partial reaction (i.e., the metal ion-assisted, Brønsted base-catalyzed proton abstraction of the α-proton of carboxylic acid substrates) and structural features ((β/α)₇β-barrel and N-terminal α + β capping domains) with a vast group of homologous, yet functionally diverse, enzymes in the enolase superfamily. Mechanistic and structural studies have developed this enzyme into a paradigm for understanding how enzymes such as those of the enolase superfamily overcome kinetic and thermodynamic barriers to catalyze the abstraction of an α-proton from a carbon acid substrate with a relatively high pK_a value. Structural studies on MR bound to intermediate/transition state analogues have delineated those structural features that MR uses to stabilize transition states and enhance reaction rates of proton abstraction. Kinetic, site-directed mutagenesis, and structural studies have also revealed that the phenyl ring of the substrate migrates through the hydrophobic cavity within the active site during catalysis and that the Brønsted acid-base catalysts (Lys 166 and His 297) may be utilized as binding determinants for inhibitor recognition. In addition, structural studies on the adduct formed from the irreversible inhibition of MR by 3-hydroxypyruvate revealed that MR can form and deprotonate a Schiff-base with 3-hydroxypyruvate to yield an enol(ate)-aldehyde adduct, suggesting a possible evolutionary link between MR and the Schiff-base forming aldolases. As the archetype of the enolase superfamily, mechanistic and structural studies on MR will continue to enhance our understanding of enzyme catalysis and furnish insights into the evolution of enzyme function.

AGeNNT: annotation of enzyme families by means of refined neighborhood networks

BACKGROUND

Large enzyme families may contain functionally diverse members that give rise to clusters in a sequence similarity network (SSN). In prokaryotes, the genome neighborhood of a gene-product is indicative of its function and thus, a genome neighborhood network (GNN) deduced for an SSN provides strong clues to the specific function of enzymes constituting the different clusters. The Enzyme Function Initiative ( http://enzymefunction.org/ ) offers services that compute SSNs and GNNs.

RESULTS

We have implemented AGeNNT that utilizes these services, albeit with datasets purged with respect to unspecific protein functions and overrepresented species. AGeNNT generates refined GNNs (rGNNs) that consist of cluster-nodes representing the sequences under study and Pfam-nodes representing enzyme functions encoded in the respective neighborhoods. For cluster-nodes, AGeNNT summarizes the phylogenetic relationships of the contributing species and a statistic indicates how unique nodes and GNs are within this rGNN. Pfam-nodes are annotated with additional features like GO terms describing protein function. For edges, the coverage is given, which is the relative number of neighborhoods containing the considered enzyme function (Pfam-node). AGeNNT is available at https://github.com/kandlinf/agennt .

CONCLUSIONS

An rGNN is easier to interpret than a conventional GNN, which commonly contains proteins without enzymatic function and overly specific neighborhoods due to phylogenetic bias. The implemented filter routines and the statistic allow the user to identify those neighborhoods that are most indicative of a specific metabolic capacity. Thus, AGeNNT facilitates to distinguish and annotate functionally different members of enzyme families.