On the reproducibility of enzyme reactions and kinetic modelling.

Enzyme reactions are highly dependent on reaction conditions. To ensure reproducibility of enzyme reaction parameters, experiments need to be carefully designed and kinetic modeling meticulously executed. Furthermore, to enable quality control of enzyme reaction parameters, the experimental conditions, the modeling process as well as the raw data need to be reported comprehensively. By taking these steps, enzyme reaction parameters can be open and FAIR (findable, accessible, interoperable, re-usable) as well as repeatable, replicable and reproducible. This review discusses these requirements and provides a practical guide to designing initial rate experiments for the determination of enzyme reaction parameters and gives an open, FAIR and re-editable example of the kinetic modeling of an enzyme reaction. Both the guide and example are scripted with Python in Jupyter Notebooks and are publicly available (https://fairdomhub.org/investigations/483/snapshots/1). Finally, the prerequisites of automated data analysis and machine learning algorithms are briefly discussed to provide further motivation for the comprehensive, open and FAIR reporting of enzyme reaction parameters.

Real-Time NMR Monitoring of Spatially Segregated Enzymatic Reactions in Multilayered Hydrogel Assemblies*.

Compartmentalized chemical reactions at the microscale are important in biotechnology, yet monitoring the molecular content at these small scales is challenging. To address this challenge, we integrate a compact, reconfigurable reaction cell featuring electrochemical functionality with high-resolution NMR spectroscopy. We demonstrate the operation of this system by monitoring the activity of enzymes immobilized in chemically distinct layers within a multi-layered chitosan hydrogel assembly. As a benchmark, we observed the parallel activities of urease (Urs), catalase (Cat), and glucose oxidase (GOx) by monitoring reagent and product concentrations in real-time. Simultaneous monitoring of an independent enzymatic process (Urs) together with a cooperative process (GOx + Cat) was achieved, with chemical conversion modulation of the GOx + Cat process demonstrated by varying the order in which the hydrogel was assembled.

Simulation Foundry: Automated and F.A.I.R. Molecular Modeling.

The Simulation Foundry (SF) is a modular workflow for the automated creation of molecular modeling (MM) data. MM allows for the reliable prediction of the microscopic and macroscopic properties of multicomponent systems from first principles. The SF makes MM repeatable, replicable, and findable, accessible, interoperable, and reusable (F.A.I.R.). The SF uses a standardized data structure and file naming convention, allowing for replication on different supercomputers and re-entrancy. We focus on keeping the SF simple by basing it on scripting languages that are widely used by the MM community (bash, Python) and making it reusable and re-editable. The SF was developed to assist expert users in performing parameter studies of multicomponent systems by high throughput molecular dynamics simulations. The usability of the SF is demonstrated by simulations of thermophysical properties of binary mixtures. A standardized data exchange format enables the integration of simulated data with data from experiments. The SF also provides a complete documentation of how the results were obtained, thus assigning provenance. Increasing computational power facilitates the intensification of the simulation process and requires automation and modularity. The SF provides a community platform on which to integrate new methods and create data that is reproducible and transparent (https://fairdomhub.org/studies/639/snapshots/1, https://fairdomhub.org/studies/639/snapshots/2).

Two tyrosine residues, Tyr-108 and Tyr-503, are responsible for the deprotonation of phenolic substrates in vanillyl-alcohol oxidase.

A number of oxidoreductases from the VAO/para-cresol methylhydroxylase flavoprotein family catalyze the oxidation of para-substituted phenols. One of the best-studied is vanillyl-alcohol oxidase (VAO) from the fungus Penicillium simplicissimum For oxidation of phenols by VAO to occur, they must first be bound in the active site of the enzyme in their phenolate anion form. The crystal structure of VAO reveals that two tyrosine residues, Tyr-108 and Tyr-503, are positioned to facilitate this deprotonation. To investigate their role in catalysis, we created three VAO variants, Y108F, Y503F, and Y108F/Y503F, and studied their biochemical properties. Steady-state kinetics indicated that the presence of at least one of the tyrosine residues is essential for efficient catalysis by VAO. Stopped-flow kinetics revealed that the reduction of VAO by chavicol or vanillyl alcohol occurs at two different rates: kobs1, which corresponds to its reaction with the deprotonated form of the substrate, and kobs2, which corresponds to its reaction with the protonated form of the substrate. In Y108F, Y503F, and Y108F/Y503F, the relative contribution of kobs2 to the reduction is larger than in wild-type VAO, suggesting deprotonation is impaired in these variants. Binding studies disclosed that the competitive inhibitor isoeugenol is predominantly in its deprotonated form when bound to wild-type VAO, but predominantly in its protonated form when bound to the variants. These results indicate that Tyr-108 and Tyr-503 are responsible for the activation of substrates in VAO, providing new insights into the catalytic mechanism of VAO and related enzymes that oxidize para-substituted phenols.

On the origin of vanillyl alcohol oxidases.

Vanillyl alcohol oxidase (VAO) is a fungal flavoenzyme that converts a wide range of para-substituted phenols. The products of these conversions, e.g. vanillin, coniferyl alcohol and chiral aryl alcohols, are of interest for several industries. VAO is the only known fungal member of the 4-phenol oxidising (4PO) subgroup of the VAO/PCMH flavoprotein family. While the enzyme has been biochemically characterised in great detail, little is known about its physiological role and distribution in fungi. We have identified and analysed novel, fungal candidate VAOs and found them to be mostly present in Pezizomycotina and Agaricomycotina. The VAOs group into three clades, of which two clades do not have any characterised member. Interestingly, bacterial relatives of VAO do not form a single outgroup, but rather split up into two separate clades. We have analysed the distribution of candidate VAOs in fungi, as well as their genomic environment. VAOs are present in low frequency in species of varying degrees of relatedness and in regions of low synteny. These findings suggest that fungal VAOs may have originated from bacterial ancestors, obtained by fungi through horizontal gene transfer. Because the overall conservation of fungal VAOs varies between 60 and 30% sequence identity, we argue for a more reliable functional prediction using critical amino acid residues. We have defined a sequence motif P-x-x-x-x-S-x-G-[RK]-N-x-G-Y-G-[GS] that specifically recognizes 4PO enzymes of the VAO/PCMH family, as well as additional motifs that can help to further narrow down putative functions. We also provide an overview of fingerprint residues that are specific to VAOs.

The ins and outs of vanillyl alcohol oxidase: Identification of ligand migration paths.

Vanillyl alcohol oxidase (VAO) is a homo-octameric flavoenzyme belonging to the VAO/PCMH family. Each VAO subunit consists of two domains, the FAD-binding and the cap domain. VAO catalyses, among other reactions, the two-step conversion of p-creosol (2-methoxy-4-methylphenol) to vanillin (4-hydroxy-3-methoxybenzaldehyde). To elucidate how different ligands enter and exit the secluded active site, Monte Carlo based simulations have been performed. One entry/exit path via the subunit interface and two additional exit paths have been identified for phenolic ligands, all leading to the si side of FAD. We argue that the entry/exit path is the most probable route for these ligands. A fourth path leading to the re side of FAD has been found for the co-ligands dioxygen and hydrogen peroxide. Based on binding energies and on the behaviour of ligands in these four paths, we propose a sequence of events for ligand and co-ligand migration during catalysis. We have also identified two residues, His466 and Tyr503, which could act as concierges of the active site for phenolic ligands, as well as two other residues, Tyr51 and Tyr408, which could act as a gateway to the re side of FAD for dioxygen. Most of the residues in the four paths are also present in VAO's closest relatives, eugenol oxidase and p-cresol methylhydroxylase. Key path residues show movements in our simulations that correspond well to conformations observed in crystal structures of these enzymes. Preservation of other path residues can be linked to the electron acceptor specificity and oligomerisation state of the three enzymes. This study is the first comprehensive overview of ligand and co-ligand migration in a member of the VAO/PCMH family, and provides a proof of concept for the use of an unbiased method to sample this process.

Meta-analysis of viscosity of aqueous deep eutectic solvents and their components.

Deep eutectic solvents (DES) formed by quaternary ammonium salts and hydrogen bond donors are a promising green alternative to organic solvents. Their high viscosity at ambient temperatures can limit biocatalytic applications and therefore requires fine-tuning by adjusting water content and temperature. Here, we performed a meta-analysis of the impact of water content and temperature on the viscosities of four deep eutectic solvents (glyceline, reline, N,N-diethylethanol ammonium chloride-glycerol, N,N-diethylethanol ammonium chloride-ethylene glycol), their components (choline chloride, urea, glycerol, ethylene glycol), methanol, and pure water. We analyzed the viscosity data by an automated workflow, using Arrhenius and Vogel-Fulcher-Tammann-Hesse models. The consistency and completeness of experimental data and metadata was used as an essential criterion of data quality. We found that viscosities were reported for different temperature ranges, half the time without specifying a method of desiccation, and in almost half of the reports without specifying experimental errors. We found that the viscosity of the pure components varied widely, but that all aqueous mixtures (except for reline) have similar excess activation energy of viscous flow [Formula: see text]= 3-5 kJ/mol, whereas reline had a negative excess activation energy ([Formula: see text]= - 19 kJ/mol). The data and workflows used are accessible at  https://doi.org/10.15490/FAIRDOMHUB.1.STUDY.767.1 .

Vanillyl alcohol oxidase.

This review presents a historical outline of the research on vanillyl alcohol oxidase (VAO) from Penicillium simplicissimum, one of the canonical members of the VAO/PCMH flavoprotein family. After describing its discovery and initial biochemical characterization, we discuss the physiological role, substrate scope, and catalytic mechanism of VAO, and review its three-dimensional structure and mechanism of covalent flavinylation. We also explain how protein engineering provided a deeper insight into the role of certain amino acid residues in determining the substrate specificity and enantioselectivity of the enzyme. Finally, we summarize recent computational studies about the migration of substrates and products through the enzyme's structure and the phylogenetic distribution of VAO and related enzymes.

A single loop is essential for the octamerization of vanillyl alcohol oxidase.

UNLABELLED: The VAO/PCMH family of flavoenzymes is a family of structurally related proteins that catalyse a wide range of oxidation reactions. It contains a subfamily of enzymes that catalyse the oxidation of para-substituted phenols using covalently bound FAD cofactors (the 4PO subfamily). This subfamily is composed of two oxidases, vanillyl alcohol oxidase (VAO) and eugenol oxidase (EUGO), and two flavocytochrome dehydrogenases, para-cresol methylhydroxylase (PCMH) and eugenol hydroxylase (EUGH). Although they catalyse similar reactions, these enzymes differ in terms of their electron acceptor preference and oligomerization state. For example, VAO forms homo-octamers that can be described as tetramers of stable dimers, whereas EUGO is exclusively dimeric in solution. A possible explanation for this difference is the presence of a loop at the dimer-dimer interface in VAO that is not present in EUGO. Here, the role played by this loop in determining the quaternary structure of these enzymes is investigated. A VAO variant where the loop was deleted, loopless VAO, exclusively formed dimers. However, introduction of the loop into EUGO was not sufficient to induce its octamerization. Neither variant displayed major changes in its catalytic properties as compared to the wild-type enzyme. Bioinformatic analysis revealed that the presence of the loop is conserved within putative fungal oxidases of the 4PO subgroup, but it is never found in putative bacterial oxidases or dehydrogenases. Our results shed light on the molecular mechanism of homo-oligomerization of VAO and the importance of oligomerization for its enzymatic function. ENZYMES: p-cresol methylhydroxylase (4-methylphenol:acceptor oxidoreductase (methyl-hydroxylating), EC 1.17.99.1); vanillyl alcohol oxidase (vanillyl alcohol:oxygen oxidoreductase, EC 1.1.3.38).

Differential modes of peptide binding onto replicative sliding clamps from various bacterial origins.

Bacterial sliding clamps are molecular hubs that interact with many proteins involved in DNA metabolism through their binding, via a conserved peptidic sequence, into a universally conserved pocket. This interacting pocket is acknowledged as a potential molecular target for the development of new antibiotics. We previously designed short peptides with an improved affinity for the Escherichia coli binding pocket. Here we show that these peptides differentially interact with other bacterial clamps, despite the fact that all pockets are structurally similar. Thermodynamic and modeling analyses of the interactions differentiate between two categories of clamps: group I clamps interact efficiently with our designed peptides and assemble the Escherichia coli and related orthologs clamps, whereas group II clamps poorly interact with the same peptides and include Bacillus subtilis and other Gram-positive clamps. These studies also suggest that the peptide binding process could occur via different mechanisms, which depend on the type of clamp.