Biocatalysis needs improved reproducibility and quality of research reporting. Our interdisciplinary team has developed a flexible and extensible metadata catalogue based on STRENDA guidelines, essential for describing complex experimental setups in biocatalysis. The catalogue is available online via GitHub for community use.

The measurement of values of apparent equilibrium constants K′ for enzyme-catalyzed reactions involve a substantial number of critical details, neglect of which could lead to systematic errors. Here, interferences, impurities in the substances used, and failure to achieve equilibrium are matters of substantial consequence. Careful reporting of results is of great importance if the results are to have archival value. Thus, attention must be paid to the identification of the substances, specification of the reaction(s), the conditions of reaction, the definition of the equilibrium constant(s) and standard states, the use of standard nomenclature, symbols, and units, and uncertainties. This document contains a general discussion of various aspects of these equilibrium measurements as well as STRENDA (Standards for Reporting Enzymology Data) recommendations regarding the measurements and the reporting of results.

Biochemistry and Molecular Biology EducationVolume 50, Issue 4 p. 352-353 EDITORIAL Teaching enzyme kinetics – Time to abandon starting with the quasi-steady state approximation? Peter J. Halling, Corresponding Author Peter J. Halling p.j.halling@strath.ac.uk orcid.org/0000-0001-5077-4088 WestCHEM, Dept P & A Chemistry, University of Strathclyde, Glasgow, UK Correspondence Peter J. Halling, WestCHEM, Dept P & A Chemistry, University of Strathclyde, Glasgow G1 1XL, UK. Email: p.j.halling@strath.ac.ukSearch for more papers by this author Peter J. Halling, Corresponding Author Peter J. Halling p.j.halling@strath.ac.uk orcid.org/0000-0001-5077-4088 WestCHEM, Dept P & A Chemistry, University of Strathclyde, Glasgow, UK Correspondence Peter J. Halling, WestCHEM, Dept P & A Chemistry, University of Strathclyde, Glasgow G1 1XL, UK. Email: p.j.halling@strath.ac.ukSearch for more papers by this author First published: 21 June 2022 https://doi.org/10.1002/bmb.21639Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume50, Issue4July/August 2022Pages 352-353 RelatedInformation

The kinetics of enzymatic desymmetrisation were analysed for the most common kinetic mechanisms: ternary complex ordered (prochiral ketone reduction); ping-pong second (ketone amination, diol esterification, desymmetrisation in the second half reaction); ping-pong first (diol ester hydrolysis) and ping-pong both (prochiral diacids). For plausible values of enzyme kinetic parameters, the product enantiomeric excess (ee) can decline substantially as the reaction proceeds to high conversion. For example, an ee of 0.95 at the start of the reaction can decline to less than 0.5 at 95% of equilibrium conversion, but for different enzyme properties it will remain almost unchanged. For most mechanisms a single function of multiple enzyme rate constants (which can be termed ee decline parameter, eeDP) accounts for the major effect on the tendency for the ee to decline. For some mechanisms, the concentrations or ratios of the starting materials have an important influence on the fall in ee. For the application of enzymatic desymmetrisation it is important to study if and how the product ee declines at high conversion.

The eQuilibrator component contribution method allows calculation of the overall Gibbs energy changes for conversion of glucose to a wide range of final products in the absence of other oxidants. Values are presented for all possible combinations of products with up to three carbons and selected others. The most negative Gibbs energy change is for the formation of graphite and water (-499 kJ mol-1) followed by CH4 and CO2 (-430 kJ mol-1), the observed final products of anaerobic digestion. Other favored products (with various combinations having Gibbs energy changes between -300 and -367 kJ mol-1) are short-chain alkanes, fatty acids, dicarboxylic acids, and even hexane and benzene. The most familiar products, lactate and ethanol + CO2, are less favored (Gibbs energy changes of -206 and -265 kJ mol-1 respectively). The values presented offer an interesting perspective on observed metabolism and its evolutionary origins as well as on cells engineered for biotechnological purposes.

When using discontinuous assay of reactions, initial rates are often estimated from a limited number of time points. There has been no detailed study of how best to do this. In this work, time courses were simulated by different theoretical equations (including strong product inhibition, first order, Michaelis-Menten and truly linear), but with random error addition to each data point. Various methods were tested to fit an initial rate to the data, and the result compared with the known "true" value. Fitting a simple quadratic generally gives initial rates as accurate as any other curve, and is better than a linear fit if there are about 8 or more time points. For fewer points a linear fit gives less variable and often more accurate rates. The absolute contribution to data point error has a major impact on rate accuracy, and often dominates that due to curvature, so that sampling to at least 10% conversion is preferred. The accuracy of a linear fit can be improved by methods that reject some later points based on curvature tests. Awareness of these effects can help avoid rate inaccuracies of 10% or more due to poor methods of data analysis.

Cassava peels provide a cheap non-food biomass waste that can be hydrolyzed to simple sugars as a useful feedstock. Unlike most crop wastes, they have high starch content as well as lignocellulose. In this study, an enzymatic treatment of cassava peels by various concentrations of amylase and glucoamylase is considered. Steam explosion pre-treatments reduced rate and yield of hydrolysis. Milled peels suspended at 10% w/v yielded a maximum reducing sugar of 0.41 g (as glucose) per gram of peels. HPLC analysis showed that levels of soluble oligosaccharides remained low throughout. A pretreatment with amylase at 95 degrees C slightly increased rates although final yield was the same. Additional treatment with cellulolytic enzymes increases the total hydrolysis yield to 0.61 g (as glucose) per gram of peels representing 91% of the carbohydrate in cassava peels.

Proteins represent complex biomolecules capable of wide-ranging but also highly specific functionalities. Their immobilization on material supports can enable broad applications from sensing and industrial biocatalysis to biomedical interfaces and materials. We demonstrate the advantages of using aqueous-processed cross-linked polyphenol coatings for immobilizing proteins, including IgG, avidin, and various single and multidomain enzymes on diverse materials, to enable active biofunctional structures (e.g., ca. 2.2, 1.7, 1.1, and 4.8 mg·m-2 active phosphatase on nanoporous cellulose and alumina, steel mesh, and polyester fabric, respectively). Enzyme assays, X-ray photoelectron spectroscopy, silver staining, supplemented with contact angle, solid-state 13C NMR, HPLC, and ESI-MS measurements were used to characterize the polyphenols, coatings, and protein layers. We show that the functionalization process may be advantageously optimized directly for protein activity rather than the traditional focus on the thickness of the coating layer. Higher activities (by more than an order of magnitude in some cases) and wider process pH and material compatibility are demonstrated with polyphenol coatings than other approaches such as polydopamine. Coatings formed from different plant polyphenol extracts, even at lowered purity (and cost), were also found to be highly functional. Chemically, our results indicate that polyphenol coatings differ from polydopamine mainly because of the elimination of amine groups, and that polyphenol layers with intermediate levels of reactivity may better lead to high immobilized protein activity. Overall, an improved understanding of simple-to-use polyphenol coatings has been obtained, which enabled a significant development in active protein surfaces that may be applied across diverse materials and nanostructured supports.

The optimal experimental design (OED) for observation strategy is investigated in this paper to collect the most informative experimental data for parameter estimation. The aim is to determine the best sampling time points and also select the most valuable measurement state variables through OED. The two design objectives are integrated together as a single-objective optimisation problem in which the variables and their sampling times are weighted in an expanded time sampling framework. Three optimisation methods, i.e., the Powell's method, the sequential selection method, and the sequential quadratic programming method, are employed to solve the optimisation problem. Their computation efficiencies are compared using a biodiesel case study system simulation. Simulation results demonstrate the effectiveness of the proposed method in reducing parameter estimation uncertainties as well as reducing parameter correlations. It can also be observed that the integrated OED doesn't cost extra computation efforts when variable selection is considered together with the time sampling task.

Nuclear magnetic resonance (NMR) is a powerful tool for investigating atomic-scale structure in heterogeneous or composite materials where long-range order is absent. In this work solid-state 1H and 1H-detected NMR experiments were performed with fast magic angle spinning (νR = 75 kHz) and at high magnetic fields (B0 = 20 T) and used to gain structural insight into a heterogeneous biocatalyst consisting of an enzyme, human carbonic anhydrase II (hCA II), covalently immobilized on epoxy-functionalized silica. Two-dimensional 1H-1H NOESY-type correlation experiments were able to provide information on 1H environments in silica, epoxy-silica and the immobilized enzyme. Two distinct signals originating from water protons were observed: water associated with the surface of the silica and the water associated with the immobilized enzyme. Additional two-dimensional 1H-1H double-single quantum (DQ-SQ) correlation experiments suggested that the immobilized enzyme is not in close contact with the silica surface. Most significantly, comparison of two-dimensional 1H-15N spectra of the immobilized enzyme and the solution-state enzyme confirmed that the structural integrity of the protein is well preserved upon covalent immobilization.

A key component of enzyme function experiments is reporting of considerable metadata, to allow other researchers to replicate, interpret properly or use fully the results. This paper evaluates the completeness of enzyme function data reporting for reproducibility. We present a detailed examination of 11 recent papers (and their supplementary material) from two leading journals. We found that in every paper we were not able to collect some critical information necessary to reproduce the enzyme function findings. Study of 100 papers used by the SABIO-RK database confirmed some of the most common omissions: concentration of enzyme or its substrates, identity of counter-ions in buffers. A computer system should be better at preventing such omissions, helping secure the scientific record. Many of the omissions found would be trapped by the currently available version of STRENDA DB.

A systematic framework for optimal experimental design (OED) of multiple experimental factors is proposed to support data collection in chemical engineering systems with the purpose to obtain the most informative data for modeling. The structural identifiability is firstly investigated through a combined procedure with the generating series method and the identifiability tableau. Next the parameter estimability is analyzed via the orthogonalized sensitivity analysis in order to identify crucial and identifiable model parameters. Traditionally OED treats separate problems such as the choice of input conditions, the selection of variables to measure, and the design of sampling time profile. A new OED strategy is proposed that optimizes these interdependent factors in one framework. An iterative two-layer design structure is developed. In the lower layer for observation design, the sampling profile and the measurement set selection are combined and formulated as a single integrated observation design problem, which is relaxed to a convex optimization problem that can be solved with a local method. Thus the measurement set selection and the sampling profile can be determined simultaneously. In the upper layer for input design, the optimization of input intensities is obtained through stochastic global searching. In this way, the multi-factor optimization problem is solved through the integration of a stochastic method, for the upper layer, and a deterministic method, for the lower layer. Case studies are conducted on two biochemical systems with different complexities, one is an enzyme kinetically controlled synthesis system and the other one is a lab-scale enzymatic biodiesel production system. Numerical results demonstrate the effectiveness of this iterative double-layer OED optimization strategy in reducing parameter estimation uncertainties compared with conventional approaches.

Standards for reporting enzymology data (STRENDA) DB is a validation and storage system for enzyme function data that incorporates the STRENDA Guidelines. It provides authors who are preparing a manuscript with a user-friendly, web-based service that checks automatically enzymology data sets entered in the submission form that they are complete and valid before they are submitted as part of a publication to a journal.

Sugar fatty acid esters (SFAEs) are biocompatible nonionic surfactants with broad applications in food, cosmetic, and pharmaceutical industries. They can be synthesized enzymatically with many advantages over their chemical synthesis. In this study, SFAE synthesis was investigated by using two reactions: (1) transesterification of glucose with fatty acid vinyl esters and (2) esterification of methyl glucoside with fatty acids, catalyzed by Lipozyme TLIM and Novozym 435 respectively. Fourteen ionic liquids (ILs) and 14 deep eutectic solvents (DESs) were screened as solvents, and the bisolvent system composed of 1-hexyl-3-methylimidazolium trifluoromethylsulfonate ([HMIm][TfO]) and 2-methyl-2-butanol (2M2B) was the best for both reactions, yielding optimal productivities (769.6 and 397.5 µmol/h/g, respectively) which are superior to those reported in the literature. Impacts of different reaction conditions were studied for both reactions. Response surface methodology (RSM) was employed to optimize the transesterification reaction. Results also demonstrated that as co-substrate, methyl glucoside yielded higher conversions than glucose, and that conversions increased with an increase in the chain length of the fatty acid moieties. DESs were poor solvents for the above reactions presumably due to their high viscosity and high polarity.

We construct a fluid-dynamical model for the flow of a solution with a free surface at which surface tension acts. This model can describe both classical surfactants, which decrease the surface tension of the solution relative to that of the pure solvent, and antisurfactants (such as many salts when added to water, and small amounts of water when added to alcohol) which increase it. We demonstrate the utility of the model by considering the linear stability of an infinitely deep layer of initially quiescent fluid. In particular, we predict the occurrence of an instability driven by surface-tension gradients, which occurs for antisurfactant, but not for surfactant, solutions.

As nonionic surfactants derived from naturally renewable resources such as sugars and fatty acids, sugar fatty acid esters have been widely utilized in food, cosmetic and pharmaceutical industries. Our present study has demonstrated that the inexpensive and halogen-free tetraalkylammonium salts (e.g., [Bu4N][Ac], [Et4N][Ac] and [Me4N][Ac]) can act as dual solvents–catalysts for regioselective acylation to produce glucose laurate. This non-enzymatic synthesis can proceed under mild conditions with high specificity, and the conversions obtained were superior to that when an enzyme catalyst (lipase, EC 3.1.1.3) was added. A higher yield was obtained in the ammonium salt with a longer alkyl chain on the cation, while no product was obtained in [Bu4N][HSO4] and [Bu4P][Ac]. A reaction mechanism has been proposed, which is supported by phase-transfer catalysis and law of matching water affinity.

A new strategy of optimal experimental design (OED) is proposed for a kinetically controlled synthesis system by considering both the observation design and the input design. The observation design that combines sampling scheduling and measurement set selection is treated as a single optimization problem arranged in the inner loop, while the optimization of the input intensities is conducted in the outer loop. This multi-objective dynamic optimization problem is solved via the integration of the particle swarm algorithm (for the outer loop) and the interior-point method (for the inner loop). Numerical studies demonstrate the efficiency of this optimization strategy and show the effectiveness of this integrated OED in reducing parameter estimation uncertainties. In addition, process optimization of the case study enzyme reaction system is investigated with the aim to obtain the maximum production rate by taking into account of the experimental cost.

Low molecular weight gelators are able to form nanostructures, typically fibers, which entangle to form gel-phase materials. These materials have wide-ranging applications in biomedicine and nanotechnology. While it is known that supramolecular gels often represent metastable structures due to the restricted molecular dynamics in the gel state, the thermodynamic nature of the nanofibrous structure is not well understood. Clearly, 3D extended structures will be able to form more interactions than 1D structures. However, self-assembling molecules are typically amphiphilic, thus giving rise to a combination of solvophobic and solvophilic moieties where a level of solvent exposure at the nanostructure surface is favorable. In this study, we introduce a simple packing model, based on prisms with faces of different nature (solvophobic and solvophilic) and variable interaction parameters, to represent amphiphile self-assembly. This model demonstrates that by tuning shape and "self" or "solvent" interaction parameters either the 1D fiber or 3D crystal may represent the thermodynamic minimum. The model depends on parameters that relate to features of experimentally known systems: the number of faces exposed to the solvent or buried in the fiber; the overall shape of the prism; and the free energy penalties associated with the interactions can be adjusted to match their chemical nature. The model is applied to describe the pH-dependent gelation/precipitation of well-known gelator Fmoc-FF. We conclude that, despite the fact that most experimentally produced gels probably represent metastable states, one-dimensional fibers can represent thermodynamic equilibrium. This conclusion has critical implications for the theoretical treatment of gels.