Kinetics Of Enzymatic Reaction Research Articles

Charge‐Mediated Interactions Affect Enzymatic Reactions in Peptide Condensates

AbstractBiomolecular condensates, formed through liquid‐liquid phase separation (LLPS), serve as enzymatic reaction centers in cells by increasing local concentrations of enzymes and substrates, thereby facilitating reaction kinetics and regulatory mechanisms. Inspired by these natural systems, synthetic condensates are being developed for diverse applications, including payload delivery, sensing, and as microreactors where enzymatic reaction kinetics can be modulated by factors like pH, viscosity, and enzyme‐substrate co‐localization. Here, we investigate how the physicochemical properties of enzymes and substrates influence condensate formation and function as microreactors. Focusing on cellulase and alkaline phosphatase, which differ in molecular weight and isoelectric point, we employed a minimalistic complex coacervation system of oppositely charged LLPS‐promoting peptides. Our findings show how electrostatic forces within condensates influence their role as microreactors. Specifically, the ability of condensates to encapsulate or exclude phosphatase, cellulase, and their substrates, which is pivotal for the regulation of reaction kinetics, is determined by the enzyme surface charge, substrate charge, and condensate charge stoichiometry. These results highlight the potential of utilizing electrostatic forces within condensates to modulate enzymatic reactions, providing critical insights for developing synthetic condensates as microreactors in biotechnology and materials science.

Hydromechanical Modulation of Enzymatic Kinetics Using Microfluidically Configurable Nanoconfinement Arrays.

Confinement of molecules occurs ubiquitously in nature and fundamentally affects their properties and reactions. Developing synthetic confinement systems capable of precise modulation of chemical reactions is critical to understanding the underlying mechanisms and to promoting numerous applications including biosensing. However, current nanoconfinement systems often require sophisticated fabrication and operation. Here we report a simplified nanoconfinement approach termed Configurable Hydromechanical Enzyme Modulation by Nanoconfinement Landscaping of Chemical Kinetics (CHEMNLOCK). This approach exploits a simple micropost device to generate an array of nanogaps with tunable geometries, enabling flexible spatial modulation of the kinetics of surface-bound enzymatic reactions and substantial enhancement of single-molecule reactions. We envision that the CHEMNLOCK concept could pave a new way for developing scalable and practical nanoconfinement systems with profound impacts on biosensing and clinical diagnostics.

Beyond conventional models: integer and fractional order analysis of nonlinear Michaelis-Menten kinetics in immobilised enzyme reactors

PurposeThis study explores the immobilisation of enzymes within porous catalysts of various geometries, including spheres, cylinders and flat pellets. The objective is to understand the irreversible Michaelis-Menten kinetic process within immobilised enzymes through advanced mathematical modelling.Design/methodology/approachMathematical models were developed based on reaction-diffusion equations incorporating nonlinear variables associated with Michaelis-Menten kinetics. This research introduces fractional derivatives to investigate enzyme reaction kinetics, addressing a significant gap in the existing literature. A novel approximation method, based on the independent polynomials of the complete bipartite graph, is employed to explore solutions for substrate concentration and effectiveness factor across a spectrum of parameter values. The analytical solutions generated through the bipartite polynomial approximation method (BPAM) are rigorously tested against established methods, including the Bernoulli wavelet method (BWM), Taylor series method (TSM), Adomian decomposition method (ADM) and fourth-order Runge-Kutta method (RKM).FindingsThe study identifies two main findings. Firstly, the behaviour of dimensionless substrate concentration with distance is analysed for planar, cylindrical and spherical catalysts using both integer and fractional order Michaelis-Menten modelling. Secondly, the research investigates the variability of the dimensionless effectiveness factor with the Thiele modulus.Research limitations/implicationsThe study primarily focuses on mathematical modelling and theoretical analysis, with limited experimental validation. Future research should involve more extensive experimental verification to corroborate the findings. Additionally, the study assumes ideal conditions and uniform catalyst properties, which may not fully reflect real-world complexities. Incorporating factors such as mass transfer limitations, non-uniform catalyst structures and enzyme deactivation kinetics could enhance the model’s accuracy and broaden its applicability. Furthermore, extending the analysis to include multi-enzyme systems and complex reaction networks would provide a more comprehensive understanding of biocatalytic processes.Practical implicationsThe validated bipartite polynomial approximation method presents a practical tool for optimizing enzyme reactor design and operation in industrial settings. By accurately predicting substrate concentration and effectiveness factor, this approach enables efficient utilization of immobilised enzymes within porous catalysts. Implementation of these findings can lead to enhanced process efficiency, reduced operating costs and improved product yields in various biocatalytic applications such as pharmaceuticals, food processing and biofuel production. Additionally, this research fosters innovation in enzyme immobilisation techniques, offering practical insights for engineers and researchers striving to develop sustainable and economically viable bioprocesses.Social implicationsThe advancement of enzyme immobilisation techniques holds promise for addressing societal challenges such as sustainable production, environmental protection and healthcare. By enabling more efficient biocatalytic processes, this research contributes to reducing industrial waste, minimizing energy consumption and enhancing access to pharmaceuticals and bio-based products. Moreover, the development of eco-friendly manufacturing practices through biocatalysis aligns with global efforts towards sustainability and mitigating climate change. The widespread adoption of these technologies can foster a more environmentally conscious society while stimulating economic growth and innovation in biotechnology and related industries.Originality/valueThis study offers a pioneering approximation method using the independent polynomials of the complete bipartite graph to investigate enzyme reaction kinetics. The comprehensive validation of this method through comparison with established solution techniques ensures its reliability and accuracy. The findings hold promise for advancing the field of biocatalysts and provide valuable insights for designing efficient enzyme reactors.

Improving dairy manure hydrolysis and acidification through microbial community restructuring by adaptation to hyperthermophilic conditions

Dairy manure (DM) contributes significantly to greenhouse gas emissions and ecosystem degradation, yet its resistance to biodegradation hinders widespread bioprocessing applications. Lignocellulosic materials in DM pose a particular challenge because of their recalcitrance. Bioprocessing under hyperthermophilic (≥70 °C) conditions potentially offers an advantage over traditional fermentation temperatures due to enhanced activity of enzymes and the kinetics of enzymatic reactions. This can lead to a higher conversion rate and a greater extent of biomass hydrolysis and acidification. To test the validity of this hypothesis, the current study evaluated the efficacy of anaerobic hydrolysis and acidogenic fermentation of DM under mesophilic, thermophilic, and hyperthermophilic conditions. All inocula were adapted to corresponding temperatures but were derived from the same mesophilic source. Hyperthermophilic conditions resulted in superior DM hydrolysis efficiency (53%) compared to mesophilic (34%) and thermophilic (42%) conditions. The hyperthermophilic environment was particularly favorable to the decomposition of crude proteins and hemicellulose, which were reduced by 64% and 54%, respectively. Furthermore, hyperthermophilic fermentation also yielded the highest volatile fatty acid (VFA) production rate of 460 mg/L/day during the first four days, representing improvements of 50% and 90% over mesophilic and thermophilic conditions. In part, this was attributed to the enhanced production of branched-chain VFAs, including an increase of 6–10% in isobutyric acid and 12–13% in isovaleric acid. At hyperthermophilic conditions, however, there was no accumulation of VFAs during the days 5–8 of fermentation, which could be due to acetate conversion by the syntrophic acetate-oxidizing bacteria. A considerable gain in hydrolysis efficiency and VFA production rate were accompanied by a reduction in microbial diversity, which suggests that hyperthermophilic temperature is a favorable environment for the selection of organisms with enhanced DM hydrolysis and fermentation capabilities. A significantly increased relative abundance of xylanolytic Caldicoprobacter (23% of population) and proteolytic Thermovirga (9% of population) could be the major contributors to improved decomposition of hemicellulose and protein. As revealed by the techno-economic analysis, acidogenic fermentation of DM at 70 °C and a retention period of 4 days provides the greatest positive net present value, highest internal rate of return of 9.2%, and shortest investment payback period of 9 years. This study demonstrates that hyperthermophilic conditions enable superior deconstruction and bioconversion of lignocellulose-containing biomass into VFAs under reduced retention times, offering a promising approach for improving DM management and generating bioproducts.

MPEK: a multitask deep learning framework based on pretrained language models for enzymatic reaction kinetic parameters prediction.

Enzymatic reaction kinetics are central in analyzing enzymatic reaction mechanisms and target-enzyme optimization, and thus in biomanufacturing and other industries. The enzyme turnover number (kcat) and Michaelis constant (Km), key kinetic parameters for measuring enzyme catalytic efficiency, are crucial for analyzing enzymatic reaction mechanisms and the directed evolution of target enzymes. Experimental determination of kcat and Km is costly in terms of time, labor, and cost. To consider the intrinsic connection between kcat and Km and further improve the prediction performance, we propose a universal pretrained multitask deep learning model, MPEK, to predict these parameters simultaneously while considering pH, temperature, and organismal information. Through testing on the same kcat and Km test datasets, MPEK demonstrated superior prediction performance over the previous models. Specifically, MPEK achieved the Pearson coefficient of 0.808 for predicting kcat, improving ca. 14.6% and 7.6% compared to the DLKcat and UniKP models, and it achieved the Pearson coefficient of 0.777 for predicting Km, improving ca. 34.9% and 53.3% compared to the Kroll_model and UniKP models. More importantly, MPEK was able to reveal enzyme promiscuity and was sensitive to slight changes in the mutant enzyme sequence. In addition, in three case studies, it was shown that MPEK has the potential for assisted enzyme mining and directed evolution. To facilitate in silico evaluation of enzyme catalytic efficiency, we have established a web server implementing this model, which can be accessed at http://mathtc.nscc-tj.cn/mpek.

Rapid screening and isolation of potential xanthine oxidase inhibitors in Ganoderma lucidum

Given the abundance and intricate nature of the chemical components found in natural food ingredients, functional food research has long grappled with two significant technical challenges: rapid and precise screening of active substances and targeted preparation. To enhance the efficiency of fungal food preparation, novel methodologies for screening and the production of xanthine oxidase inhibitors from G. lucidum have been developed. The xanthine oxidase inhibitors were rapidly screened using AUF-LC-MS. Molecular docking and molecular dynamics simulation were used to verify the anti-gout activity of active compounds. Subsequently, with activity screening as the guide, HSCCC and SPLC were employed to separate the active ingredients. Simultaneously, the mechanism of action of xanthine oxidase inhibitors was analyzed by enzymatic reaction kinetics. Finally, the anti-gout activity of chemical components in G. lucidum was verified by network pharmacology, and its mechanism of action was discussed. Four potential xanthine oxidase inhibitors, namely ganoderic acid C2, B, A, and D2, were screened from G. lucidum. Their docking binding energies with xanthine oxidase were −6.29, −6.65, −4.29, and −5.96 kcal/mol, respectively. The purity of the four triterpenoid active ingredients isolated from G. lucidum was more than 90 %. These triterpenoid active ingredients showed a reversible inhibitory effect on xanthine oxidase. Network pharmacological studies revealed 71 common targets of active ingredients and gout, obtained by screening and intersecting the two targets, and identified the main metabolic pathways. The results indicate that G. lucidum extract can be employed for the prevention and treatment of gout disease. We enhance the efficiency and purity of active compounds preparation by incorporating enzyme inhibition assays and computerized virtual screening with compound chromatography. With this approach, we seamlessly incorporate fast discovery, screening, and focused preparation of active ingredients, as well as delving into the mechanisms of action of active monomers and proteases, and the molecular-level interactions between active ingredients and proteases. This study providing more opportunities to discover and develop new potential therapeutics from health food resources.

Monitoring Enzymatic Reaction Kinetics and Activity Assays in Confined Nanospace.

Enzyme-mediating biotransformations commonly occur in micro- and nanospace, which is crucial to maintain the essential biochemical processes and physiological functions in living systems. Probing enzyme-catalytic reactions in a biomimetic fashion remains challenging due to the lack of competent tools and methodology. Here, we show that studying enzymatic reaction kinetics can be readily achieved by a well-designed solid-state nanopore. Using tyrosine as a classical substrate, we quantitatively characterize the catalytic activity of tyrosinase (TYR) and tyrosine decarboxylase (TDC) in a nanoconfined space. Tyrosine was first immobilized in the nanopipette, wherein the active sites of tyrosine were left unoccupied. When successively exposed to TYR and TDC, a two-step cascade reaction can spontaneously take place. In this process, the surface wettability and charge of the nanopipette stemming from the catalytic products can sensitively regulate ion transport and ionic current rectification behavior, which were monitored by ionic current signal. In this biomimetic scenario, we obtained the enzymatic reaction kinetics of monophenyl oxidase that were not previously actualized in the conventional macroenvironment. Significantly, TYR showed higher enzyme activity, with a Km value of 1.59 mM, which was lower than that measured in a free and open space (with a Km of 3.01 mM). This suggests that tyrosine should be the most appropriate substrate of TYR, thus improving our understanding of tyrosine-associated biochemical reactions. This work offers an applicable technical platform to mimic enzyme-mediated biotransformations and biometabolisms.

Comprehensive profiling of acetylcholinesterase inhibitors from fried centipede using activity-oriented online preparation technology

Fried centipede, a popular food in southern China and Vietnam, is well known for its notable health benefits owing to its unique chemical composition. This study focused on acetylcholinesterase (AChE) inhibitor screening, bioactivity evaluation, and the extraction of bioactive compounds derived from fried centipedes. To determine the accuracy of in vitro AChE inhibitor screening, receptor-ligand affinity ultrafiltration and enzymatic reaction kinetics technologies were employed for the rapid screening and structural identification of bioactive compounds and to verify the enzyme inhibition activity and mechanism of the compounds. Moreover, molecular docking and dynamic simulations were utilized to assess the effectiveness of the target, and the integration of experimental and computational approaches facilitated a comprehensive analysis of the active compounds and their activities at four levels. To address the issues of low content and low extraction and separation efficiencies of bioactive compounds derived from centipedes, an activity-oriented complex preparation method (consecutive ultrasonic-assisted centrifugal extraction coupled online with UNIFAC countercurrent chromatography and semi-high-performance liquid chromatography (HPLC) was developed for efficient extraction, online concentration, and complex separation of the identified AChE ligands. As a result, six active compounds, including cytidine, guanine, uracil, hypoxanthine, xanthine, and β-thymidine demonstrated significant binding affinity to the AChE active sites within 3 h. This study provided valuable insights into the active compounds of fried centipedes and their potential anti-Alzheimer's disease properties. These findings contribute to the advancement of animal food preparation methodologies by combining cutting-edge extraction techniques, biological activity screening, and the development of AChE inhibitors from fried centipedes. Our method serves as a valuable reference for exploring and developing functional animal materials from diverse medicinal resources.

Unveiling a New Perspective on Cadmium-Induced Hormesis in Soil Enzyme Activity: The Relative Importance of Enzymatic Reaction Kinetics and Microbial Communities

Hormesis in soil enzymes is well-established, yet the underlying mechanism remains elusive. In this novel study, we investigated the effects of low-dose Cd exposure (0, 0.03, 0.3, 3, and 30 mg·kg−1) in farmland soil within a typical constructed wetland environment. We assessed the activities of four soil enzymes (urease (URE), denitrification enzyme (DEA), dehydrogenase (DHA), and alkaline phosphatase (ALP)) at varying exposure durations (0 h, 24 h, and 48 h), evaluating hormetic characteristics across these time intervals. Additionally, we determined kinetic parameters, specifically the Michaelis constant (Km) and maximum reaction velocity (Vmax), for these enzymes while examining potential alterations in microbial community structure. Our findings revealed hormesis in all four soil enzymes at 24 h of exposure, with varying stimulus width and maximum hormesis rates. Interestingly, heavy metals did not significantly influence the diversity of soil microbial communities, but they did inhibit the ability of soil microbial communities to secrete extracellular enzymes. This resulted in a reduction in the soil enzyme pool and a consequential shift in overall soil enzyme activities. The conclusion of this study is that low-dose Cd primarily reduced extracellular enzyme secretion by soil microorganisms, leading to a reduction in the size of the soil enzyme pool and thereby inducing hormesis in soil enzyme activities.

Kinetic View of Enzyme Catalysis from Enhanced Sampling QM/MM Simulations.

The rate constants of enzyme-catalyzed reactions (kcat) are often approximated from the barrier height of the reactive step. We introduce an enhanced sampling QM/MM approach that directly calculates the kinetics of enzymatic reactions, without introducing the transition-state theory assumptions, and takes into account the dynamical equilibrium between the reactive and non-reactive conformations of the enzyme/substrate complex. Our computed kcat values are in order-of-magnitude agreement with the experimental data for two representative enzymatic reactions.

IMPULSIVE DIFFERENTIAL EQUATION MODEL IN HIV-1 INHIBITION: ADVANCES IN DUAL INHIBITORS OF HIV-1 RT AND IN FOR THE PREVENTION OF HIV-1 REPLICATION

Reverse transcriptase (RT) and integrase (IN) are two pivotal enzymes in HIV-1 replication. RT converts the single-stranded viral RNA genome into double-stranded DNA and IN catalyzes the integration of viral double-stranded DNA into host DNA. Currently, dual inhibitors of HIV-1 RT and IN have become a hotspot in new anti-HIV drug research and development. A dual inhibitor of HIV-1 RT/IN does the same thing as the two independent drugs would do. In this paper, we develop a mathematical model comprising a system of nonlinear differential equations describing HIV-1 RT/IN catalyzed biochemical reactions based on Michaelis–Menten enzyme kinetic reaction. In the formulated model we incorporate HIV-1 RT/IN dual inhibitor which simultaneously works as a non-nucleoside RT inhibitor and IN inhibitor. To examine the efficacy of HIV-1 RT/IN dual inhibitor in the treatment of HIV-1 infection, we have introduced a one-dimensional impulsive differential equation model and determined an effective dosing regimen for applying the inhibitor numerically. Furthermore, the exact closed form solution of the impulsive differential equation model is carried out by using the Lambert W function and the local stability of the periodic solution is also obtained analytically. The results obtained from analytical as well as numerical studies provide a basic idea to investigate the minimum dose with the highest efficacy for administering HIV-1 RT/IN dual inhibitors to prevent HIV-1 infection.

Biomineralization of heavy metals based on urea transport and hydrolysis within a new bacterial isolate, B. intermedia TSBOI

A newly isolated ureolytic bacteria, Brucella intermedia TSBOI, exhibited microbially induced calcite precipitation (MICP) which is a promising technique for the remediation of heavy metals in polluted environments. Brucella intermedia TSBOI achieved 90–100% removal of 1 mmol/L Cu2+/Pb2+/Zn2+ within 72 h. A distinctive feature lies in B. intermedia TSBOI’s capacity for the transport and hydrolysis of urea, considered to be critical for its strong urease activity. This study explored the mechanisms of this capacity at the genetic, molecular and protein levels through complete genome sequencing, molecular docking and enzymatic reaction kinetics. The results revealed that, for urea hydrolysis, B. intermedia TSBOI exhibited a comprehensive urease gene cluster, with the key gene ureC demonstrating an absolute expression level approximating to 4 × 104 copies/RNA ng under optimal conditions. Results also confirmed the strong spontaneous, energy-independent binding ability of it’s urease to urea, with the lowest Gibbs free energy binding site linking to the three amino acids, alanine, asparagine and serine. The urea transport gene yut presented and expressed, with the absolute expression enhanced in response to increasing urea concentrations. The significant positive correlation between ureC/yut expression levels and urease activity provided a theoretical basis for B. intermedia TSBOI's heavy metal bioremediation potential. Environmental ImplicationHeavy metals (Cu, Pb and Zn) were studied in this study. Heavy metals are hazardous due to their toxicity, persistence, and ability to bioaccumulate in living organisms. They can cause severe health issues, harm ecosystems, and contaminate air, water, and soil. A novel ureolytic bacteria, Brucella intermedia TSBOI, exhibited microbially induced carbonate precipitation capability was isolated which removed 90–100% of 1 mmol/L Cu2+/Pb2+/Zn2+ within 72 h. Its advantages in urea hydrolysis and transport facilitate the remediation of actual heavy metal contaminated environments.

Nanoconfined zero-valent iron effectively enhances the catalytic degradation of phenolic pollutants by Fe-Mn bimetallic peroxidase-like compound

Peroxidase mimics can activate H2O2 to degrade organic pollutants in water. A novel bimetallic active center of MOF-based peroxidase-like (POD-like) (Fe@PCN-222(Mn)) was synthesized, with Fe0 uniformly doped within the channels of PCN-222(Mn). This nano-constrained strategy greatly improves the catalytic stability and anti-interference performance of Fe@PCN-222(Mn). Enzymatic reaction kinetics studies showed that Fe0 doping significantly increased the reaction rate. Compared to externally exposed Fe/PCN-222(Mn), pure PCN-222 and PCN-222(Mn), Fe@PCN-222(Mn) exhibited a more stable and efficient performance in the 4-NP-catalyzed degradation process, assisted by both bimetallic synergism and nanoconfinement. Within 60 min, the removal of 4-NP was as high as 100%, while the removal of TOC was 56.74%. The large amount of 1O2 produced in the Fe@PCN-222(Mn)/H2O2 system is the main reason for the rapid degradation of 4-NP. This is because the distance between the pollutant molecules and the ROS is greatly shortened under the nanoconfined conditions, and the electron transfer efficiency between Fe/Mn is also effectively improved. Furthermore, the electronegativity difference between Fe/Mn drives the reaction. This work expands the application of POD-like and offers a new approach to designing and developing Fenton-like catalysts.

OPTIMAL CONTROL ON FRACTIONAL ENZYME KINETICS WITH INHIBITORS

In enzyme kinetic chemical reaction, inhibitors are working as a regulators of the metabolism of the systems and the biochemical activities as well. The main focus of this study is to explore the fractional dynamics of enzyme kinetic biochemical reactions with competitive and uncompetitive inhibitors. Further, the analysis continuous with the optimal controls on the system which accelerate biochemical reactions and maximize product generation. Eventually, the numerical analysis have been done by the Adams predictor–corrector method and the forward–backward sweep method for the dynamics and optimal control study, respectively.

Efficient and fast screening and separation based on computer-aided screening and complex chromatography methods for lipoxygenase inhibitors from Ganoderma lucidum.

Accurate screening and targeted preparative isolation of active substances from natural medicines have long been technical challenges in natural medicine research. This study outlines a new approach for improving the efficiency of natural product preparation, focusing on the rapid and accurate screening of potential active ingredients in Ganoderma lucidum and efficient preparation of lipoxidase inhibitors, with the aim of providing new ideas for the treatment of Alzheimer's disease with G.lucidum. The medicinal plant G.lucidum was selected through ultrafiltration coupled with liquid chromatography and mass spectrometry (UF-LC-MS) and computer-assisted screening for lipoxygenase (LOX) inhibitors. In addition, the inhibitory effect of the active compounds on LOX was studied using enzymatic reaction kinetics, and the underlying mechanism is discussed. Finally, based on the earlier activity screening guidelines, the identified ligands were isolated and purified through complex chromatography (high-speed countercurrent chromatography and semi-preparative high-performance liquid chromatography). Five active ingredients, ganoderic acids A, B, C2, D2, and F, were identified and isolated from G.lucidum. We improved the efficiency and purity of active compound preparation using virtual computer screening and enzyme inhibition assays combined with complex chromatography. The innovative methods of UF-LC-MS, computer-aided screening, and complex chromatography provide powerful tools for screening and separating LOX inhibitors from complex matrices and provide a favourable platform for the large-scale production of bioactive substances and nutrients.

A carbon-based bifunctional heterogeneous enzyme: toward sustainable pollution control.

We present a study on an immobilized functional enzyme (IFE), a novel biomaterial with exceptional sustainability in enzyme utility, widely employed across various fields worldwide. However, conventional carriers are prone to eroding the active functional domain of the IFE, thereby weakening its intrinsic enzyme activity. Consequently, there is a burgeoning interest in developing next-generation IFEs. In this study, we engineered a carbon-based bifunctional heterogeneous enzyme (MIP-AMWCNTs@lipase) for the intelligent recognition of di(2-ethylhexyl)phthalate (DEHP), a common plasticizer. The heterogeneous enzyme contains a bifunctional structural domain that both enriches and degrades DEHP. We investigated its dual-response performance for the enrichment and specific removal of DEHP. The imprinting factor of the carrier for DEHP was 3.4, demonstrating selectivity for DEHP. The removal rate reached up to 94.2% over a short period. The heterogeneous enzyme exhibited robust activity, catalytic efficiency, and excellent stability under harsh environmental conditions, retaining 77.7% of its initial lipase activity after 7 cycles. Furthermore, we proposed a stepwise heterogeneous enzyme reaction kinetic model based on the Michaelis-Menten equation to enhance our understanding of enzyme reaction kinetics. Our study employs a dual-effect recognition strategy of molecular blotting and enzyme immobilization to establish a method for the removal of organic pollutants. These findings hold significant implications for the fields of biomaterials and environmental science.

Seasonal activity of anaerobic dehydrogenase of peat soils as related with some chemical factors of the redox environment of drained forest mires

The aim of the study was to study the specifics of seasonal fluctuations of anaerobic dehydrogenase of peat soils under the influence of forestry hydromelioration, a powerful exogenous factor affecting the speed and direction of biochemical processes. Location and time of the study. The southern taiga one of West Siberia during June–October 2001–2003 (geographical coordinates 56°23'071" NL, 84°34'04" EL). Methods. Investigation of the seasonal dynamics of the activity of anaerobic dehydrogenase and chemical components of the soil environment – C, NH4+, Fe2+, Fe3+, Fec (associated with organic matter) using the method of systemic ecological analysis. Results. The profile of drained forest peat soils was clearly differentiated into three zones: 0-5 cm of high anaerobic dehydrogenase activity, 5-10 cm of moderate activity and 10-30 cm of low activity of the enzyme. The main trend in seasonal fluctuations of the dehydrogenase activity from June to October was approximated by a second-order parabola. According to the regression equation parameters, in poorly drained soils the weekly increase in dehydrogenase activity averaged 0,205 units with a weekly average deceleration of 0,022. In the strongly drained soils, there was a weekly deceleration by an average of 0,131 with a weekly average acceleration of 0,022 units. Positively increased activity of anaerobic dehydrogenase was measured in 0-5 cm soil horizons, with the highest rates detected under poor drainage. Downwards the profile, there was mainly a negative increase during the entire observation period. A functional relationship between the activity of anaerobic dehydrogenase, mobile forms of iron, water-soluble organic matter and ammonium of medium and high density according to the type of parabola was revealed. Conclusions. The chemical components of the aqueous extract are the most important environmental factors controlling the kinetics of enzymatic reactions of peat soils. The cumulative proportion of the explained dispersion of dehydrogenase activity by mobile forms of iron (Fe2+, Fe3+, Fec) was 61 and 41%, by biogenic elements (organic matter and NH4+) – 25 and 44% respectively in weakly and intensively drained soils. The dominant factors determining seasonal fluctuations of the enzyme are iron-organic complexes and ammonium, regardless of the drainage regime, and oxidized iron under poor and reduced iron under strong drainage, respectively.

Investigating Enzyme-Based Electrode Processes Using Electrochemical Impedance Spectroscopy and Distribution of Relaxation Time Analysis

Enzymatic fuel cells (EFCs) are an emerging class of electrochemical devices that have the potential to harness renewable energy sources by converting the chemical energy of an organic substrate into electrical energy. Enzymes are responsible in an EFC for highly selective and efficient electrode processes under typically mild ambient conditions, such as the oxidation reaction at the anode and the reduction reaction at the cathode 1. In addition to more conventional techniques, electrochemical impedance spectroscopy (EIS) can be employed to characterize such systems. Electrochemical behavior of enzymatic electrodes, such as enzyme reaction kinetics, substrate mass transport, and electrode stability, can be studied by measuring the system's impedance over a wide frequency range and then performing a precise post-process analysis based on the distribution of relaxation time (DRT). DRT analysis is rarely used to interpret EIS spectra within the EFCs research field, despite the fact that it is widely acknowledged as relevant for properly understanding the EIS potential to improve power density in fuel cells 2,3. Glucose oxidase (GOx) and bilirubin oxidase (BOD) were immobilized on multi-walled carbon nanotubes (MWCNTs) to catalyze the bioelectrocatalytic oxidation of glucose at the anode and the bioelectrocatalytic reduction of oxygen at the cathode, respectively. This study presents a promising approach for the investigation of enzyme-based anodic and cathodic processes by measuring them with EIS and then interpreting the results with DRT analysis, as depicted in Figure 1. By varying different operating parameters, such as the enzymatic loading on the electrode surface or electrolyte conditions, this method can be used to identify three primary relaxation processes occurring at both electrodes. At the interface between the electrolyte and the electrode, it is possible to conclude that high-frequency processes are accountable for ionic conduction, intermediate-frequency processes are accountable for charge transfer, and low-frequency processes are accountable for oxygen surface exchange and diffusion.This method provides access to preliminary fundamental information about enzymatic bioelectrode processes, which can be used to optimize biofuel cell construction and compositions and increase their power output. Figure 1. Schematic representation of the characterization method used to characterize a GOx-CNT-modified anode consisting of EIS measurements and subsequent DRT analysis. Concentration of glucose 175 mM in 0.1 M HEPES Buffer, pH 7; EIS parameters: 20 mV sinusoidal excitation, 0.1 Hz-100 kHz. References K. Herkendell, A. Stemmer and R. Tel-Vered, Nano Res., 12(4), 767–775 (2019). H. Wang, X. Long, Y. Sun, D. Wang, Z. Wang, H. Meng, C. Jiang, W. Dong and N. Lu, Frontiers in microbiology, 13, 973501 (2022). F. Ciucci, Current Opinion in Electrochemistry, 13, 132–139 (2019). Figure 1

Methyl oleate for plant protection products formulations: Enzymatic synthesis, reaction kinetics and application testing

This study presents a solvent-free enzymatic approach for the synthesis of fatty acid methyl esters (FAMEs), such as methyl oleate, for their application as adjuvant in plant protection products (PPP) formulations. The direct esterification between free fatty acid and methanol was optimized to achieve 98% acid conversion. The kinetics of this conversion was accurately described by a simple second order mechanism and non-linear regression was applied to calculate the rate constants of the forward and backward reactions based on full progress curves data. The rate constant of the forward reaction (synthesis) was one order of magnitude higher than the backward reaction (hydrolysis) and favored formation of the target methyl ester product, rendering the removal of water unnecessary. Enzymatically synthesized methyl oleate was benchmarked against the chemically synthesized compound, showing matching results in terms of stability, spreadability and emulsifying capacity in plant care formulations. The enzymatic synthesis of FAMEs under solvent free conditions allows to achieve a safer and more sustainable character for carrier solvents in PPP formulations.

Innovative biocatalyst synthesis of pectinolytic enzymes by cross-linking strategy: Potentially immobilised pectinases for the production of pectic-oligosaccharides from pectin

Pectinases are outstanding multienzymes, which have the potential to produce new emerging pectic-oligosaccharides (POS) via enzymatic hydrolysis of pectin. However, free pectinase is unable to undergo repeated reaction for the production of POS. This study proposed a sustainable biocatalyst of pectinases known as cross-linked pectinase aggregates (CLPA). Pectinase from Aspergillus aculeatus was successfully precipitated using 2 mg/mL pectinase and 60 % acetone for 20 min at 20 °C, which remained 36.3 % of its initial activity. The prepared CLPA showed the highest activity recovery (85.0 %), under the optimised conditions (0.3 % (v/v) starch and glutaraldehyde mixture (St/Ga), 1.5: 1 of St/Ga, 25 °C, 1.5 h). Furthermore, pectin-degrading enzymes from various sources were used to produce different CLPA. The alteration of pectinase secondary structure gave high stability in acidic condition (pH 4), thermostability, deactivation energy and half-life, and improved storage stability at 4 °C for 30 days. Similarly to their free counterpart, the CLPA exhibited comparable enzymatic reaction kinetics and could be reused eight times with approximately 20 % of its initial activity. The developed CLPA does not only efficaciously produced POS from pectin as their free form, but also exhibited better operational stability and reusability, making it more suitable for POS production.