Search Results (257)

Biocatalysis is one of the oldest fields that has been used in industrial applications, with one of the earliest purposeful examples being the mass production of acetic acid from an immobilized Acinetobacter strain in the year 1815. Efficiency, specificity, reduced reaction times, lower overall costs, and environmental friendliness are some advantages biocatalysis has over conventional chemical synthesis, which has made biocatalysis increasingly used in industry. We highlight three necessary fields that are fundamental to advancing industrial biocatalysis, including biocatalyst engineering, solvent engineering, and mechanistic engineering. However, the fundamental mechanism of enzyme function is often overlooked or given less attention, which can limit the engineering process. In this review, we describe how mechanistic enzymology benefits industrial biocatalysis by elucidating key fundamental principles, including the k_cat and k_cat/K_m parameters. Mechanistic enzymology presents a unique field that provides in-depth insights into the molecular mechanisms of enzyme activity and includes areas such as reaction kinetics, catalytic mechanisms, structural analysis, substrate specificity, and protein dynamics. In line with the objective of protein engineering to optimize enzyme activity, we summarize a range of strategies reported in the literature aimed at improving the product release rate, the chemical step of catalysis, and the overall catalytic efficiency of enzymes. Further into this review, we delineate kinetic solvent viscosity effects (KSVEs) as a very efficient, cost-effective, and easy-to-perform method to probe different aspects of enzyme reaction mechanisms, including diffusion-dependent kinetic steps and rate-limiting steps. KSVEs are cost-effective because simple kinetic enzyme assays, such as the Michaelis–Menten kinetic approach, can be combined with them without the need for specialized and costly equipment. Other techniques in protein engineering and genetic engineering are also covered in this review. Additionally, we provide information on solvent systems in enzymatic reactions, details on immobilized biocatalysts, and common misconceptions that misguide enzyme design and optimization processes. Full article

Developing precision models to describe agricultural growth is a necessary step to promote sustainable agriculture and increase resource circulation. In this study, the researchers hydroponically cultivated Bibb lettuce (Lactuca sativa) across a variety of nitrogen, phosphorus, and potassium (NPK)-limited treatments and developed robust data-driven kinetic models observing nutrient uptake, biomass growth, and tissue composition based on all three primary macronutrients. The resulting Dynamic μ model is the first to integrate plant maturity’s impact on growth rate, significantly improving model accuracy across limiting nutrients, treatments, and developmental stages. This reduced error supports this simple expansion as a practical and necessary inclusion for agricultural kinetic modeling. Furthermore, analysis of nutrient uptake refines the ideal hydroponic nutrient balance for Bibb lettuce to 132, 35, and 174 mg L⁻¹ (N, P, and K, respectively), while qualitative cell yield analysis identifies minimum nutrient thresholds at approximately 26.2–41.7 mg-N L⁻¹, 3.7–5.6 mg-P L⁻¹, and 17.4–31.5 mg-K L⁻¹ to produce compositionally healthy lettuce. These findings evaluate reclaimed wastewater’s ability to offset the fertilizer burden for lettuce by 23–45%, 14–57%, and 3–23% for N, P, and K and guide the required minimum amount of wastewater pre-processing or nutrient supplements needed to completely fulfill hydroponic nutrient demands. Full article

(1) Background: Overexpression of P-glycoprotein (P-gp) is one mediator of multidrug resistance in cancer. While many studies demonstrate the efficacy of modulating P-glycoprotein expression to increase drug response in cancer cells, the nature of the mathematical relationship between drug sensitivity and P-glycoprotein surface density is not yet characterized. (2) Methods: In this study, we employ siRNA to modulate P-gp expression in two model cell lines and evaluate their steady-state response to three common chemotherapeutics in vitro. Additionally, we model the kinetics of calcein-AM, a P-gp substrate, as a function of P-gp expression. (3) Results: For both cell lines, a robust linear relationship governs chemotherapeutic sensitivity as a function of P-gp expression, demonstrating that characterization of P-gp surface density is a strong indicator of drug response in drug-resistant cells. Furthermore, calcein accumulation and initial influx rate exhibit first-order kinetics with respect to P-gp density, further elucidating the nature of substrate interactions with P-gp-overexpressing cells. When transport kinetics are evaluated using a Michaelis–Menten model, V_max varies with P-gp density according to a first-order relationship. (4) Conclusions: These results establish the mathematical relationships between chemotherapeutic response and substrate influx as a function of P-gp expression and suggest that rational changes in P-gp expression could be used as a predictive measure of drug sensitivity in model cell lines. Full article

This study discloses the noncovalent immobilization of a bienzyme cascade composed of glucose oxidase (GOx) and horseradish peroxidase (HRP) onto magnetically responsive polyamide microparticles (PA MPs). Porous PA6, PA4, and PA12 MPs containing iron fillers were synthesized via activated anionic ring-opening polymerization in suspension, alongside neat PA6 MPs used as a reference. Four hybrid catalytic systems (GOx/HRP@PA) were prepared through sequential adsorption of HRP and GOx onto the various PA MP supports. The initial morphologies of the supports and the hybrid biocatalysts were characterized by SEM, followed by evaluation of the catalytic performance using a two-step glucose oxidation cascade process. Among all systems, the GOx/HRP@PA4-Fe complex exhibited the highest activity, being approximately 1.5 times greater than the native enzyme dyad, followed by the PA6-supported system with slightly inferior performance. All systems obeyed Michaelis–Menten kinetics, with the immobilized cascades displaying higher Kₘ and Vₘₐₓ values than the non-immobilized enzyme pair while maintaining comparable catalytic efficiencies, CE (CE = k_cat/Kₘ). Subsequently, the immobilized and native enzyme systems were employed for the polymerization of aniline. According to UV–VIS, complete monomer conversion was achieved within 24 h for selected catalysts, and FTIR analysis confirmed the formation of polyaniline in the emeraldine base form without the use of template molecules. These findings highlight the potential of Fe-containing polyamide microparticles as efficient supports for the sustainable, enzyme-mediated synthesis of intrinsically conductive aromatic polymers. Full article

The non-monotonic behavior of amperometric enzyme-based biosensors under uncompetitive and noncompetitive (mixed) substrate inhibition is investigated computationally using a two-compartment model consisting of an enzyme layer and an outer diffusion layer. The model is based on a system of reaction–diffusion equations that includes a nonlinear term associated with non-Michaelis–Menten kinetics of the enzymatic reaction and accounts for the partitioning between layers. In addition to the known effect of substrate inhibition, where the maximum biosensor current differs from the steady-state output, it has been determined that external diffusion limitations can also cause the appearance of a local minimum in the current. At substrate concentrations greater than both the Michaelis–Menten constant and the uncompetitive substrate inhibition constant, and in the presence of external diffusion limitation, the transient response of the biosensor, after immersion in the substrate solution, may follow a five-phase pattern depending on the model parameter values: it starts from zero, reaches a global or local maximum, decreases to a local minimum, increases again, and finally decreases to a steady intermediate value. The biosensor performance is analyzed numerically using the finite difference method. Full article

Background: Glucuronide recycling in the gut and liver profoundly affects the systemic and/or local exposure of drugs and their glucuronide metabolites, impacting both clinical efficacy and toxicity. This recycling also alters drug exposure in the colon, making it critical to establish local concentration for drugs targeting colon (e.g., drugs for colon cancer and inflammatory bowel disease). Methods: In this study, a parent–metabolite middle-out physiologically based pharmacokinetic (PBPK) model was built for genistein and its glucuronide metabolite to estimate the systemic and local exposure of the glucuronide and its corresponding aglycone in rats by incorporating UDP-glucuronosyltransferase (UGT)-mediated metabolism and transporter-dependent glucuronide disposition in the liver and intestine, as well as gut microbial-mediated deglucuronidation that enables the recycling of the parent compound. Results: This parent–metabolite middle-out rat PBPK model utilized in vitro-to-in vivo extrapolated (IVIVE) metabolic and transporter clearance values based on in vitro kinetic parameters from surrogate species, the rat tissue abundance of relevant proteins, and saturable Michaelis–Menten mechanisms. Inter-system extrapolation factors (ISEFs) were used to account for transporter protein abundance differences between in vitro systems and tissues and between rats and surrogate species. Model performance was evaluated at multiple dose levels for genistein and its glucuronide. Model sensitivity analyses demonstrated the impact of key parameters on the plasma concentrations and local exposure of genistein and its glucuronide. Our model was applied to simulate the quantitative impact of glucuronide recycling on the pharmacokinetic profiles in both plasma and colonocytes. Conclusions: Our study underlines the importance of glucuronide recycling in determining local drug concentrations in the intestine and provides a preliminary modeling tool to assess the influence of transporter-mediated drug–drug interactions on glucuronide recycling and local drug exposure, which are often misrepresented by systemic plasma concentrations. Full article

In recent years, an increasing number of published articles on biocatalysis have reported new enzymes that exhibit biotechnologically interesting catalytic activities. Some authors rush to publish their work in an attempt to ensure “novelty” and often present their results with various types of graphs, such as scatter plots or line-and-symbol plots using nonexistent parameters as ordinates, e.g., “Relative Activity (%)” and the like, vs. abscissae such as pH value, temperature, etc. Nevertheless, in vitro enzyme kinetics remains a valuable tool for understanding, optimizing, and effectively applying these biocatalysts under diverse reaction conditions, taking advantage of all available experimental results. This work aims to emphasize the importance of processing experimental data from enzymatic reactions through appropriate fitting with known kinetic equations and to discourage the use of nonexistent parameters. To support this integrated approach, specific examples are provided for the calculation of significant kinetic and thermodynamic parameters, as well as rate constants. Full article

Balancing food security with fertilizer-driven climate impacts remains critical in intensive agriculture. While organic–inorganic substitution enhances soil fertility, its effects on nitrous oxide (N₂O) and nitric oxide (NO) emissions remain uncertain. This study evaluated N₂O/NO emissions, crop yields, and agronomic parameters in a subtropical wheat–maize rotation under four fertilization regimes: inorganic-only (NPK), manure-only (OM), and partial substitution with crop residues (CRNPK, 15%) or manure (OMNPK, 30%), all applied at 280 kg N ha⁻¹ yr⁻¹. Emissions aligned with the dual Arrhenius–Michaelis–Menten kinetics and revised “hole-in-the-pipe” model. Annual direct emission factors (EF_d) for N₂O and NO were 1.01% and 0.11%, respectively, with combined emissions (1.12%) exponentially correlated to soil nitrogen surplus (p < 0.01). CRNPK and OMNPK reduced annual N₂O+NO emissions by 15–154% and enhanced NUE by 10–45% compared with OM, though OMNPK emitted 1.7–2.0 times more N₂O/NO than CRNPK. Sole OM underperformed in yield, while partial substitution—particularly with crop residues—optimized productivity while minimizing environmental risks. By integrating emission modeling and agronomic performance, this study establishes CRNPK as a novel strategy for subtropical cereal systems, reconciling high yields with low greenhouse gas emissions. Full article

Cytochrome P450s (CYPs) play an integral role in drug and xenobiotic metabolism in humans, and thus, understanding CYP inhibition and/or activation by new therapeutic candidates is an important step in the drug development process. Ideally, CYP inhibition/activation assays should be high-throughput, use commercially available components, allow for analysis of metabolism by the majority of human CYPs, and allow for kinetic analysis of inhibition type and time-dependent inhibition. Here, we developed pFluor50, a 384-well microtiter plate-based fluorogenic kinetic enzyme assay system using substrates metabolized by six human CYPs to generate fluorescent products and determined the Michaelis–Menten kinetics constants (K_M) and product formation rates (V_max) for each substrate–CYP pair. The pFluor50 assay was also used to elucidate inhibition type and time-dependent inhibition for some inhibitors, demonstrating its utility for characterizing the observed inhibition, even mechanism-based inhibition. The pFluor50 assay system developed in this study using commercially available components should be very useful for high-throughput screening and further characterization of potential therapeutic candidates for inhibition/activation with the most prevalent human CYPs. Full article

In groundwater quality analysis, nonlinear models are typically used, with domains spanning the entire real number line. In this study, alongside these models (Logistic, Gompertz and Richards), nonlinear models defined based on functions whose domain is only the positive part of the real number line are presented (Michaelis–Menten, Hill 1 and 2 and Rosin–Rammler 1 and 2). Two case studies were observed in the paper: (i) the dependence of nitrate concentration on the pumping rate in the Bartolovec wellfield, and (ii) the dependence of nitrate concentration on the distance from the source of pollution in the Varaždin wellfield. Both wellfields are located in the alluvial aquifer in northwestern Croatia. In this way, the curves obtained on the basis of the mentioned mathematical functions were fitted to the experimental data. The results show a good fit, so that the values of the coefficients of determination R² are greater than 0.82 for the case study (i) and greater than 0.96 for the case study (ii). Since the models differ in the number of parameters (e.g., three parameters for Michaelis–Menten and five parameters for Rosin–Rammler), the corrected Akaike information criterion (AIC_c) was used for their comparison. In this way, the best fit for the case study (i) was obtained for the Rosin–Rammler 1 model, while for the case study (ii), it was for the Hill 1 model. A t-test was performed for all models, and they can be considered reliable at a significance level of 0.05. However, t-values and p-values were also calculated for each parameter of each model. Based on these results, it is concluded that all model parameters can be considered reliable at a significance level of 0.05 only for the Hill 1 and Rosin–Rammler 1 models in both case studies. For this reason, these models can generally be considered the best fit to the experimental data. The study demonstrates the superiority of nonlinear models with domains restricted to positive real numbers (e.g., Hill 1, Rosin–Rammler 1) over traditional models (e.g., Logistic, Richards) in groundwater quality analysis. These findings offer practical tools for predicting contaminant extremes (e.g., maximum/minimum concentrations) and optimizing groundwater management strategies. Full article

Alternative models for the respiration rate (RR) of ready-to-eat strawberries were evaluated as a function of O₂ and CO₂ concentration and temperature. The effect of the gaseous atmosphere and temperature on RR was determined in a total factorial experiment where 45 treatments were applied by combining factors: oxygen (0–21%) and carbon dioxide (0–15%) concentration at three levels and temperature (4–26 °C) at five levels. Both phenomenological (Michaelis–Menten, Langmuir) and non-phenomenological (Generalized linear and Quadratic) approaches were used to fit RR data. The temperature effect was modeled by Arrhenius, exponential, and power models. Model selection was performed based on R2-adjusted, RMSE, and IAC indicators. Models with R² greater than 0.80, lower RMSE, and AIC were selected. The quadratic model and Michaelis–Menten Uncompetitive-with power model for temperature dependence were the best predictors of the experimental data. An integrated mathematical model based on strawberry respiration activity considering the influence of oxygen, carbon dioxide, and temperature was obtained, allowing its use for MAP modeling. Full article

In this paper, we present a kinetic–metabolic model describing adeno-associated virus (AAV) production via HEK293 cells that encompasses the main metabolic pathways, namely, glycolysis, tricarboxylic acid cycle (TCA), pyruvate fates, the pentose phosphate pathway, anaplerotic reaction, amino acid metabolism, nucleotides synthesis, biomass synthesis, and the metabolic pathways of protein synthesis of the AAV (capsid and Rep proteins). For the modeling, Michaelis–Menten kinetics was assumed to define the metabolic model. A dataset from bioreactor cultures containing metabolite profiles of adeno-associated virus 6 (AAV6) production via triple transient transfection in a low-cell-density culture, including the concentration profiles of glutamine, glutamic acid, glucose, lactate, and ammonium, was utilized for fitting and computing the model parameters. The model that resulted from the adjusted parameters defined the experimental data well. Subsequently, a Sobol-based global sensitivity analysis procedure was applied to determine the most sensitive parameters in the final model. Full article

The first luciferase from Antarctic krill (LAK) was cloned and successfully expressed in Escherichia coli BL21(DE3). LAK exhibits the unique ability to emit bright violet fluorescence at an emission wavelength of 350 nm, which represents the lowest reported bioluminescence wavelength for luciferases. However, its low thermal stability poses a limitation to its broader application. In this study, we employed a rational design approach to introduce three pairs of artificial disulfide bonds into LAK. Circular dichroism (CD) analysis revealed that the introduction of artificial disulfide bonds resulted in a significant increase in the secondary structural content of α-helices and β-sheets compared to the wild-type (WT) enzyme. However, these modifications did not influence the emission spectrum. Among the resultant mutant strains, two exhibited markedly enhanced thermal stability. Notably, Mut2 demonstrated a 6.18-fold increase in half-life at 50 °C. Molecular docking studies indicated that D-fluorescein can form additional hydrogen bonds with surrounding amino acid residues (A323, T347, and K534). The docking energies between the enzyme and substrate for WT and Mut2 were −19.5 kcal/mol and −23.4 kcal/mol, respectively, thereby establishing strong interactions within the catalytic pocket region. These interactions likely contribute to a 2.92-fold improvement in substrate affinity, as evidenced by a reduced Michaelis–Menten constant (Km). Our thermal stability and catalytic activity analyses revealed that the linker region between the N- and C-domains plays a crucial role in the overall stability of the enzyme. Furthermore, the C-terminus of LAK does not participate in substrate-binding and catalysis; its local excessive rigidity was found to restrict the release of the AMP product, thereby negatively impacting catalytic activity. These findings offer new insights into the mutagenesis of luciferases and pave the way for the further optimization of LAK for various biotechnological applications. Full article

Foxtail millet (Setaria italica), vital in northern China, has its quality and taste influenced by starch and protein. Existing models do not simulate the accumulation of these components during growth. To address this, we enhanced the DSSAT-CERES-Millet model (referred to as DSSAT) by integrating two newly developed modules: the protein simulation module and the starch simulation module. The protein simulation module uses a nitrogen-to-protein conversion coefficient to determine grain protein accumulation based on grain nitrogen accumulation simulated by the DSSAT model. In the starch simulation module, the carbon source supply (carbohydrates) received by millet grains is calculated based on the simulated aboveground and vegetative dry matter by the DSSAT model, and starch synthesis is modeled using the Michaelis–Menten equation to convert carbohydrates into starch within the grains. The integrated model demonstrates good performance in simulating grain protein and starch accumulation, with NRMSE (normalized root mean square error) values of 3.06–26.22% and 4.06–26.88%, respectively. It also accurately simulates grain amylopectin and amylose accumulation at maturity, achieving an NRMSE of less than 14%. The enhanced DSSAT-CERES-Millet model can provide guidance for optimizing irrigation and nitrogen management to enhance the protein and starch quality of millet grains. Full article

The utility of four mineral adsorbents as potential feed additives to bind the boar taint compounds, androstenone and skatole, was assessed with an in vitro system. The adsorbents were bentonite (BNT), diatomaceous earth (DE), spent filter aid (SFA) and hydrated sodium–calcium aluminosilicate (HSCAS), with activated charcoal (AC) as a positive control. The binding capacity (B_max) and binding affinity (K) of androstenone (AND), estrone (E1), estrone sulfate (E1S), and skatole were estimated using the modified Michaelis–Menten kinetics. The Langmuir and Freundlich isotherm models were also used to assess the adsorption behaviour. The B_max values with AND were 77.7 ± 1.12%, 71.9 ± 1.93%, 55.0 ± 7.85%, and 69.5 ± 1.39% for BNT, DE, SFA, and HSCAS, respectively, with no differences in the binding affinity K (p > 0.05). All the mineral adsorbents had very low binding with E1S. SFA bound skatole with a B_max of 89.9 ± 1.09%, while the B_max values for skatole binding by BNT, DE and HCAS were approximately 15%. Most adsorbent–adsorbate complexes fit best with the Freundlich isotherm model. We conclude that all four mineral adsorbents bound androstenone, but not E1S, and only SFA effectively bound skatole. This suggests that SFA may act as a selective dietary binding agent to control boar taint, but further research using animal models is needed to explore the utility and selectivity of these adsorbents as feed additives to control boar taint. Full article