Valacyclovir and Acyclovir Are Substrates of the Guanine Deaminase Cytosolic PSD-95 Interactor (Cypin).

Valacyclovir, enzymatically hydrolyzed in the body to acyclovir, is a guanine-based nucleoside analog commonly prescribed as an antiviral therapy. Previous reports suggest that guanosine analogs bind to guanine deaminase; however, it is unclear whether they act as inhibitors or substrates. Data from our laboratory suggest that inhibition of guanine deaminase by small molecules attenuates spinal cord injury-induced neuropathic pain. Here, we examine whether the guanosine analogs valacyclovir and acyclovir are deaminated by cypin (cytosolic PSD-95 interactor), the major guanine deaminase in the body, or if they act as cypin inhibitors. Using purified Rattus norvegicus cypin, we use NADH-coupled assay to confirm deamination of valacyclovir and determined Michaelis-Menten constants. Subsequently, we use tryptophan fluorescence quenching assay to calculate dissociation constants for valacyclovir and acyclovir and find that inclusion of the valine motif in valacyclovir increases affinity for cypin compared to acyclovir. To our knowledge, neither Km nor KD values for cypin has been previously reported for either compound. We use Amplex Red assay and demonstrate that both valacyclovir and acyclovir are cypin substrates and that their metabolites are further processed by xanthine oxidase and uricase. Using molecular dynamics simulations, we demonstrate that an alpha helix near the active site is displaced when valacyclovir binds to cypin. Furthermore, we used LC-MS-based assay to directly confirm deamination of valacyclovir by cypin. Taken together, our results demonstrate a novel role for cypin in deamination of valacyclovir and acyclovir and suggest that therapeutics based on purine structures may be inactivated by cypin, decreasing inhibitory efficacy.

Modulating Polymerase Activity through Light-Oxygen-Voltage Domain Insertion.

Biochemical reaction networks adapt to environmental conditions by sensing chemical or physical stimuli and using tightly controlled mechanisms. While most signals come from molecules, many cells can also sense and respond to light. Among the biomolecular structures that enable light sensing, we selected a light-oxygen-voltage (LOV) domain in a previous study that tested the engineering of novel regulatory mechanisms into a nucleic acid polymerase. In this follow-up study, we studied the activities of previously selected variants in kinetic detail, and we generated additional LOV-polymerase fusion variants based on further insertion criteria. Our results provide mechanistic insights into how LOV domain insertion influences polymerase activity in a light-responsive manner: All active and photoresponsive enzyme variants studied by us to date were partially inhibited (i.e., "turned off") after irradiation with blue light at 470 nm, which can be explained by specific obstructions of the polymerase entry or exit structures (substrate entry channels or product exit channels, or both). Although the effects observed are moderate, we anticipate further engineering strategies that could be used to improve the extent of switchability and possibly to develop a "turn-on mode" insertion.

Understanding Cytochrome P450 Enzyme Substrate Inhibition and Prospects for Elimination Strategies.

Cytochrome P450 (CYP450) enzymes, which are widely distributed and pivotal in various biochemical reactions, catalyze diverse processes such as hydroxylation, epoxidation, dehydrogenation, dealkylation, nitrification, and bond formation. These enzymes have been applied in drug metabolism, antibiotic production, bioremediation, and fine chemical synthesis. Recent research revealed that CYP450 catalytic kinetics deviated from the classic Michaelis-Menten model. A notable substrate inhibition phenomenon that affects the catalytic efficiency of CYP450 at high substrate concentrations was identified. However, the substrate inhibition of various reactions catalyzed by CYP450 enzymes have not been comprehensively reviewed. This review describes CYP450 substrate inhibition examples and atypical Michaelis-Menten kinetic models, and provides insight into mechanisms of these enzymes. We also reviewed 3D structure and dynamics of CYP450 with substrate binding. Outline methods for alleviating substrate inhibition in CYP450 and other enzymes, including traditional fermentation approaches and protein engineering modifications. The comprehensive analysis presented in this study lays the foundation for enhancing the catalytic efficiency of CYP450 by deregulating substrate inhibition.

Kinetic analysis of T4 polynucleotide kinase via isothermal titration calorimetry.

T4 polynucleotide kinase (T4 PNK) phosphorylates the 5'-terminus of DNA and RNA substrates. It is widely used in molecular biology. Single nucleotides can serve as substrates if a 3'-phosphate group is present. In this study, the T4 PNK-catalyzed conversion of adenosine 3'-monophosphate (3'-AMP) to adenosine-3',5'-bisphosphate was characterized using isothermal titration calorimetry (ITC). Although ITC is typically used to study ligand binding, in this case the instrument was used to evaluate enzyme kinetics by monitoring the heat production due to reaction enthalpy. The reaction was initiated with a single injection of 3'-AMP substrate into the sample cell containing T4 PNK and ATP at pH 7.6 and 30 °C, and Michaelis-Menten analysis was performed on the reaction rates derived from the plot of differential power versus time. The Michaelis-Menten constant, KM, was 13 µM, and the turnover number, kcat, was 8 s-1. The effect of inhibitors was investigated using pyrophosphate (PPi). PPi caused a dose-dependent decrease in the apparent kcat and increase in the apparent KM under the conditions tested. Additionally, the intrinsic reaction enthalpy and the activation energy of the T4 PNK-catalyzed phosphorylation of 3'-AMP were determined to be -25 kJ/mol and 43 kJ/mol, respectively. ITC is seldom used as a tool to study enzyme kinetics, particularly for technically-challenging enzymes such as kinases. This study demonstrates that quantitative analysis of kinase activity can be amenable to the ITC single injection approach.

Sequence similarity network analysis of drug- and dye-modifying azoreductase enzymes found in the human gut microbiome.

Drug metabolism by human gut microbes is often exemplified by azo bond reduction in the anticolitic prodrug sulfasalazine. Azoreductase activity is often found in incubations with cell cultures or ex vivo gut microbiome samples and contributes to the xenobiotic metabolism of drugs and food additives. Applying metagenomic studies to personalized medicine requires knowledge of the genes responsible for sulfasalazine and other drug metabolism, and candidate genes and proteins for drug modifications are understudied. A representative gut-abundant azoreductase from Anaerotignum lactatifermentan DSM 14214 efficiently reduces sulfasalazine and another drug, phenazopyridine, but could not reduce all azo-bonded drugs in this class. We used enzyme kinetics to characterize this enzyme for its NADH-dependent reduction of these drugs and food additives and performed computational docking to provide the groundwork for understanding substrate specificity in this family. We performed an analysis of the Flavodoxin-like fold InterPro family (IPR003680) by computing a sequence similarity network to classify distinct subgroups of the family and then performed chemically-guided functional profiling to identify proteins that are abundant in the NIH Human Microbiome Project dataset. This strategy aims to reduce the number of unique azoreductases needed to characterize one protein family in the diverse set of potential drug- and dye-modifying activities found in the human gut microbiome.

Cloning and characterization of a novel nitric oxide synthase gene from Exiguobacterium profundum and its expression in Escherichia coli.

The recognition and characterization of gene-encoded nitric oxide synthase (NOS) from Exiguobacterium profundum are reported in this study. A new gene was sequenced and cloned from E. profundum and heterologously expressed in E. coli for functional identification, followed by protein purification using the His-tag. The stability and activity characteristics of the recombinant NOS were evaluated using different concentrations of IPTG at various time points. A band of approximately 42 kDa was observed by SDS-PAGE. The Km value of NOS, calculated based on the Michaelis-Menten equation was 0.59 µmol/L. Additionally, homologous sequence alignment analysis indicated that the new NOS shared 80.48 % similarity with the same protein from Bacillus subtilis and Umezawaea. The construction of the NOS expression vector and the purification of the recombinant protein provide a foundation for further functional research and inhibitor development.

The unreasonable effectiveness of the total quasi-steady state approximation, and its limitations.

In this note, we discuss the range of parameters for which the total quasi-steady-state approximation of the Michaelis-Menten reaction mechanism holds validity. We challenge the prevalent notion that total quasi-steady-state approximation is "roughly valid" across all parameters, showing that its validity cannot be assumed, even roughly, across the entire parameter space - when the initial substrate concentration is high. On the positive side, we show that the linearized one-dimensional equation for total substrate is a valid approximation when the initial reduced substrate concentration s0/KM is small. Moreover, we obtain a precise picture of the long-term time course of both substrate and complex.

A modified Michaelis-Menten equation estimates growth from birth to 3 years in healthy babies in the USA.

BACKGROUND: Standard pediatric growth curves cannot be used to impute missing height or weight measurements in individual children. The Michaelis-Menten equation, used for characterizing substrate-enzyme saturation curves, has been shown to model growth in many organisms including nonhuman vertebrates. We investigated whether this equation could be used to interpolate missing growth data in children in the first three years of life and compared this interpolation to several common interpolation methods and pediatric growth models. METHODS: We developed a modified Michaelis-Menten equation and compared expected to actual growth, first in a local birth cohort (N = 97) then in a large, outpatient, pediatric sample (N = 14,695). RESULTS: The modified Michaelis-Menten equation showed excellent fit for both infant weight (median RMSE: boys: 0.22 kg [IQR:0.19; 90% < 0.43]; girls: 0.20 kg [IQR:0.17; 90% < 0.39]) and height (median RMSE: boys: 0.93 cm [IQR:0.53; 90% < 1.0]; girls: 0.91 cm [IQR:0.50;90% < 1.0]). Growth data were modeled accurately with as few as four values from routine well-baby visits in year 1 and seven values in years 1-3; birth weight or length was essential for best fit. Interpolation with this equation had comparable (for weight) or lower (for height) mean RMSE compared to the best performing alternative models. CONCLUSIONS: A modified Michaelis-Menten equation accurately describes growth in healthy babies aged 0-36 months, allowing interpolation of missing weight and height values in individual longitudinal measurement series. The growth pattern in healthy babies in resource-rich environments mirrors an enzymatic saturation curve.

Convex Representation of Metabolic Networks with Michaelis-Menten Kinetics.

Polyhedral models of metabolic networks are computationally tractable and can predict some cellular functions. A longstanding challenge is incorporating metabolites without losing tractability. In this paper, we do so using a new second-order cone representation of the Michaelis-Menten kinetics. The resulting model consists of linear stoichiometric constraints alongside second-order cone constraints that couple the reaction fluxes to metabolite concentrations. We formulate several new problems around this model: conic flux balance analysis, which augments flux balance analysis with metabolite concentrations; dynamic conic flux balance analysis; and finding minimal cut sets of networks with both reactions and metabolites. Solving these problems yields information about both fluxes and metabolite concentrations. They are second-order cone or mixed-integer second-order cone programs, which, while not as tractable as their linear counterparts, can nonetheless be solved at practical scales using existing software.

Maud Menten: Pioneering Pediatric-Perinatal Pathologist, Clinician-Scientist, and "the Most Wonderful Human Being in the World".

Maud Menten was born and raised in remote regions of Canada. She obtained her MB/MD at the University of Toronto (1907/1911) and her PhD in biochemistry at the University of Chicago (1916). From 1907 to 1916, she trained at the Rockefeller Institute for Medical Research, the New York Infirmary for Women and Children, Western Reserve University in Cleveland, the Berlin Municipal Hospital in Germany, and the Barnard Free Skin and Cancer Hospital in St Louis. In 1916, she was appointed as pathologist at the Elizabeth Steel Magee Hospital, a charitable maternity hospital in Pittsburgh. She received a faculty appointment at the University of Pittsburgh (1918) and was appointed pathologist at Pittsburgh Children's Hospital (1926). In addition to being one of the first woman academic pathologists, she was likely the first perinatal, the second pediatric-perinatal, and the fourth pediatric pathologist to practice in North America. The importance of Menten's overall scientific contributions place her in the very upper echelon of 20th century pathologists. Her enzyme kinetic work resulted in the Michaelis-Menten equation, and her work in George Crile's laboratory in Cleveland provided a physiological basis for improved surgical outcomes. Her work in Pittsburgh was equally innovative, including initiating the field of enzyme histochemistry.

Target-mediated drug disposition model for drugs with N > 2 binding sites that bind to a target with one binding site.

The paper extended the TMDD model to drugs with more than two (N > 2) identical binding sites (N-to-one TMDD). The quasi-steady-state (N-to-one QSS), quasi-equilibrium (N-to-one QE), irreversible binding (N-to-one IB), and Michaelis-Menten (N-to-one MM) approximations of the model were derived. To illustrate properties of new equations and approximations, N = 4 case was investigated numerically. Using simulations, the N-to-one QSS approximation was compared with the full N-to-one TMDD model. As expected, and similarly to the standard TMDD for monoclonal antibodies (mAb), N-to-one QSS predictions were nearly identical to N-to-one TMDD predictions, except for times of fast changes following initiation of dosing, when equilibrium has not yet been reached. Predictions for mAbs with soluble targets (slow elimination of the complex) were simulated from the full 4-to-one TMDD model and were fitted to the 4-to-one TMDD model and to its QSS approximation. It was demonstrated that the 4-to-one QSS model provided nearly identical description of not only the observed (simulated) total drug and total target concentrations, but also unobserved concentrations of the free drug, free target, and drug-target complexes. For mAb with a membrane-bound target, the 4-to-one MM approximation adequately described the data. The 4-to-one QSS approximation converged 8 times faster than the full 4-to-one TMDD.

Rationalizing the Influence of the Binding Affinity on the Activity of Phosphoserine Phosphatases.

The Sabatier principle states that catalytic activity can be maximized when the substrate binding affinity is neither too strong nor too weak. Recent studies have shown that the activity of several hydrolases is maximized at intermediate values of the binding affinity (Michaelis-Menten constant: Km ). However, it remains unclear whether this concept of artificial catalysis is applicable to enzymes in general, especially for those which have evolved under different reaction environments. Herein, we show that the activity of phosphoserine phosphatase is also enhanced at an intermediate Km value of approximately 0.5 mM. Within our dataset, the variation of Km by three orders of magnitude accounted for a roughly 18-fold variation in the activity. Owing to the high phylogenetic and physiological diversity of our dataset, our results support the importance of optimizing Km for enzymes in general. On the other hand, a 77-fold variation in the activity was attributed to other physicochemical parameters, such as the Arrhenius prefactor of kcat , and could not be explained by the Sabatier principle. Therefore, while tuning the binding affinity according to the Sabatier principle is an important consideration, the Km value is only one of many physicochemical parameters which must be optimized to maximize enzymatic activity.

Phosphorus storage and utilization strategies of two bloom-forming freshwater cyanobacteria.

The inter-relationships between cellular phosphorus (P) storage, dissolved inorganic P (DIP) uptake affinity, alkaline phosphatase activity (APA) and dissolved inorganic nitrogen (DIN) concentrations were studied in two ubiquitous diazotrophic freshwater cyanobacteria, Raphidiopsis raciborskii (six strains) and Chrysosporum ovalisporum (two strains). DIP uptake kinetics were measured using rates of incorporation of the radio-isotope, 33P and APA as a proxy for DOP-ester utilization. The study showed that DIP uptake of individual strains followed Michaelis-Menten kinetics (modified in our study to incorporate cellular P quotas), but differed with DIN and P availability, and between growth stages. High-affinity DIP uptake and APA were activated below a P quota threshold of approximately 0.01 µg P µg-1 C across the species and strains. C. ovalisporum had significantly higher APA and P quotas (per unit C and cell) but lower uptake affinity than R. raciborskii. Demand for DIP by C. ovalisporum increased when N fixation occurred, but typically not for R. raciborskii. Our results indicate that cyanobacterial species and strains differ in their strategies to P limiting conditions, and highlight the interplay between N and P. Physiological adaptations like APA and diazotrophy of cyanobacteria adapting to low DIP and/or DIN conditions may occur simultaneously and drive species dominance in oligotrophic environments.

Comparative study of two Saccharomyces cerevisiae strains with kinetic models at genome-scale.

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

The Potential Roles of Transacylation in Intracellular Lipolysis and Related Qssa Approximations.

Fatty acids (FAs) are crucial energy metabolites, signalling molecules, and membrane building blocks for a wide range of organisms. Adipose triglyceride lipase (ATGL) is the first and presumingly most crucial regulator of FA release from triacylglycerols (TGs) stored within cytosolic lipid droplets. However, besides the function of releasing FAs by hydrolysing TGs into diacylglycerols (DGs), ATGL also promotes the transacylation reaction of two DG molecules into one TG and one monoacylglycerol molecule. To date, it is unknown whether DG transacylation is a coincidental byproduct of ATGL-mediated lipolysis or whether it is physiologically relevant. Experimental evidence is scarce since both, hydrolysis and transacylation, rely on the same active site of ATGL and always occur in parallel in an ensemble of molecules. This paper illustrates the potential roles of transacylation. It shows that, depending on the kinetic parameters but also on the state of the hydrolytic machinery, transacylation can increase or decrease downstream products up to 80% respectively 30%. We provide an extensive asymptotic analysis including quasi-steady-state approximations (QSSA) with higher order correction terms and provide numerical simulation. We also argue that when assessing the validity of QSSAs one should include parameter sensitivity derivatives. Our results suggest that the transacylation function of ATGL is of biological relevance by providing feedback options and altogether stability to the lipolytic machinery in adipocytes.

Algorithmic criteria for the validity of quasi-steady state and partial equilibrium models: the Michaelis-Menten reaction mechanism.

We present "on the fly" algorithmic criteria for the accuracy and stability (non-stiffness) of reduced models constructed with the quasi-steady state and partial equilibrium approximations. The criteria comprise those introduced in Goussis (Combust Theor Model 16:869-926, 2012) that addressed the case where each fast time scale is due to one reaction and a new one that addresses the case where a fast time scale is due to more than one reactions. The development of these criteria is based on the ability to approximate accurately the fast and slow subspaces of the tangent space. Their validity is assessed on the basis of the Michaelis-Menten reaction mechanism, for which extensive literature is available regarding the validity of the existing various reduced models. The criteria predict correctly the regions in both the parameter and phase spaces where each of these models is valid. The findings are supported by numerical computations at indicative points in the parameter space. Due to their algorithmic character, these criteria can be readily employed for the reduction of large and complex mathematical models.

Nutrient dose-responsive transcriptome changes driven by Michaelis-Menten kinetics underlie plant growth rates.

An increase in nutrient dose leads to proportional increases in crop biomass and agricultural yield. However, the molecular underpinnings of this nutrient dose-response are largely unknown. To investigate, we assayed changes in the Arabidopsis root transcriptome to different doses of nitrogen (N)-a key plant nutrient-as a function of time. By these means, we found that rate changes of genome-wide transcript levels in response to N-dose could be explained by a simple kinetic principle: the Michaelis-Menten (MM) model. Fitting the MM model allowed us to estimate the maximum rate of transcript change (Vmax), as well as the N-dose at which one-half of Vmax was achieved (Km) for 1,153 N-dose-responsive genes. Since transcription factors (TFs) can act in part as the catalytic agents that determine the rates of transcript change, we investigated their role in regulating N-dose-responsive MM-modeled genes. We found that altering the abundance of TGA1, an early N-responsive TF, perturbed the maximum rates of N-dose transcriptomic responses (Vmax), Km, as well as the rate of N-dose-responsive plant growth. We experimentally validated that MM-modeled N-dose-responsive genes included both direct and indirect TGA1 targets, using a root cell TF assay to detect TF binding and/or TF regulation genome-wide. Taken together, our results support a molecular mechanism of transcriptional control that allows an increase in N-dose to lead to a proportional change in the rate of genome-wide expression and plant growth.

Motile ghosts of the halophilic archaeon, Haloferax volcanii.

Archaea swim using the archaellum (archaeal flagellum), a reversible rotary motor consisting of a torque-generating motor and a helical filament, which acts as a propeller. Unlike the bacterial flagellar motor (BFM), ATP (adenosine-5'-triphosphate) hydrolysis probably drives both motor rotation and filamentous assembly in the archaellum. However, direct evidence is still lacking due to the lack of a versatile model system. Here, we present a membrane-permeabilized ghost system that enables the manipulation of intracellular contents, analogous to the triton model in eukaryotic flagella and gliding Mycoplasma We observed high nucleotide selectivity for ATP driving motor rotation, negative cooperativity in ATP hydrolysis, and the energetic requirement for at least 12 ATP molecules to be hydrolyzed per revolution of the motor. The response regulator CheY increased motor switching from counterclockwise (CCW) to clockwise (CW) rotation. Finally, we constructed the torque-speed curve at various [ATP]s and discuss rotary models in which the archaellum has characteristics of both the BFM and F1-ATPase. Because archaea share similar cell division and chemotaxis machinery with other domains of life, our ghost model will be an important tool for the exploration of the universality, diversity, and evolution of biomolecular machinery.

Mathematical Model of Synaptic Long-Term Potentiation as a Bistability in a Chain of Biochemical Reactions with a Positive Feedback.

Nitric oxide (NO) is involved in synaptic long-term potentiation (LTP) by multiple signaling pathways. Here, we show that LTP of synaptic transmission can be explained as a feature of signal transduction-bistable behavior in a chain of biochemical reactions with positive feedback, formed by diffusion of NO to the presynaptic site and facilitating the release of glutamate (Glu). The dynamics of Glu, calcium (Ca2+) and NO is described by a system of nonlinear reaction-diffusion equations with modified Michaelis-Menten (MM) kinetics. Numerical investigation reveals that the chain of biochemical reactions analyzed can exhibit a bistable behavior under physiological conditions when production of Glu is described by MM kinetics and decay of NO is modeled by means of two enzymatic pathways with different kinetic properties. Our finding extends understanding of the role of NO in LTP: a short high-intensity stimulus is "memorized" as a long-lasting elevation of NO concentration. The conclusions obtained by analysis of the chain of biochemical reactions describing LTP can be generalized to other chains of interactions or for creating the logical elements for biological computers.

The influence of UV light on the course of fluorescent enzyme assays.

Experiments were carried out to illustrate the effect of UV light on the course of the enzymatic reaction of the coumarin derivative. Only the pulsating light of the UV diode gives the correct results for the determination of the kinetic constants of the enzymatic reaction. The enzyme concentration limit was found where the description of the M-M model breaks. It was shown that the system determines the kinetic parameters of enzymatic reactions: Vmax-the maximum rate of reaction and KM-the Michaelis constant. This method produces kinetic constants calculated from the changes in enzyme product concentration using the Michaelis-Menten model. To verify the results, we used a statistical analysis that checks the correctness of the model used.