Enzyme Databases in the Era of Omics and Artificial Intelligence.

Enzyme research is important for the development of various scientific fields such as medicine and biotechnology. Enzyme databases facilitate this research by providing a wide range of information relevant to research planning and data analysis. Over the years, various databases that cover different aspects of enzyme biology (e.g., kinetic parameters, enzyme occurrence, and reaction mechanisms) have been developed. Most of the databases are curated manually, which improves reliability of the information; however, such curation cannot keep pace with the exponential growth in published data. Lack of data standardization is another obstacle for data extraction and analysis. Improving machine readability of databases is especially important in the light of recent advances in deep learning algorithms that require big training datasets. This review provides information regarding the current state of enzyme databases, especially in relation to the ever-increasing amount of generated research data and recent advancements in artificial intelligence algorithms. Furthermore, it describes several enzyme databases, providing the reader with necessary information for their use.

Substrate-dependent inactivation of recombinant paraoxonase 1 during catalytic dihydrocoumarin turnover and the protective properties of surfactants.

Human paraoxonase-1 (PON1) is the most studied member of the paraoxonases (PONs) family and catalyzes the hydrolysis of various substrates (lactones, aryl esters, and paraoxon). Numerous studies link PON1 to oxidative stress-related diseases such as cardiovascular disease, diabetes, HIV infection, autism, Parkinson's, and Alzheimer's, where the kinetic behavior of an enzyme is characterized by initial rates or by modern methods that obtain enzyme kinetic parameters by fitting the computed curves over the entire time-courses of product formation (progress curves). In the analysis of progress curves, the behavior of PON1 during hydrolytically catalyzed turnover cycles is unknown. Hence, progress curves for enzyme-catalyzed hydrolysis of the lactone substrate dihydrocoumarin (DHC) by recombinant PON1 (rePON1) were analyzed to investigate the effect of catalytic DHC turnover on the stability of rePON1. Although rePON1 was significantly inactivated during the catalytic DHC turnover, its activity was not lost due to the product inhibition or spontaneous inactivation of rePON1 in the sample buffers. Examination of the progress curves of DHC hydrolysis by rePON1 led to the conclusion that rePON1 inactivates itself during catalytic DHC turnover hydrolysis. Moreover, human serum albumin or surfactants protected rePON1 from inactivation during this catalytic process, which is significant because the activity of PON1 in clinical samples is measured in the presence of albumin.

Investigation of Paraoxonase-1 Genotype and Enzyme-Kinetic Parameters in the Context of Cognitive Impairment in Parkinson's Disease.

Cognitive impairment is a common non-motor symptom of Parkinson's disease (PD), which often progresses to PD dementia. PD patients with and without dementia may differ in certain biochemical parameters, which could thus be used as biomarkers for PD dementia. The enzyme paraoxonase 1 (PON1) has previously been investigated as a potential biomarker in the context of other types of dementia. In a cohort of PD patients, we compared a group of 89 patients with cognitive impairment with a group of 118 patients with normal cognition. We determined the kinetic parameters Km and Vmax for PON1 for the reaction with dihydrocoumarin and the genotype of four single nucleotide polymorphisms in PON1. We found that no genotype or kinetic parameter correlated significantly with cognitive impairment in PD patients. However, we observed associations between PON1 rs662 and PON1 Km (p < 10-10), between PON1 rs662 and PON1 Vmax (p = 9.33 × 10-7), and between PON1 rs705379 and PON1 Vmax (p = 2.21 × 10-10). The present study is novel in three main aspects. (1) It is the first study to investigate associations between the PON1 genotype and enzyme kinetics in a large number of subjects. (2) It is the first study to report kinetic parameters of PON1 in a large number of subjects and to use time-concentration progress curves instead of initial velocities to determine Km and Vmax in a clinical context. (3) It is also the first study to calculate enzyme-kinetic parameters in a clinical context with a new algorithm for data point removal from progress curves, dubbed iFIT. Although our results suggest that in the context of PD, there is no clinically useful correlation between cognitive status on the one hand and PON1 genetic and enzyme-kinetic parameters on the other hand, this should not discourage future investigation into PON1's potential associations with other types of dementia.

iFIT: An automated web tool for determining enzyme-kinetic parameters based on the high-curvature region of progress curves.

The area where progress curve exhibits maximum curvature contains the most information about kinetic parameters. To determine these parameters more accurately from progress curves, we propose an iterative approach that calculates the area of maximum curvature based on an estimate of kinetic parameters and then recalculates the parameters based on time-concentration data points within this area. Based on this algorithm, we developed a computer script called iFIT as a free web application at http://www.i-fit.si. The benefits of working with iFIT are that it decreases the importance of initial substrate concentration and the impact of certain side reactions on the final calculated kinetic parameters.

The Removal of Time-Concentration Data Points from Progress Curves Improves the Determination of Km: The Example of Paraoxonase 1.

Several approaches for determining an enzyme's kinetic parameter Km (Michaelis constant) from progress curves have been developed in recent decades. In the present article, we compare different approaches on a set of experimental measurements of lactonase activity of paraoxonase 1 (PON1): (1) a differential-equation-based Michaelis-Menten (MM) reaction model in the program Dynafit; (2) an integrated MM rate equation, based on an approximation of the Lambert W function, in the program GraphPad Prism; (3) various techniques based on initial rates; and (4) the novel program "iFIT", based on a method that removes data points outside the area of maximum curvature from the progress curve, before analysis with the integrated MM rate equation. We concluded that the integrated MM rate equation alone does not determine kinetic parameters precisely enough; however, when coupled with a method that removes data points (e.g., iFIT), it is highly precise. The results of iFIT are comparable to the results of Dynafit and outperform those of the approach with initial rates or with fitting the entire progress curve in GraphPad Prism; however, iFIT is simpler to use and does not require inputting a reaction mechanism. Removing unnecessary points from progress curves and focusing on the area around the maximum curvature is highly advised for all researchers determining Km values from progress curves.

The Structure and Function of Paraoxonase-1 and Its Comparison to Paraoxonase-2 and -3.

Serum paraoxonase-1 (PON1) is the most studied member of the group of paraoxonases (PONs). This enzyme possesses three enzymatic activities: lactonase, arylesterase, and paraoxonase activity. PON1 and its isoforms play an important role in drug metabolism as well as in the prevention of cardiovascular and neurodegenerative diseases. Although all three members of the PON family have the same origin and very similar amino acid sequences, they have different functions and are found in different locations. PONs exhibit substrate promiscuity, and their true physiological substrates are still not known. However, possible substrates include homocysteine thiolactone, an analogue of natural quorum-sensing molecules, and the recently discovered derivatives of arachidonic acid-bioactive δ-lactones. Directed evolution, site-directed mutagenesis, and kinetic studies provide comprehensive insights into the active site and catalytic mechanism of PON1. However, there is still a whole world of mystery waiting to be discovered, which would elucidate the substrate promiscuity of a group of enzymes that are so similar in their evolution and sequence yet so distinct in their function.

Interactions of Paraoxonase-1 with Pharmacologically Relevant Carbamates.

Mammalian paraoxonase-1 hydrolyses a very broad spectrum of esters such as certain drugs and xenobiotics. The aim of this study was to determine whether carbamates influence the activity of recombinant PON1 (rePON1). Carbamates were selected having a variety of applications: bambuterol and physostigmine are drugs, carbofuran is used as a pesticide, while Ro 02-0683 is diagnostic reagent. All the selected carbamates reduced the arylesterase activity of rePON1 towards the substrate S-phenyl thioacetate (PTA). Inhibition dissociation constants (Ki), evaluated by both discontinuous and continuous inhibition measurements (progress curves), were similar and in the mM range. The rePON1 displayed almost the same values of Ki constants for Ro 02-0683 and physostigmine while, for carbofuran and bambuterol, the values were approximately ten times lower and two times higher, respectively. The affinity of rePON1 towards the tested carbamates was about 3-40 times lower than that of PTA. Molecular modelling of rePON1-carbamate complexes suggested non-covalent interactions with residues of the rePON1 active site that could lead to competitive inhibition of its arylesterase activity. In conclusion, carbamates can reduce the level of PON1 activity, which should be kept in mind, especially in medical conditions characterized by reduced PON1 levels.

Evaluation of the paraoxonase-1 kinetic parameters of the lactonase activity by nonlinear fit of progress curves.

Although paraoxonase-1 (PON1) activity has been demonstrated to be a reliable biomarker of various diseases, clinical studies have been based only on relative comparison of specific enzyme activities, which capture differences mainly due to (usually unknown) PON1 concentration. Hence, the aim of this report is to present for the first time the simple evaluation method for determining autonomous kinetic parameter of PON1 that could be also associated with polymorphic forms and diseases; i.e. the Michaelis constant which is enzyme concentration independent quantity. This alternative approach significantly reduces the number of experiments needed, and it yields the results with great accuracy.

Time-course of enzyme-catalyzed competing substrate degradation for michaelian behavior and for enzymes showing activation/inhibition by excess substrate.

Progress curves for competing substrates were analyzed to investigate the effect of an "invisible" substrate (B) on the time-course of enzyme-catalyzed substrate degradation of a "visible" (reporter) substrate (A). Rate equations were integrated for Michaelis-Menten kinetics and in the case of activation or inhibition of degradation of A by excess of substrate B. The shape of progress curves depends on the ratio of specificity constants (kcat/Km)B/A, the competition matrix (R). Mathematical solutions exist for R ≫ 1, R = 1, R ≪ 1. Working at constant reporter substrate A concentration, from the shape of progress curves (sigmoidal or non-sigmoidal), it is possible to define the type of competitor (B), and from the dependence of retardation time (at 90% completion of A, and at inflexion point for sigmoid-like shaped progress curves) on "invisible" substrate B concentration, it is therefore possible to access to catalytic parameters, and/or to titrate enzyme active sites. This competing substrate approach is suitable for investigating new substrates and reversible inhibitors of toxicological and pharmacological interest, investigating enzyme promiscuity, screening of enzymes degrading numerous compounds, and mining new enzymes of medical or biotechnological interest.

Time-course of human cholinesterases-catalyzed competing substrate kinetics.

Competing substrate kinetic analysis of human butyrylcholinesterase (BChE) and acetylcholinesterase (AChE) from the time-course of enzyme-catalyzed substrate hydrolysis, using spectrophotometric assays is described. This study is based on the use of a chromogenic reporter "visible" substrate (substrate A), whose complete hydrolysis time course is retarded by a competing "invisible" substrate (substrate B). For BChE, four visible substrates were used, two thiocholine esters, benzoylthiocholine and butyrylthiocholine, and two aryl-acylamides, o-nitro trifluoro acetaminide and 3-(acetamido)-N,N,N-trimethylanilinium. Three different competing invisible substrates were used, phenyl acetate, acetylcholine and butyrylcholine. For AChE, two visible substrates were used, acetylthiocholine and 3-(acetamido)-N,N,N-trimethylanilinium. For AChE, acetylcholine was competing with visible substrates. The ratio (R) of bimolecular rate constants, kcat/Km, for all couples of substrates, invisible/visible (B/A) covered all possible limit situations, R ≪ 1, R ≈ 1 and R ≫ 1. The kinetic approach, based on the method developed by Golicnik and Masson allowed determination of binding and catalytic parameters of cholinesterases for both visible and invisible substrates. This analysis was applied to michaelian and non-michaelian catalytic behaviors (activation and inhibition by excess substrate). Reevaluation of catalytic parameters obtained for acetylcholine and butyrylcholine more than 50 years ago was made. The method is fast, reliable, and particularly suitable for poorly soluble substrates and for substrates B when no direct spectrophotometric assays exist. Moreover, replacing substrate B by a reversible inhibitor, mechanism of cholinesterase inhibition was possible to study. It is therefore, useful for screening libraries of new substrates and inhibitors, and/or screening of new cholinesterase mutants. This method can be applied to any other enzymes.

Transition-State Interactions in a Promiscuous Enzyme: Sulfate and Phosphate Monoester Hydrolysis by Pseudomonas aeruginosa Arylsulfatase.

Pseudomonas aeruginosa arylsulfatase (PAS) hydrolyzes sulfate and, promiscuously, phosphate monoesters. Enzyme-catalyzed sulfate transfer is crucial to a wide variety of biological processes, but detailed studies of the mechanistic contributions to its catalysis are lacking. We present linear free energy relationships (LFERs) and kinetic isotope effects (KIEs) of PAS and analyses of active site mutants that suggest a key role for leaving group (LG) stabilization. In LFERs PASWT has a much less negative Brønsted coefficient (ßleaving groupobs-Enz = -0.33) than the uncatalyzed reaction (ßleaving groupobs = -1.81). This situation is diminished when cationic active site groups are exchanged for alanine. The considerable degree of bond breaking during the transition state (TS) is evidenced by an 18Obridge KIE of 1.0088. LFER and KIE data for several active site mutants point to leaving group stabilization by active site K375, in cooperation with H211. 15N KIEs and the increased sensitivity to leaving group ability of the sulfatase activity in neat D2O (Δßleaving groupH-D = +0.06) suggest that the mechanism for S-Obridge bond fission shifts, with decreasing leaving group ability, from charge compensation via Lewis acid interactions toward direct proton donation. 18Ononbridge KIEs indicate that the TS for PAS-catalyzed sulfate monoester hydrolysis has a significantly more associative character compared to the uncatalyzed reaction, while PAS-catalyzed phosphate monoester hydrolysis does not show this shift. This difference in enzyme-catalyzed TSs appears to be the major factor favoring specificity toward sulfate over phosphate esters by this promiscuous hydrolase, since other features are either too similar (uncatalyzed TS) or inherently favor phosphate (charge).

Cytochrome P450 metabolism of the post-lanosterol intermediates explains enigmas of cholesterol synthesis.

Cholesterol synthesis is among the oldest metabolic pathways, consisting of the Bloch and Kandutch-Russell branches. Following lanosterol, sterols of both branches are proposed to be dedicated to cholesterol. We challenge this dogma by mathematical modeling and with experimental evidence. It was not possible to explain the sterol profile of testis in cAMP responsive element modulator tau (Crem τ) knockout mice with mathematical models based on textbook pathways of cholesterol synthesis. Our model differs in the inclusion of virtual sterol metabolizing enzymes branching from the pathway. We tested the hypothesis that enzymes from the cytochrome P450 (CYP) superfamily can participate in the catalysis of non-classical reactions. We show that CYP enzymes can metabolize multiple sterols in vitro, establishing novel branching points of cholesterol synthesis. In conclusion, sterols of cholesterol synthesis can be oxidized further to metabolites not dedicated to production of cholesterol. Additionally, CYP7A1, CYP11A1, CYP27A1, and CYP46A1 are parts of a broader cholesterol synthesis network.

Exploring the aryl esterase catalysis of paraoxonase-1 through solvent kinetic isotope effects and phosphonate-based isosteric analogues of the tetrahedral reaction intermediate.

Although a recent study of Debord et al. in Biochimie (2014; 97:72-77) described the thermodynamics of the catalysed hydrolysis of phenyl acetate by human paraoxonase-1, the mechanistic details along the reaction route of this enzyme remain unclear. Therefore, we briefly present the solvent kinetic isotope effects on the phenyl acetate esterase activity of paraoxonase-1 and its inhibition with the phenyl methylphosphonate anion, which is a stable isosteric analogue that mimics the high-energy tetrahedral intermediate on the hydroxide-promoted hydrolysis pathway. The data show normal isotope effects, while proton inventory analysis indicates that two protons contribute to the kinetic isotope effect. Coherently, moderate competitive inhibition with the phenyl methylphosphonate anion reveals that the rate-limiting transition state suboptimally resembles the tetrahedral intermediate. The implications of these findings can be attributed to two possible reaction mechanisms that might occur during the paraoxonase-1-catalysed hydrolysis of phenyl acetate.

Progress-curve analysis through integrated rate equations and its use to study cholinesterase reaction dynamics.

Michaelis and Menten found the direct mathematical analysis of their studied enzyme-catalyzed reaction unrealistic 100 years ago, and hence, they avoided this problem by correct adaptation and analysis of the experiment, i.e., differentiation of the progress-curve data into rates. However, the most elegant and ideal simplification of the evaluation of kinetics parameters from progress curves can be performed when the algebraic integration of the rate equation results in an explicit mathematical equation that describes the dynamics of the model system of the reaction. Recently, it was demonstrated that such an alternative approach can be considered for enzymes that obey the generalized Michaelis­Menten reaction dynamics, although its use is now still limited for cholinesterases, which show kinetics that deviate from saturationlike hyperbolic behavior at high concentrations of charged substrates. However, a mathematical approach is reviewed here that might provide an alternative to the decades-old problemof data analysis of cholinesterase-catalyzed reactions, through the more complex Webb integrated rate equation.

Inducible cAMP early repressor regulates the Period 1 gene of the hepatic and adrenal clocks.

Light, restricted feeding, and hormonal inputs may operate as time givers (zeitgebers) for the circadian clock within peripheral organs through the activation of tissue-specific signaling cascades. cAMP signaling through CREM (cAMP-responsive element modulator) and its variant ICER (inducible cAMP early repressor) is linked to the circadian regulation of pineal melatonin synthesis, although little is known about its influence in other organs. We performed experiments in the absence of light and feeding-time cues to test which core clock genes are controlled by CREM/ICER in the liver and adrenal gland. In vivo, Crem loss-of-function mutation resulted in fine-tuning of all measured adrenal clock genes (Per1/2/3, Cry1/2, Bmal1, and Rev-erbα), whereas only Per1 and Cry1 were affected in the liver. Icer expression was circadian in the adrenal gland, with peak gene expression at zeitgeber 12 and the highest protein levels at zeitgeber ∼20. The expression of both Icer and Per1 genes responded to cAMP stimuli in an immediate-early fashion. In immortal cells, forskolin induced expression of Per1 after 2 h, and de novo protein synthesis led to Per1 attenuation. We show that the de novo synthesized protein responsible for Per1 attenuation is ICER. Indeed, Per1 expression is up-regulated in cells ectopically expressing antisense Icer, and mobility shift experiments identified ICER binding to cAMP-responsive elements of the Per1 promoter. We propose that ICER acts as a noise filter for different signals that could affect transcription in the adrenal gland. Because ICER is an immediate-early repressor, the circadian nature of adrenal Icer expression could serve a role in a time-dependent gating mechanism.

The integrated Michaelis-Menten rate equation: déjà vu or vu jàdé?

A recent article of Johnson and Goody (Biochemistry, 2011;50:8264-8269) described the almost-100-years-old paper of Michaelis and Menten. Johnson and Goody translated this classic article and presented the historical perspective to one of incipient enzyme-reaction data analysis, including a pioneering global fit of the integrated rate equation in its implicit form to the experimental time-course data. They reanalyzed these data, although only numerical techniques were used to solve the model equations. However, there is also the still little known algebraic rate-integration equation in a closed form that enables direct fitting of the data. Therefore, in this commentary, I briefly present the integral solution of the Michaelis-Menten rate equation, which has been largely overlooked for three decades. This solution is expressed in terms of the Lambert W function, and I demonstrate here its use for global nonlinear regression curve fitting, as carried out with the original time-course dataset of Michaelis and Menten.

The interplay of cis-regulatory elements rules circadian rhythms in mouse liver.

The mammalian circadian clock is driven by cell-autonomous transcriptional feedback loops that involve E-boxes, D-boxes, and ROR-elements. In peripheral organs, circadian rhythms are additionally affected by systemic factors. We show that intrinsic combinatorial gene regulation governs the liver clock. With a temporal resolution of 2 h, we measured the expression of 21 clock genes in mouse liver under constant darkness and equinoctial light-dark cycles. Based on these data and known transcription factor binding sites, we develop a six-variable gene regulatory network. The transcriptional feedback loops are represented by equations with time-delayed variables, which substantially simplifies modelling of intermediate protein dynamics. Our model accurately reproduces measured phases, amplitudes, and waveforms of clock genes. Analysis of the network reveals properties of the clock: overcritical delays generate oscillations; synergy of inhibition and activation enhances amplitudes; and combinatorial modulation of transcription controls the phases. The agreement of measurements and simulations suggests that the intrinsic gene regulatory network primarily determines the circadian clock in liver, whereas systemic cues such as light-dark cycles serve to fine-tune the rhythms.

Detection of phosphorylation states by intermolecular sensitization of lanthanide-peptide conjugates.

The luminescence of a designed peptide equipped with a coordinatively-unsaturated lanthanide complex is modulated by the phosphorylation state of a serine residue in the sequence. While the phosphorylated state is weakly emissive, even in the presence of an external antenna, removal of the phosphate allows coordination of the sensitizer to the metal, yielding a highly emissive supramolecular complex.

Estimation of kinetic parameters for enzyme-inhibition reaction models using direct time-dependent equations for reactant concentrations.

To facilitate the determination of a reaction type and its kinetics constants for reversible inhibitors of Michaelis-Menten-type enzymes using progress-curve analysis, I present here an explicit equation for direct curve fitting to full time-course data of inhibited enzyme-catalyzed reactions. This algebraic expression involves certain elementary functions where their values are readily available using any standard nonlinear regression program. Hence this allows easy analysis of experimentally observed kinetics without any data conversion prior to fitting. Its implementation gives correct parameter estimates that are in very good agreement with results obtained using both the numerically integrated Michaelis-Menten rate equation or its exact closed-form solution which is expressed in terms of the Lambert W function.

Explicit reformulations of the Lambert W-omega function for calculations of the solutions to one-compartment pharmacokinetic models with Michaelis-Menten elimination kinetics.

The exact closed-form solutions to the integrated rate equations for one-compartment pharmacokinetic models that obey Michaelis-Menten elimination kinetics were derived recently (Tang and Xiao in J Pharmacokin Pharmacodyn 34:807-827, 2007). These solutions are expressed in terms of the Lambert W(x)-omega function; however, unfortunately, most of the available computer programs are not set up to handle equations that involve the W(x) function. Therefore, in this article, I provide alternative explicit analytical equations expressed in terms of elementary mathematical functions that accurately approximate exact solutions and can be simply calculated using any optional standard software.