Author Report for: Golicnik M

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.

Several approaches for determining an enzyme's kinetic parameter K(m) (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 K(m) values from 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.

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 (K(i)), 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 K(i) 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.

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.

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 delta-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.

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 approximately 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.

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 PAS(WT) has a much less negative Bronsted coefficient (beta(leavingsgroup)(obs-Enz) = -0.33) than the uncatalyzed reaction (beta(leavingsgroup)(obs) = -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 (18)O(bridge) 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. (15)N KIEs and the increased sensitivity to leaving group ability of the sulfatase activity in neat D(2)O (deltabeta(leavingsgroup)(H-D) = +0.06) suggest that the mechanism for S-O(bridge) bond fission shifts, with decreasing leaving group ability, from charge compensation via Lewis acid interactions toward direct proton donation. (18)O(nonbridge) 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).

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.

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 Michaelis-Menten reaction dynamics, although its use is now still limited for cholinesterases, which show kinetics that deviate from saturation-like hyperbolic behavior at high concentrations of charged substrates. However, a mathematical approach is reviewed here that might provide an alternative to the decades-old problem of data analysis of cholinesterase-catalyzed reactions, through the more complex Webb integrated rate equation.

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.

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.

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.

BACKGROUND: Many pharmacodynamic processes can be described by the nonlinear saturation kinetics that are most frequently based on the hyperbolic Michaelis-Menten equation. Thus, various time-dependent solutions for drugs obeying such kinetics can be expressed in terms of the Lambert W(x)-omega function. However, unfortunately, computer programs that can perform the calculations for W(x) are not widely available. To avoid this problem, the replacement of the integrated Michaelis-Menten equation with an empiric integrated 1--exp alternative model equation was proposed recently by Keller et al. (Ther Drug Monit. 2009;31:783-785), although, as shown here, it was not necessary.
METHODS: Simulated concentrations of model drugs obeying Michaelis-Menten elimination kinetics were generated by two approaches: 1) calculation of time-course data based on an approximation equation W2*(x) performed using Microsoft Excel; and 2) calculation of reference time-course data based on an exact W(x) function built in to the Wolfram Mathematica.
RESULTS: I show here that the W2*(x) function approximates the actual W(x) accurately. W2*(x) is expressed in terms of elementary mathematical functions and, consequently, it can be easily implemented using any of the widely available software. Hence, with the example of a hypothetical drug, I demonstrate here that an equation based on this approximation is far better, because it is nearly equivalent to the original solution, whereas the same characteristics cannot be fully confirmed for the 1--exp model equation. CONCLUSION: The W2*(x) equation proposed here might have an important role as a useful shortcut in optional software to estimate kinetic parameters from experimental data for drugs, and it might represent an easy and universal analytical tool for simulating and designing dosing regimens.

The Michaelis-Menten rate equation can be found in most general biochemistry textbooks, where the time derivative of the substrate is a hyperbolic function of two kinetic parameters (the limiting rate V, and the Michaelis constant K(M) ) and the amount of substrate. However, fundamental concepts of enzyme kinetics can be difficult to understand fully, or can even be misunderstood, by students when based only on the differential form of the Michaelis-Menten equation, and the variety of methods available to calculate the kinetic constants from rate versus substrate concentration "textbook data." Consequently, enzyme kinetics can be confusing if an analytical solution of the Michaelis-Menten equation is not available. Therefore, the still rarely known exact solution to the Michaelis-Menten equation is presented here through the explicit closed-form equation in terms of the Lambert W(x) function. Unfortunately, as the W(x) is not available in standard curve-fitting computer programs, the practical use of this direct solution is limited for most life-science students. Thus, the purpose of this article is to provide analytical approximations to the equation for modeling Michaelis-Menten kinetics. The elementary and explicit nature of these approximations can provide students with direct and simple estimations of kinetic parameters from raw experimental time-course data. The Michaelis-Menten kinetics studied in the latter context can provide an ideal alternative to the 100-year-old problems of data transformation, graphical visualization, and data analysis of enzyme-catalyzed reactions. Hence, the content of the course presented here could gradually become an important component of the modern biochemistry curriculum in the 21st century.

Various explicit reformulations of time-dependent solutions for the classical two-step irreversible Michaelis-Menten enzyme reaction model have been described recently. In the current study, I present further improvements in terms of a generalized integrated form of the Michaelis-Menten equation for computation of substrate or product concentrations as functions of time for more real-world, enzyme-catalyzed reactions affected by the product. The explicit equations presented here can be considered as a simpler and useful alternative to the exact solution for the generalized integrated Michaelis-Menten equation when fitted to time course data using standard curve-fitting software.

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.

The exact closed-form solution to the Michaelis-Menten equation is expressed in terms of the Lambert W(x) function. However, the utility of this solution is limited because the W(x) function is not widely available in curve-fitting software. Based on various approximations to the W(x) function, different explicit equations expressed in terms of the elementary functions are proposed here as useful shortcuts to fit time depletion of substrate concentration directly to progress curves using commonly available nonlinear regression computer programs. The results are compared with those obtained by fitting other algebraic equations that have been proposed previously in the literature.

In spite of several reports demonstrating that acetylcholinesterase (AChE [EC 3.1.1.7]) expression is importantly regulated at the level of its mRNA, we still know little about the relationship between AChE mRNA level and the level of mature, catalytically active enzyme in the cell. Better insight into this relationship is, however, essential for our understanding of the molecular pathways underlying AChE synthesis in living cells. We have approached this problem previously (Grubic et al., 1995; Brank et al., 1998; Mis et al., 2003; Jevsek et al., 2004); however, recently introduced small interfering RNA (siRNA) methodology, which allows blockade of gene expression at the mRNA level, opens new possibilities in approaching the AChE mRNA-AChE activity relationship. With this technique one can eliminate AChE mRNA in the cell, specifically and at selected times, and follow the effects of such treatment at the mature enzyme level. In this study we followed AChE activity in siRNA-treated cultured human myoblasts. Our aim was to find out how the temporal profile of the AChE mRNA decrease is reflected at the level of AChE activity under normal conditions and after inhibition of preexisting AChE by diisopropyl phosphorofluoridate (DFP).AChE activity was determined at selected time intervals after siRNA treatment in both myoblast homogenates and in culture medium to follow the effects of siRNA treatment at the level of intracellular AChE synthesis and at the level of AChE secreted from the cell.

The results of our recent investigations on the expression and distribution of acetylcholinesterase (EC. 3.1.1.7, AChE) in the experimental model of the in vitro innervated human muscle are summarized and discussed here. This is the only model allowing studies on AChE expression at all stages of the neuromuscular junction (NMJ) formation in the human muscle. Since it consists not only of the motor neurons and myotubes but also of glial cells, which are essential for the normal development of the motor neurons, NMJs become functional and differentiated in this system. We followed AChE expression at various stages of the NMJ formation and in the context of other events characteristic for this process. Neuronal and muscular part were analysed at both, mRNA and mature enzyme level. AChE is expressed in motor neurons and skeletal muscle at the earliest stages of their development, long before NMJ starts to form and AChE begins to act as a cholinergic component. Temporal pattern of AChE mRNA expression in motor neurons is similar to the pattern of mRNA encoding synaptogenetic variant of agrin. There are no AChE accummulations at the NMJ at the early stage of its formation, when immature clusters of nicotinic receptors are formed at the neuromuscular contacts and when occasional NMJ-mediated contractions are already observed. The transformation from immature, bouton-like neuromuscular contacts into differentiated NMJs with mature, compact receptor clusters, myonuclear accumulations and dense AChE patches begins at the time when basal lamina starts to form in the synaptic cleft. Our observations support the concept that basal lamina formation is the essential event in the transformation of immature neuromuscular contact into differentiated NMJ, with the accumulation of not only muscular but also neuronal AChE in the synaptic cleft.

The hydrolysis of substrates by cholinesterases does not follow the Michaelis-Menten reaction mechanism. The well-known inhibition by excess substrate is often accompanied by an unexpectedly high activity at low substrate concentrations. It appears that these peculiarities are the consequence of an unusual architecture of the active site, which conducts the substrate molecule over many stages before it is cleaved and released. Structural and kinetic data also suggest that two substrate molecules can attach at the same time to the free, as well as to the acetylated, enzyme. We present a procedure which provides an unbiased framework for mathematical modelling of such complex reaction mechanisms. It is based on regression analysis of a rational polynomial using classical initial rate data. The determination of polynomial degree reveals the number of independent parameters that can be evaluated from the available information. Once determined, these parameters can substantially facilitate the construction and evaluation of a kinetic model reflecting the expected molecular events in an enzymic reaction. We also present practical suggestions for testing the postulated kinetic model, using an original thermodynamic approach and an isolated effect in a specifically mutated enzyme.

We revisit a previous analysis of the classical Michaelis-Menten enzyme reaction for the case in which the free enzyme incurs the loss of its activity by an irreversible inhibitor concentration dependent but time unaltered rate constant (see Golicnik, M. J. Chem. Inf. Comput. Sci. 2002, 42, 157-161). We study the kinetic model of an enzyme-catalyzed reaction in the presence of an equimolar irreversible inhibitor showing a time dependent inactivation rate constant because of considerable inhibitor amount depletion during the course of the reaction. We show that an analytical solution containing the nonelementary Gauss hypergeometric function can be found for the reactants in equation Phi of an implicit type that precludes direct calculation of the extent of reaction at any time. The transformation theory of the hypergeometric function is used to obtain rapidly convergent power series, and for the root calculation of equation Phi the divergence-proof root bracketing algorithm according to Van Wijngaarden-Dekker-Brent is performed. Numerically generated data are analyzed according to this mathematical procedures, and the results are compared with ones obtained by the numerical integration treatment.

D-Tubocurarine, a reversible peripheral inhibitor of cholinesterases accelerates methanesulfonylation of Drosophila melanogaster wild type and W359L mutant. The kinetic evaluation of the process was performed in a step-by-step analysis. The second order overall sulfonylation rate constants, determined from classical residual activity measurements, were used in the subsequent analysis of progress curves. The latter were obtained by measuring the hydrolysis of acetylthiocholine in a complex reaction system of enzyme, substrate, irreversible and reversible inhibitor. The underlying kinetic mechanisms, from such a complex data, could only be untangled by targeted inspection and successive incorporation of reaction steps for which experimental evidence existed. The study showed that the peripheral ligand D-tubocurarine, by binding at the entrance into the active site of the two investigated enzymes (Golicnik et al., Biochemistry 40 (2001) 1214), enhances the affinity for small methanesulfonylfluoride, rather to speeding up the formation of a stable covalent enzyme-inhibitor complex. The specific arrangements at the rim of the active site of each individual enzyme dictate the actual events which can be detected by kinetic means.

The analytical equation describing progress curves of an enzyme catalyzed reaction acting upon the Michaelis-Menten mechanism has been known for the case in which only the free enzyme incurs a loss of its activity, either spontaneously or as a result of an irreversible inhibitor action. The solution of differential equations which defines the rates of enzyme inactivation and substrate utilization is expressed by a nonelementary function in equation of an implicit type that precludes direct calculation of the extent of reaction at any time. Previously, the implicit equations have been rearranged to the alternative formulas and solved by the Newton-Raphson method, but this procedure may fail when used upon the presented equation. For this reason the other root-finding numerical method was applied, and the enzyme kinetic parameters of such numerically solved implicit equation for the reaction mechanism of irreversibly inhibited acetylcholinesterase were fitted to the experimental data by a nonlinear regression computer program.

The mechanism of action of a potent peptidic inhibitor fasciculin 2 (Fas2) on electric eel acetylcholinesterase (eleelAChE) has been examined in a three-level analysis. Classical steps included equilibration experiments for the evaluation of high affinity binding constant and the existence of residual hydrolytic activity in a solution of completely Fas2 saturated enzyme. The two rate constants for the association (k(on)) and the dissociation (k(off)) of Fas2 with free enzyme were determined by the time course of residual enzyme activity measurements. In the third step, with a nonclassical progress curve analysis, we found that the Fas2-enzyme complex exhibited hydrolytic activity in a butyrylcholinesterase-like kinetics. The switch appears to be a consequence of steric obstruction, but also the consequence of subtle rapid conformational changes around catalytic site, upon slow single-step binding of large Fas2 molecule at the peripheral site. An unusual unilateral effect of bound Fas2 is reflected by acylation-independent association and dissociation rates and might indeed be due to inability of small acylation agent to influence the binding of a large opponent.

The kinetic rate constants for interaction of (-)-eseroline-(3aS-cis)-1,2,3,3a,8,8a-hexahydro-1,3a,8-trimethylpyrrolo-[2,3-b]in dol-5-ol with electric eel acetylcholinesterase (EC 3.1.1.7, acetylcholine acetylhydrolase) were measured at a low substrate concentration according to a transient kinetic approach by using a rapid experimental technique. The measurements were carried out on a stopped-flow apparatus where pre-incubated samples of enzyme with various inhibitor concentrations were diluted with a buffer solution containing the substrate. The experimental data in the form of sigmoid-shaped progress curves were analysed by applying an explicit progress curve equation that described the time dependence of product released during the reaction. The kinetic parameters were evaluated by non-linear regression treatment and the values of the corresponding constants showed approximately the equal affinities of eseroline and eserine (cf. Stojan, J. and Zorko, M. (1997) Biochim. Biophys. Acta, 1337, 75-84.) for binding into the active centre of the enzyme. On the other hand, the kinetic rates for association and dissociation of eseroline were two grades of magnitude higher than those of eserine. The explanation appears to be a substantionally impaired gliding of eserine into the active site gorge by the great mobility of the carbamoyl tail as well as by its numerous possible interactions with the residues lining the gorge. Additionally, a study of the dependence of the transition phase information on the inhibitor concentration was carried out using our experimental data.

The action of a potent tricyclic cholinesterase inhibitor ethopropazine on the hydrolysis of acetylthiocholine and butyrylthiocholine by purified horse serum butyrylcholinesterase EC 3.1.1.8 was investigated at 25 and 37 C The enzyme activities were measured on a stopped-flow apparatus and the analysis of experimental data was done by applying a six-parameter model for substrate hydrolysis The model which was introduced to explain the kinetics of Drosophila melanogaster acetylcholinesterase Stojan et al 1998 FEBS Lett 440 85?88 is defined with two dissociation constants and four rate constants and can describe both cooperative phenomena apparent activation at low substrate concentrations and substrate inhibition by excess of substrate For the analysis of the data in the presence of ethopropazine at two temperatures we have enlarged the reaction scheme to allow primarily its competition with the substrate at the peripheral site but the competition at the acylation site was not excluded The proposed reaction scheme revealed upon analysis competitive effects of ethopropazine at both sites at 25 C three enzyme inhibitor dissociation constants could be evaluated at 37 C only two constants could be evaluated Although the model considers both cooperative phenomena it appears that decreased enzyme sensitivity at higher temperature predominantly for the ligands at the peripheral binding site makes the determination of some expected enzyme substrate and/or inhibitor complexes technically impossible The same reason might also account for one of the paradoxes in cholinesterases activities at 25 C at low substrate concentrations are higher than at 37 C Positioning of ethopropazine in the active-site gorge by molecular dynamics simulations shows that A328 W82 D70 and Y332 amino acid residues stabilize binding of the inhibitor 2002 Elsevier Science

Tetraalkylammonium (TAA) salts are well known reversible inhibitors of cholinesterases. However, at concentrations around 10 mm, they have been found to activate the hydrolysis of positively charged substrates, catalyzed by wild-type human butyrylcholinesterase (EC 3.1.1.8) [Erdoes, E.G., Foldes, F.F., Zsigmond, E.K., Baart, N. & Zwartz, J.A. (1958) Science 128, 92]. The present study was undertaken to determine whether the peripheral anionic site (PAS) of human BCHE (Y332, D70) and/or the catalytic substrate binding site (CS) (W82, A328) are involved in this phenomenon. For this purpose, the kinetics of butyrylthiocholine (BTC) hydrolysis by wild-type human BCHE, by selected mutants and by horse BCHE was carried out at 25 degreeC and pH 7.0 in the presence of tetraethylammonium (TEA). It appears that human enzymes with more intact structure of the PAS show more prominent activation phenomenon. The following explanation has been put forward: TEA competes with the substrate at the peripheral site thus inhibiting the substrate hydrolysis at the CS. As the inhibition by TEA is less effective than the substrate inhibition itself, it mimics activation. At the concentrations around 40 mm, well within the range of TEA competition at both substrate binding sites, it lowers the activity of all tested enzymes.

The kinetic behaviour of insect acetylcholinesterases deviates from the Michaelis-Menten pattern. These deviations are known as activation or inhibition at various substrate concentrations and can be more or less observable depending on mutations around the active site of the enzyme. Most kinetic studies on these enzymes still rely on initial rate measurements. It is demonstrated here that according to this method one of the deviations can be overlooked. We attempt to point out that in such cases a detailed step-by-step progress curves analysis is successful. The study is focused on two different methods of analysing progress curves: (i) the first one is based on an integrated initial rate equation which can sufficiently fit truncated progress curves under corresponding conditions; and (ii) the other one precludes the algebraic formulae, but uses numerical integration for searching a non analytical solution of ordinary differential equations describing a kinetic model. All methods are tested on three different acetylcholinesterase mutants from Drosophila melanogaster. The results indicate that kinetic parameters for the E107K mutant with highly expressive activation and inhibition can be well evaluated applying any analysis method. It is quite different for E107W and E107Y mutants where latent activation is present, but discovered only using one or the other progress curves analysis methods.

Homotropic cooperativity in Drosophila melanogaster acetylcholinesterase seems to be a consequence of an initial substrate binding to a high-affinity peripheral substrate binding site situated around the negative charge of D413 (G335, Torpedo numbering). An appropriate mutation which turns the peripheral binding site to a low-affinity spot abolishes apparent activation but improves the overall enzyme effectiveness. This contradiction can be explained as less effective inhibition due to a shorter occupation of such a peripheral site. A similar effect can be achieved by an appropriate peripheral inhibitor such as TC, which can in special cases, when less effective heterotropic inhibition prevails over homotropic, acts as an activator. At the highest substrate concentrations, however, these enzymes are always inhibited, although steric components may influence the strength of inhibition like in the F368G mutant (F290, Torpedo numbering). Cooperative effects thus may include a steric component, but covering of the entrance must affect influx and efflux to different extents.