Interactions of the Organophosphates Paraoxon and Methyl Paraoxon with Mouse Brain Acetylcholinesterase

Stacey A. Kardos and Lester G. Sultatos1

Department of Pharmacology and Physiology, New Jersey Medical School, University of Medicine and Dentistry of New Jersey, 185 South Orange Avenue, Newark, New Jersey 07103

Received May 23, 2000; accepted August 2, 2000


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The mechanism of acute toxicity of the organophosphorus insecticides has been known for many years to be inhibition of the critical enzyme acetylcholinesterase (EC 3.1.1.7), with the resulting excess acetylcholine accumulation leading to symptoms of cholinergic excess. The bimolecular inhibition rate constant ki has been used for decades to describe the inhibitory capacity of organophosphates toward acetylcholinesterase. In the current study, a new approach based on continuous systems modeling was used to determine the appkis of paraoxon and methyl paraoxon towards mouse brain acetylcholinesterase over a wide range of oxon concentrations. These studies revealed that the bimolecular inhibition rate constants for paraoxon and methyl paraoxon appeared to change as a function of oxon concentrations. For example, the appki found with a paraoxon concentration of 1000 nM was 0.16 nM–1h–1, whereas that for 0.1 nM paraoxon was 1.60 nM–1h–1, indicating that the efficiency of phosphorylation appeared to decrease as the paraoxon concentration increased. These data suggested that the current understanding of how these organophosphates interact with acetylcholinesterase is incomplete. Modeling studies using several different kinetic schemes, as well as studies using recombinant monomeric mouse brain acetylcholinesterase, suggested the existence of a second binding site in addition to the active site of the enzyme, to which paraoxon and methyl paraoxon bound, probably in a reversibly manner. Occupation of this site likely rendered more difficult the subsequent phosphorylation of the active site by other oxon molecules, probably by steric hindrance or allosteric modification of the active site. It cannot be ascertained from the current study whether the putative second binding site is identical to or shares common elements with the well-characterized propidium-specific peripheral binding site of acetylcholinesterase.

Key Words: paraoxon; methyl paraoxon; organophosphate; acetylcholinesterase; peripheral binding site; computer modeling.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The mechanism of the acute toxicity of the organophosphorus insecticides has been known for many years to be inhibition of the critical enzyme acetylcholinesterase (EC 3.1.1.7), with the resulting excess acetylcholine accumulation leading to symptoms of cholinergic excess (Mileson et al., 1998Go). Inhibition occurs as a result of phosphorylation of the serine (S200) included in the catalytic triad of the active center by the organophosphate (Aldridge, 1950Go; Aldridge and Reiner, 1972Go; Fukuto, 1990Go; Rachinsky et al., 1990Go; Sussman et al., 1991Go). Although this reaction is usually considered irreversible, reactivation of phosphorylated acetylcholinesterase can occur slowly as a result of hydrolytic cleavage (Aldridge and Reiner, 1972Go; Sultatos, 1994Go), provided the process of aging has not occurred. Aging is a poorly understood reaction in which one alkoxy group is hydrolyzed, leaving the monoalkoxy phosphate bound essentially irreversibly to the active site of the enzyme (Sultatos, 1994Go). In the absence of aging, the phosphorylation of acetylcholinesterase by organophosphates is often viewed kinetically as a Ping Pong Bi Bi reaction that reduces to an Ordered Uni Bi reaction, as water, the second substrate, is present in excess (Segel, 1975Go) (Fig. 1AGo).



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FIG. 1. Kinetic mechanisms for the interaction of an organophosphate (AB) with acetylcholinesterase (AChE) that form the bases for the models utilized. Panel A represents the basis for the full kinetic model based on an Ordered Uni Bi kinetic mechanism. The two dots to the right of AChE represent reversible binding of AB to the active site vicinity, while the solid line to the right of AChE represents the covalent bond between S200 at the active site and the phosphoryl moiety (A) of AB. Water is not indicated as the second substrate, as it is present in excess. Panel B represents the basis for the ki model, utilizing the concept of ki developed by Main (1964). Ki is defined in terms of rate constants indicated in Panel A. Panel C represents the basis for the p-site model. The rate constants k+1 and k-1 describe reversible binding of AB to a peripheral binding site, and the two dots to the left of AChE represent the reversible binding of AB to the peripheral binding site. Ki` represents an altered ki as a result of occupation of a peripheral binding site. In all panels the first-order rate constant k3 represents reactivation of phosphorylated enzyme.

 
The classic report of Main (1964) derived a bimolecular rate constant, ki, that quantifies the inhibitory power of an organophosphate toward acetylcholinesterase (Fig. 1BGo). This bimolecular rate constant includes in its derivation an affinity constant as well as a phosphorylation constant (Main, 1964Go) (Fig. 1BGo), and therefore recognizes that the inhibitory power of an organophosphate can be a function of both binding affinity to the active site and the rate of phosphorylation (Main, 1964Go). This bimolecular rate constant continues to be used as the single best approach for comparing inhibitory powers of various organophosphates (Fukuto, 1990Go; Mortensen et al., 1998Go).

Subsequent to the derivation of ki (Main, 1964Go), a variety of approaches were undertaken to determine experimentally ki, as well as the affinity constant (Ka in Figure 1BGo) and the phosphorylation constant (k2 in Figure 1AGo) (Hart and O'Brien, 1973Go, 1976Go; Main and Iverson, 1966Go). However, all have been based upon the original procedure developed by Main (1964), and all have been limited by the assumption that the reaction in vitro approximates first-order conditions with respect to uninhibited enzyme (i.e., the oxon concentration is much higher than the enzyme concentration). In contrast, using a new approach capable of utilizing any organophosphate concentration relative to the enzyme concentration for determination of ki, preliminary studies from this laboratory suggested that the appki of paraoxon for mouse brain acetylcholinesterase changed as a function of the paraoxon concentration. This report was undertaken to characterize this relationship and to explore possible mechanisms that might account for such a phenomenon.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Chemicals.
Paraoxon (O,O-diethyl O-(p-nitrophenyl) phosphate) and methyl paraoxon (O,O-dimethyl O-(p-nitrophenyl) phosphate) were purchased from Chem Services (West Chester, PA). Acetylthiocholine chloride (ATC), 5,5`-dithio-bis (2-nitrobenzoic acid)(DTNB), glycerol, and tetraisopropylpyrophosphoramide (iso-OMPA) were purchased from Sigma Chemical Company (St. Louis, MO).

Animals and tissue preparations.
Male TAC:(SW)FBR Swiss mice (20–30 g) were purchased from Taconic Farms (Germantown, NY). They were housed under standard laboratory conditions and given free access to water and food (Purina Rodent Chow 5001). Recombinant monomeric mouse brain acetylcholinesterase was kindly provided by Dr. Palmer Taylor (University of California, San Diego, La Jolla, CA).

Mice were decapitated, and their brains were immediately removed and placed on ice. They were weighed, pooled, and homogenized in 9 volumes of 100 mM sodium phosphate buffer (pH 7.4) (phosphate buffer), using a Polytron® homogenizer (Brinkmann Instruments, Westbury, NY). The homogenates were stored in individual 1-ml aliquots at –70°C.

Incubations and assay.
After thawing, a 1-ml aliquot of homogenate was added to 13 ml of phosphate buffer. All homogenate incubations included 200 µl of this diluted mouse brain homogenate in a total volume of 400 µl, with the indicated oxon concentrations, as described by Wang and Murphy (1982a). Incubations were done at either 23°C or 37°C in a shaking water bath. Controls did not include organophosphate, or received the organophosphate at the end of the incubation, just before addition of buffer for the determination of activity (see below). No differences in results were observed with or without the addition of 3 mM EDTA to the buffer to inhibit A-esterase (Sultatos, 1994; data not shown), so EDTA was not routinely included. Similarly, inclusion of 100 µM iso-OMPA to inhibit butyrylcholinesterase (EC 3.1.1.8) (Mortensen et al., 1998Go) had a negligible effect on the results (data not shown), and was therefore not routinely included in the incubations.

Due to the instability of recombinant monomeric mouse brain acetylcholinesterase, incubations containing this enzyme preparation and oxon were performed at 4°C in phosphate buffer containing 50% glycerol in a total volume of 3050 µl. The final enzyme concentration was 0.4318 nM. Previous studies have documented that glycosylation, which is lacking in recombinant monomeric mouse brain acetylcholinesterase, is required for thermal stability but not catalytic activity (Velan et al., 1993Go).

Uninhibited mouse brain acetylcholinesterase was determined by the Ellman method (Ellman et al., 1961Go). In the case of mouse brain homogenate assays, incubations were terminated by dilution with 4.6 ml phosphate buffer. ATC was added to give a final concentration of 0.4 mM, and DTNB was added to give a final concentration of 0.1 mM, with a final volume of 5 ml. These incubations were carried out for 30 min in a shaking water bath at 23°C. The change in absorbance at 412 nm was used as an indication of uninhibited acetylcholinesterase. Measurement of uninhibited recombinant monomeric mouse brain acetylcholinesterase was performed in a similar manner, except that 500 µl of the recombinant acetylcholinesterase incubation was removed and diluted with 10 ml phosphate buffer with 0.4 mM ATC and 0.1 mM DTNB. This incubation was carried out at 23°C for 7 min, and the change in absorbance at 412 nm was recorded.

Model structures.
Several computer models were used. The first, referred to as the ki model, was based on the equation derived by Main (1964) (Fig. 1BGo). The equations descriptive of this model were as follows:

(1)

(2)

(3)
where Vt represents the volume of the incubation, AChET represents the total concentration of acetylcholinesterase (both inhibited and uninhibited), ABT represents the starting concentration of organophosphate, and all other symbols are as defined in Figure 1Go. It should be noted that no evidence of aging was observed in any of the studies in the current report. For example, complete reactivation of inhibited enzyme occurred after inhibition by 0.1 nM paraoxon (Fig. 2Go). Therefore, aging was not included in the models. The second modelused, referred to as the full kinetic model, was based on the Ordered Uni Bi reaction summarized in Figure 1AGo. The equations descriptive of this model were as follows:

(4)

(5)

(6)

(7)



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FIG. 2. Determination of enzyme active site concentration and appki at a paraoxon concentration of 0.1 nM. The upper panel shows the profile of enzyme activity with time, using the optical density (OD) as a measure of activity. Circles represent experimental data where each is a single observation. The dashed line in the upper panel represents the mean control OD (0.72) at time zero, whereas the dotted line represents the mean OD of maximal inhibition (0.55) (occurring at 6 h). The lower panel shows the optimized simulation and the experimental data. The best-fit was found when total enzyme active site concentration was 0.4318 nM, with an appki of 1.6 nM–1h–1 (from Fig. 4Go).

 
The symbols are the same as those described above for the ki model, or are defined in Figure 1Go. The third model, the p-site model, was based on the presence of a peripheral binding site on acetylcholinesterase, which, when occupied by paraoxon, altered the appki for paraoxon (Fig. 1CGo). The equations descriptive of this model were as follows:

(8)

(9)


(10)

(11)

(12)
The symbols are the same as those described above for the ki model, or are defined in Figure 1CGo. All simulations were performed on desktop computers using Advance Continuous Simulation Language (ACSL, Mitchell and Gauthier Associates, Concord, MA).

Determination of parameters through model optimization.
Appkis were determined by optimization of the ki model to experimental data. The optimization procedure consisted of determination of that appki that gave the best-fit (as judged by the smallest sum of squares) to the experimental data. Optimization for acetylcholinesterase active site concentration in mouse brain homogenate was accomplished with experimental data transformed as percent of control to account for heterogeneous variance. In certain instances, Monte Carlo simulations were incorporated into the modeling in order to estimate standard deviations for optimized appkis. In these cases, Monte Carlo simulations were performed with a computer program modified from that of Thomas et al. (1996), written in ACSL. Simulations were truncated at zero, as negative values (which otherwise would occasionally appear) for the parameters simulated cannot occur biologically. Means and standard deviations of experimental data for organophosphate-induced inhibition of acetylcholinesterase activity over time were incorporated into Monte Carlo simulations to generate 1000 optimizations, from which the appki standard deviations were calculated. All experimental data used in the Monte Carlo simulations were judged normally distributed by the Kolmogorov-Smirnov test for normality.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Before the models shown schematically in Figure 1Go could be applied routinely to in vitro incubations of paraoxon and mouse brain homogenates, the acetylcholinesterase active site concentration within the incubations had to be established. Inspection of the profile of enzyme activity with time following addition of 0.1 nM paraoxon at room temperature revealed that maximum inhibition was 26% of total activity (Fig. 2Go, upper panel). Consequently, in the absence of reactivation of phosphorylated enzyme, the concentration of acetylcholinesterase active sites within the incubation would have been 0.3846 nM, as one molecule of paraoxon inhibits one active site of acetylcholinesterase (Figs. 1A and 1BGoGo). However, due to the occurrence of enzyme reactivation simultaneously with enzyme inhibition (Figs. 1A, 1B, and 3GoGoGo), a final, more refined estimate of enzyme active site concentration had to be determined through optimization of active site concentration in conjunction with optimization of appki (Fig. 4Go). This process yielded final values of 0.4318 nM for acetylcholinesterase active sites and 1.6 nM–1h–1 for appki (Fig. 4Go and Fig. 2Go, lower panel). Figure 2Go also established that enzyme activity returned to control levels by 24 h, demonstrating the lack of significant aging of phosphorylated acetylcholinesterase under these conditions.



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FIG. 3. Determination of the first-order reactivation constant for acetylcholinesterase inhibited by 0.1 nM paraoxon. Circles represent the best-fit for the terminal portion of the curve. The first-order reactivation constant (k3 in Fig. 1Go), calculated as described by Levine and Murphy (1977), was found to be 0.07 h–1.

 


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FIG. 4. Three-dimensional plot of enzyme active site concentration (E), appki, and sum of squares. The sum of squares represents the measure of the goodness of fit between the computer simulations and the empirical data. Regression analyses yielded the minimal sum of squares at E = 0.4318 nM and appki = 1.60 nM–1h–1.

 
Surprisingly, determinations of appkis for a range of concentrations of paraoxon (Fig. 5Go) revealed that the appki changed as a function of paraoxon concentration, yielding a relationship described by the equation for a rectangular hyperbola (Fig. 6Go). The method for determination of appki originally described by Main (1964) was also used to estimate an appki for paraoxon at inhibitor concentrations of 5 nM and greater. Data generated with lower oxon concentrations were not used, as those incubations did not satisfy the underlying assumption of first-order conditions with respect to uninhibited enzyme (Main, 1964Go). Calculations as described by Main (1964) yielded an appki of 0.19 nM–1h–1 (Figs. 7 and 8GoGo), thereby validating the model optimization routines, which provided an identical appki for paraoxon concentrations many times greater than enzyme concentration (Fig. 6Go).



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FIG. 5. Determinations of appki at 1 nM (upper panel), 200 nM (middle panel), and 1000 nM (lower panel) paraoxon. Circles represent experimental data where each is a single observation. The solid lines represent the simulation of the ki model (Fig. 1BGo) optimized for appki. The appkis were found to be as follows: at 1 nM paraoxon, 0.32 nM–1h–1; at 200 nM paraoxon, 0.14 nM–1h–1; and at 1000 nM paraoxon, 0.16 nM–1h–1.

 


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FIG. 6. Nonlinear regression analysis of the relationship between appki and paraoxon concentration (PO) at 23°C (room temperature). Data were fit to the equation appki = 1/((A*PO)/(B + PO) + I). The following values were obtained: A = 5.36; B = 1.86; I = 0.34; and r2 = 0.98; therefore, the y intercept was 2.94 nM–1h–1, and the appki at an infinitely high concentration of paraoxon was 0.19 nM–1h–1.

 


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FIG. 7. Inhibition of mouse brain homogenate acetylcholinesterase with time at various paraoxon concentrations. The upper panel shows the optical density from the Ellman assay versus the time of the oxon incubation for oxon concentrations of 5 nM (circles) or 15 nM (triangles). The lower panel shows the same, except with paraoxon concentrations of 200 nM (circles), 500 nM (triangles), or 1000 nM (squares). Lines represent the best-fit to the data with all correlation coefficients equal to or greater than 0.98, except for the 15 nM paraoxon data set where r2 = 0.95. Determination of line slopes represents the first step in the calculation of the appki as described by Main (1964).

 


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FIG. 8. Secondary plot for determination appki of paraoxon towards mouse brain acetylcholinesterase. When the reciprocal of the paraoxon concentration (ordinate) is plotted against the reciprocal of the slopes (abscissa) obtained from the curves in Figure 7Go (where v equals the optical densities from Fig. 7Go), the slope of the resultant line is the appki (Main, 1964Go). The straight line represents the best-fit by regression analyses, with r2 = 0.99, and an appki (slope) of 0.19 nM–1h–1.

 
An appki that changed as a function of oxon concentration was also observed with incubations at 37°C and with methyl paraoxon, as well as with recombinant mouse brain acetylcholinesterase (Fig. 9Go). It should be noted that the appkis descriptive of the interaction of paraoxon and recombinant mouse brain acetylcholinesterase were substantially lower than other appkis (Figs. 5, 6, and 9GoGoGo). The slower phosphorylation of recombinant mouse brain acetylcholinesterase by paraoxon, compared to mouse brain homogenate, reflected the incubation conditions required to prevent spontaneous breakdown of the enzyme (i.e., the presence of glycerol and incubation temperatures of 4°C).



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FIG. 9. Variable appkis for methyl paraoxon at 37°C (A), paraoxon at 37°C (B), and recombinant monomeric mouse brain acetylcholinesterase at 4°C (C). In all cases, each bar represents an appki obtained from optimization of an experimental data set. Standard deviations were obtained from Monte Carlo simulations as described in the Materials and Methods section.

 
Several steps in the derivation of ki by Main (1964) required the assumption that interaction of an organophosphate with acetylcholinesterase was first order with respect to the enzyme (i.e., that the inhibitor concentration was great enough to prevent its significant decrease during the course of the reaction). Consequently, the validity of the application of the concept of ki under conditions that violated this assumption had to be determined to evaluate if deviation from first-order conditions might have accounted for the relationship observed in Figure 6Go. Therefore, a full kinetic model was developed (Fig. 1AGo) with imagined or "supposed" values assigned to each parameter of the model (Table 1Go). Subsequently, a ki model was constructed with an appki calculated from the full kinetic model parameters (Table 1Go). Solution of both models at inhibitor concentrations much lower and much higher than the enzyme concentration revealed essentially identical outputs from each model (Fig. 10Go), demonstrating that the use of ki to describe the interaction between acetylcholinesterase and an inhibitor is valid, regardless of the reaction order.


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TABLE 1 Values of Critical Kinetic Parameters Used in the Full Kinetic and ki Models
 


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FIG. 10. Comparison of the output from the full kinetic model (solid line) and the ki model (dotted line) at 500 nM paraoxon (upper panel) and 0.1 nM paraoxon (lower panel). Critical parameter values are shown in Table 1Go.

 

    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Because the application of ki is valid under first-order or second-order conditions (Fig. 10Go), the observed changes in appki as a function of inhibitor concentration (Fig. 6Go) demonstrated that the current understanding of how organophosphates interact with acetylcholinesterase is incomplete. The kinetic schemes represented in Figures 1A and 1BGoGo allow only for a single, constant value for ki, indicating their inability to explain the current results.

Anomalous kinetic results for the interaction of diisopropylfluorophosphate with acetylcholinesterase have been attributed previously to multiple forms of the enzyme with differential sensitivities to this organophosphate (Main, 1969Go). The existence of multiple forms of mouse brain acetylcholinesterase with differential sensitivities towards paraoxon and methyl paraoxon could provide an explanation for the change in appki as a function of inhibitor concentration. However, this explanation seems unlikely, as their differential sensitivities would have to be striking (the appki for paraoxon changed from 2.94 nM–1h–1 to 0.19 nM–1h–1; Fig. 6Go). Although multiple forms of acetylcholinesterase exist in the mouse, they are all the product of a single gene and have a constant catalytic core. Their differences arise through alternative mRNA processing and association of the catalytic subunits with structural subunits (Taylor and Radic, 1994Go). In addition, Friboulet et al. (1990) have demonstrated that all the molecular forms of muscle acetylcholinesterase have similar susceptibilities to inhibition by O-ethyl S-(2-(diisopropylamino)ethyl) methyphosphonothioate (MPT). Furthermore, Mortensen et al. (1998) have shown that no age-dependent or tissue-specific differences in acetylcholinesterase sensitivity towards chlorpyrifos oxon exist in the rat after immunoprecipitation of the enzyme.

Although the existence of multiple acetylcholinesterases with differential sensitivities toward paraoxon and methyl paraoxon cannot be entirely discounted, a more credible explanation for the unusual kinetic behavior presented in the current report involves a second binding site on acetylcholinesterase, distinct from the active site, to which paraoxon and methyl paraoxon could bind reversibly, and through allosteric modification or steric hindrance impede the subsequent phosphorylation of the active site by additional oxon molecules (hence decreasing the appki) (Fig. 1CGo). This hypothesis is supported by the observation that recombinant monomeric mouse brain acetylcholinesterase also displayed an appki that changed as a function of the paraoxon concentration (Fig. 9Go). A second or peripheral binding site on acetylcholinesterase, first suggested by Changeux (1966), was implied by an early study of Aldridge and Reiner (1969), which proposed that haloxon (di-(2-chloroethyl) 3-chloro-4-methylcoumarin-7-yl phosphate), coroxon (diethyl 3-chloro-4-methylcoumarin-7-yl phosphate), coumarin, acetylcholine, and acetylthiocholine can bind to this second site, thereby decreasing the reactivity of the active site. Subsequent studies have established the existence of a peripheral binding site that has been characterized by site-directed mutagenesis (Barak et al., 1994Go, 1995Go; Radic et al., 1993Go; Shafferman et al., 1992Go; Velan et al., 1996Go). Binding of ligands such as propidium and fasciculin, specific for this peripheral site, appears to inhibit enzymatic activity by allosteric modification of the active site through affecting the orientation of the Trp-86 indole moiety located at the base of the gorge that contains the active site (Barak et al., 1995Go; Berman et al., 1980Go; Bourne et al., 1995Go, 1999Go; Radic et al., 1984Go, 1991Go, 1995Go; Taylor and Lappi, 1975Go; Taylor and Radic, 1994Go; Velan et al., 1996Go).

Whereas the report of Aldridge and Reiner (1969) implied that the organophosphates haloxon and coroxon bound reversibly to a peripheral binding site, Friboulet et al. (1990) established directly that the organophosphorus compound MPT bound reversibly to the peripheral binding site, thereby reducing its own turnover at the active site. Other organophosphates have been thought not to bind to this site, as they have been reported to follow simple second-order kinetics (Aldridge and Reiner, 1972Go; Friboulet et al., 1990Go; Hart and O'Brien, 1973Go). However, the current study indicates that, at least with paraoxon and methyl paraoxon, inhibitor concentrations similar to that of enzyme (i.e., not many times higher than the acetylcholinesterase concentration) must be used in order to observe their anomalous kinetic behavior (Fig. 6Go), conditions that have not been satisfied by previous kinetic studies. In that regard, the appki determined at a paraoxon concentration (1000 nM) far greater than the enzyme concentration (0.4398 nM) (Fig. 5Go) was similar to that determined by the method developed by Main (1964) (Figs. 7 and 8GoGo). Moreover, the appkis determined at high oxon levels in the current study (0.19 nM–1h–1) (Figs. 6–8GoGoGo) are in close agreement to those reported previously by Wang and Murphy (1982b) (0.11 nM–1h–1) for paraoxon and acetylcholinesterase in rat brain homogenate.

In order to determine if the binding of paraoxon (or methyl paraoxon) to such a peripheral binding site could account for the changes in appki as a function of paraoxon concentration (Fig. 6Go), a kinetic model incorporating appki and a peripheral binding site (Fig. 1CGo, referred to as the p-site model) was constructed. In this model, appki had two possible values depending on whether or not the peripheral binding site was occupied by paraoxon. It should be noted that this exercise was not intended to yield a best-fit simulation for in vitro inhibition of acetylcholinesterase by paraoxon (such as that shown in Figs. 2 and 5GoGo), but was instead meant to determine if the interaction of paraoxon with a peripheral binding site could, in theory, account for the relationship observed in the current study between paraoxon concentration and appki (Fig. 6Go). Nonlinear regression analyses revealed the relationship between appki and paraoxon concentration was best-fit by a rectangular hyperbola, with a theoretical appki of 2.94 nM–1h–1 at 0 nM paraoxon, and an appki of 0.19 nM–1h–1 when paraoxon was infinitely high (Fig. 6Go). Therefore, with the peripheral binding site unoccupied (at 0 nM paraoxon) the appki was 2.94 nM–1h–1. Similarly, paraoxon's binding to the peripheral binding site, which became saturated at about 3 nM paraoxon (Fig. 6Go), reduced the appki to 0.19 nM–1h–1. Consequently 2.94 nM–1h–1 and 0.19 nM–1h–1 represented appki and appki`, respectively, in the p-site model, based on the scheme outlined in Figure 1CGo. Although optimization studies could not reveal the actual values for appk+1 and appk1 in Figure 1CGo, it could be shown that

(13)
and that k+1 was likely greater than 50 nM–1h–1, indicating that binding to the peripheral site in this model was rapid (data not shown). Computer simulations with the p-site model under a variety of paraoxon concentrations (see Figure 11Go for two examples) indicated that the kinetic scheme that included a peripheral binding site for paraoxon (Fig. 1CGo) adequately described the in vitro interaction of paraoxon and mouse brain acetylcholinesterase (Fig. 6Go).



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FIG. 11. Comparison of output from the ki model (solid line) and the p-site model (dotted line) at 1000 nM paraoxon (upper panel) and 0.1 nM paraoxon (lower panel). The ki model (Fig. 1BGo) utilized appkis calculated from the equation presented in Figure 6Go (1.63 nM–1h–1 for a paraoxon concentration of 0.1 nM, and 0.19 nM–1h–1 for a paraoxon concentration of 1000 nM). The p-site model (Fig. 1CGo) utilized an appki of 2.94 nM–1h–1 when the peripheral site was unoccupied, and an appki` of 0.19 nM–1h–1 when the peripheral site was occupied (Fig. 6Go).

 
The data presented in the current study indicate that the capacity of individual paraoxon and methyl paraoxon molecules to inhibit acetylcholinesterase is variable, depending on the concentration of oxon relative to that of the enzyme (Fig. 6Go). Individual molecules of paraoxon and methyl paraoxon have a greater inhibitory capacity (as assessed by the appki) as the total paraoxon concentration is reduced (Fig. 6Go). Although the occurrence of this phenomenon in vivo cannot be directly confirmed, there currently does not exist a compelling reason to conclude that it is restricted to in vitro incubations. Therefore, these data suggest that the extrapolation of acetylcholinesterase activity after high doses of parathion or methyl parathion to activity at low doses of these insecticides must be done cautiously, as the capacity of individual oxon molecules to inhibit acetylcholinesterase varies as a function of oxon concentration.

In summary, the data presented in the present study suggest that the reversible binding of paraoxon or methyl paraoxon to a site on acetylcholinesterase distinct from the active site reduces their subsequent capacity to phosphorylate the active site. However it cannot be ascertained from these data whether this putative second site is identical to or overlaps with the well-established propidium-specific peripheral binding site of acetylcholinesterase. In that regard, Radic and Taylor (1999) have reported that the peripheral site ligands propidium, gallamine, D-tubocurarine, and atropine enhanced paraoxon's rate of inhibition of wild-type mouse acetylcholinesterase, whereas coumarin derivatives inhibited this same reaction. However, the absence of details regarding the paraoxon and enzyme concentrations make the interpretation of these results difficult within the context of the current report.


    NOTES
 
1 To whom correspondence should be addressed. Fax: (973) 972-4554. E-mail: sultatle{at}umdnj.edu Back


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Aldridge, W. N. (1950). Some properties of specific cholinesterase with particular reference to the mechanism of inhibition by diethyl p-nitrophenyl thiophosphate and analogs (E605). Biochem. J. 46, 451–460.[ISI]

Aldridge, W. N., and Reiner, E. (1969). Acetylcholinesterase. Two types of inhibition by an organophosphorus compound: one the formation of phosphorylated enzyme and the other analogous to inhibition by substrate. Biochem. J. 115, 147–162.[ISI][Medline]

Aldridge, W. N., and Reiner, E. (1972). Enzyme Inhibitors as Substrates. Interactions of Esterases with Esters of Organophosphorus and Carbamic Acids. North Holland, Amsterdam.

Barak, D., Kronman, C., Ordentlich, A., Ariel, N., Bromberg, A., Marcus, D., Lazar, A., Velan, B., and Shafferman, A. (1994). Acetylcholinesterase peripheral anionic site degeneracy conferred by amino acid arrays sharing a common core. J. Biol. Chem. 269, 6296–6305.[Abstract/Free Full Text]

Barak, D., Ordentlich, A., Bromberg, A., Kronman, C., Marcus, D., Lazar, A., Ariel, N., Velan, B., and Shafferman, A. (1995). Allosteric modulation of acetylcholinesterase activity by peripheral ligands involves a conformational transition of the anionic subsite. Biochemistry 34, 15444–15452.[ISI][Medline]

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