Structural Alerts for the Excess Toxicity of Acrylates, Methacrylates

Article pubs.acs.org/crt

Structural Alerts for the Excess Toxicity of Acrylates, Methacrylates, and Propiolates Derived from Their Short-Term and Long-Term Bacterial Toxicity Ulrike Blaschke,†,‡ Kathleen Eismann,†,§ Alexander Böhme,† Albrecht Paschke,† and Gerrit Schüürmann*,†,‡ †

UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstrasse 15, 04318 Leipzig, Germany ‡ Institute for Organic Chemistry, Technical University Bergakademie Freiberg, Leipziger Strasse 29, 09596 Freiberg, Germany § UFZ Department of Proteomics, Helmholtz Centre for Environmental Research, Permoserstrasse 15, 04318 Leipzig, Germany ABSTRACT: For eight acrylates, three methacrylates, and three propiolates as three subclasses of α,β-unsaturated esters, short-term and long-term bacterial toxicity with Vibrio fischeri was determined in terms of EC50 (effective concentration 50%) values for the 30-min bioluminescence and 24-h growth inhibition. To this end, experimental exposure concentrations were corrected for volatilization through a thermodynamic model based on Henry’s law constant of the compounds. Moreover, toxicity enhancements Te as the ratio of narcosispredicted over actual EC50 were determined and discussed in terms of underlying mechanisms of reaction of the electrophiles with endogenous nucleophiles such as glutathione (GSH) and proteins. Overall, log EC50 [M] ranges from −2.28 to −3.70 (30 min) and from −2.80 to −5.28 (24 h), respectively, indicating a significantly larger sensitivity of the growth inhibition bioassay for the reactive toxicity of these Michael acceptors. The latter is also reflected in the observed toxicity enhancements, where log Te > 1 was obtained for only 5 of 14 30-min EC50 values but for 11 of 13 24-h EC50 values. Moreover, the average long-term to short-term difference in log Te is 1 unit for the acrylates and 0.7 units for both methacrylates and propiolates. Methacrylates exert narcosis-level toxicity except for the methyl derivative in the long-term assay. The log EC50 (24 h) of a subset of 10 mostly excess-toxic acrylates and a propiolate correlates with their logarithmic rate constants of reaction with GSH, log kGSH, significantly more than with log Kow (r2 0.76 vs 0.47), yielding a respective regression rms of 0.34 log units. For allyl and propargyl acrylate as well as propargyl methacrylate, the observed excess toxicity is likely caused by initial enzymatic hydrolysis and subsequent oxidation of the α,β-unsaturated alcohols to the respective carbonyls. The latter shows that in the context of nonanimal testing schemes such as for REACH, the metabolic capacity of in vitro screens requires attention.

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INTRODUCTION Acrylates and methacrylates are high-volume industrial chemicals with a wide range of applications including coatings, printing inks, adhesives, sealants, textiles, plastic monomers, dental resins, and as chemical intermediates. Their key structural feature is a carboxylic ester group conjugated with a double bond between the α- and β-carbon of the acid moiety (CβCα−COOR). Accordingly, they are electrophilic at the βcarbon and may undergo Michael-type additions to nucleophiles. Methacrylates differ from acrylates through α-methyl substitution (Cα(CH3)− vs Cα(H)−) that is known to reduce their Michael-acceptor reactivity.1−3 Propiolates as a further variant of α,β-unsaturated esters have a triple bond conjugated to the ester group (CβCα−COOR), which is accompanied by an increased electrophilicity at the β-carbon as compared to acrylates.3,4 © 2011 American Chemical Society

Early investigations of the acrylate and methacrylate toxicity toward fish5,6 showed that the latter could be described through a general ester narcosis model, while the acrylates turned out to be more toxic. These results and later studies of their reactivity and aquatic toxicity2,7,8 indicated that the higher toxicity of acrylates can be traced back to their higher electrophilic reactivity, and that the corresponding reactivity of methacrylates appears to be too low to interfere with endogenous nucleophilic targets. In principle, electrophilic xenobiotics may react with and thus deplete intracellular GSH as the main nonprotein thiol that is typically present in millimolar concentrations, serving both as antielectrophile and antioxidant agent (supported by glutathione-S-transferase). Electrophiles may also attack nucleophilic Received: September 9, 2011 Published: November 25, 2011 170

dx.doi.org/10.1021/tx200395k | Chem. Res. Toxicol. 2012, 25, 170−180

Chemical Research in Toxicology

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sites of DNA and proteins, and in the case of GSH depletion, respective chemical modifications of these macromolecules may become prevalent and result in severe physiological damage.9 Indeed, similar second-order rate constants of reaction with GSH and protein binding sites were obtained for ethyl acrylate in respective in vitro studies,10 while this α,β-unsaturated ester did not form adducts with deoxyribonucleosides.11 Accordingly, acrylates and methacrylates have been classified as nongenotoxic and thus not DNA-reactive, keeping in mind that demonstrated in vitro clastogenicity (chromosome aberration) contrasts with both in vitro and in vivo mutagenicity.12 It follows that the toxicity of α,β-unsaturated esters may be caused to a large degree by their Michael-type addition at GSH and nucleophilic protein sites (Scheme 1), provided that the electrophilic reactivity is sufficient to enable respective turnover rates at relevant levels.

Article

MATERIALS AND METHODS

Test Organism. The toxicity tests were performed with the bioluminescent bacteria Vibrio f ischeri strain NRRL B-11177 from the German Resource Centre for Biological Material (DSMZ, Braunschweig, Germany). Vibrio f ischeri, formerly called Photobacterium f ischeri, has been reclassified as Aliivibrio fischeri.26 Test Compounds. The test set comprised 14 compounds, covering eight acrylates, three methacrylates, and three propiolates. Methyl acrylate, ethyl acrylate, butyl acrylate, ethyl methacrylate, and ethyl propiolate were purchased from Merck (Darmstadt, Germany), methyl methacrylate from Fluka (Buchs, Switzerland), and propyl acrylate, isobutyl acrylate, tert-butyl acrylate, propargyl acrylate, allyl acrylate, propargyl methacrylate, methyl propiolate, and tert-butyl propiolate from Alfa Aesar (Karlsruhe, Germany). All chemicals were at least of “p.a.” purity. For all test compounds, the logarithmic octanol/water partition coefficient, log Kow, was calculated using KOWWIN,27 and the hydrolysis half-life (t1/2) at pH 7 was estimated employing the ChemProp software.28 For Henry’s law constant as the dimensionless air/water partition coefficient Kaw, experimental values were taken from the literature29 if available, and otherwise predicted values were used employing HENRYWIN.27 Short-Term Bioassay (30-min Bioluminescence). As described in more detail elsewhere,23 inhibition of the bioluminescence of Vibrio f ischeri was determined in a luminometer (Hach Lange, Düsseldorf, Germany) after 30 min of exposure for different concentrations of chemicals in 2% (w/v) NaCl at 15 °C. The resultant EC50 values (see below) quantify the compound concentration yielding 50% bioluminescence inhibition. Long-Term Bioassay (24-h Growth). Using the earlier described procedure,23 Vibrio f ischeri was incubated for 24 h in rich medium at room temperature, spiked with a concentration gradient of the test chemical and measured in a CASY cell counter (Model TTC, Innovatis, Germany). Exposure Control. For chemicals with a lower water solubility (Sw < 1 mol/L), dimethyl sulfoxide (DMSO) was used as additional solvent at concentrations below 0.1% (v/v) to avoid biological effects (the latter of which was confirmed through respective measurements with DMSO as the only test compound). At this low DMSO concentration, mixture toxicity effects resulting from the combined exposure to DMSO and the test compound are not expected to take place to a relevant extent. Volatilization of the compounds from the test vials was evaluated through calculating the compound loss under thermodynamic equilibrium conditions according to the following equation:23

Scheme 1. Michael-Type Addition of Acrylates, Methacrylates, and Propiolates to Endogenous Nucleophilesa

Top: Methyl acrylate as prototype of acrylates (CβCα(H)−COOR) and methacrylates (CβCα(CH3)−COOR), reacting with a nucleophile NuH. The initially formed enol may tautomerize to the ester as the final product. Bottom: Methyl propiolate as prototype of propiolates (CβCα−COOR). The initially formed enolic cumulene may tautomerize to an acrylate derivative as the final product. a

In recent years, there has been increasing interest in methods for quantifying the electrophilic reactivity of Michael acceptors either experimentally3,4,13 or with quantum chemical methods,14−18 and for predicting their aquatic toxicity from hydrophobicity in terms of the logarithmic octanol/water partition coefficient, log Kow, and (measured or calculated) second-order rate constants of reaction with GSH, kGSH.4,18,19 In addition, structural alerts as predictive indicators of excess toxicity, defined through a minimum toxicity enhancement over narcosis-level toxicity (see below), have been developed for various compound classes from experimental results with fish, daphnids, bacteria, and ciliates.20−24 In the present study, the bacterial toxicity of 14 α,βunsaturated esters covering eight acrylates, three methacrylates, and three propiolates has been determined in both the 30-min bioluminescence and the 24-h growth inhibition bioassay with Vibrio f ischeri. Comparison of the resultant EC50 (effective concentration 50%) values with respective narcosis-level predictions enabled the identification of structural conditions associated with a significant potential for large toxicity enhancements (Te). Moreover, systematic differences between the short-term and long-term EC50 and Te values were found, providing guidance for the potential use of 24-h bacterial toxicity as an in vitro screen in the context of integrated testing strategies under the REACH directive.25

c (nom) − c w(vol) Δc w(vol) = w c w(nom) ⎞ ⎛ ⎜ Kaw ⎟ ⎟ = 1 − ⎜1 − V ⎜ Kaw + w ⎟ Va ⎠ ⎝ Kaw = V Kaw + w Va

= fa

(1)

In eq 1, Δcw(vol) quantifies the compound loss due to volatilization as the fractional number, cw(nom) the nominal (initial) compound concentration in the bioassay solution, cw(vol) the compound concentration in the headspace (volatilized), Kaw the air/water partition coefficient (dimensionless Henry’s law constant), Vw the volume of the bioassay solution (5 mL in the 24-h growth test and 1 mL in the 30-min bioluminescence test), Va the air volume of the headspace (65 mL in the 24-h growth test and 3.5 mL in the 30-min bioluminescence test), and fa the compound fraction in air. Equation 1 has been demonstrated earlier to yield a sufficiently accurate 171



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Table 1. Test Set of 14 Acrylates, Methacrylates, and Propiolates with Information about Their Physicochemical Properties and Short-Term Bacterial Toxicity toward Vibrio f ischeri in the 30-Min Bioluminescence Inhibition Bioassaya no.

name

CAS

log Kow

t1/2 [day]

fa [%]

Kaw

EC50 [M]

A1 A2 A3 B1 B2 B3 C1 C2

methyl acrylate ethyl acrylate propyl acrylate butyl acrylate isobutyl acrylate tert-butyl acrylate propargyl acrylate allyl acrylate

96-33-3 140-88-5 925-60-0 141-32-2 106-63-8 1663-39-4 10477-47-1 999-55-3

0.73 1.22 1.71 2.20 2.13 2.09 0.94 1.57

645 1131 2017 2112 2546 115300 90 637

D1 D2 D3

methyl methacrylate ethyl methacrylate propargyl methacrylate

80-62-6 97-63-2 13861-22−8

1.28 1.77 1.49

1496 2620 209

Acrylates 8.13·10−3 2.8 2.10·10−3 1.39·10−2 4.6 5.30·10−3 −3 6.66·10 2.3 7.00·10−4 −2 2.68·10 8.6 6.00·10−4 3.09·10−2 9.8 3.00·10−4 7.15·10−3 2.4 5.00·10−4 −4 8.25·10 0.3 2.00·10−4 −3 3.79·10 1.3 7.00·10−4 Methacrylates 1.30·10−2 4.4 5.20·10−3 −2 2.34·10 7.6 1.30·10−3 −3 1.29·10 0.4 1.30·10−3

E1 E2 E3

methyl propiolate ethyl propiolate tert-butyl propiolate

922-67-8 623-47-2 13831-03-3

0.09 0.58 1.45

10 17 1775

Propiolates 0.7 1.03·10−5 1.99·10−3 −3 2.64·10 0.9 9.61·10−5 −3 4.65·10 1.6 2.32·10−5

(±) ΔEC50 [M]

log EC50 [M]

log Te

Hill slope

CDRGSH [1/day]

1.00·10−4 1.00·10−3 9.43·10−5 7.82·10−5 3.79·10−5 2.00·10−4 1.92·10−5 1.00·10−4

−2.68 −2.28 −3.15 −3.22 −3.52 −3.30 −3.70 −3.15

1.09 0.20 0.58 0.15 0.52 0.34 1.90 0.72

1.4 1.0 1.1 1.4 1.3 0.7 1.4 1.0

34.5 80.9 10.3 7.4 n.a. 1.8 14.8 19.8

1.50·10−3 1.00·10−4 2.00·10−4

−2.28 −2.89 −2.89

0.14 0.25 0.53

1.0 0.9 0.9

0.5 0.1 0.4

6.00·10−7 5.38·10−6 2.94·10−6

−4.99 −4.02 −4.63

4.05 2.58 2.32

1.3 1.6 1.2

1.7 14.5 n.a.

a The compound numbering refers to Scheme 2. Logarithmic octanol/water partition coefficients, log Kow, were predicted using EPISuite,27 the hydrolysis half-lives t1/2 at pH 7 were predicted using ChemProp,28 and Henry’s law constants in terms of air−water partition coefficients, Kaw, were taken from ChemIDplus Advanced29 where available (A1-A3, B1-B2, and D1-D2) and otherwise calculated (B3, C1-C2, D3, E1-E3) using EPISuite,27 and the compound fraction in air (headspace of test vial), fa, was calculated through eq 1. EC50 [mol/L] denotes the effective concentration yielding 50% bioluminescence after 30 min exposure, ΔEC50 represents the associated standard error, log Te quantifies the toxicity enhancement relative to 30-min baseline narcosis (eq 3), and Hill slope refers to eq 2. The critical GSH depletion rate constant CDRGSH (eq 9) was calculated with kGSH data taken from earlier investigations;3,4 n.a. denotes not available.

quantification of the volatilization loss under the Vibrio f ischeri bioassay conditions.23 For compounds with fa > 5%, a modified experimental setting with a three-fold test volume in shorter cuvettes was used for the 30-min bioluminescence test, employing specifically manufactured caps to minimize the headspace. In the 24-h growth assay, a test setup with specifically manufactured flasks closed with a cap and septum was used. EC50 Determination. For the 30-min bioluminescence as well as for the 24-h growth test, the measured data were used to generate four-parameter logistic curves through the application of the SigmaPlot 11 software (Systat Software Inc., Chicago, USA).

y = min +

log EC50(growth, 24 h)[M] = − 0.77(± 0.05)log K ow − 0.81(± 0.13)

with root-mean-square errors (rms) for log EC50 of 0.44 (30 min) and 0.37 (24 h), respectively. The ratio of predicted narcosis-level over actual (experimental) EC50 quantifies the toxicity enhancement Te:20,21

Te =

(5)

but is called toxicity (Te was originally termed “excess toxicity” enhancement because it is a dimensionless toxicity ratio). While it is difficult to justify a certain Te threshold for discriminating narcosis from other modes of toxicological action (also in view of data uncertainty), the following setting considering typical confounding factors such as laboratory bias and biological data variation appears reasonable:22−24 Te values 10 is understood to indicate a significant toxicity enhancement driven by specific or reactive mechanisms, resulting in corresponding excess toxicity (i.e., a significantly smaller EC50 than predicted by baseline narcosis) of the compounds. Critical GSH Depletion Rate Constant. Following Freidig et al.,7 the intracellular GSH concentration, cGSH(t), reflects the balance between endogenous synthesis expressed as zero-order rate constant ks, endogenous consumption characterized by a respective first-order elimination rate constant ke, and additional elimination through reaction with xenobiotic electrophiles at its internal concentration cint(t) with a second-order rate constant kGSH:

(2)

In the Hill model of eq 2, x denotes the exposure concentration of the test compound, y the associated inhibition expressed as the percentage (usually between 0 and 100), min and max the respective minimum and maximum inhibition values, Hill slope the slope parameter, and EC50 the exposure concentration yielding 50% inhibition of the endpoint of interest. For volatile compounds (see above), x was corrected for the volatilization loss before generating the concentration−response curve. Excess Toxicity. Measured toxicity was compared with corresponding baseline narcosis.20,21 The latter was predicted from the previously derived linear regression equations for 30-min bioluminescence and 24-h growth inhibition:23

dcGSH(t ) = − (ke + k GSHc int(t ))cGSH(t ) + k s dt

log EC50(lum, 30 min)[M] = − 1.01(± 0.06)log K ow − 0.85(± 0.15)

EC50(narc) EC50(exp) 20,21

max − min ⎛ x ⎞−Hill slope 1+⎜ ⎟ ⎝ EC50 ⎠

(4)

(6)

Assuming further that the toxicant concentration in the intracellular aqueous phase is in thermodynamic equilibrium with its external concentration (EC50) and that the bioassay meets the steady-state

(3) 172



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conditions results in cint = EC50 as the time-independent value.7 Introduction of the latter in eq 6 enables one to solve this first-order inhomogenous differential equation (DEQ) through combining the solution of the respective homogeneous DEQ (c GSH (t) = constant·exp(−[ke + kGSH·EC50]t) if ks = 0) with a particular solution of the inhomogenous DEQ (cGSH = [ke + kGSH·EC50]/ks if ks ≠0), determining the integration constant through evaluating cGSH(0):

Scheme 2. Chemical Structures of the Test Set of 14 Acrylates, Methacrylates, and Propiolatesa

⎛ ⎞ ks cGSH(t ) = ⎜cGSH(0) − ⎟· ke + k GSH· EC50 ⎠ ⎝ exp( − [ke − k GSH· EC50]t ) ks + ke + k GSH· EC50

(7)

Constant electrophile exposure will result in a constant (steadystate) GSH concentration that accounts for both the physiological synthesis and consumption and the toxicant-mediated depletion. This steady-state cGSH value can be obtained from eq 7 as the limit value for t → ∞ (in which case the product term of eq 7 vanishes because of exp(−∞) = 0):

cGSH(t → ∞) =

ks ke + k GSH· EC50

≡ cGSH

(8)

Equation 8 shows further that constant cGSH requires kGSH·EC50 to be also constant, the latter of which represents the pseudo-first-order depletion rate constant of GSH concerning its reaction with the electrophile. Accordingly, the model equation for predicting the critical GSH depletion rate constant, CDRGSH [day−1] from kGSH [M−1 day−1] and the toxicity in terms of EC50 [M] reads:7

CDR GSH = k GSH· EC50

a

Acrylates: methyl acrylate (A1), ethyl acrylate (A2), propyl acrylate (A3), butyl acrylate (B1), isobutyl acrylate (B2), tert-butyl acrylate (B3), propargyl acrylate (C1), and allyl acrylate (C2). Methacrylates: methyl methacrylate (D1), ethyl methacrylate (D2), and propargyl methacrylate (D3). Propiolates: methyl propiolate (E1), ethyl propiolate (E2), and tert-butyl propiolate (E3).

(9)

Interestingly, log Te is largest for the three propiolates (2.32−4.05), indicating a substantial reactivity contribution to their (also largest) toxicities. It reflects the higher reactivity of the triple-bonded sp carbon to nucleophiles as compared4 to the double-bonded sp2 carbon (see Scheme 1). This systematic difference in toxicity is illustrated through comparing methyl, ethyl, and t-butyl acrylate (A1, A2, and B3 in Scheme 2) with their propiolate counterparts (E1−E3). As can be seen from Table 1, EC50 of the former is larger and thus their toxicity is smaller by 2.3−1.4 log units than the latter, although the acrylate log Kow is larger by ca. 0.7 than the one of the propiolate analogue. Except for methyl acrylate, all alkyl acrylates (A2−B3) and methacrylates (D1−D2) yield 30-min toxicities at or reasonably close to the narcosis level, indicating that in this subgroup the Michael-acceptor reactivity does not play a role in the shortterm bacterial toxicity. It follows that also for methacrylates with larger alkyl chains (but no additional reactive sites), narcosis-level toxicity is expected, with potencies slightly larger than those for the corresponding acrylates because of the respective difference in log Kow. Figure 1 shows the data distribution of log EC50 vs log Kow for all 14 compounds augmented by the narcosis line of eq 3 and its parallel with log Te = 1, facilitating the discrimination between narcosis-level and excess toxicity. The log Te values of allyl acrylate (C2) and propargyl acrylate (C1) indicate a slight (0.7) and significant (1.9) toxicity enhancement, respectively. As discussed earlier for allyl methacrylate,2,7 it is likely that these compounds undergo enzymatic hydrolysis mediated by carboxylesterase (CES) as was shown for several acrylates,30 and that the unsaturated alcohol as initial metabolite is biotransformed further via

Equation 9 was applied to both short-term (30 min) and long-term (24 h) EC50 values in order to check this GSH-depletion model of reactive toxicity toward bacteria for the present set of acrylates, methacrylates and propiolates. Statistical Parameters. The statistical regression performance was evaluated through the following parameters: squared correlation coefficient, r2; predictive squared correlation coefficient evaluated through leave-1-out cross-validation, qcv2 ; root-mean-square error of calibration, rms; cross-validated root-mean-square error of prediction, rmscv; F-test value, Fi,n−(i+1) (with i = number of variables, and n = number of compounds).

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RESULTS AND DISCUSSION Short-Term Toxicity toward Vibrio f ischeri. For the eight acrylates, three methacrylates, and three propiolates, information about their hydrophobicity and short-term toxicity is summarized in Table 1. Interestingly, the variation in 30-min EC50 (bioluminescence inhibition) of 2.7 log units is significantly larger than the variation in log Kow (2.1 units), with quite similar Hill slopes from 0.7 (tert-butyl acrylate) to 1.6 (ethyl propiolate). The latter indicate that across all 14 test compounds, the steepness of the concentration−response curves varies by a factor of only 2. The subgroup of low-hydrophobic propiolates with a triple bond in the α,β-position (E1−E3 in Scheme 2) is significantly more toxic than both the acrylates (A1−C2) and methacrylates (D1−D3), with methyl propiolate (E1) yielding the overall smallest EC50 (1.03·10−5 M) and thus highest toxicity despite its lowest log Kow (0.09) among all 14 compounds tested. Comparison with the narcosis-level bacterial toxicity (eq 323) shows further that for five α,β-unsaturated esters, the toxicity enhancement Te (eq 6) is larger than a factor of 10 (log Te > 1). 173



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Scheme 4. Metabolic Transformation of Propargyl Acrylatea

Figure 1. Short-term (30-min) bioluminescence inhibition of acrylates (■), methacrylates (●), and propiolates (▲) with the bacteria Vibrio fischeri shown as log EC50 [mol/L] vs log Kow, using the toxicity data listed in Table 1. The solid line represents baseline narcosis (eq 3) and the broken line the threshold log Te = 1 (toxicity enhancement; see eq 2) for discriminating between narcosis-level and excess toxicity.

a

Top: Enzymatic hydrolysis mediated by carboxylesterase (CES) yields acrylic acid and propargyl alcohol. Right: Oxidation of propargyl alcohol catalyzed by alcohol dehydrogenase (ADH) generates the Michael acceptor propargyl aldehyde that may react with endogenous nucleophiles (NuH). Left: Epoxidation catalyzed by cytochrome P450 yields an electrophilic oxirene that may directly attack endogenous nucleophiles (NuH) and then tautomerize to the respective ketone. Alternatively, oxirene rearrangement yields an electrophilic ketene that provides a further option for attacking endogenous nucleophiles, followed by tautomerism of the formed enol (bottom left) to the respective ketone (bottom right).

alcohol dehydrogenase (ADH) to yield an α,β-unsaturated aldehyde (here: acrolein and propargyl aldehyde; see Schemes Scheme 3. Metabolic Transformation of Allyl Acrylatea

type ring-opening reactions with endogenous nucleophiles23,24 or through the described oxirene and ketene chemistry. Note further that for glycidyl methacrylate log Te values of 1.56 (30-min bioluminescence) and 1.42 (24-h growth) had been determined,23 suggesting still larger toxicity enhancements for the α-H analogue glycidyl acrylate as the P450-generated epoxide metabolite of allyl acrylate as well as for the intrinsically still more reactive glycidyl propiolate as the corresponding oxirene metabolite. However, we are not aware of experimental evidence for the P450 biotransformation pathway as opposed to the ADH-mediated metabolic activation.9,30,31 While the latter refers to rat, fish hepatocytes, and to in vivo fish liver studies, but not to bacteria, the metabolic capacity of bacteria is known to include CES32 (found for Vibrionaceae), ADH,33 and P450,34 thus making the outlined biotransformation pathways possible in principle. Keeping in mind the demonstrated metabolic conversion of allyl acrylate to allyl alcohol,9,30,31 we conclude that the CES-ADH metabolic route is at least faster and overall significantly more efficient than the alternative P450-catalyzed biotransformation for these compounds. Comparison of the three α,β-unsaturated methyl esters (A1, D1, and E1) shows that except for the respective methacrylate, significant excess toxicity (log Te > 1) is observed. It reflects the reduced electrophilic reactivity of methacrylates,1,2 probably due to both the positive inductive effect and steric crowding of the α-alkyl substituent. Interestingly, however, the bacterial sensitivity to methyl methacrylate (D1) increases with time as outlined in the next section (see below). A further observation concerns the difference in toxicity impact of the triple bond when comparing the α,β-unsaturated bond of the acid moiety (methyl propiolate, E1) with the propargylic bond of the alcohol moiety (propargyl acrylate, C1). The former yields a significantly larger log Te (4.5 vs

a

Top: Hydrolysis catalyzed by carboxylesterase (CES) generates acrylic acid and allyl alcohol. Right: Oxidation of allyl alcohol mediated by alcohol dehydrogenase (ADH), yielding the electrophile acrolein that may react as Michael acceptor with endogenous nucleophiles (NuH). Left: Epoxidation of the allylic double bond catalyzed by cytochrome P450, followed by an SN2-type ring-opening reaction with endogenous nucleophiles.

3 and 4, right) as Michael acceptor.9 It suggests that the latter as ultimate electrophilic metabolite is ready to attack endogenous nucleophilic sites, thus providing the reactivity component to the toxicity of these and related compounds. In this context, the significantly larger Te for propargyl acrylate suggests a larger reactivity of the triple bond for the metabolic conversion. A possible alternative biotransformation pathway of allyl and propargyl acrylate would be an epoxidation of the terminal unsaturated bond of their alcohol moieties catalyzed by the monooxygenase cytochrome P450, yielding an epoxide (Scheme 3, left) and oxirene (Scheme 4, left), respectively, the latter of which may rearrange to a ketene that after the formation of an enol through the addition of an endogenous nucleophile may tautomerize to the corresponding ketone (Scheme 4, bottom). Thus, in both cases electrophilic metabolites would be formed with a correspondingly increased disposition for reactive toxicity, in this case either through SN2174



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Table 2. Test Set of 14 Acrylates, Methacrylates, and Propiolates with Information about Their Long-Term Bacterial Toxicity toward Vibrio f ischeri in the 24-h Growth Inhibition Bioassaya no.

name

fa [%]

EC50 [M]

A1 A2 A3 B1 B2 B3 C1 C2

methyl acrylate ethyl acrylate propyl acrylate butyl acrylate isobutyl acrylate tert-butyl acrylate propargyl acrylate allyl acrylate

9.6 15.3 8.0 25.9 28.6 8.4 1.1 4.7

3.00·10−4 4.00·10−4 4.00·10−4 2.00·10−4 1.00·10−4 5.00·10−4 3.86·10−5 n.d.

D1 D2 D3

methyl methacrylate ethyl methacrylate propargyl methacrylate

14.5 23.3 1.7

1.50·10−3 1.60·10−3 6.00·10−4

E1 E2 E3

methyl propiolate ethyl propiolate tert-butyl propiolate

2.5 3.3 5.7

1.28·10−5 5.22·10−6 9.53·10−6

(±) ΔEC50 [M] Acrylates 1.77·10−5 3.96·10−5 7.74·10−5 3.68·10−5 2.10·10−5 5.58·10−5 1.46·10−6 n.d. Methacrylates 2.00·10−4 3.00·10−4 1.00·10−4 Propiolates 5.22·10−7 2.85·10−7 9.01·10−7

log EC50 [M]

log Te

Hill slope

CDRGSH [1/day]

−3.52 −3.40 −3.40 −3.70 −4.00 −3.30 −4.41 n.d.

2.15 1.65 1.27 1.19 1.55 0.88 2.88 n.d.

2.6 2.9 1.7 2.0 1.7 1.6 3.4 n.d.

4.9 6.1 5.9 2.5 n.a. 1.8 2.9 n.d.

−2.82 −2.80 −3.22

1.03 0.62 1.26

1.1 1.6 1.6

0.2 0.1 0.2

−4.89 −5.28 −5.02

4.01 4.03 3.09

4.7 4.6 2.8

2.2 0.8 n.a.

a

The compound numbering refers to Scheme 2. For CAS numbers, log Kow, hydrolysis half-life, Henry’s law constant and the critical GSH depletion rate constant CDRGSH, see Table 1; the compound fraction in air (headspace of test vial), fa, was calculated according to eq 1. EC50 [mol/L] denotes the effective concentration yielding 50% growth inhibition after 24 h exposure, ΔEC50 represents the associated standard error, log Te quantifies the toxicity enhancement relative to 24-h baseline narcosis (eq 4) according to eq 5, and Hill slope refers to eq 2; n.d. denotes not determined, n.a. denotes not available.

acrylate (B2) and ethyl methacrylate (D2). Note further that as opposed to the latter compound, propargyl methacrylate (D3) is excess-toxic (log Te = 1.26), suggesting again a metabolic activation through initial hydrolysis and formation of propargyl aldehyde as ultimate electrophile, as was discussed above for propargyl acrylate (C1; see Scheme 4, right). The data distribution of log EC50 vs log Kow is shown in Figure 2. Comparative analysis of the six alkyl acrylates (A1−

1.90), indicating that the need for various biotransformation steps before depleting GSH or attacking nucleophilic protein sites reduces the overall excess toxicity in accord with general expectation. Long-Term Toxicity to Vibrio f ischeri. In Table 2, the bacterial toxicity in terms of 24-h growth inhibition 50% (24-h EC50) is summarized for 13 α,β-unsaturated esters; allyl acrylate was not tested in this long-term assay. For 10 of the 13 compounds, the 24-h EC50 values are smaller than the corresponding 30-min results, which is in accord with the general expectation that toxicity would increase with increasing time. Interestingly, these findings contrast with our results for epoxides as well as for narcotics, where a slightly larger bacterial sensitivity in the short term bioassay had been observed.23 It demonstrates that when comparing the 30-min inhibition of bioluminescence with the 24-h inhibition of growth, the order of bacterial sensitivity depends on compound class and in particular does not always increase with increasing exposure time, keeping in mind an additional complication due to differences in the physiological characteristics of the two endpoints (30-min impairment of physiological performance vs 24-h integral impairment of growth including adaptation processes) as discussed earlier.23 For the subset of seven acrylates, the 24-h growth toxicity is larger than the 30-min bioluminescence toxicity by 0.6 log units on the average (log EC50: −3.68 vs −3.12), accompanied by an average Te increase of one log unit (log Te: 1.65 vs 0.69; see Tables 1 and 2). Slightly smaller average differences by 0.5 log EC50 and 0.7 log Te units are observed for the three propiolates (log EC50, −5.06 vs −4.55; log Te, 3.70 vs 2.98), and again smaller average differences by 0.3 log EC50 units and 0.7 log Te units hold for the subset of three methacrylates (log EC50, −2.95 vs −2.69; log Te, 0.97 vs 0.31). Now, 11 of 13 tested α,β-unsaturated esters show toxicity enhancements as compared to the narcosis level by more than a factor of 10 (log Te > 1), the only exceptions being t-butyl

Figure 2. Long-term (24-h) growth inhibition of acrylates (■), methacrylates (●), and propiolates (▲) with the bacteria Vibrio fischeri shown as log EC50 [mol/L] vs log Kow, using the toxicity data listed in Table 2. The solid line represents baseline narcosis (eq 4) and the broken line the threshold log Te = 1 (toxicity enhancement; see eq 2) for discriminating between narcosis-level and excess toxicity.

B3) reveals a systematic decrease in 24-h Te with increasing size of the alkyl group, which holds also for the two alkyl methacrylates tested (D1−D2). Concerning the alkyl propiolates, the methyl and ethyl derivatives show similar Te values, while introduction of the t-butyl group (E3) is accompanied by a Te decrease of one log unit. Overall, these findings indicate that increasing the size of the alkyl substituent (and thus both 175



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log Kow and the associated narcotic potency) decreases the reactive contribution to toxicity, which is in line with earlier observations for the toxicity toward fish2,35 and ciliates24 of epoxides as another class of electrophiles.24,35 The higher sensitivity of 24-h growth toward acrylate exposure enables also an evaluation of the toxicity impact of α-methyl substitution when comparing methyl and ethyl acrylate (A1 and A2) with methyl and ethyl methacrylate (D1 and D2). As can be seen from Tables 1 and 2, α-alkylation reduces Te by ca. one log unit (log Te: 2.15 and 1.65 vs 1.03 and 0.63), reflecting the already mentioned reduction in Michael-acceptor reactivity for methacrylates as compared to acrylates. Note further that concerning fish toxicity, a similar trend had been reported earlier2 when comparing ethyl and isobutyl acrylate with methyl and isopropyl methacrylate (log Te: 2.1 and 1.4 vs 0.04 and 0.2). Moreover, a fish toxicity log Te of 3.3 had been observed for allyl methacrylate2 and explained by the hepatotoxic action of its metabolite allyl alcohol, a situation similar to our 30-min and 24-h bacterial toxicity results for propargyl and allyl acrylate (C1 and C2) as well as for propargyl methacrylate (see above and Schemes 3 and 4). Regarding the acrylate vs propiolate difference in Te, comparison of methyl, ethyl, and t-butyl acrylate (A1, A2, and B3) with the corresponding propiolates (E1−E3) shows that for the latter, the 24-h Te is larger by 1.9 to 2.4 log units, again reflecting a substantially larger Michael-acceptor reactivity of the α,β-unsaturated triple bond as compared to the corresponding double bond. Note further that while the methyl and ethyl propiolates yield almost identical 24-h Te values (4.01 vs 4.03, Table 2), their 30-min Te values differ by 1.5 log units (4.05 vs 2.58, see Table 1), with methyl propiolate showing essentially the same toxicity enhancement in both the shortterm and long-term assay. These observations suggest that the 30-min toxicity of methyl propiolate is unusually large as compared to both the other α,β-unsaturated esters and to the corresponding 24-h growth inhibition result, for which we have no explanation at hand. Overall, the present findings demonstrate that depending on the compound class under investigation, the toxicological information content of the 24-h growth inhibition bioassay may differ significantly from the one gained through the 30-min bioluminescence inhibition. Critical GSH Depletion Rate Constant. As outlined in the Introduction, the reaction of organic electrophiles with cellular GSH may result in GSH depletion, which in turn makes the cell more vulnerable to electrophilic attacks at nucleophilic protein sites. In this context, Freidig et al.7 have introduced a model for evaluating the GSH depletion rate that results from both normal physiological consumption and electrophilic attack, assuming thermodynamic equilibrium between the external concentration of the reactive toxicant and its concentration in the intracellular aqueous phase. In particular, this toxicokinetic model implies a constant GSH depletion rate constant under thermodynamic bioassay conditions. In Tables 1 and 2, the respective critical GSH depletion rate constant, CDRGSH, has been calculated according to eq 9 for both the 30-min bioluminescence and 24-h growth inhibition EC50 values, taking into account experimental second-order rate constants of the reaction of a subset of 12 acrylates, methacrylates, and propiolates with GSH, kGSH.4 As can be seen from the tables, CDRGSH varies by a factor of 742 (from 0.1 to 80.9 day−1) for the 30-min bioluminescence assay, while

24-h growth inhibition yields a significantly reduced, but still substantial, CDRGSH variation by a factor of 46 (from 0.13 to 6.1 day−1). It follows that with the two presently employed bioassays, CDRGSH is far from being constant. However, the significant reduction in CDRGSH variation for the long-term assay suggests that besides apparent limitations of the validity of eq 6 (that ignores stress-induced adaptation and defense processes such as an increased GSH synthesis rate), the assumption of a thermodynamic equilibrium between internal and external toxicant concentration may be less valid for the 30min exposure. Interestingly, however, four 24-h CDRGSH values of Table 2 correspond approximately to the average CDRGSH of 1.8 ± 0.8 day−1 derived from the 4-day fish toxicity of acrylamide, acrylonitrile, acrolein, and ethyl acrylate,7 and three further values are larger by factors of only 1.6 and 3.3, respectively. Moreover, the systematically smaller critical GSH depletion rate constant for the three methacrylates would be in accord with their systematically smaller electrophilic reactivity (disregarding the model requirement of a constant CDRGSH within a given electrophilic reaction mechanism). Overall, the present results are in conflict with a constant CDRGSH, which may have different (or several) causes. First, the rate constants of intracellular GSH depletion might differ in their trend from the chemoassay-derived kGSH values, which, however, appears unlikely in view of the results from previous investigations4,7−11 and the additional fact that all kGSH values used here come from the same laboratory employing a sensitive kinetic assay.3 Second, GSH depletion and protein-thiol depletion may compete differently for different electrophiles, thus resulting in different steady-state CDRGSH values for different thiol-reactive xenobiotics. Third, both nonproteinthiol and protein-thiol depletion may also compete with the electrophilic attack at nucleophilic sites of the DNA, again leading to toxicant-specific critical GSH depletion rate constants. Fourth and as mentioned already above, the derivation of a constant CDRGSH assumes thermodynamic equilibrium between the internal and external electrophile concentration as well as the absence of stress-induced adaptation processes such as an increase of the intracellular GSH synthesis rate. Except for the question of a toxicological applicability of kGSH, all of these potential causes touch upon different aspects of the assumptions underlying eq 6 and its implication for CDRGSH. Accordingly, further analysis of this mechanistic model for reactive toxicity appears useful for identifying the scope and limitations of the constant CDRGSH model, in order to gain further insight into the molecular level of the toxic action of organic electrophiles. Relationship of Toxicity with Reactivity toward GSH. For the present set of α,β-unsaturated esters, the excess toxicity is expected to be driven by their Michael-acceptor reaction with endogenous nucleophilic sites of GSH or proteins (Scheme 1), keeping in mind confounding factors such as multiple-step reactions (where the primary electrophilic attack may not necessarily be the rate-determining step) including those with initial metabolic activation (Schemes 3 and 4). Thus, it was of interest to explore the degree of correlation of their Michaelacceptor reactivity with both short-term and long-term toxicities. For 12 of the 14 acrylates, methacrylates, and propiolates, second-order rate constants of their reaction with GSH, kGSH, were available from previous investigations3,4 (and have been used already for calculating CDRGSH as outlined above). Linear 176



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regression of log EC50 on log kGSH yields r2 = 0.42 for the 30min bioluminescence inhibition and r2 = 0.74 for the 24-h growth inhibition. At first sight, the low correlation of the 30min toxicity with reactivity may be surprising. Note, however, that here only four of the 12 esters exert significant excess toxicities (log Te > 1; see Table 1), while for the eight compounds with log Te < 1 log EC50 is (of course) mainly driven by log Kow (r2 = 0.71, rms = 0.24). In this context, we note that as a general rule, r2 decreases with decreasing value range of the explaining variable,36 which should be taken into account when evaluating r2 between toxicity and hydrophobicity for the presently analyzed narcosis-level α,βunsaturated esters. Apart from that, reactivity to nonthiol nucleophilic sites of proteins may also contribute to the observed excess toxicity, keeping in mind that both absolute values and the trend of electrophilic reactivity depend also on the type of the nucleophilic reaction site. Interestingly, an earlier analysis with ciliates4 yielded an r2 of 0.83 (and rms = 0.37) between log EC50 (24-h growth inhibition of Tetrahymena pyriformis) and log kGSH for 16 acrylates, methacrylates, and propiolates, which increases to r2 = 0.95 (with rms = 0.20) when confined to the 12 derivatives of the present set with available kGSH values. Coming back to our present 30-min log EC50 data, inclusion of log Kow as a second regression parameter yields only a marginal improvement in the correlation (r2 = 0.47, rms = 0.61). The latter reflects the relatively small log Kow variation (see above) and the fact that for only five of the 14 compounds both hydrophobicity and reactivity contribute significantly to toxicity. Overall, the present findings suggest that the 30-min bioluminescence assay has only a low sensitivity toward the reactive toxicity of α,β-unsaturated esters, and in this respect is not recommended as in vitro screening instrument. With regard to long-term bacterial toxicity, a moderate but significant correlation between log EC50 and log kGSH is observed, and here the inclusion of log Kow (with an intercorrelation r2 of 0.3 with log kGSH) yields an improved description of the overall log EC50 variation:

log EC50(growth, 24 h)[M] = − 0.42( ± 0.10)log k GSH + 0.29( ±0.18) log K ow − 3.73( ±0.29) 2

(13)

qcv2

where n = 10, r = 0. 82, rms = 0.31, = 0.69, rmscv = 0.41, and F2,7 = 16.3 (with an intercorrelation r2 between log kGSH and log Kow of 0.23). Given the small number of only 10 compounds, eq 13 can be considered as tentative. Note further that in contrast to expectations and previous findings,4 the log Kow regression coefficient in eqs 11 and 13 is positive, suggesting a decrease in toxicity with increasing hydrophobicity. However, in both equations the standard error of the log Kow regression coefficient is relatively large. Nevertheless, the separate regression of log EC50 on log Kow yields an only moderate but again positive correlation for the 11 mostly excess-toxic α,β-unsaturated esters (log EC50 = 0.847·log Kow − 4.79, r2 = 0.47, rms = 0.57), with statistics clearly inferior to the ones of eq 10. In this context, the apparently metabolism-mediated toxicity of propargyl acrylate and methacrylate (C1 and D3) requires attention concerning the respective rate-determining step. Exclusion of these two compounds, however, does not affect the correlation substantially (r2 = 0.80, rms = 0.45). Note that the latter could also be a fortuitous result, considering both the overall biotransformation rate and the Michael-acceptor reactivity of the ultimately formed electrophile. The data distribution of log EC50 vs log kGSH according to eq 12 is shown in Figure 3. Overall, the regression analyses confirm that the

log EC50(growth, 24 h)[M] = − 0.59( ± 0.12)log k GSH − 3.32( ±0.15)

(10)

2 where n = 11, r2 = 0.74, rms = 0.43, qcv = 0.69, rmscv = 0.50, and F1,9 = 26.2;

log EC50(growth, 24 h)[M]

Figure 3. log EC50 [M] for the 24-h growth inhibition of Vibrio fischeri vs log kGSH (second-order rate constants of reaction with glutathione [M−1 min−1])3,4 according to eq 12 (n = 10, r2 = 0.76, rms = 0.34) with six acrylates (■), three methacrylates (●), and one propiolate (▲). Ethyl propiolate (△) as the outlier was not included in the regression equation (log EC50 [mol/L] predicted = −4.28 vs experimental = −5.28).

= − 0.47( ± 0.13)log k GSH + 0.38( ±0.23) log K ow − 3.88( ±0.37)

(11)

2 where n = 11, r2 = 0.81, rms = 0.40, qcv = 0.74, rmscv = 0.45, and F2,8 = 16.9. Inspection of the data distributions reveals ethyl propiolate (E2) as an outlier, for which we have at present no explanation. Omission of this compound yields

24-h growth inhibition assay is more sensitive toward the reactivity contribution to toxicity of this compound class as compared to the short-term bioluminescence assay. Structural Alerts for Excess Toxicity. From the present set of eight acrylates, three methacrylates and three propiolates, the following rules can be derived for structural features associated with significant long-term excess toxicities (log Te > 1) toward bacteria, relying mostly on the 24-h growth inhibition results. First, acrylates with alkyl groups up to C4

log EC50(growth, 24 h)[M] = − 0.49( ± 0.10)log k GSH − 3.29( ±0.12)

(12)

2 where n = 10, r2 = 0.76, rms = 0.34, qcv = 0.61, rmscv = 0.41, and F1,8 = 25.3;

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Future work may investigate the potential relevance of this latter P450 oxidation pathway, e.g., through analyzing the toxicity of such derivatives where the allylic or propargylic carbon has no H atom (and thus blocks the ADH-mediated step as discussed above). Regarding acute fish toxicity, Reinert5 reported 96-h log LC50 [mol/L] values (LC50 = lethal concentration 50%) with fathead minnow (Pimephales promelas) for five acrylates and seven methacrylates that ranged from −2.82 (methyl methacrylate) to −5.16 (hexyl acrylate) log units. Comparison with baseline narcosis for this fish species yields log Te values >1 for nine of the 12 compounds, including isobutyl and cyclohexyl acrylate (log Te 1.55, 1.16). However, log Te < 1 was observed for hexyl acrylate (0.83) as well as for both methyl and isopropyl methacrylate (0.27 and 0.58). Comparison with Scheme 5 suggests that the 24-h bacterial toxicity is slightly less sensitive to the reactive toxicity of alkyl acrylates than the 96-h fish toxicity (excess toxic C4 vs C6) but slightly more sensitive toward the reactive toxicity of methacrylates (C1 vs C0). Overall, however, it appears that the presently employed 24-h growth inhibition assay with Vibrio f ischeri provides Te information that holds more generally, at least with regard to qualitative trends. By contrast, the 30-min bioluminescence response to the presently analyzed acrylates, methacrylates, and propiolates shows a strong bias toward narcosis, which differs significantly from a much more informative 30-min response to epoxides, 23 indicating substantial differences in the T e sensitivity of this short-term assay across different compound classes. Accordingly, the nonanimal 24-h growth bioassay appears strongly preferred over the 30-min bioluminescence to screen α,β-unsaturated esters for their potential to exert excess toxicity as a component of integrated testing strategies for REACH,25 thus providing pertinent information that may support the toxicological evaluation of this class of organic electrophiles. An illustration of the latter is given in Table 3 that presents experimental LC50 and EC50 data for fish5,7 and bacteria for four alkyl acrylates and methyl methacrylate. In addition, baseline narcosis LC50 values for fathead minnow (Pimephales promelas) have been given, using a respective literature model.37 Inspection of Table 3 shows a qualitative agreement concerning excess toxicity (Te > 10) for four of the five α,β-unsaturated esters between the bacterial 24-h growth inhibition and acute fish toxicity (LC50 and EC50 data with asterisks in the table). By contrast, only one of the four alkyl acrylates exerting excess toxicity toward fish yields Te > 10 also in the 30-min bioluminescence assay. Note further that concerning absolute values, the comparison in Table 3 indicates that acute fish lethality is more sensitive than 24-h bacterial growth inhibition. Accordingly, bacterial 24-h growth inhibition Te values appear to be informative for the excess toxicity toward fish, while the absolute values of bacterial EC50 data are systematically larger than corresponding acute fish LC50 data.

(butyl) as alcohol moieties are expected to be excess-toxic; the respective structural alert is depicted in Scheme 5 (top left). As Scheme 5. Structural Alerts for the Excess Toxicity of Acrylates, Methacrylates, and Propiolatesa

a

For each of the three subclasses of acrylates (left), methacrylates (middle), and propiolates (right), the structural condition of the alkyl group (top) or reactive side chain (bottom) associated with a potential for a significant toxicity enhancement Te (eq 5) over the narcosis level is specified.

discussed above, Te decreases with increasing alkyl chain length, and derivatives with larger alkyl groups are likely to exert narcosis-level toxicity. Second, respective methacrylates show a significant toxicity enhancement only for the methyl derivative, reflecting the reduction in Michael-acceptor reactivity due to substitution at the α-C (Scheme 5, top middle). Third, propiolates (CαCβ) with alkyl groups as alcohol moieties have larger toxicity enhancements than their acrylate (CαCβ) counterparts, apparently reflecting a higher electrophilic reactivity of the sp β-C as compared to the sp2 β-C. Because t-butyl propiolate (E3) as the test compound with the largest alkyl group in the 24-h growth inhibition test still yields a substantial log Te value of 3.02 (Table 2), we tentatively include alkyl groups up to C6 in the respective structural alert (Scheme 5, top right). Fourth, the allyl and propargyl groups represent reactive alcohol moieties and may lead to significant toxicity enhancements of respectively substituted acrylates, methacrylates, and propiolates due to metabolic conversion to acrolein (acrylate and methacrylate; see Scheme 3, top and right) or propargyl aldehyde (propiolate; see Scheme 4, top and right) as the ultimate electrophile. The ADH-mediated oxidation as the second step of this metabolic pathway works only for primary and secondary alcohols and thus rules out an accordingly caused toxicity enhancement for derivatives with fully substituted allylic or propargylic carbon. Considering further that substitution at both the α and β positions results in a substantial reduction of the Michael-acceptor reactivity,4 the respective structural alerts include corresponding restrictions as outlined in Scheme 5 (bottom). Note that the alternative biotransformation pathway initiated by a P450-mediated oxidation with epoxides (here, glycidyl acrylate), oxirenes (here, glycidyl propriolate), and ketenes as ultimate electrophiles (Schemes 3 and 4, right) would also be possible for acrylates, methacrylates, and propiolates with fully substituted allylic or propargylic carbon. For the time being, however, we confine the allyl and propargyl structural alert to the CES-ADH biotransformation pathway due to respective experimental evidence,9,30,31 assuming that the alternative P450 route is at least significantly less efficient as discussed above.

■

CONCLUSIONS The comparative analysis of the bacterial toxicity of acrylates, methacrylates, and propiolates in terms of 30-min bioluminescence and 24-h growth inhibition EC50 values indicates a significantly larger sensitivity of the long-term bioassay for the reactive toxicity of α,β-unsaturated esters. Interestingly, the situation was the reverse though much less pronounced in our previous study with epoxides.23 These findings indicate that for electrophilic compounds, the short-term to long-term ratio of 178



■ ■

Table 3. Subset of Four Acrylates and One Methacrylate with Experimental Data for Acute Fish Toxicity As Well As ShortTerm and Long-Term Bacterial Toxicitya fish log LC50 [M] no.

compd

A1

methyl acrylate ethyl acrylate isobutyl acrylate n-butyl acrylate methyl methacrylate

A2 B2 B1 D1

72-h C. auratus

96-h narcosis

30-min V. f ischeri

24-h V. f ischeri

n.a.

−4.24*

−2.03

−2.68*

−3.52*

−4.60* −4.79*

−4.30* −4.71*

−2.45 −3.22

−2.28 −3.52

−3.40* −4.00*

n.a.

−4.41*

−3.28

−3.22

−3.70*

−2.82

−2.26

−2.50

−2.28

ABBREVIATIONS EC50, effective concentration 50%; GSH, glutathione; Kow, octanol/water partition coefficient; Te, toxicity enhancement; log kGSH, rate constant of reaction with GSH; CDRGSH [day−1], critical GSH depletion rate constant; LC50, lethal concentration 50%

■

REFERENCES

(1) Greim, H., Ahlers, J., Blas, R., Broecker, B., Hollander, H., Gelbke, H. P., Jacobi, S., Klimisch, H. J., Mangelsdorf, I., Mayr, W., Schon, N., Stropp, G., Stahnecker, P., Vogel, R., Weber, C., Zieglerskylakakis, K., and Bayer, E. (1995) Assessment of structurally related chemicals − toxicity and ecotoxicity of acrylic−acid and acrylic−acid alkyl esters (acrylates), methacrylic−acid and methacrylic−acid alkyl esters (methacrylates). Chemosphere 31, 2637−2659. (2) Freidig, A. P., Verhaar, H. J. M., and Hermens, J. L. M. (1999) Quantitative structure−property relationships for the chemical reactivity of acrylates and methacrylates. Environ. Toxicol. Chem. 18, 1133−1139. (3) Böhme, A., Thaens, D., Paschke, A., and Schüürmann, G. (2009) Kinetic glutathione chemoassay to quantify thiol reactivity of organic electrophiles − application to α,β−unsaturated ketones, acrylates, and propiolates. Chem. Res. Toxicol. 22, 742−750. (4) Bö hme, A., Thaens, D., Schramm, F., Paschke, A., and Schüürmann, G. (2010) Thiol reactivity and its impact on the ciliate toxicity of α,β-unsaturated aldehydes, ketones and esters. Chem. Res. Toxicol. 23, 1905−1912. (5) Reinert, K. H. (1987) Aquatic toxicity of acrylates and methacrylates: quantitative structure-activity relationships based on Kow and LC50. Regul. Toxicol. Pharmacol. 7, 384−389. (6) Russom, C. L., Drummond, R. A., and Hoffman, A. D. (1988) Acute toxicity and behavioral effects of acrylates and methacrylates to juvenile fathead minnows. Bull. Environ. Contam. Toxicol. 41, 589−596. (7) Freidig, A. P., Verhaar, H. J. M., and Hermens, J. L. M. (1999) Comparing the potency of chemicals with multiple modes of action in aquatic toxicology: Acute toxicity due to narcosis versus reactive toxicity of acrylic compounds. Environ. Sci. Technol. 33, 3038−3043. (8) Harder, A., Escher, B., Landini, P., Tobler, N., and Schwarzenbach, R. (2003) Evaluation of bioanalytical assays for toxicity assessment and mode of toxic action classification of reactive chemicals. Environ. Sci. Technol. 37, 4962−4970. (9) Ohno, Y., Ormstad, K., Ross, D., and Orrenius, S. (1985) Mechanism of ally1 alcohol toxicity and protective effects of lowmolecular-weight thiols studied with isolated rat hepatocytes. Toxicol. Appl. Pharmacol. 78, 169−179. (10) Potter, D. W., and Tran, T.-B. (1992) Rates of ethyl acrylate binding to glutathione and protein. Toxicol. Lett. 62, 275−285. (11) McCarthy, T. J., Hayes, E. P., Schwartz, C. S., and Witz, G. (1994) The reactivity of selected acrylate esters toward glutathione and deoxyribonucleosides in vitro: structure−activity relationships. Fundam. Appl. Toxicol. 22, 543−548. (12) Johannsen, F. R., Vogt, B., Waite, M., and Deskin, R. (2008) Mutagenicity assessment of acrylate and methacrylate compounds and implications for regulatory toxicology requirements. Regul. Toxicol. Pharmacol. 50, 322−335. (13) Roberts, D. W., and Natsch, A. (2009) High throughput kinetic profiling approach for covalent binding to peptides: application to skin sensitization potency of michael acceptor electrophiles. Chem. Res. Toxicol. 22, 592−603. (14) Wondrousch, D., Böhme, A., Thaens, D., Ost, N., and Schüürmann, G. (2010) Local electrophilicity predicts toxicity− relevant reactivity of Michael acceptors. J. Phys. Chem. Lett. 1, 1605−1610.

−2.82*

a

The four alkyl acrylates are listed in the order of increasing log Kow, the latter of which is almost identical for ethyl acrylate and methyl methacrylate (see Table 1). Experimental fish LC50 data for fathead minnow (Pimephales promelas) and goldfish (Carassius auratus) were taken from literature,5,7 and the baseline narcosis model for fathead minnow 96-h LC50 was log LC50 [M] = −0.85 log Kow − 1.41.37 The experimental EC50 data for 30-min bioluminescence inhibition and 24h growth inhibition of the bacteria Vibrio f ischeri were taken from Tables 1 and 2, respectively. Log LC50 and log EC50 values with asterisks denote toxicity enhancements Te > 10 (see eq 3), using the respective baseline narcosis predictions for comparison (but employing the fathead minnow baseline narcosis model for both fathead minnow and goldfish LC50 data).

their toxicity may depend on the reactive mechanism of action. In the case of α,β-unsaturated esters, the latter is assumed to be governed by a Michael-type addition to endogenous nucleophiles and in the case of epoxides by a corresponding SN2-type ring-opening reaction. With regard to compoundclass-specific trends, the order of bacterial toxicity is propiolates > acrylates > methacrylates, apparently reflecting the respective order of Michael-acceptor reactivity. In the absence of additional reactive functionalities, methacrylates are generally expected to exert narcosis-level toxicity, thus enabling an even quantitative prediction of their aquatic toxicity for those species where baseline narcosis models are available. For acrylates and propiolates, electrophilic reactivity contributes significantly to their aquatic toxicity up to a certain (but class-specific) alkyl size, beyond which the derivatives exert narcosis-level toxicity. Separate reactive functionalities may offer additional toxicologically relevant reaction sites without or, in case of the allyl and propargyl group, after metabolic activation, again resulting in excess toxicity, which holds similarly for acrylates, methacrylates, and propiolates. Here, in vitro screening may be confounded by the lack of respective enzymes, which requires attention for the design of appropriate nonanimal testing strategies.

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ACKNOWLEDGMENTS

We thank Uwe Schröter for providing technical support.

bacteria log EC50 [M]

96-h P. promelas

Article

AUTHOR INFORMATION

Corresponding Author

*Tel: +49-341-235-1262. Fax: +49-341-235-1785. E-mail: [email protected]. Funding

Financial support was provided by the European Commission through the project OSIRIS (Optimized Strategies for Risk Assessment of Industrial Chemicals through Integration of Non-Test and Test Information, EU Contract No. GOCE-CT2007-037017), which is gratefully acknowledged. 179



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Structural Alerts for the Excess Toxicity of Acrylates, Methacrylates

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