Mechanistic Applicability Domains for Non-Animal Based Prediction of

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Chem. Res. Toxicol. 2006, 19, 1228-1233

Mechanistic Applicability Domains for Non-Animal Based Prediction of Toxicological Endpoints. QSAR Analysis of the Schiff Base Applicability Domain for Skin Sensitization David W. Roberts,*,† Aynur O. Aptula,‡ and Grace Patlewicz§ School of Pharmacy and Chemistry, LiVerpool John Moores UniVersity, Byrom Street, LiVerpool L3 3AF, England, Safety and EnVironmental Assurance Centre, UnileVer Colworth, Sharnbrook, Bedford MK44 1LQ England, and European Chemicals Bureau IP582, Institute for Health and Consumer Protection, Joint Research Centre, European Commission, Via Fermi 21020, Ispra (VA) Italy ReceiVed May 10, 2006

Several recent (1999 onward) publications on skin sensitization to aldehydes and ketones, which can sensitize by covalent binding to skin protein via Schiff base formation, present QSARs based on the Taft σ* parameter to model reactivity and log P to model hydrophobicity. Here, all of the data are reanalyzed together in a stepwise self-consistent way using the parameters log P (octanol/water) and Σσ*, the latter being the sum of Taft σ* values for the two groups R and R′ in RCOR′. A QSAR is derived: pEC3 ) 1.12((0.07) Σσ* + 0.42((0.04) log P - 0.62((0.13); n ) 16 R2 ) 0.952 R2adj ) 0.945 s ) 0.12 F ) 129.6, based on mouse local lymph node assay (LLNA) data for 11 aliphatic aldehydes, 1 R-ketoester and 4 R,β-diketones. In developing this QSAR, an initial regression equation for a training set of 10 aldehydes was found to predict a test set consisting of the other 6 compounds. The QSAR is found to be well predictive for LLNA data on a series of R,γ-diketones and also correctly predicts the nonsensitizing properties of simple dialkylketones. It is shown to meet all of the criteria of the OECD principles for applicability within regulatory practice. In view of the structural diversity within the sets of compounds considered here, the present findings confirm the view that within the mechanistic applicability domain the differences in sensitization potential are dependent solely on differences in chemical reactivity and partitioning. Introduction In the light of new legislation (e.g., the REACH initiative in the European Union) several initiatives have recently emerged to increase acceptance of (quantitative) structure-activity relationships (QSARs) to reduce reliance on animal testing. Skin sensitization is an important end point. Sensitization of workers and consumers is a major problem for individuals, employers and for marketing certain products. It is an effect for which no threshold can be established yet, and it is a lifelong effect. In REACH, the sensitizing potential should, therefore, be assessed for chemicals below the 10 ton threshold (Annex V). No in Vitro alternative is available yet, nor will it be in the near future. According to an ECB assessment of additional testing needs under REACH, the highest number of tests is required for this end point (EC 2003) (1). Skin sensitization (contact allergic dermatitis) is a reactive toxicity end point: the sensitizing compound, either as such or after metabolic or abiotic conversion, binds covalently to skin protein, acting in most cases as an electrophile toward nucleophilic groups on the protein, leading to the formation of antigens (2). In our preceding article (3), we developed a “natural” classification into applicability domains on the basis of considerations regarding how a compound and the target organism between them “decide” on the nature and extent of the toxic effect. With particular emphasis on reactive toxicity, we * Corresponding author. Phone: + 44 151 231 2066. Fax: + 44 151 231 2170. E-mail: [email protected]. † Liverpool John Moores University. ‡ Unilever Research. § Joint Research Centre.

presented rules, based on organic reaction mechanistic principles, for classifying reactive toxicants into their appropriate mechanistic applicability domains, and argued that it should be possible to develop QSARs generally applicable within their mechanistic applicability domains, on the basis of reactivity and hydrophobicity parameters. In this article, we present a skin sensitization QSAR analysis for the Schiff base (SB) mechanistic applicability domain.

Materials and Methods The mouse local lymph node assay (LLNA) is the source of the biological data analyzed here. In the LLNA, a single dose of the test compound is given, by application of a solution to the skin of the ear. The end point is a quantitative inferential indicator of sensitization rather than a clinical response. Lymph node uptake of tritiated thymidine, which is an indicator of T-cell proliferation, is measured, and this is effectively the indicator for the sensitization process. The response is recorded as a stimulation index (SI), this being the ratio of tritiated thymidine uptake in treated animals to uptake in control animals. The assay is usually carried out over a range of dosages of test compound, and from dose-response analysis, it is usually possible to derive an EC3 value, this being the dose (expressed as percent concentration by weight) giving SI ) 3. For purposes of QSAR analysis, the EC3 values were converted to a molar logarithmic parameter pEC3 () log(M/EC3), where M is molecular weight). EC3 values are usually considered to be accurate within a factor of ca. 2, that is, within (0.3 on pEC3 (4). Compounds can be classified into potency categories in terms of their EC3 values: compounds with EC3 100% as nonsensitizers (5). The log P (P ) octanol/water partition coefficient) values for most of the compounds have been reported previously (6-10), and were calculated by the method of Hansch and Leo (11), modified, as appropriate, by the use of the Roberts method for branching in hydrophobic chains (12). The same method was used for new log P calculations. Taft σ* values were taken from the compilation of Perrin et al. (13) or calculated using the methods presented by Perrin et al. (13). QSAR equations were generated by multiple linear regression analysis using MINITAB software version 13.1 (MINITAB Inc., State College, PA). Data Sources and Approach for QSAR Analysis. A sequence of publications on aldehyde and ketone skin sensitization (6-10) present QSARs based on Taft σ* values (σ* values are the aliphatic counterparts of the Hammett values used for aromatic systems) to model reactivity and log P to model hydrophobicity. However, these publications are not the outcome of a single coordinated project but arose from more than one program with different objectives. The earliest article (6) resulted from an informal initiative within Unilever, two (8, 10) come from a European Union Fifth Framework project on fragrance allergens, and two (7, 9) present Unileverfunded work. We have, therefore, carried out the following reanalysis in order to draw out the overall implications. Our approach is as follows: 1. Perform a new regression analysis for SB aldehydes of ref 8. We consider that two of the compounds included in the original QSAR should be excluded because their high log P values suggest that they are in the region of parameter space where stratum corneum penetration is sensitization-determining, and potency is inversely correlated with log P. Therefore, the regression is carried out on a training set of 10 compounds. 2. Use the data on hexanal and methyl pyruvate (10) and the four R,β-diketones of ref 6 as a test set to compare the observed sensitization potentials with predictions from the QSAR derived from the 10-compound training set. 3. Explore the predictive performance of this QSAR across the wider SB mechanistic applicability domain, using further LLNA data, mainly from a recently published data set (14).

Figure 1. Training set carbonyl compounds. Table 2. Schiff Base LLNA Sensitization Test Set compound

log P

Σσ*

pEC3obs

pEC3calc

camphorquinone MeCOCOMe PhCOCOMe furil hexanal Me pyruvate

0.69 -1.22 1.02 1.42 1.95 0.10

1.62 1.81 2.20 0.50 0.26 2.00

1.55 0.79 2.30 0.80a 0.35 1.63

1.50 0.93 2.28 0.54 0.49 1.68

a Furil was classified as a nonsensitizer (6), having failed to give a stimulation index of 3 or above at the concentrations tested (up to 25%). The pEC3 value given here is from a dose-response QSAR plot for the first four compounds in the Table and corresponds to an extrapolated EC3 value of 30%.

The regression equation is pEC3 ) 1.12((0.11)Σσ* + 0.41((0.05) log P - 0.60((0.18) n ) 10, R2 ) 0.937, R2adj ) 0.919, s ) 0.11, F ) 52.2

(1)

Test Set. The test set is shown in Table 2, and structures are given in Figure 2. Table 2 also compares the observed pEC3 and EC3 values with those calculated from eq 1.

Results Training Set. The 12 aldehydes, which form the basis of the QSAR reported in ref 8, are shown in Table 1. For aldehydes, only one group attached to the carbonyl group is variable (R in RCHO); the other group (H) is constant. In ref 8, the reactivity parameter was the σ* value of the R group in RCHO. For the reanalysis, we added the σ* value for H (+0.49) so that the reactivity parameter is Σσ*. The Σσ* values are shown, together with log P values and pEC3 values, in Table 1. Figure 1 shows the structures.

Figure 2. Test set carbonyl compounds. Note that the noncyclic 1,2diketones exist predominantly as their transoid conformers.

The agreement between predicted and observed values is good. Linear regression gives:

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Roberts et al.

pEC3obs ) 0.99((0.11)pEC3calc + 0.01((0.15) n ) 6, R2 ) 0.957, R2adj ) 0.946, s ) 0.17, F ) 88.1

(2)

Note that although the training set consists entirely of aldehydes (incuding one dialdehyde, glyoxal), the test set, which it predicts very well, contains only one aldehyde, the others being ketones activated by another group (another keto group or, in the case of methyl pyruvate, a CO2Me group). The regression equation for the training and test sets combined is: pEC3 ) 1.12((0.07)Σσ* + 0.42((0.04) logP - 0.62((0.13) n ) 16, R2 ) 0.952, R2adj ) 0.945, s ) 0.12, F ) 129.6

(3)

This relationship is shown in Figure 3 as a graphical plot of pEC3obs against pEC3calc. We now assess the predictive performance of eq 3 across the wider SB mechanistic applicability domain. Simple Aliphatic Ketones. To our knowledge, no simple ketones (alkanones) of general structure RCOR (both Rs being alkyl) have been reported as sensitizers. Indeed, acetone is often used as a vehicle in sensitization tests. Table 3 shows the predictions of eq 3 for acetone and some higher homologues. It is not necessary to consider isomers other than the 2-alkanones because they have lower Σσ* values (σ* is 0 for Me and is negative for alkyl > Me). It is clear from Table 3 that simple ketones are predicted to be no more than very weak sensitizers in the LLNA. Above 2-undecanone (maybe before), penetration will become sensitization-determining and EC3 will increase with log P. However, bearing in mind that LLNA results appear to be influenced more than guinea pig tests by impaired ability to penetrate, it is possible that higher 2-alkanones could be positive in guinea pigs and humans. Ketones with electronegative substituents in the vicinity of the keto group will be more reactive than simple alkanones and, if appropriately hydrophobic, are more likely to be sensitizers. For example, the divalent C(OH)-CO-CH2OH grouping is part of the steroid skeleton (the highlighted carbon atom is numbered 17 in the steroid ring numbering system) of hydrocortisone. It has been proposed (15) that skin sensitization to hydrocortisone occurs via oxidation or dehydration to a highly electrophilic diketo group, either C(OH)-CO-CHO or CH-CO-CHO. However, the OH group is electronegative, and the effect of the two OH groups is to give a σ* value of about 0.95 for the CO group of C(OH)-CO-CH2OH. With a log P value in the range of 3-4, eq 3 would predict an EC3 value in the range 3-7% for hydrocortisone. Thus, it is not necessary to postulate an activation step; hydrocortisone itself is predicted to be reactive enough to sensitize. 1,3-Dicarbonyl Compounds. Recently a very useful compilation of LLNA data for 211 compounds has become available (14). Included in this compilation are data for 11 1,3-dicarbonyl compounds (9 are 1,3-diketones and 2 are beta-keto esters). A complicating feature of such compounds is their tendency to enolize. Usually, the ketoenol form is more hydrophobic than the diketo form because of intramolecular hydrogen bonding. For example, the calculated log P for the diketo structure PhCOCH2COCF3 is 1.65, whereas for the ketoenol form PhCOCHdC(OH)CF3 it is 2.95. Furthermore, the position of the keto-enol equilibrium is solvent-dependent, with polar solvents like water favoring the diketo form and nonpolar solvents favoring the ketoenol form (16). For unsymmetrical

Figure 3. Training and test sets combined: pEC3 observed vs pEC3 calculated from eq 3. Table 3. Aliphatic Ketones compound

log P

Σσ*

pEC3calc

EC3calc

acetone 2-octanone 2-decanone 2-undecanone

-0.24 2.46 3.54 4.08

0 -0.25 -0.25 -0.25

-0.72 0.13 0.59 0.81

304.95 94.19 40.39 26.11

1,3-diketones, there are two possible ketoenol forms; enolization of the keto group with the more electronegative substituent is favored. The Σσ* value for one carbonyl group in a 1,3-diketone is different according to whether or not the other carbonyl group is enolized. These complicating features add up to a substantial body of chemical information required to make a confident prediction of sensitization potential for a 1,3-dicarbonyl compound. We would need to know or be able to estimate the diketo/ketoenol equilibrium constants of the compound in the lymphatic medium and in the membrane medium where protein binding is assumed to occur. For the lymphatic medium, water is probably an adequate model, but the membrane medium is more difficult to model in this respect. Although the interior of the lipid bilayer in membranes is nonpolar and could be well modeled by a hydrocarbon solvent (which would tend to favor ketoenol forms), the phospholipid head groups at the membrane surface are H-polar and consequently could well have a similar effect to water on the diketo-ketoenol equilbrium. In the absence of experimental data on diketo-ketoenol equiibria in membrane-water systems, we started with the simplifying assumption that the 1,3-diketones with at least one nonaromatic carbonyl group are in the diketo form. For calculation of Σσ* values, we made the simplifying assumption that all ArCOCH2 groups can be treated as C6H5COCH2, with a σ* value of 0.88 (2.20 for PhCO multiplied by 0.4 for transmission of the inductive effect through the CH2 group (13)). For most of the compounds discussed here, we are confident that this is a reasonable approximation. However, for 1-(3′,4′,5′trimethoxyphenyl)-4-dimethylpentane-1,3-dione, the mesomeric effect of the 4′-methoxy group makes the carbonyl group less electronegative, as a result of which it is possible that the true Σσ* value is somewhat less than our calculated value. Eq 3 was used to predict pEC3 and EC3 values of all such 1,3-dicarbonyl compounds in the Gerberick et al. (14) data set. Table 4 compares the observed EC3 values with calculated values from eq 3. There are two compounds in the data set that were classed as nonsensitizers, having failed to reach an SI value of 3 at any

QSARs for Schiff Base Allergens

Chem. Res. Toxicol., Vol. 19, No. 9, 2006 1231

Table 4. 1,3-Diketones 1,3-diketones PhCOCHMeCOMe PhCOCH2COBu(n) 2-acetylcyclohexanone 1-(2′,5′-diethylphenyl)butane-1,3-dione 1-(2′,5′-dimethylphenyl)butane-1,3-dione 2,2,6,6-tetramethylheptane-3,5-dione 1-(2′,3,′4,′5′-tetramethylphenyl)butane-1,3-dione 4,4,4-trifluro-1-phenylbutane-1,3-dione 1-(3′,4′,5′-trimethoxyphenyl)-4-dimethylpentane-1,3-dione

log P Σσ* pEC3calc pEC3obs

EC3calc EC3obs (%) (%)

1.21 3.05 0.97 3.14

29 11 >40 10

0.68 0.63 0.53 0.88

0.65 1.37 0.38 1.68

0.78 1.30 1.36

39 9 59 4.6

2.09 0.88

1.24

1.17

11

13

2.45 0.32

0.77

0.84

32

27

2.93 0.88

1.60

1.43

5.6

8.3

1.65 3.49

3.98

3.98a

0.02

20

39b

>40

2.03

0.58b

0.88

a See text and Table 5. b The true Σσ* value may be rather less than the calculated value shown here (see text); this would lead to a higher EC3calc figure.

Table 5. Skin Sensitization Data for Aromatic Carbonyl Compounds compound

CAS

p-NO2C6H4CHO 2,3,4,5-Me4C6HCOCH2CO2Et C6H5COCH2CO2Et p-MeC6H4COCOC6H4Me(p) p-BrC6H4COCOC6H4Br(p) PhCOCHdC(OH)CF3a

555-16-8 170928-69-5 94-02-0 3457-48-5 35578-47-3 326-06-7

a

log P Σσ* 1.50 3.73 1.87 4.38 5.20 2.95

1.75 1.57 1.57 2.79 3.06 2.73

EC3calc EC3obs (%) (%) >50 33 >40 >50 20.5 20

2.6 0.5 2.3 0.009 0.004 0.05

Ketoenol form of 4,4,4-trifluro-1-phenyl-butane-1,3-dione (see text). Table 6. Skin Sensitization Data for Formaldehyde and Glutaraldehyde

compound

CAS

log P

Σσ*

pEC3calc

EC3calc (%)

EC3obs (%)

formaldehyde glutaraldehyde

50-00-0 111-30-8

0.35 -0.17

0.98 0.63

0.62 0.01

7.1 97.0

0.61 0.10

of the concentrations tested. One of these is 2-acetylcyclohexanone, tested up to 40%, for which our calculated EC3 is 59%. The other is 1-(3′,4′,5′-trimethoxyphenyl)-4-dimethylpentane1,3-dione, tested up to 40%, for which our calculated EC3 is 39% (but likely to be an underestimate due to neglect of the mesomeric effect; see above). Thus, we regard these two compounds as well predicted by eq 3. With 4,4,4-trifluro-1phenyl-butane-1,3-dione, which we discuss below, excluded, the sensitization potential of the six 1,3-diketones for which EC3 values were recorded is well predicted by eq 3. Comparing calculated and observed pEC3 values, the most positive and most negative residuals are 0.12 and -0.32, respectively, the mean residual is -0.06, and the standard deviation of the residuals is 0.16. 4,4,4-Trifluro-1-phenyl-butane-1,3-dione is much less potent than predicted from its diketostructure. The ketoenol forms of compounds of general structure ArCOCH2COR (R being alkyl), to the extent that they are present, will have the general structure ArC(OH)dCHCOR. The Ar group being more electronegative than the R group, the aromatic carbonyl group has a greater tendency than the aliphatic carbonyl group to enolize. However, it appears that in most of the cases in Table 4, the degree of enolization is not sufficient to greatly affect the sensitization potential. 4,4,4-Trifluro-1-phenyl-butane-1,3-dione, is an exception. In its diketo form PhCOCH2COCF3, it should be very reactive at the highlighted carbonyl group because of the electronegativity of the CF3 group. This is reflected in its high Σσ* value and

Figure 4. Atranol and chloroatranol and their tautomeric forms.

the low EC3calc value shown in Table 4. However, because the CF3 group is much more electronegative than any of the other substituents present in the compounds of Table 4, 4,4,4-trifluro1-phenyl-butane-1,3-dione has a much greater tendency to enolize than the other compounds, and it is the aliphatic carbonyl group that has the greater tendency to enolize. Consequently, 4,4,4-trifluro-1-phenyl-butane-1,3-dione is predicted to exist predominantly in the form PhCOCHdC(OH)CF3. The carbonyl group in this tautomer is aromatic and, hence, deactivated. This explains why 4,4,4-trifluro-1-phenyl-butane-1,3-dione is only a weak sensitizer. Aromatic Carbonyl Compounds. Aromatic groups are strongly deactivating for skin sensitization by reaction at the carbonyl group. In Patlewicz et al. (7), all of the aromatic aldehydes studied, of general formula ArCHO, were nonsensitizers. The effect was been attributed to the aryl group stabilizing the aldehyde by resonance to a greater extent than it stabilizes the transition state by its inductive effect. An analogous explanation has been proposed for the low reactivity of acetophenone, PhCOCH3, relative to alkylmethyl ketones RCOCH3 in their reactions with sodium bisulphite to form R-hydroxysulphonate addition products Ph-C(CH3)(OH)-SO3Na and R-C(CH3)(OH)-SO3Na (17). Some idea of the magnitude of the aromatic deactivating effect for skin sensitization is given by further data shown in Table 5, which compares LLNA data with predictions of eq 3. From Table 5, it can be seen that although an aromatic group does not always completely deactivate carbonyl groups for sensitization, its effect is large (in some cases over 3 orders of magnitude), and none of the compounds listed are more than very weak sensitizers. Formaldehyde and Glutaraldehyde. These two compounds have been proposed (18) to be specially potent as skin sensitizers because of their effectiveness as protein cross-linking agents (this property is the basis of their use as preserving and embalming agents). Comparison of their observed EC3 values with those calculated from eq 3 confirms that these compounds are indeed especially potent (Table 6). Atranol and Chloroatranol. These two compounds, whose structures are shown in Figure 4, are aromatic aldehydes and as such might be expected to be nonsensitizers. However LLNA data have been reported (19), indicating these compounds to be strong sensitizers. We hypothesise that they may be more reactive via their ketoenol tautomeric forms and, consequently, able to sensitize by the SB mechanism. The tautomeric forms are shown in Figure 4.

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In order to make predictions using the SB QSAR (eq 3), the Σσ* values for the reactive tautomers have to be calculated. The calculations (using the method of Perrin et al. (13)) are shown below: σ*(-CH2COR) + 0.5 σ*(-OH) + σ*(-CHdC(Me)R) ) 0.62 + 0.66 + 0.11 ) 1.39 Chloratranol T3: σ*(-CH2COR) + 0.5 σ*(-OH) + σ*(-CH2Cl) ) 0.62 + 0.66 + 0.94 ) 2.22

Atranol T2:

Using these Σσ* values together with the reported log P values (2.20 for Atranol and 2.73 for Chloratranol), EC3 values can be calculated from eq 3. The results are presented in Table 7. Table 7. Experimental and Calculated EC3 Values for Atranol and Chloratranol

atranol chloratranol

EC3calc from eq 3

EC3obs reported

2.1 0.2

0.6 0.4

The agreement is reasonable, bearing in mind the approximate nature of the Σσ* calculations and bearing in mind that the partitioning of the mixtures of tautomers may not be accurately reflected by the log P value of the nonenol forms. The agreement between experimental and calculated values supports but does not prove the hypothesis that these compounds sensitize by the SB mechanism through their ketoenol tautomers. Application of the OECD Principles to the New QSAR (eq 3). The recently proposed EU-REACH system calls for an increased use of QSARs and other non-animal methods, especially for the assessment of the low production volume chemicals. Therefore, several initiatives have recently emerged to increase acceptance of QSARs. The main principles for the validity of QSARs were identified in a workshop organized by CEFIC/ICCA in Setubal in 2002 and have since been evaluated by OECD (as part of the ad hoc Expert group for QSARs). These are now referred to as the OECD principles (20), which read as follows: “To facilitate the consideration of a QSAR model for regulatory purposes, it should be associated with the following information: -a defined end point -an unambiguous algorithm -a defined domain of applicability -appropriate measures of goodness-of-fit, robustness and predictivity -a mechanistic interpretation, if possible QSARs, which fulfill these criteria, may in principle be applicable within the regulation practice to predict mammalian end points.” Our skin sensitization QSAR, eq 3, for the SB mechanistic applicability domain, is now analyzed against these principles. 1. Defined End Point (Principle 1). The end point, EC3, is clearly defined and is accepted as an appropriate end point for the LLNA (Dir 2004/73/EC, method B42). 2. Defined Algorithm (Principle 2). This principle is met. The descriptors are calculated by methods that are well documented: Σσ* by the method of Perrin et al. (13) and log P by the method of Leo and Hansch (11). 3. Domain of Applicability (Principle 3). The QSAR is applicable across the whole SB mechanistic applicability domain. To use it confidently, it is of course necessary to be able to assign a compound to this applicability domain. This

requires organic chemistry expertise. All aliphatic aldehydes and ketones belong to this domain, unless they have other functional groups enabling them to be stronger sensitizers via the reaction chemistry of other mechanistic applicability domains. Aromatic aldehydes and ketones, without aliphatic aldehyde or keto groups, are excluded. For prediction of LLNA pEC3 values, there is a log P cutoff around 4.0. For compounds with log P values above 4.0, the pEC3 values in the LLNA would be increasingly overpredicted. However, for such compounds, the predicted values may give a better estimate of the true hazard to humans than real LLNA results. There is evidence that stratum corneum penetration becomes sensitization-determining at lower log P values for the LLNA than for guinea pigs tests and probably for humans. Thus, for alkyl alkanesulfonates RSO3R1 with R + R1 in the range C13-C19, the sensitization potential is an increasing function of log P in guinea pig assays but a decreasing function of log P for the LLNA (21-23). Humans are very easily sensitized to poison ivy (allergen a mixture of 3- pentadec(en)yl and 3-hetpadec(en)yl catechols, all with very high log P) and to many other very hydrophobic phytochemical and synthetic allergens such as sultones (24, 25). This argument applies more generally and, therefore, we would assert that for high log P electrophiles and proelectrophiles a QSAR prediction may be better than an LLNA test result for risk assessment purposes. It is also appropriate to consider the limits of the applicability of eq 3 in terms of the ranges of the parameter values. Eq 3 can be regarded as a quantitative mechanistic model, in that its general form is derived not from statistical evaluation of candidate variables but from physical organic chemistry based mathematical modeling: the Roberts and Williams RAI (Relative Alkylation Index) model (26). The model should apply for the whole range of Σσ* and log P values unless there are cutoffs where the physicochemical basis of the model ceases to apply. The only such cutoff apparent is the upper limit of about 4.0 for log P, as discussed above. There are no lower limits of applicability for log P and Σσ*: as these values decrease the predicted EC3 increases, to the point where it exceeds 100%, and the compound is predicted as a nonsensitizer. Within the error limits of the regression coefficients in eq 3 (these error limits on the prediction, of course, become wider as the values of log P and Σσ* fall further below the range represented in the training set), these predictions should be correct. The upper limit for log P is, as discussed above, about 4.0. There is a practical upper limit for Σσ*, based on the largest σ* values of R in R2CdO for which the compound is stable. One of the most electronegative (highest σ* values) R groups is nitro (-NO2, σ* ) 4.25). However the corresponding R2CdO compound is unknown. Among the most electron deficient stable types of carbonyl compound we can envisage would be compounds such as OdC(CO2Et)2 (diethyl ketomalonate: CAS, 609-09-6; Σσ*, 4.00; log P, -0.77, predicted EC3, 0.05%), OdC(CHO)2 (mesoxaldehyde: CAS, 497-16-5; Σσ*, 4.30; log P; -2.60, predicted EC3, 0.07%). These compounds are predicted to be in the extreme potency category. Perfluoroketones OdC(RF)2, which have Σσ* >5 and have log P values above 1.0 (except for hexafluoroacetone, log P, 0.91, which is a gas), are predicted to be even stronger sensitizers. 4. Internal Performance (Principle 4a). As stated previously, the QSAR equation (eq 3) fits the data very well (R2 ) 0.952). The compounds from which eq 3 was derived consist of 11 aldehydes, 1 R-ketoester, and 4 R,β-diketones. In developing the QSAR, an initial regression equation for a training set of 10 aldehydes was found to predict a test set

QSARs for Schiff Base Allergens

consisting of the other 6 compounds. Eq 3 is for the combined training and test sets. 5. External Validation for Predictivity (Principle 4b). Predictions of eq 3 are in good agreement with experimental data for nine 1,3-diketones. One further 1,3-diketone, PhCOCH2COCF3, is significantly less potent than predicted by eq 3. This is rationalized in terms of its thermodynamically more stable keto-enol tautomer, PhCOCHdC(OH)CF3, being an aromatic ketone and, hence, relatively unreactive. Predictions of eq 3 are also consistent with the lack of evidence for sensitization by simple aliphatic monoketones. 6. Mechanistic Basis (Principle 5). The mechanistic basis for the QSAR is very clear. It is based on the RAI pharmacokinetic model (26) relating sensitization potential to proteinbinding-reaction kinetics and partitioning. The protein-binding reaction involves nucleophilic attack on the carbonyl group. 7. Overall. The QSAR meets all of the criteria of the OECD principles.

Conclusions Starting from a QSAR for aliphatic aldehydes, we have developed a QSAR (eq 3) applicable across the whole Schiff base (SB) reaction mechanistic applicability domain. The QSAR is mechanistic model derived, being based on the RAI principle. It meets all of the criteria of the OECD principles. A diverse range of compounds, for which the only feature in common is the presence of an aliphatic carbonyl group capable of SB formation, is well predicted by this QSAR. In view of the structural diversity within the sets of compounds considered here, the present findings confirm the view expressed in our earlier publication (9) that within the mechanistic applicability domain the differences in sensitization potential are dependent solely on differences in chemical reactivity and partitioning. The findings we report here encourage us to investigate whether domain-wide QSARs can be developed for other mechanistic applicability domains. Acknowledgment. The work presented here was carried out as part of an ECB (European Chemicals Bureau) project, JRC contract CCR.IHCP.C430412.X0: Validation of (quantitative) structure-activity relationships for toxicological end points of regulatory importance. Lot 3: (Q)SARs for skin sensitization.

Chem. Res. Toxicol., Vol. 19, No. 9, 2006 1233

(5)

(6) (7) (8)

(9) (10)

(11) (12) (13) (14)

(15) (16) (17) (18) (19)

(20) (21) (22)

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relative contact allergenic potency. Contact Dermatitis 42, 344348. Kimber, I., Basketter, D. A., Butler, M., Gamer, A., Garrigue, J. L., Gerberick, G. F., Newsome, C., Steiling, W., and Vohr, H. W. (2003) Classification of contact allergens according to potency: proposals. Food Chem. Toxicol. 41, 1799-1809. Roberts, D. W., York, M., and Basketter, D. A. (1999) Structureactivity relationships in the murine local lymph node assay for skin sensitization: R, β-diketones. Contact Dermatitis 41, 14-17. Patlewicz, G., Basketter, D. A., Smith, C. K., Hotchkiss, S. A., and Roberts, D. W. (2001) Skin-sensitization structure-activity relationships for aldehydes. Contact Dermatitis 44, 331-336. Patlewicz, G., Wright, Z. M., Basketter, D. A., Pease, C. K., Lepoittevin, J.-P., and Arnau, E. G. (2002) Structure-activity relationships for selected fragrance allergens. Contact Dermatitis 47, 219226. Patlewicz, G., Roberts, D. W., and Walker, J. D. (2003) QSARs for the skin sensitization potential of aldehydes and related compounds. QSAR & Comb. Sci. 22, 196-203. Patlewicz, G., Basketter, D. A., Pease, C. K., Wilson, K., Wright, Z. M., Roberts, D. W., Bernard, G., Gimenez, A. E., and Lepoittevin, J.-P. (2004) Further evaluation of quantitative structure-activity relationship models for the prediction of the skin sensitization potency of selected fragrance allergens. Contact Dermatitis 50, 91-97. Hansch, C., and Leo, A. J. (1979) Substituent Constants for Correlation Analysis in Chemistry and Biology. Wiley and Sons, New York. Roberts, D. W. (1991) QSAR issues in aquatic toxicity of surfactants. Sci. Total EnViron. 109/110, 557-568. Perrin, D. D., Dempsey, B., and Serjeant, E. P. (1981) pKa Prediction for Organic Acids and Bases. Chapman and Hall, London. Gerberick, G. F., Ryan, C. A., Kern, P. S., Schlatter, H., Dearman, R. J., Kimber, I., Patlewicz, G. Y., and Basketter, D. A. (2005) Compilation of historical local lymph node data for evaluation of skin sensitization alternative methods. Dermatitis 16, 157-202. Bundgaard, H. (1980) The possible implication of steroid-glyoxal degradation products in allergic reactions to corticosteroids. Arch. Pharm. Chemi, Sci. Ed. 8, 83-90. Hine, J. (1962) Physical Organic Chemistry, 2nd ed, international student edition, p 176, McGraw-Hill, NY. Fieser, L. F., and Fieser, M. (1961) AdVanced Organic Chemistry, pp. 417-418, Reinhold, NY. Aptula, A. O., Patlewicz, G., and Roberts, D. W. (2005) Skin sensitization: reaction mechanistic applicability domains for structureactivity relationships. Chem. Res. Toxicol. 18, 1420-1426. SCCP (2004). Opinion on Atranol and Chloroatranol present in natural extracts (e.g., oak moss and tree moss extract). European Commission, Health & Consumer Protection Directorate General. December 2004. http://europa.eu.int/comm/health/ph_risk/committees/04_sccp/docs/ sccp_o_006.pdf (site accessed 10/8/2005). Organisation for Economic Co-operation and Development (OECD) (2004)http://www.oecd.org/document/23/0,2340,en_2649_34365_33957015 _1_1_1_1, 00.html Roberts, D. W., and Basketter, D. A. (1990) A quantitative structureactivity/dose-response relationship for contact allergic potential of alkyl group transfer agents. Contact Dermatitis 23, 331-335. Roberts, D. W., and Basketter, D. A. (1997) Further evaluation of the quantitative structure-activity relationship for skin-sensitizing alkyl transfer agents. Contact Dermatitis 37, 107-112. Roberts, D. W., and Basketter, D. A. (2000) Quantitative structureactivity relationships: sulfonate esters in the local lymph node assay. Contact Dermatitis 42, 154-161. Roberts, D. W., and Lepoittevin, J.-P. (1998) Hapten-Protein Interactions. In Allergic Contact Dermatitis. The Molecular Basis (Lepoittevin, J-P., Basketter, D. A., Goossens, A., and Karlbert, A-T., Eds) pp 129-154, Springer-Verlag, Heidelberg, Germany. Roberts, D. W. (1994) Structure-activity relationships in allergic contact dermatitis. Commun. Jorn. Com. Esp. Deterg. 25, 43-64. Roberts, D. W., and Williams, D. L. (1982) The derivation of quantitative correlations between skin sensitisation and physicochemical parameters for alkylating agents and their application to experimental data for sultones. J. Theor. Biol. 99, 807-825.

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