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The definition of the applicabilitydomain relevant to skin sensitizationfor the aromatic nucleophilicsubstitution mechanismS.J. Enoch a , T.W. Schultz b & M.T.D. Cronin aa School of Pharmacy and Chemistry, Liverpool John MooresUniversity, Liverpool, Englandb Department of Comparative Medicine, College of VeterinaryMedicine, The University of Tennessee, Knoxville, Tennessee, USAPublished online: 30 May 2012.

To cite this article: S.J. Enoch , T.W. Schultz & M.T.D. Cronin (2012) The definition ofthe applicability domain relevant to skin sensitization for the aromatic nucleophilicsubstitution mechanism, SAR and QSAR in Environmental Research, 23:7-8, 649-663, DOI:10.1080/1062936X.2012.679691

To link to this article: http://dx.doi.org/10.1080/1062936X.2012.679691

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SAR and QSAR in Environmental ResearchVol. 23, Nos. 7–8, October–December 2012, 649–663

The definition of the applicability domain relevant to skin sensitization for

the aromatic nucleophilic substitution mechanism

S.J. Enocha, T.W. Schultzb and M.T.D. Cronina*

aSchool of Pharmacy and Chemistry, Liverpool John Moores University, Liverpool, England;bDepartment of Comparative Medicine, College of Veterinary Medicine, The University ofTennessee, Knoxville, Tennessee, USA

(Received 19 January 2012; in final form 10 March 2012)

This study outlines how a glutathione reactivity assay (so-called in chemico data)can be used to define the applicability domain for the nucleophilic aromaticsubstitution (SNAr) reaction for benzenes. This reaction is one of the sixmechanistic domains that have been shown to be important in toxicologicalendpoints in which the ability to bind covalently to a protein is a key molecularinitiating event. This study has analysed the experimental data, allowing a clearand interpretable structure–activity relationship to be developed for the SNArdomain. The applicability domain has resulted in a series of structural alerts. Thedefinition of the applicability domain for the SNAr reaction and the resultingstructural alerts are likely to be beneficial in the development of computationaltools for category formation and read-across. The study concludes with how thisinformation can be used in the development of adverse outcome pathways.

Keywords: in chemico; SNAr; structural alerts; electrophilic reaction chemistry;adverse outcome pathways

1. Introduction

Integrated approaches to testing and assessment have been described as a way to logicallycombine, and thus make efficient use of, the data related to a particular in vivo hazard [1].One aspect of integrated approaches to testing is to use chemical category formation to filldata gaps for chemicals where toxicological data are missing. These category approachesare based on the hypothesis that ‘similar chemicals will have similar toxicological profiles’[2–4], and have been suggested to perform best when similarity is based on chemical andbiological similarity [2,4,5]. It is therefore important that the key chemical and biologicalevents that can be measured and/or predicted are investigated. Recent efforts haveconcluded that these key events should be organized into so-called adverse outcomepathways [6].

Computational approaches to the formation of chemical categories such as the OECD(Q)SAR Toolbox currently focus on grouping chemicals using the molecular initiatingevent (the first event in the biological pathway) as the measure of similarity [7]. Thisapproach has been shown to be successful, especially for hazard identification in which atoxic/not toxic answer is often sufficient [8,9]. However, identification of the key events ina given biological pathway would enable more robust chemical categories to be formed,

*Corresponding author. Email: m.t.cronin@ljmu.ac.uk

ISSN 1062–936X print/ISSN 1029–046X online

� 2012 Taylor & Francis

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based on additional chemical and biological information, that are relevant to the endpointof interest. Such categories are likely to be of more use in the full risk assessment process,especially where an indication of potency is required.

Skin sensitization is an important hazard endpoint that is often taken intoconsideration in regulatory decisions. It is Type IV contact allergy that is described intwo phases – the induction of sensitization and the subsequent elicitation [10]. While thereis general agreement regarding the sequential set of events leading to skin sensitization,understanding of the underlying biology of many of the key events remains incomplete [11].Because of biological complexity (e.g. multiple organs and multiple cell types), skinsensitization has historically been evaluated with in vivo tests. Among the in vivo methodsused to assess skin sensitization are the occluded patch test [12], the Magnusson–Kligmanguinea pig maximization test [13], and the local lymph node assay (LLNA) [14].

Initially, the chemical or allergen penetrates the outer epidermis of the skin prior to theformation of a stable conjugate with skin proteins. This stable conjugate or hapten–protein complex, is then processed by the epidermal dendritic cells (i.e. Langerhans cells),which subsequently mature and migrate out of the skin to the local lymph nodes. In thelymph nodes, the dendritic cells donate major histocompatibility complex moleculescontaining part of the hapten–protein complex to naive T cells. This leads to productionand proliferation of allergen chemical-specific memory T cells, some of which re-circulatethroughout the body.

The second (elicitation or challenge) phase occurs following a subsequent contact withthe allergen. Again, the hapten–protein conjugate is formed and subsequently taken up byepidermal dendritic cells, as well as other cell types. The circulating allergen-specificactivated memory T cells are triggered to secrete specific cytokines, which induce therelease of inflammatory cytokines and mobilization of other T cells, as well as otherinflammatory cells from the circulating blood. These cells migrate to the epidermis of theskin and induce the distinguishing local inflammatory response of red rash, blisters andwelts, and itchy and burning skin.

Since the work of Landsteiner and Jacobs [15,16], there has been growing evidence thatthe primary potency-determining step in skin sensitization is the formation of a stablehapten–protein conjugate. Consequently, the molecular initiating event leading to skinsensitization is postulated to be covalent binding with selected nucleophilic molecular sitesin dermal proteins, in particular the thiol groups found in cysteine or the amino groupfound in lysine [11,17].

Aromatic nucleophilic substitution involves a nucleophile attacking an aromatic ringsystem such as benzene that has been activated by the presence of electron-withdrawinggroups [18]. This reaction leads to the expulsion of an electronegative leaving group,typically a halogen, resulting in the formation of a new covalent bond between thenucleophile and chemical (Figure 1). Information defining the structural boundaries ofelectrophilic reactions is amenable to computational coding, and such computer-assistedtools are used in the formation of chemical categories for SNAr electrophiles.

The formation of good-quality mechanism-based categories relies on the identificationof the structural boundaries of the mechanistic domains. A number of studies haveattempted to define the structural domain of the various mechanisms by analysing toxicitydata for skin sensitization [3,17]. These approaches, while useful, run into difficulty due toareas of chemical space where a lack of in vivo data prevents the identification of structuralalerts. This is especially the case for chemicals projected to act via the SNAr mechanism, asthere are few chemicals in sensitization databases [19–21].

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The rate of the SNAr reaction is dependent on the ability of the electron-withdrawingactivating groups to stabilize the intermediate anion after attack of the nucleophile, and onthe ability of the leaving groups to stabilize the anionic intermediate. Quantifying theeffects of different activating groups and different leaving groups through in chemicoreactivity testing provides a means of scaling reactivity (and thus, skin sensitizationpotential) within the SNAr mechanism. Moreover, it provides a method of prioritizingchemicals for further in vitro testing, allowing the chemical space of the SNAr reaction tobe covered with a minimal number of tests.

The aim of this study, therefore, was to use in chemico data to experimentally define thechemical space of the SNAr reactivity domain for direct-acting electrophiles for an inchemico glutathione assay (direct-acting electrophiles do not require abiotic or metabolictransformation to be reactive). In addition, these in chemico data were used to define iso-reactive mechanistic clusters encoded as 2D structural alerts. Finally, an approach towardsthe development of the adverse outcome pathway for skin sensitization in which focussedtesting in relevant in vitro based assays is discussed.

2. Methods

2.1 Test chemicals

The chemicals examined in this investigation included substituted benzenes, in particularthose containing halogens and electron-withdrawing substituents. The selection of the testcompounds was based on commercial availability, with the intention to cover the chemicalspace of benzene derivatives’ likely reaction via the SNAr mechanism [18]. In order toprovide a definition of the SNAr mechanistic domain, certain compounds withoutin chemico reactivity were also assessed. All test substances were purchased fromcommercial sources (SigmaAldrich.com or Alfa.com) in the highest purity available (95%minimum) and were not further purified prior to testing.

2.2 Measurement of reactivity

Reactivity with the thiol group of glutathione (GSH) was measured in a simple and rapidspectrophotometric-based assay, with the free thiol quantified by its reaction with5,50-dithio-bis(2-nitrobenzoic acid) (DTNB) with the absorption of the product measuredat 412 nm. Briefly, experiments were performed by (a) freshly preparing GSH at 1.375mMby dissolving 0.042 g of reduced GSH into 100ml of phosphate buffer at pH 7.4; (b) freshlypreparing stock solutions of each tested compound by dissolving the test chemical in

-

Nu

X –

Y

Y

Y

Y

X

Y

Y

X NuNu

+

Figure 1. SNAr mechanism between a nucleophile and an activated benzene system resulting in theformation of a new covalent bond (Nu¼ biological nucleophile, Y¼ electron-withdrawing activatinggroups, X¼ electronegative leaving group).

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dimethyl sulfoxide (DMSO) to which phosphate buffer was subsequently added; and (c)combining the correct amounts of GSH solution, stock solution, and buffer to bring thefinal concentration of thiol to 0.1375mM, in a manner so the concentration of DMSO inthe final solution was always <10%.

Following range-finding experiments, ultimate experiments were performed withconcentrations adjusted to 90, 80, 60, 40, 20 and 10% of the stock solution. Associatedwith each assay was a control containing GSH and a blank without GSH. The RC50 values(the concentration giving 50% reaction in a fixed time of 2 h) were determined fromnominal chemical concentrations (dependent variable) and absorbance normalized to thecontrol (independent variable) using Probit Analysis of the Statistical Analysis Systemsoftware (SAS Institute, Cary, NC, USA). Chemicals with a RC50 value of >135mM wereconsidered non-reactive, as a contaminant at the level of 1% could be the cause of suchreactivity. Similarly, RC50 values of >70mM were treated as ‘suspect’, as a contaminant atthe 2% level could be the cause of such reactivity.

Additional reactivity testing was performed on selected benzenes that were not reactivein the buffer-based method. In these cases, the reactivity assessment was performed in amedium of 50% methanol and 50% buffer, with all other parameters being the same asdescribed above. This modification increased the solubility of test substances withoutaltering inherent reactivity (where appropriate these data are denoted in the RC50 (MeOH)column in the Tables). The comparability between reactivity measurements made inaqueous solution and methanol has been demonstrated previously [22].

2.3 Definition of activating and leaving groups

This study makes reference to the terms leaving and activating groups throughout thediscussion of the structure–activity relationship (SAR) for glutathione reactivity towardsbenzene derivatives. The term ‘leaving group’ refers to the types of organic functionalgroups that are sufficiently electronegative as to be able to ‘leave’ during the SNAr reaction(group ‘X’ in Figure 1). The potential leaving groups investigated in this study were F, Cl,Br, I, OCF3, CN and CHO. The term ‘activating group’ refers to organic functionalgroups that are sufficiently electron-withdrawing as to be able to ‘activate’ the benzenering system, making it more susceptible to the SNAr reaction (group ‘Y’ in Figure 1). Thesegroups help stabilize the negatively charged intermediate and thus lower the energyrequired for the reaction to proceed. The activating groups investigated in this study wereNO2, CN, CHO, COCH3, CF3 and multiple fluorine substituents.

3. Results and discussion

The aim of this study was to define the applicability domain of the nucleophilic aromaticsubstitution (SNAr) reaction using glutathione reactivity data for direct-acting electro-philes (selected data to illustrate the SARs present in the data are shown in Tables 1–6. Thefull dataset is available as supporting information, available via the SupplementaryContent tab on the article’s online page at http://dx.doi.org) [23]. This study details a SARanalysis of experimental data from which a series of structural alerts for the SNAr domainhave been developed. These structural alerts represent an update to the alerts previouslydeveloped using skin sensitization data, and have been developed using the iso-reactive

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Table 2. Activating group SAR based on analysis of 2,4-disubstituted fluorobenzene analogues.

Structure R ¼ RC50 (mM)

NO2

H

H H

R

FNO2 0.07CN 1.20CHO 2.80CF3 NR

NO2H

H

R

H

FNO2 0.07COCH3 0.10CHO 0.20CF3 0.62

Table 3. SAR for di-substitution patterns in dinitrochlorobenzenes.

Structure

NO2

NO2H

H H

Cl

O2N NO2

H

H

H

Cl

NO2

NO2

H

H

H

Cl

RC50 (mM) 1.60 1.80 2.30

Table 1. Leaving group SAR based on analysis of 2,4-dinitrobenzene analogues (NR¼ notreactive).

Structure R¼ RC50 (mM)

NO2

NO2H

H H

RF 0.07OCF3 0.21Br 1.00Cl 1.60CN 1.70I NRCHO NR

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Table 6. SAR for penta, tetra, tri and di-fluoro nitrobenzenes (NR¼ not reactive).

StructureNumber ofF atoms

F at atomnumbers RC50 (mM)

6

5

4

3

2

NO25 2–6 0.104 2–5 0.314 2–4, 6 0.453 2–4 0.833 3–5 0.843 2, 4, 5 1.1 (MeOH)3 2, 4, 6 2.6 (MeOH)2 2, 6 NR

Table 4. SAR for the addition of a third activating group to 2,6-dinitrochlorobenzene.

Structure

CN

H H

Cl

O2N NO2

CF3

H H

Cl

O2N NO2 O2N NO2

H

H

H

Cl

RC50 (mM) 0.07 0.11 1.80

Table 5. SAR for pentafluorobenzenes activated by a series of electron withdrawing R groups(NR¼ not reactive).

Structure R¼ RC50 (mM)

F

F

F

F

F

RNO2 0.10CN 0.43CHO 0.47COCH3 NR

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groupings concept [18,22,24]. In addition, a strategy for further in vitro testing in supportof the development of an adverse outcome pathway for skin sensitization is proposed.

3.1 General SAR analysis

Analysis of the glutathione data shows that in order for a benzene system to undergo anSNAr reaction it needs to contain a suitable leaving group and two or more electron-withdrawing activating groups. This is highlighted by the lack of reactivity towardsglutathione associated with any of the 4-halo-nitrobenzenes (see supplementary informa-tion, available via the Supplementary Content tab on the article’s online page). Theaddition of a second nitro group in the 2-position results in increased reactivity towardsglutathione, with 2,4-dinitrofluorobenzene being the most reactive chemical in the series(Table 1). The 2,4-dinitrobenzene series of chemicals also allow the leaving groups to berationalized in terms of increasing reactivity (Table 1). This ranking is the same as thatseen for reactions when the nucleophile is thiophenolate [25]. Finally, the effect of theactivating groups in both the 2- and 4-positions can be rationalized by inspecting thereactivity data when the leaving group is fluorine (Table 2).

In addition, examination of reactivity towards glutathione of the three di-substitutedchlorobenzenes shows the 2,4-substition pattern to be the most reactive, followed by the2,6-substitution pattern, with the 3,4-subsitution pattern the least reactive (Table 3).Finally, analysis of the addition of a third activating group to 2,6-dinitrochlorobenzeneshows that the presence of a third activating group results in increased reactivity (Table 4).

The final class of chemicals that were found to be reactive towards glutathione werethose containing a single activating group and three or more fluorine atoms. Analysis ofthe effect of the presence of the activating groups showed nitro to be the most reactive, andmethyl ketone to be unreactive towards glutathione (Table 5). Reducing the number offluorine atoms results in a corresponding decrease in reactivity towards glutathione(Table 6). Finally, replacing fluorine with chlorine results in the complete loss of reactivitytowards glutathione, as pentachloronitrobenzene was found to be unreactive.

3.2 Structural alerts based on iso-reactive groupings

The above data allow the chemical space for direct-acting electrophiles for the SNArmechanistic domain to be defined in terms of structural alerts. These structural alerts areuseful for grouping chemicals into broad categories. However, one of the key factorsgoverning a chemical’s potency as a skin sensitizer is its rate of reactivity towardsglutathione [22,25–27]. It has been previously shown that grouping chemicals with similarreactivity towards glutathione (in terms of their RC50 values) resulted in categoriescontaining chemicals with similar skin-sensitizing potencies [22]. In the current study, theboundaries shown in Table 7 were used to define four classes of iso-reactive groups:extremely reactive, highly reactive, moderately reactive and slightly reactive.

Analysis of the structural alerts detailed above and the associated reactivity data allowthem to be assigned to the iso-reactive groupings outlined in Table 7. Interestingly, all ofthe structural alerts fall into either the extremely, highly or moderately reactive iso-reactivegroupings. In addition, the structural alerts for which no experimental data exist (thosepredicted from the SAR analysis) have also been assigned to an iso-reactive grouping.

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These assignments are, obviously, more speculative than those supported byreactivity data.

3.2.1 Extremely reactive

Two structural alerts derived from chemicals with experimental data can be assigned tothis iso-reactive grouping. These are shown in Figure 2. In addition, a further twostructural alerts can be defined. The first of these (structure 1 in Figure 3) is derived fromthe fact that the SAR analysis showed fluoro, trifluoromethoxy, bromo and cyano groupsto be at least as reactive as chloro in studies on the 2,4-dinitrobenzene derivatives(Table 1).

3.2.2 Highly reactive

Nine structural alerts can be defined from the experimental data that can be assigned tothe highly reactive iso-reactive category. These structural alerts are shown in Figure 4.

R1 = F, OCF3, Br, CN R2 = NO2, CHO, CN

HH

R2

R1

NO2O2N

Figure 3. Structural alerts for chemicals predicted to belong to the extremely reactive iso-reactivegrouping.

Table 7. RC50 boundaries used to define iso-reactive groupings.

Iso-reactive grouping RC50 values (mM)

Extremely reactive <0.1Highly reactive � 0.1, <0.99Moderately reactive � 1.0, � 15.0Slightly reactive � 16.0, � 70.0

HHH

H

H

ClF

NO2

NO2

CN

NO2O2N

Figure 2. Structural alerts for the extremely reactive iso-reactive grouping.

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Analysis of the SAR data allows two further structural alerts that are likely to be belong tothe highly reactive iso-reactive grouping to be defined (Figure 5). The first of these twostructural alerts (structure 1 in Figure 5) is derived based on the same identification ofadditional leaving groups as was discussed for the extremely reactive iso-reactive grouping.The second alert (structure 2 Figure 5) is, as before, derived based on the analysis of theeffect of modifying the substituent in the 4-postion upon glutathione reactivity in fluorobenzene derivatives. In the derivation of this structural alert experimental data areavailable for the trifluoromethyl derivative (structure 5 in Figure 4), thus the SAR datasuggest that the nitro, aldehyde and methyl ketone derivatives will be at least as reactivetowards glutathione.

3.2.3 Moderately reactive

A final nine structural alerts were defined from the experimental reactivity data that can beassigned to the moderately reactive iso-reactive grouping. These alerts are shown inFigure 6. Two additional structural alerts can be predicted to belong to the moderatelyreactive iso-reactive grouping (Figure 7). These two alerts are derived based on theestablished ordering of the leaving groups in which fluoro trifluoromethoxy, bromo andcyano are all at least as reactive as chloro. However, in the case of the structural alertbased on the 3,4-dinitrobenzene scaffold (structure 1 in Figure 7) the cyano group is notincluded, as experimentally it falls into the highly reactive iso-reactive grouping (structure

(3)

R1 = CHO, COCH3, CF3

(2)(1)

(5)(4)

(9)(8)(7)(6)

HHH

HH

H

H H H H

HH

HH

H

HH

H

H

F

F

F

F

F

F

F

F

F

F

F

F

F

F

Cl

Cl

F

R1

F

NO2 NO2 NO2 NO2

CF3

NO2O2N

CF3

NO2

OCF3

NO2

NO2

NO2

CN

NO2

NO2

Figure 4. Structural alerts for the highly reactive iso-reactive grouping.

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3 in Figure 4). Thus, it is much more reactive than the trend in leaving groups wouldpredict for the 3-, 4-substitution pattern. One possible explanation for this is that it is thenitro rather than cyano that acts as the leaving group for 3,4-dinitrocyanobenzene. Thistype of reaction is also likely to be favoured due to nitro group being activated bysubstituents in the 2- and 4-positions (rather than the 3- and 4-positions if cyano is theleaving group). In contrast, the chloro group is a much poorer activating group,highlighted by the lack of reactivity towards glutathione for pentachloronitrobenzene.Thus, for 3,4-dinitrochlorobezene the reaction occurs with chloro as the leaving group.This is also likely to be true for the fluoro, bromo and trifluoromethoxy leaving groups

(3) (4) (5)

R1 = NO2, CN, CHO

(6) (7) (8) (9)

R1 = CN, CHO

(2)

R1 = Cl, Br, CN

(1)

H

H

H

H

H H

H

H H H

H H

H

H

H

H

H

HH

H

H

R1

R1

F

F

F

F

F

F F

F

F

F

F

F

R1

F F

F

ClClCl

NO2

NO2

NO2

NO2CHOCHO

NO2O2N

NO2

NO2

CHO

NO2

Figure 6. Structural alerts for the moderately reactive iso-reactive grouping.

R1 = NO2, CHO, COCH3

(2)

R1 = F, OCF3, Br, CN

(1)

HHHH

R1

Cl

R1

F

CF3

NO2O2N NO2

Figure 5. Structural alerts predicted to belong to the highly reactive iso-reactive grouping.

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(although no data exist to confirm this). The differing mechanisms are summarized inFigure 8.

3.3 Adverse outcome pathway for skin sensitization and targeted in vitro testing

The adverse outcome pathway concept has been recently introduced in eco-toxicology as amethod for a more intelligent approach to risk assessment testing [6,28]. A number ofstudies have investigated some of the key mechanistic steps involved in skin sensitization,these being: penetration through the epidermis, covalent binding to skin proteins[11,26,27,29], gene expression of antioxidant response elements in keratinocytes [30–32],activation of dendritic cells [33–36] and T-cell proliferation [19,20]. With the exception ofT-cell proliferation data (which are drawn from the in vivo LLNA assay), the remainder ofthese mechanistic studies have been carried out using in vitro assays on a relatively smallnumber of chemicals, usually selected based on those previously tested in the LLNA.

HNO2

HCl

S

S

SH

Cl

G

NO2

CN

G

NO2

NO2

G

NO2

NO2

CN

NO2

NO2

+

+

Figure 8. Possible mechanistic explanation for the apparent increased reactivity of3,4-dinitrocyanobenzene compared to 3,4-dinitrochlorobenzene (GSH¼ glutathione).

R1 = F, Br, OCF3

(1)

R1 = F, Br, OCF3, CN

(2)

H

H

H

R1

H

H

H

R1

NO2O2N

NO2

NO2

Figure 7. Structural alerts predicted to belong to the moderately reactive iso-reactive grouping.

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Clearly, this approach to chemical selection has been beneficial in allowing the developersof these assays to benchmark their findings against known skin sensitizers (as measured bythe LLNA). However, it fails to take into account the knowledge of the types of chemistrythat are likely to undergo the molecular initiating event [37], resulting in, at best, the samecoverage in each of the mechanistic domains. This is especially true in the SNArmechanistic domain, for which only 10 chemicals have been tested in the LLNA [21,38].

The current study (in addition to a previous study investigating the Michael additionmechanistic domain [39]) gives an indication of how a more focussed approach towardsin vitro testing could be undertaken in the future using an adverse outcome pathway-basedapproach. This approach would involve the testing a representative sample of thechemicals from each of the iso-reactive groupings investigated in studies such as this one inthe appropriate in vitro assays [30–36]. This would allow for the development of chemicaldatabases for the key mechanistic steps involved in skin sensitization that cover thechemical space of the five mechanistic domains associated with the molecular initiatingevent. Analysis of such databases would allow for the development of in silico sub-profilersbased on the additional mechanistic knowledge gained from analysis of in vitro data. Suchsub-profilers would be used after an initial profiler (developed from in chemico data) todevelop category-containing chemicals that are as mechanistically similar as possible. Thisapproach would be a clear advantage to the current category approach (as implemented intools such as the OECD (Q)SAR Toolbox), in which only knowledge of the molecularinitiating event is used as the mechanistic basis for category formation. This process ofprofiling and sub-profiling using a combination of in chemico and in silico data issummarized in Figure 9 (n.b. the suggested in vitro sub-profilers are for illustration only,step 4 indicates that other in vitro data based sub-profilers may also be useful).

4. Conclusions

This study has shown how in chemico reactivity data can be used to define the applicabilitydomain of direct-acting electrophiles acting via the SNAr mechanism. In addition, it has

1. MIE based profiler based on in chemico data

MIE based chemical category

2. Sub-profiler based on gene expression in vitro

data

3. Sub-profiler based on activation of dendritic

cells in vitro data

4. Sub-profiler based on additional in vitro data

MIE and additional mechanistic steps based chemical

category

Figure 9. Category formation using profilers and sub-profilers based on mechanistic knowledgedeveloped from in chemico and in vitro data.

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also highlighted how such data can be used to develop iso-reactivity groupings within

which the rate of reactivity towards glutathione can be considered as relatively constant.

Such iso-reactive groupings are useful in the development of chemical categories in which

it is possible to group chemicals based on their similarity in terms of reactivity. It is also

clear from this study that future in vitro testing efforts need to focus on the testing of

chemicals that cover the applicability domain of the molecular initiating event, and in

particular the various iso-reactive groupings present in a given domain. Such focussed

testing would allow for the development of improved in silico profilers and thus the

formation of chemical categories that take into account information about additional

mechanistic steps in the skin sensitization process. Such categories are likely to be of use in

a regulatory risk assessment environment, especially when the prediction of potency is

important. This study has also outlined how this information can be used in the

development of adverse outcome pathways.

Acknowledgements

The funding of the European Chemicals Agency Service Contract No. ECHA/2008/20/ECA.203 isgratefully acknowledged. The project was sponsored by Defra through the Sustainable Arable LinkProgramme.

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