Modeling skin sensitization potential of mechanistically hard-to-be-classified aniline and phenol compounds with quantum mechanistic properties
© Ouyang et al.; licensee BioMed Central. 2014
Received: 31 March 2014
Accepted: 20 November 2014
Published: 24 December 2014
Advanced structure-activity relationship (SAR) modeling can be used as an alternative tool for identification of skin sensitizers and in improvement of the medical diagnosis and more effective practical measures to reduce the causative chemical exposures. It can also circumvent ethical concern of using animals in toxicological tests, and reduce time and cost. Compounds with aniline or phenol moieties represent two large classes of frequently skin sensitizing chemicals but exhibiting very variable, and difficult to predict, potency. The mechanisms of action are not well-understood.
A group of mechanistically hard-to-be-classified aniline and phenol chemicals were collected. An in silico model was established by statistical analysis of quantum descriptors for the determination of the relationship between their chemical structures and skin sensitization potential. The sensitization mechanisms were investigated based on the features of the established model. Then the model was utilized to analyze a subset of FDA approved drugs containing aniline and/or phenol groups for prediction of their skin sensitization potential.
Results and discussion
A linear discriminant model using the energy of the highest occupied molecular orbital (ϵ HOMO) as the descriptor yielded high prediction accuracy. The contribution of ϵ HOMO as a major determinant may suggest that autoxidation or free radical binding could be involved. The model was further applied to predict allergic potential of a subset of FDA approved drugs containing aniline and/or phenol moiety. The predictions imply that similar mechanisms (autoxidation or free radical binding) may also play a role in the skin sensitization caused by these drugs.
An accurate and simple quantum mechanistic model has been developed to predict the skin sensitization potential of mechanistically hard-to-be-classified aniline and phenol chemicals. The model could be useful for the skin sensitization potential predictions of a subset of FDA approved drugs.
KeywordsChemical mechanisms Structure-activity relationship Skin sensitizer Anilines Phenols Quantum mechanism
Skin sensitization related dermatitis and rash represents the most common manifestation of chemical immunotoxicity in humans, which results in a cost estimated $1 billion annually due to lost work, reduced productivity, medical care, and disability payments in USA [1, 2]. In addition, as part of the regulatory review process, an increase in the incidence of skin allergies and hypersensitivity-related adverse events associated with the use of FDA regulated products or approved drugs has been observed, suggesting a safety gap between premarket review and the post market surveillance .
Common testing methods to assess skin sensitization potential of materials include: (1) guinea pig maximization test (GPMT); (2) murine-based local lymph node assay (LLNA). In GPMT tests, hazard identification is done by visual observations of erythema and edema reactions, which are subjective, are difficult to differentiate between contact allergens and strong irritants, and is time consuming . The LLNA is recommended by international regulatory agencies; however, inconsistencies between LLNA and clinical observations have been documented . Considering the existence of vast compounds around today, developing rapid and effective methods for chemical sensitizer identification/risk assessment is still a challenge .
In silico approaches are an attractive alternative to animal testing through analyzing the structural features of sensitizers/non-sensitizers to derive predictive rules or models . The risks of thousands of commercially available chemicals could be assessed in a cost effective manner. Among these approaches, mechanism based rules, which investigate the structural characteristics of sensitizers, are promising .
Historically, the first study of chemical reactivity and skin sensitization was reported in 1936 . A mechanism of small organic molecules to form an immunogenic complex by reacting with macromolecules (proteins or others) in the skin to cause sensitization was postulated. Currently, a more plausible mechanism reported involves a formation of covalent bonding between electrophilic allergens and nucleophilic moieties of amino acids from skin proteins (usually side chains) . Such amino acids include cysteine thiol (mainly) and lysine (amino), and to a lesser extent arginine, histidine, methionine and tyrosine . Based on the well-established principles of mechanistic organic chemistry, the skin sensitization potential of a chemical in many cases was predicted by its reactivity with these residues [9, 10]. However, some compounds need to be activated via either autoxidation outside the skin (prehaptens) or bioactivation inside the skin (prohaptens) to be able to form immunogenic complexes with skin proteins .
Structure-activity relationship (SAR) studies of skin sensitization potential have been successfully carried out for epoxyaldehydes , enone , halogenated aromatics , benzaldehydes , dienes , oximes , aldehydes  and epoxides . Aniline/aromatic amine and/or phenol derivatives are two large classes of frequently sensitizing chemicals. Quite a few pilot studies have been conducted [20–23]. Roberts et al. specifically investigated the sensitization mechanisms of diaminobenzenes or dihydroxylbenzenes . However, the predictability of the skin sensitization potential for these two classes of chemicals is unsatisfactory [6, 25]. Further exploration of novel sensitization mechanisms will be informative for constructing better SAR models/rules. In addition, aniline and phenol moieties that are often present in approved drugs can also cause skin sensitization. For example, contact dermatitis occurs in one individual following prolonged subcutaneous infusion of hydromorphone , a cancer pain treatment agent which contains one phenol moiety.
Drug-induced skin reactions may be associated with several biological mechanisms, but in many cases the precise mechanism is unclear . It is well-known that Type IV allergic reaction induced by many chemicals and drugs is a T-cell mediated delay type hypersensitivity which can cause skin sensitization/dermatitis .
In this study, we intended to establish an in silico model for a class of mechanistically hard-to-classify anilines and phenols to study the relationship between their chemical reactivity and biological allergic response. We then investigated sensitization mechanisms of action associated with these compounds based on the features of this model. The model was further utilized to analyze a subset of FDA approved drugs containing aniline and/or phenol groups in skin sensitization potential. The predicted skin sensitization potential for these drugs was validated according to relevant literatures and adverse event reports.
Quantum mechanics calculations
All chemical optimization and subsequent orbital analysis were performed by using the Gaussian 03 suite of programs . Chemicals were optimized using the AM1 Hamiltonian with the default optimization criteria [38, 39]. Calculations of the frontier molecular orbital, charge distribution and other quantum properties were carried out by using the 6-31Gd basis set. The quantum descriptors used in this study include the energies of the highest occupied molecular orbital (ϵ HOMO), the lowest unoccupied molecular orbital (ϵ LUMO), the second lowest unoccupied molecular orbital (ϵ LUMO+1), the second highest occupied molecular orbital (ϵ HOMO-1), the Mulliken atomic charges of the most negative (Q min) and most positive atoms (Q max), the Mulliken atomic charges of the N atom (Q N) in anilines or O atom (Q O) in phenols, the average of the absolute values of the charges on all atoms (Q m), and molecular dipole moment (μ). The shapes of the resulting orbitals were visualized using the GaussView application within Gaussian 03. All structures were either drawn or converted from SMILES (Simplified molecular-input line-entry system) strings, using Chembiodraw Ultra V12.0 (PerkinElmer Informatics Desktop Software).
The skin sensitization potency of a compound was symbolized by 1 (Yes) and 0 (No). The values of each quantum descriptor were linearly normalized to the same range (0 to 1), stepwise linear regressions between the quantum properties and experimental outputs of the training set were performed by the statistical package of R program version 3.0.0 . The properties with lower weighting factors were abandoned in the second step of linear regression.
Results and discussion
The compounds with aniline and/or phenol moieties can be classified into a single subclass for consideration of skin sensitizers. However, not all of the compounds possessing aniline or phenol groups are sensitizers, suggesting some compounds can form covalent bonds with skin proteins whereas others cannot. In this study, the sensitization potential of anilines and phenols were modeled using quantum mechanical descriptors.
Modeling the skin sensitization potential by quantum properties of anilines and phenols
The linear relationship between the predicted values and ϵ HOMO also suggests that a chemical with higher predicted value implies a higher reactivity for oxidation consequently resulting in higher skin sensitization potential. The LLNA data as a quantitative endpoint, posed a semi-dose-dependent manner, allows for prediction of potency. The EC3 values (effective concentration for a three-fold proliferation of lymph node cells) from the reported LLNA experiments of most allergen phenols were also collected as shown in Table 1. Weak sensitizers with higher EC3 values (meaning lower sensitization potential) have smaller P values. For example, P values of five weak sensitizers with100 > EC3 > 10 i.e., eugenol (CAS: 97-53-0, EC3 = 13.95), Dihydroeugenol (CAS: 2785-87-7, EC3 = 12.45), 2,2’-azodiphenol (CAS: 2050-14-8, EC3 = 27.90), 3-methyleugenol (CAS: 186743-26-0,EC3 = 32), and aniline (CAS: 62-53-3, EC3 = 89) were 0.549, 0.672, 0.580, 0.580, and 0.702, respectively. On the other hand, two moderate sensitizers, 2-Methoxy-4-methyl-phenol (CAS: 93-51-6, EC3 = 5.8), 4-Chloroaniline (CAS: 106-47-8, EC3 = 6.5), have a slightly higher P value 0.672, 0.656, respectively. Another two moderate sensitizers with smaller EC3 value, isoeugenol (CAS: 97-54-1, EC3 = 3.5) and 1-naphthol (CAS: 90-15-3, EC3 = 1.3) have greater P values, 0.840 and 0.886, respectively. For most chemicals, their -logEC3 values correlate with P values quite well, but for aniline, its –logEC3 value is much less potent than its P value predicted. This may indicate that the initial oxidation of aniline, which is quite fast, is not in this case the rate-determining step for protein haptenation. The analysis of the relationship between EC3 and ϵHOMO for these nine chemicals was reported in the Additional file 1.
Possible reaction mechanisms of aromatic anilines and phenols
Occurrence of electrophilic–nucleophilic reactions between chemical and skin proteins is a primary reason of chemical induced skin sensitization . Most chemicals with high skin sensitization potential can be classified as Michael acceptors (MA), SN2 electrophiles, SNAr electrophiles, Schiff base formers, or acylation agents. The reaction mechanisms of anilines and phenols, however, are poorly understood and very few of them can be classified into the aforementioned five categories. One proposed mechanism is that sensitization occurs via oxygen attack ortho to an amino group or via oxidative quinone-methide formation [25, 41]. For example, Roberts et al. reported the mechanistic chemistry of aromatic diamino-, dihydroxy-, and amino-hydroxy compounds  where two parallel chemical mechanisms were described as the most possible processes: oxidation to electrophilic (protein reactive) quinones, quinone imines, or quinone di-imines or formation of protein reactive free radicals. These mechanisms, unfortunately, are not applicable to the all single NH/OH substituted anilines and phenols. For instance, aniline and 4-butylaniline are sensitizers whereas 4-aminobenzoic acid, 4-aminobenzenesulfonamide, and 4-aminobenzenesulfonic acid are non-sensitizers. Beside the solubility effects and the formation of ions/zwitterions, the reactivity variety of chemical entities by substituent effects play an important role in reducing dermal penetration and immunogenicity of protein conjugates.
By analyzing the relationship between quantum properties and chemical reactivity, we successfully modeled the skin sensitization potential of two groups of chemicals (aromatic anilines and phenols) with a single coefficient of ϵ HOMO, while the energy of the lowest unoccupied molecular orbital (ϵ LUMO), considered as the critical factor for most electrophilic reactions [8, 11], was poorly correlated with sensitization potential. These results suggest the skin sensitization mechanism of those compounds may result from several steps but not a directly electrophilic reaction.
Predicting skin sensitization potentials of a subset of FDA approved drugs with aniline and phenol groups
There are no effective tools to predict the skin sensitization potential of drugs, because drug-induced skin reactions may be caused by several mechanisms either single or mixed . The skin sensitization, in the context, refers to T-cell mediated sensitization (type IV allergy). The reaction of chemicals with proteins was recognized as one of the necessary process of the T-cell mediated sensitization . The in silico mechanistic models may offer valuable insights into better understanding the initiation of drug induced allergies.
Prediction of skin sensitization potential for 6 FDA approved drugs that have side effect of allergic dermatitis reported in MetaADEDB database
This study has demonstrated how quantum chemical calculations can be utilized to predict skin sensitization potential and to infer the reaction mechanism for a class of mechanistically hard-to-be-classified chemicals containing aniline and phenol moieties. The outcomes emphasized that the energy of highest occupied molecular orbital plays an important role for predicting skin sensitization potential of these compounds, indicating the activation process occurred via either autoxidation or direct reaction with free radical. Our model was further applied to predict the allergenic potential of the approved drugs containing aniline and/or phenol moieties. Several of these drugs were identified as sensitizers and the prediction agreed well with their “allergic dermatitis” side effect. Thus, the data indicate that our newly developed in silico algorithm shows promise as a preclinical risk assessment tool for screening allergenic potential.
Again, we should point out that skin allergic reactions are not commonly seen for drugs given via the oral route. Though they may share similar mechanisms, caution should be taken when extrapolating our model from skin sensitization potential for topically applied chemicals to predict “allergic potential” of drugs.
Allergic contact dermatitis
Austin model 1
Chemical abstracts service
Effective concentration for a three-fold proliferation of lymph node cells
Food and drug administration
Guinea pig maximization test
Highest occupied molecular orbital
The murine-based local lymph node assay
Lowest unoccupied molecular orbital
Simplified molecular-input line-entry system
- SN2 :
A kind of nucleophilic substitution reaction mechanism
Nucleophilic aromatic substitution.
OQ would like to acknowledge the support from the National Natural Science Foundation of China (NSFC21202201).
The mention of commercial products, their sources, or their use in connection with material reported herein is not to be construed as either an actual or implied endorsement of such products by the Department of Health and Human Services. The findings and conclusions in this article have not been formally disseminated by the Food and Drug Administration and should not be considered to represent any agency determination or policy.
Release of copyright permission
There is no copyright in U.S. Government work (per 17 U.S.C. 105), and the work I am providing is a U.S. Government work.
- Lushniak BD: Occupational contact dermatitis. Dermatol Ther. 2004, 17 (3): 272-277. 10.1111/j.1396-0296.2004.04032.x.View ArticlePubMedGoogle Scholar
- Wizemann T: Public Health Effectiveness of the FDA 510(k) Clearance Process: Measuring Postmarket Performance and Other Select Topics: Workshop Report (2011). 2011Google Scholar
- Basketter DA, Scholes EW: Comparison of the local lymph-node assay with the guinea-pig maximization test for the detection of a range of contact allergens. Food Chem Toxicol. 1992, 30 (1): 65-69. 10.1016/0278-6915(92)90138-B.View ArticlePubMedGoogle Scholar
- Uter W, Johansen JD, Borje A, Karlberg AT, Liden C, Rastogi S, Roberts D, White IR: Categorization of fragrance contact allergens for prioritization of preventive measures: clinical and experimental data and consideration of structure-activity relationships. Contact Dermatitis. 2013, 69 (4): 196-230. 10.1111/cod.12117.View ArticlePubMedGoogle Scholar
- Teubner W, Mehling A, Schuster PX, Guth K, Worth A, Burton J, van Ravenzwaay B, Landsiedel R: Computer models versus reality: how well do in silico models currently predict the sensitization potential of a substance. Regul Toxicol Pharmacol. 2013, 67 (3): 468-485. 10.1016/j.yrtph.2013.09.007.View ArticlePubMedGoogle Scholar
- Enoch SJ, Cronin MT, Schultz TW, Madden JC: An evaluation of global QSAR models for the prediction of the toxicity of phenols to Tetrahymena pyriformis. Chemosphere. 2008, 71 (7): 1225-1232. 10.1016/j.chemosphere.2007.12.011.View ArticlePubMedGoogle Scholar
- Landsteiner K, Jacobs J: Studies on the sensitization of animals with simple chemicals compounds. II. J Exp Med. 1936, 64: 625-639. 10.1084/jem.64.4.625.View ArticlePubMedPubMed CentralGoogle Scholar
- Aptula AO, Roberts DW: Mechanistic applicability domains for nonanimal-based prediction of toxicological end points: general principles and application to reactive toxicity. Chem Res Toxicol. 2006, 19 (8): 1097-1105. 10.1021/tx0601004.View ArticlePubMedGoogle Scholar
- Divkovic M, Pease CK, Gerberick GF, Basketter DA: Hapten–protein binding: from theory to practical application in the in vitro prediction of skin sensitization. Contact Dermatitis. 2005, 53 (4): 189-200. 10.1111/j.0105-1873.2005.00683.x.View ArticlePubMedGoogle Scholar
- Aleksic M, Thain E, Roger D, Saib O, Davies M, Li J, Aptula A, Zazzeroni R: Reactivity profiling: covalent modification of single nucleophile peptides for skin sensitization risk assessment. Toxicol Sci. 2009, 108 (2): 401-411. 10.1093/toxsci/kfp030.View ArticlePubMedGoogle Scholar
- Enoch SJ, Madden JC, Cronin MTD: Identification of mechanisms of toxic action for skin sensitisation using a SMARTS pattern based approach. Sar Qsar Environ Res. 2008, 19 (5–6): 555-578.View ArticlePubMedGoogle Scholar
- Delaine T, Hagvall L, Rudbäck J, Luthman K, Karlberg A-T: Skin sensitization of epoxyaldehydes: importance of conjugation. Chem Res Toxicol. 2013, 26 (674): 684-Google Scholar
- Enoch SJ, Roberts DW: Predicting skin sensitization potency for michael acceptors in the LLNA using quantum mechanics calculations. Chem Res Toxicol. 2013, 26 (5): 767-774. 10.1021/tx4000655.View ArticlePubMedGoogle Scholar
- Roberts DW, Aptula AO, Patlewicz GY: Chemistry-based risk assessment for skin sensitization: quantitative mechanistic modeling for the SNAr domain. Chem Res Toxicol. 2011, 24 (7): 1003-1011. 10.1021/tx100420w.View ArticlePubMedGoogle Scholar
- Natsch A, Gfeller H, Haupt T, Brunner G: Chemical reactivity and skin sensitization potential for Benzaldehydes: can schiff base formation explain everything?. Chem Res Toxicol. 2012, 25 (10): 2203-2215. 10.1021/tx300278t.View ArticlePubMedGoogle Scholar
- Bergström MA, Luthman K, Nilsson JLG, Karlberg A-T: Conjugated dienes as prohaptens in contact allergy: in Vivo and in Vitro studies of structure - activity relationships, sensitizing capacity, and metabolic activation. Chem Res Toxicol. 2006, 19 (6): 760-769. 10.1021/tx060006n.View ArticlePubMedGoogle Scholar
- Bergström MA, Andersson SI, Broo K, Luthman K, Karlberg A-T: Oximes: metabolic activation and structure - allergenic activity relationships. J Med Chem. 2008, 51 (8): 2541-2550. 10.1021/jm701092n.View ArticlePubMedGoogle Scholar
- Patlewicz GY, Basketter DA, Smith Pease CK, Wilson K, Wright ZM, Roberts DW, Bernard G, Arnau EG, Lepoittevin J-P: Further evaluation of quantitative structure–activity relationship models for the prediction of the skin sensitization potency of selected fragrance allergens. Contact Dermatitis. 2004, 50 (2): 91-97. 10.1111/j.0105-1873.2004.00322.x.View ArticlePubMedGoogle Scholar
- Niklasson IB, Delaine T, Luthman K, Karlberg A-T: Impact of a heteroatom in a structure - activity relationship study on analogues of Phenyl Glycidyl Ether (PGE) from epoxy resin systems. Chem Res Toxicol. 2011, 24 (4): 542-548. 10.1021/tx100417r.View ArticlePubMedGoogle Scholar
- Itoh M: Sensitization potency of some phenolic compounds–with special emphasis on the relationship between chemical structure and allergenicity. J Dermatol. 1982, 9 (3): 223-233.View ArticlePubMedGoogle Scholar
- Malkowski J, Klenieswka D, Maibach H: Relationship between chemical structure and allergenicity: aromatic amines. Derm Beruf Umwelt. 1983, 31 (2): 48-50.PubMedGoogle Scholar
- Kleniewska D, Maibach H: Allergenicity of aminobenzene compounds: structure-function relationships. Derm Beruf Umwelt. 1980, 28 (1): 11-13.PubMedGoogle Scholar
- Payne MP, Walsh PT: Structure-activity-relationships for skin sensitization potential - development of structural alerts for use in knowledge-based toxicity prediction systems. J Chem Inf Comput Sci. 1994, 34 (1): 154-161. 10.1021/ci00017a019.View ArticlePubMedGoogle Scholar
- Aptula AO, Enoch SJ, Roberts DW: Chemical mechanisms for skin sensitization by aromatic compounds with hydroxy and amino groups. Chem Res Toxicol. 2009, 22 (9): 1541-1547. 10.1021/tx9000336.View ArticlePubMedGoogle Scholar
- Patlewicz G, Roberts DW, Uriarte E: A comparison of reactivity schemes for the prediction skin sensitization potential. Chem Res Toxicol. 2008, 21 (2): 521-541. 10.1021/tx700338q.View ArticlePubMedGoogle Scholar
- Cuyper C, Goeteyn M: Systemic contact dermatitis from subcutaneous hydromorphone. Contact Dermatitis. 1992, 27 (4): 220-223. 10.1111/j.1600-0536.1992.tb03249.x.View ArticlePubMedGoogle Scholar
- Lee A, Thomson J: Drug-induced skin reactions. Pharmaceut J 1999. 2006, 262: 357-362.Google Scholar
- Gerberick GF, Vassallo JD, Bailey RE, Chaney JG, Morrall SW, Lepoittevin JP: Development of a peptide reactivity assay for screening contact allergens. Toxicol Sci. 2004, 81 (2): 332-343. 10.1093/toxsci/kfh213.View ArticlePubMedGoogle Scholar
- Estrada E, Patlewicz G, Gutierrez Y: From knowledge generation to knowledge archive. a general strategy using TOPS-MODE with DEREK to formulate new alerts for skin sensitization. J Chem Inf Comput Sci. 2004, 44 (2): 688-698. 10.1021/ci0342425.View ArticlePubMedGoogle Scholar
- Barratt MD, Langowski JJ: Validation and subsequent development of the DEREK skin sensitization rulebase by analysis of the BgVV list of contact allergens. J Chem Inf Comput Sci. 1999, 39 (2): 294-298. 10.1021/ci980204n.View ArticlePubMedGoogle Scholar
- Schneider K, Akkan Z: Quantitative relationship between the local lymph node assay and human skin sensitization assays. Regul Toxicol Pharmacol. 2004, 39 (3): 245-255. 10.1016/j.yrtph.2004.02.002.View ArticlePubMedGoogle Scholar
- Roberts DW, Patlewicz G, Kern PS, Gerberick F, Kimber I, Dearman RJ, Ryan CA, Basketter DA, Aptula AO: Mechanistic applicability domain classification of a local lymph node assay dataset for skin sensitization. Chem Res Toxicol. 2007, 20 (7): 1019-1030. 10.1021/tx700024w.View ArticlePubMedGoogle Scholar
- Miller MD, Yourtee DM, Glaros AG, Chappelow CC, Eick JD, Holder AJ: Quantum mechanical structure-activity relationship analyses for skin sensitization. J Chem Inf Model. 2005, 45 (4): 924-929. 10.1021/ci050018z.View ArticlePubMedGoogle Scholar
- Kern PS, Gerberick GF, Ryan CA, Kimber I, Aptula A, Basketter DA: Local lymph node data for the evaluation of skin sensitization alternatives: a second compilation. Dermatitis. 2010, 21 (1): 8-32.PubMedGoogle Scholar
- Estrada E, Patlewicz G, Chamberlain M, Basketter D, Larbey S: Computer-aided knowledge generation for understanding skin sensitization mechanisms: the TOPS-MODE approach. Chem Res Toxicol. 2003, 16 (10): 1226-1235. 10.1021/tx034093k.View ArticlePubMedGoogle Scholar
- Basketter DA: Skin sensitization: strategies for the assessment and management of risk. Br J Dermatol. 2008, 159 (2): 267-273. 10.1111/j.1365-2133.2008.08625.x.View ArticlePubMedGoogle Scholar
- Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Montgomery JA, Vreven T, Kudin KN, Burant JC, Millam JM, Iyengar SS, Tomasi J, Barone V, Mennucci B, Cossi M, Scalmani G, Rega N, Petersson GA, Nakatsuji H, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa JIM, Nakajima T, Honda Y, Kitao O, Nakai H: Gaussian 03. In., Revision C.02. 2003, Wallingford, CT: Gaussian, IncGoogle Scholar
- Dewar MJS, Zoebisch EG, Healy EF, Stewart JJP: Development and use of quantum mechanical molecular models. 76. AM1: a new general purpose quantum mechanical molecular model. J Am Chem Soc. 1985, 107 (13): 3902-3909. 10.1021/ja00299a024.View ArticleGoogle Scholar
- Enoch SJ, Roberts DW, Cronin MTD: Mechanistic category formation for the prediction of respiratory sensitization. Chem Res Toxicol. 2010, 23 (10): 1547-1555. 10.1021/tx100218h.View ArticlePubMedGoogle Scholar
- R Development Core Team: R: A Language and Environment for Statistical Computing. 2010, Vienna, Austria: R Foundation for Statistical Computing, Retrieved from http://www.R-project.org Google Scholar
- Enoch SJ, Cronin MT, Schultz TW, Madden JC: Quantitative and mechanistic read across for predicting the skin sensitization potential of alkenes acting via Michael addition. Chem Res Toxicol. 2008, 21 (2): 513-520. 10.1021/tx700322g.View ArticlePubMedGoogle Scholar
- Karlberg AT, Bergstrom MA, Borje A, Luthman K, Nilsson JLG: Allergic contact dermatitis-formation, structural requirements, and reactivity of skin sensitizers. Chem Res Toxicol. 2008, 21 (1): 53-69. 10.1021/tx7002239.View ArticlePubMedGoogle Scholar
- Storle C, Eyer P: Reactions of the wurster blue radical cation with thiols, and some properties of the reaction-products. Chem Biol Interact. 1991, 78 (3): 333-346. 10.1016/0009-2797(91)90063-D.View ArticlePubMedGoogle Scholar
- Lepoittevin JP: Metabolism versus chemical transformation or pro- versus prehaptens?. Contact Dermatitis. 2006, 54 (2): 73-74. 10.1111/j.0105-1873.2006.00795.x.View ArticlePubMedGoogle Scholar
- Choquet-Kastylevsky G, Vial T, Descotes J: Allergic adverse reactions to sulfonamides. Curr Allergy Asthma Rep. 2002, 2 (1): 16-25. 10.1007/s11882-002-0033-y.View ArticlePubMedGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/2050-6511/15/76/prepub
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.