p​‌‍‍‍‌‍‍‍‌‍‍‍‌‌‌‌‌‌‍‍​rovide a summary using the artical ive copied and pasted below Contact allergy: the role of skin chemistry and metabolism Introduction Allergic contact dermatitis (ACD) results from the T-lymphocyte mediated immune response to a chemical allergen that comes into contact with the skin (Fig. 1). The small allergenic molecule (hapten) penetrates the skin and binds to a carrier protein, typically by a covalent bond, to form an antigenic hapten–protein complex. The antigenic complex is processed by antigen-presenting cells, principally the dendritic Langerhans cells of the epidermis. These cells migrate to the draining lymph node, where they present the chemical to the T-lymphocyte to provide the stimulus for antigenspecific commitment and the production of memory and effector T lymphocytes. Subsequent contact with a sufficient dose of the chemical will then result in the expression of the clinical signs of ACD.1 The primary elements associated with the induction of ACD involve skin penetration, possible metabolic activation of unreactive chemicals and covalent binding to skin protein. Understanding of these elements has developed rapidly in recent years, providing opportunities for greater prospective identification of potential contact allergens, as well as aiding their recognition in relation to clinical diagnosis. In this short article, we provide an overview of the state of knowledge in this area Skin penetration The first hurdle a chemical must cross in order to behave as a contact allergen is presented by the stratum corneum. Some of the physicochemical properties that modulate penetration into the viable layers of the epidermis are fairly well characterized: hydrophobicity (as measured by the log octanol ? water partition coefficient, logP), the presence of charged groups, aqueous solubility and molecular shape and size.2 All of these properties can be measured and ? or calculated for a substance of defined chemical structure. For example, chemicals with a low molecular weight (< 500 g ? mol) and with a logP of > 1 are very likely to be able to penetrate the lipid-rich stratum corneum effectively. In contrast, larger hydrophilic, charged molecules will penetrate very poorly (reviewed in ref. 2) However, the value of being able to make predictions related to skin penetration of chemicals only becomes clear when allied to an understanding of what the chemical might do once in the viable epidermal layers and thus in contact with Langerhans cells. In addition, a potentially compromised skin barrier (effected by physical or chemical insults or an inherent abnormality, e.g. ceramide deficiency) will have a substantial impact on the overall rate of penetration of a chemical into the epidermis. Chemical characteristics There is a long-established connection between the ability of chemicals to react with proteins to form covalently linked conjugates and their skin sensitization potential.3 For skin sensitization to occur, once a chemical has penetrated, it must be able to partition into and between the relevant intra-, extra- and subcellular compartments of the epidermis, in order to be appropriately and sufficiently bioavailable. Then the chemical, or its metabolite, must be sufficiently electrophilic to react covalently with nucleophilic groups on skin proteins to produce the complete antigens capable of stimulating the immune system. This reaction with protein is likely to be selective for particular amino acid units. Uncovering the mechanisms of skin sensitization provides valuable insights into the behaviour of chemicals for hazard identification purposes and subsequent risk assessment.1,4 Currently, predictive testing involving animals has to be performed with the ultimate aim of identifying sensitization hazard and potency and reducing the risk of producing allergic contact dermatitis in man. An alternative approach involves examining key physicochemical properties of substances and relating these to sensitization potential. Such structure– activity relationships (SARs) provide a means of investigating and predicting the toxicological effects of chemicals. SARs are based on the principle that the toxicological properties of a chemical are dependent upon the chemistry of the toxin of interest. One approach to establishing SARs is the Relative Alkylation Index (RAI), a mathematical model derived by Roberts and Williams,5 based on electrophilicity and hydrophobicity parameters as well as the dose of chemical. The RAI model has been used to evaluate data on various sets of skin-sensitizing chemicals including sultones, para-nitrobenzyl halides, acrylates, sulphonate esters, and substituted gamma butyrolactones.6 The RAI approach continues to prove valuable in the generation of quantitative (Q) SARs, for example in recent work on aldehydes and 1,2-ketones by Patlewicz et al. 7 However, a limitation of these types of QSAR is that they are restricted to congeneric sets of chemicals, which in effect ensures that the chemical studied will have a common reaction mechanism. Of course this limitation is in one sense a strength as it ensures that these QSARs are soundly based on a proper appreciation of the chemistry involved, which is in contrast to the statistical methods discussed below. Other approaches include the development of empirical QSARs by application of statistical methods to sets of biological data and structural descriptors. For many years, guinea pig tests have provided the data from which SARs have been derived. Enslein et al. 8 developed QSAR models for assessing dermal sensitization using guinea pig data for 315 chemicals. Two models were proposed; one for aromatics (excluding chemicals with one benzene ring) and the other for aliphatics and chemicals with one benzene ring. The models resolved a qualitative potency in terms of bands of classification. Rather than a hypothesis-based approach (with its intrinsic potential weakness), a variety of descriptors were computed for the chemicals selected; stepwise twogroup discriminant analysis was used to build the models and identify relevant descriptors. An optimum prediction space algorithm was incorporated into the model to ensure predictions were only made for new chemicals within the model domain. This model was incorporated into the Toxicity Prediction by Komputer Assisted Technology (TOPKAT) expert system. Though a useful predictive tool, the model is constrained by the limitations of the Guinea Pig Maximization Test (GPMT) assay on which it is based (which itself over-predicts the response) and the scope of the training data set, and because previously identified mechanisms of action were not considered. The introduction of the local lymph node assay (LLNA) with its quantitative endpoint for skin-sensitizing potency has proved a major boost to skin sensitization QSARs. The LLNA involves topical application of the test chemical to mouse ear skin followed by quantitative measurement of the T-cell proliferation response in the draining lymph node, assessed as a function of the incorporation of tritiated thymidine. The method is described in detail by Basketter et al. 9,10 It is possible to use LLNA dose–response studies to determine the dose required to produce a defined degree of sensitization (typically a3 fold degree; the EC3 value) by interpolating the dose–response plot.1,11,12 This is discussed in more detail in the companion paper to this article.13 Using LLNA data, Patlewicz et al. 14 developed SARs for classifying the skin-sensitizing potential of 17 aldehydes as strong, moderate or weak skin sensitizers. The aldehydes were grouped into four distinct subcategories of functionally related aldehydes: aryl-substituted aliphatic, aryl, aryl with special features (that can undergo metabolism) and a,b-unsatura​‌‍‍‍‌‍‍‍‌‍‍‍‌‌‌‌‌‌‍‍​ted aldehydes. When dealing with aldehydes as a generic class of compounds employing the statistical approach, little correlation was found between sensitization potential and generic chemical properties. However, good correlations were observed using the RAI model within the a,bunsaturated aldehydes subcategory. Chemical reactivity was modelled using the r* value of the alkyl group. The relative sensitization potency was defined as 0.99r* + 1.5. A good linear correlation was observed with an r 2 of 0.998. The equation of the straight line was y ¼ 0.09856x + 1.4963, where x is 0.99r* + 1.5 and y is log(1 ? EC3)*, where y ¼ –log(EC3) + log (molecular weight). Despite the complexities and the still limited understanding of some of the processes leading to skin sensitization, it is possible to describe some of the relationships between chemical structures and the ability to form covalent conjugates with proteins. This knowledge, which relates chemical structure to a specific endpoint, can be programmed into expert systems. A toxicity prediction expert system is a computational program that embodies a range of QSARs or other knowledge that can be used to predict the toxicity of chemicals, including those which have not been synthesized and for which no safety data are available. Deductive Estimation of Risk from Existing Knowledge (DEREK) (https://www.chem.leeds.ac.uk/ LUK/derek/index.html) is a knowledge-based expert system which reflects the current state of knowledge of structure–toxicity relationships with an emphasis on the understanding of mechanisms of toxicity and metabolism. The knowledge base covers a wide variety of important toxicological endpoints, which include carcinogenicity, mutagenicity, skin sensitization, teratogenicity, irritancy, and respiratory sensitization. The expert knowledge incorporated into the DEREK system originated from Sanderson and Earnshaw.15 These workers identified a series of substructures associated with certain types of toxic activity. These structural alerts are codified in the rule-base so that, when an unknown structure is analysed by the software, the system carries out a pattern recognition process to identify similar structural features. A strength of the DEREK expert system is that it can evolve as new knowledge is acquired. For example, the rules related to skin sensitization were updated relatively recently.16 The last version (v5.01) of the DEREK software has some 60 chemical structural rules for skin sensitization and also incorporates a reasoning engine that uses logP and an algorithm for skin permeability in order to refine the assessment of the propensity of a chemical to induce skin sensitization in humans. Figure 2 summarizes the reactive chemistry normally associated with the potential to cause skin sensitization. Skin metabolism It is generally accepted that small molecules require covalent binding to macromolecular proteins to become immunogens. However, many small molecular compounds are chemically inert and are therefore not able to bind to proteins directly. Such compounds are te prohaptens, which, although non-electrophilic in nature, may be converted into an electrophilic species. Prohaptens may be converted chemically; for example, some chemicals, such as turpentine, limonene, linalool and colophony, may be oxidized to an electrophilic protein-reactive species upon exposure to air over time. Alternatively, prohaptens may be metabolized to more reactive species by xenobiotic metabolizing enzymes, for example isoeugenol, paraphenylenediamine and pentadecylcatechol. The skin has been recognized as an important site of extrahepatic metabolism. This is especially true for the epidermis, which constitutes part of the major interface between the body and the environment. Xenobiotic metabolism is divided into at least two phases. Phase 1 reactions are predominantly mediated by cytochrome P450 isoenzymes,17 although other phase 1 enzymes, for example alcohol and aldehyde dehydrogenases, also play roles in activating chemicals in the skin.18 Metabolizing enzymes likely to be involved in the generation of reactive species in skin are summarized in Table 1. Various conjugating enzymes, for example sulphatases, glucuronidases and glutathione S-transferases, mediate phase 2 reactions, which normally lead to the formation of more hydrophilic derivatives that can be better eliminated from the body.17 In general, such metabolism results in the detoxification of xenobiotics. However, if a highly reactive intermediate is formed that cannot be easily detoxified, it may reside in the skin for long enough to bind to nucleic acids or proteins, and could result in gene mutations in the former (leading to carcinogenesis) or hapten formation (and possibly sensitization) with the latter. Hence, there is a balance between the phase 1 activation mechanisms and phase 2 detoxification mechanisms in the skin that can mediate toxicity. A good example of the role skin metabolism may play is the potential activation of cinnamic alcohol to the presumed in vivo allergen cinnamic aldehyde (Fig. 3).19 Cinnamic alcohol is a chemically unreactive constituent of the European Standard Test Allergen Fragrance Mix, yet it is known to be an allergen. The action of alcohol dehydrogenase in the epidermis yielding the strongly sensitizing cinnamic aldehyde would provide a potential explanation as to how cinnamic alcohol could give rise to ACD. In practice, it has proved hard to detect the formation of free (not protein-bound) cinnamic aldehyde from the corresponding alcohol in in vitro experiments using intact skin and skin homogenates.20,21 However, the presence of protein-bound cinnamaldehyde has been observed in skin treated with cinnamic alcohol using cinnamaldehyde-specific immunodetection methods.22 This suggests that any cinnamaldehyde formed within the skin is either detoxified rapidly (to cinnamic acid) or becomes protein-bound. However, the picture may be more complex than is predicted. In the clinic, whilst a proportion of those who are patch test positive to cinnamic alcohol also react to cinnamaldehyde (supporting the hypothesis of a common cinnamaldehyde-derived hapten), others are only cinnamic alcohol positive and do not react to cinnamaldehyde. This clinical observation suggests that there may also be other mechanisms that could contribute to cinnamic alcohol allergy (J.P. McFadden, St. John’s Institute of Dermatology, London, UK, personal communication). A true cross-reactivity patch test study has not been performed to date for these compounds. Although our understanding of the role of metabolic activation (and inactivation) in ACD is in its infancy, it seems very probable that this is one of the key elements responsible for the inter-individual differences in human responses to chemical contact allergens and may provide the rationale for why some individuals tolerate a lifetime of exposure to allergens such as p-phenylene diairune PPD, whilst others experience ACD after only modest amounts of exposure. Conclusion Through the recognition that the toxic properties of chemicals are inherent in their molecular structure, a body of knowledge has been developed with respect to the physicochemical parameters influencing skin penetration and the chemical substituents and structural alerts that define chemical reactivity with proteins. This knowledge, particularly as embodied in a computerbased expert system such as DEREK, can be employed to predict which chemicals are most likely to have the potential to cause skin sensitization. Although the predictions are not yet wholly accurate, with the consequence that in vivo models are still the most reliable, progress continues to be made in this area. Notably, improvements in understanding of the role of skin metab​‌‍‍‍‌‍‍‍‌‍‍‍‌‌‌‌‌‌‍‍​olism are crucial