Submitted by Erika Demachki (erikademachki@gmail.com) on 2014-09-05T20:11:20Z No. of bitstreams: 2 Alves, Vinicius de Medeiros - 2014.pdf: 3082084 bytes, checksum: da4838d5fe24841429f43de84204d98a (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2014-09-05T20:11:20Z (GMT). No. of bitstreams: 2 Alves, Vinicius de Medeiros - 2014.pdf: 3082084 bytes, checksum: da4838d5fe24841429f43de84204d98a (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2014-03-17 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few reports analyzing the relationships between their molecular structure and the sensitization potential including the connection to skin permeability, which is widely considered to be mechanistically implicated in sensitization. In this study, we have compiled, curated, and integrated the largest publicly available datasets related to chemically-induced skin sensitization and skin permeability. Unexpectedly, no correlation between sensitization and permeability has been found. Predictive QSAR models have been developed and validated for both skin sensitization and skin permeability using a standardized workflow fully compliant with the OECD guidelines. The classification accuracies of QSAR models discriminating sensitizers from non-sensitizers were 0.68-0.88 when evaluated on several external validation sets. When compared to the predictions generated by the OECD QSAR Toolbox skin sensitization module, our models had significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate and Negative Predicted Rate as well as Correct Classification Rate. We have also developed QSAR models of skin permeability measured quantitatively. Cross-species correlation between human and rodent permeability data was found to be low (r²=0.44); thus, skin permeability models were developed using human data only and their external accuracy was q²ext = 0.87 (for 62% of external compounds found within the model applicability domain). Skin sensitization models have been employed to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants that should be regarded as primary candidates for the experimental validation. / A exposição repetida a agentes químicos pode induzir a sensibilização da pele em indivíduos inerentemente suscetíveis e desencadear uma resposta imunológica exacerbada. Apesar de muitos compostos químicos estarem implicados na sensibilização da pele, existem poucos estudos analisando as relações entre a estrutura molecular e o potencial sensibilizador desses compostos, incluindo a conexão com a permeabilidade pela pele, a qual é referida como sendo primordial para o processo de sensibilização. Neste estudo foram compilados, integrados e preparados os maiores conjuntos de dados disponíveis publicamente relacionados tanto com a sensibilização da pele quanto à permeabilidade. Inesperadamente, não se encontrou correlação entre essas duas propriedades. Modelos de QSAR robustos e preditivos foram gerados e validados para ambas as propriedades usando um fluxo de trabalho totalmente complacente com as recomendações da OECD. As taxas de acerto dos modelos discriminaram estruturas sensibilizadoras de não sensibilizadoras com uma taxa de 0,68-0,88 de sucesso, quando avaliadas em vários conjuntos de validação externa. Quando comparados com o módulo de sensibilização da pele implementado na ferramenta QSAR Toolbox da OECD, os modelos tiveram baixa cobertura do espaço químico, mas precisão preditiva mais elevada para os mesmos conjuntos de compostos externos avaliados pelo valor de preditividade positiva e valor de preditividade negativa assim como pela acurácia balanceada. O coeficiente de correlação cruzada entre os dados de permeabilidade da pele humana e de roedores apresentou-se baixo (r²=0,44); assim, apenas o conjunto de dados de pele humana foi considerado para geração de modelos de permeabilidade, que apresentaram precisão externa de q²ext = 0,87 (para 62% dos compostos dentro do domínio de aplicabilidade). Modelos de sensibilização da pele foram empregados para identificação de toxicantes putativos no banco de dados de possíveis agentes toxicantes da Scorecard que podem ser considerados como candidatos para validação experimental.

La dermatite de contact allergique (DCA) est une réaction exacerbée du système immunitaire cutané vis-à-vis d’un allergène de contact. La prévalence de la DCA étant de 20 % au sein de la population mondiale, il est important d’identifier les composés allergisants. Différentes réglementations européennes, telles que le règlement REACh ou la directive cosmétique, interdisent l’utilisation de test sur l’animal. C’est dans ce contexte que différentes méthodes alternatives ont été développées pour évaluer la sensibilisation cutanée. La stratégie actuelle d’évaluation du potentiel sensibilisant consiste à réaliser un ensemble de tests alternatifs, chacun mimant un évènement clé du mécanisme : l’hapténisation, l’activation des kératinocytes ou des cellules dendritiques.Cependant, ces tests utilisent principalement des monocultures et ne prennent donc pas en compte les interactions cellulaires qui peuvent avoir lieu in vivo. De plus, les évaluations de la pénétration et du métabolisme cutanés sont négligées dans les tests développés.Afin de mimer la fine orchestration des événements intervenant lors de la sensibilisation cutanée, nous proposons un modèle d’épiderme humain reconstruit (RhE) co-cultivé avec la lignée cellulaire THP-1, servant de substitut aux cellules dendritiques. Nous avons caractérisé, et étudié la pertinence de ce modèle à l’aide de molécules chimiques de référence. Ce travail a permis l’identification de biomarqueurs, tels que CD54, IL-8 et CCL3, spécifiques à l’évaluation in vitro de la sensibilisation cutanée des xénobiotiques. / Allergic contact dermatitis is an exacerbated reaction of skin immune system toward contact allergen. The prevalence of DCA being 20 % among the world population, it is important to identify allergens. Different European regulations such as the REACh regulation or the cosmetic directive prohibit the use of the test on animals. It is in this context that different methods have been developed to evaluate skin sensitization. The current sensitization potential assessment strategy consists of a set of alternative tests, each of which reproduce a key event of the mechanism: the haptenation, the activation of keratinocytes or dendritic cells.However, these tests are mainly based on monocultures and therefore do not account for the cellular crosstalk that happen in vivo. In addition, the evaluations of skin penetration and metabolism are neglected in the developed tests.In order to mimic the fine orchestration of the events involved in skin sensitization, we propose a model of reconstructed human epidermis (RhE) co-cultivated with the THP-1 cell line, as a substitute for dendritic cells. We have characterized and studied the relevance of this model using reference chemical molecules. This work has enabled the identification of biomarkers, such as CD54, IL-8 and CCL3, specific to the in vitro evaluation of skin sensitization to xenobiotics.

Skin sensitization resulting for allergic contact dermatitis (ACD) is an occupational and environmental health issue. The allergic hazard for workers and consumers is a serious problem for individuals, employers and marketing certain products. Consequently, it is necessary to accurately identify chemicals skin sensitization potential. According to the new EU chemical regulation REACH (Registration, Evaluation, Authorization and Restriction of Chemicals), information of skin sensitization of chemicals manufactured or imported at or above 1 ton/year should be available. Currently, valid approaches assessing skin sensitization rely on animal testing, such as local lymph node assay (LLNA). However, it now ultimately eliminates using animals for this purpose. Based on the fact that a key step in the skin sensitization process is formatting a covalent adduct between allergic sensitizers and proteins and/or peptides in skin, a lot of additional approaches are proposed and developed for replacing or reducing animal used. In this research, three bioassays, 24 h growth inhibition toward Tetrahymena pyriformis, long term (24 h) and short term (30 min) bacterial toxicity (to Vibrio fischeri), and a kinetic glutathione chemoassay are applied for predicting the organic chemicals’ skin sensitization potential. The major results and conclusions obtained are listed as follows: 1. Toxicity enhancement (Te) of 55 chemicals comprising different sensitization potencies were determined and compared with their narcotic toxicity to predict their skin sensitization. Three linear regressions yielded for all allergic sensitizer without nonsensitizers for each bioassay. The linear regressions are improved after classifying sensitizers into five different reaction mechanistic domains. Correspondingly, five different slopes from various reaction mechanisms indicate a decreased sensitivity of toxicity enhancement to skin sensitization potential with order SNAr > SN2 > acylation ≈ Schiff base > aromatic Michael addition. Based on the fact that a key step in the skin sensitization process is forming a covalent adduct between allergic sensitizers and proteins and/or peptides, Te > 10 as a threshold is applied to discriminate these allergic sensitizers, with 100% accuracy for strong (with extreme) and weaker sensitizers, up to 72% accuracy for moderate sensitizers and less than 69% accuracy for nonsensitizers. Compared with these bioassays, a decreasing order of sensitivities is 24 h growth inhibition (Tetrahymena pyriformis) > 24 h growth inhibition (Vibrio fischeri) > 30 min bioluminescence inhibition (Vibrio fischeri). These three bioassays are useful tools for screening sensitization potency of allergic chemicals, and the toxicity enhancement (Te) can be used to discriminate sensitizers from weak or nonsensitizers. However, in this context we should separate aromatic from aliphatic Mas (Michael acceptors). Moreover, metabolic biotransformation should be considered during predicting nonsensitizers’ skin sensitization. 2. Chemical reactivity of selected 55 compounds measuring through kinetic glutathione chemoassay applies to predict their skin sensitization. This chemoassay confirms the fact that the key step of sensitizers eliciting skin sensitization is formatting a covalent adduct between sensitizers and skin proteins or peptides. The chemical reactivity of tested sensitizers strongly relates with their sensitization potential, with strong (extreme) sensitizers presenting the highest reactivity as followed with moderate sensitizers, weak sensitizers as well as nonsensitizers. Moreover, an integrated platform of this chemoassay data and three bioassays data is performed, and this performance shows good sensitivity for monitoring skin sensitization potency, with more rational accuracy for each sensitizing classifications. 3. Thiol reactivity (kGSH) as well as toxicity enhancement (Te) of additional 21 aliphatic α,β-unsaturated compounds are determined for predicting their skin sensitization potential. The linear regressions of skin sensitization versus thiol reactivity and skin sensitization versus toxicity enhancement are significantly improved after classifying these 21 compounds to four chemical subgroups (acrylates, other esters, ketones and aldehydes). Thiol reactivity of these subgroups presented different sensitivity to skin sensitization, with a decreasing order as acrylates (－2.05) > other esters (－1.26) > ketones (－0.43) > aldehydes (－0.21). Moreover, thiol reactivity is confirmed to be a more sensitive tool for predicting skin sensitization, compared with toxicity enhancement. Although the datasets are probably too small to give a definite decision, hydrophobicity reveals contribution to skin sensitization for aliphatic MAs, which is different with literature report. This study suggests that aliphatic MAs should be treated separately into different chemical subgroups for analysis, and their skin sensitization potency can be predicted using kinetic glutathione chemoassay as well as toxicity enhancement bioassay.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2017-06-12T15:19:44Z No. of bitstreams: 2 Dissertação - Vinicius de Medeiros Alves - 2014.pdf: 3082084 bytes, checksum: da4838d5fe24841429f43de84204d98a (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2017-06-12T15:21:40Z (GMT) No. of bitstreams: 2 Dissertação - Vinicius de Medeiros Alves - 2014.pdf: 3082084 bytes, checksum: da4838d5fe24841429f43de84204d98a (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-06-12T15:21:40Z (GMT). No. of bitstreams: 2 Dissertação - Vinicius de Medeiros Alves - 2014.pdf: 3082084 bytes, checksum: da4838d5fe24841429f43de84204d98a (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-05-12 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Introduction: Skin sensitization is a major environmental and human health hazard. Although many chemicals have been evaluated in humans, there have been no efforts to model these data to date. Skin sensitization is commonly evaluated using structural alerts. However, there has been a growing concern that alerts disproportionally flag too many chemicals as toxic, which questions their reliability as toxicity markers. The main goal of this thesis was to develop and apply new cheminformatics methods to predict skin sensitization of chemical compounds that lack experimental data. Methodology: It has been compiled, curated, analyzed, and compared the available human data and the murine (performed in mice) animal model data, named LLNA (local lymph node assay). Using these data, it was developed reliable computational models and applied them for virtual screening of chemical libraries to identify putative skin sensitizers. It was developed a freely accessible web-based application for the identification of potential skin sensitizers. In addition, it was demonstrated that contrary to the common perception of QSAR models as “black boxes” they can be used to identify statistically significant chemical substructures (QSAR-based alerts) that influence toxicity. Results and discussion: The overall concordance between murine LLNA and human skin sensitization responses for a set of 135 unique chemicals was low (R = 28-43%), although several chemical classes had high concordance. We have succeeded to develop predictive QSAR models of all available human data with the external correct classification rate of 71%. A consensus model integrating concordant QSAR predictions and LLNA results afforded a higher correct classification rate of 82% but at the expense of the reduced external dataset coverage (52 %). We used the developed QSAR models for virtual screening of CosIng database and identified 1,061 putative skin sensitizers; for seventeen of these compounds, we found published evidence of their skin sensitization effects. The developed Pred-Skin web app (http://www.labmol.com.br/predskin/) is based on binary QSAR models of human (109 compounds) and LLNA (515 compounds) data with good external correct classification rate (70-81% and 72-84%, respectively). It is also included a multiclass potency model based on LLNA data (accuracy ranging between 73-76%). Conclusions: Models reported herein provide more accurate alternative to LLNA testing for human skin sensitization assessment across diverse chemical data. In addition, they can also be used to guide the structural optimization of toxic compounds to reduce their skin sensitization potential. The Pred-Skin web app is a fast, reliable, and user-friendly tool for early assessment of chemically-induced skin sensitization. A new approach that synergistically integrates structural alerts and rigorously validated QSAR models for a more transparent and accurate safety assessment of new chemicals was also proposed. / Introdução: A sensibilização cutânea é um importante parâmetro de avaliação de toxicidade humana e ambiental. Embora muitos compostos tenham sido avaliados em seres humanos, não foi reportado até o momento modelos de QSAR (do inglês, quantitative structure-activity relationships) gerados com esses dados. Comumente, a sensibilização cutânea é avaliada computacionalmente usando-se alertas estruturais. No entanto, tem havido uma preocupação crescente de que alertas sinalizam a maioria dos compostos como tóxicos, o que questiona sua confiabilidade como marcadores de toxicidade. O objetivo geral do presente trabalho foi desenvolver e aplicar novos métodos de quimioinformática para predizer a sensibilização cutânea de compostos químicos que carecem de dados experimentais. Metodologia: Foram compilados, preparados, analisados e comparados os dados de sensibilização cutânea de pele humana e do modelo animal murino (realizado em camundongos), denominado LLNA (local lymph node assay). Modelos de QSAR foram desenvolvidos utilizando esses dados e aplicados para a triagem de quimiotecas virtuais para identificar potenciais sensibilizadores. Foi desenvolvido um aplicativo gratuito para a identificação de potenciais sensibilizadores cutâneos. Além disso, foi demonstrado que modelos de QSAR podem ser usados para identificar subestruturas químicas estatisticamente significativas (alertas estruturais baseados em QSAR) que influenciam a toxicidade. Resultados e discussão: A concordância global (R) entre respostas de sensibilização cutânea humana e murina para um conjunto de 135 substâncias químicas únicas foi baixa (R = 28-43%), embora várias classes químicas apresentassem alta concordância. Foi possível desenvolver modelos de QSAR preditivos com taxa de classificação correta externa de 71%. Um modelo de consenso que integrava predições concordantes de QSAR e dados de LLNA proporcionaram uma acurácia 82%. Utilizou-se os modelos de QSAR desenvolvidos para a triagem virtual da base de dados CosIng e foram identificados 1061 potenciais sensibilizadores cutâneos. Para dezessete desses compostos, encontrou-se evidências publicadas de seus efeitos de sensibilização cutânea em seres humanos. O aplicativo desenvolvido, Pred-Skin (http://www.labmol.com.br/predskin/), baseia-se em modelos de QSAR classificatórios de dados humanos (109 compostos) e murinos (515 compostos) com boa taxa de classificação correta externa (70-81% e 72-84%, respectivamente). Esse aplicativo também possui um modelo de multiclassificatório desenvolvido com dados de LLNA (precisão que varia entre 73-76%). Conclusões: Os modelos de QSAR desenvolvidos forneceram uma alternativa mais precisa do que o modelo animal para avaliação da sensibilização cutânea humana. Além disso, a interpretação dos modelos de QSAR permitem orientar a otimização estrutural de compostos tóxicos para reduzir o potencial de toxicidade. O aplicativo Pred-Skin é uma ferramenta rápida, confiável e de fácil utilização para a avaliação da sensibilização cutânea de compostos químicos. Foi também proposta uma nova abordagem que integra sinergicamente alertas estruturais e modelos de QSAR rigorosamente validados para uma avaliação de toxicidade mais transparente e precisa de novos produtos químicos.

Résumé : Depuis l'interdiction en 2013 des tests sur les animaux par le Règlement cosmétique n°1223/2009, différentes méthodes in vitro ont été développées. Toutefois, selon un consensus scientifique, aucune méthode ne peut couvrir à elle seule l’ensemble des événements clés (KE) définis pour la sensibilisation cutanée.Après un état de l’art des méthodes alternatives relatives à la sensibilisation cutanée, nous avons sélectionné et comparé 3 tests pour ensuite déterminer la meilleure stratégie à suivre. Dans le but de proposer un nouveau test intégré, nous avons adressé l’ensemble des KEs au sein d’un même type cellulaire. La cellule dendritique (DC) jouant un rôle clé dans le développement de la dermatite de contact allergique (DCA), notre choix s’est porté sur la lignée humaine pro-monocytaire THP-1. Nous avons étudié comme événements initiaux (KE1) les formes réactives à l’oxygène (FRO) et le glutathion (GSH), la voie Nrf2-Keap1 (voie centrale de détoxication) et l’expression génique pour le KE2, ainsi que les modifications phénotypiques pour le KE3.Nous avons montré que les allergisants forts induisent une production précoce des FRO associée à une réduction du GSH. Ils activent également la voie Nrf2-Keap1 et induisent l’expression des marqueurs de surface cellulaire CD54 et CD86, ainsi qu’une production de cytokines spécifiques (IL-8, IL-18,...).Pour conclure, ce travail a permis de proposer un test intégrant l’ensemble des mesures biologiques comme différents KE au sein d’un même type cellulaire. / Abstract : Since the animal testing ban in 2013 by Cosmetics Regulation n°1223/2009, various in vitro methods have been developed. However, according to a scientific consensus, no single method can stand-alone to cover the different key events (KE) defined for skin sensitization.After a state of the art of alternative methods relating to skin sensitization, we selected and compared 3 tests to determine the best strategy to follow. In order to propose a new integrated test, we wanted to address all KE within the same cell line. Because dendritic cell (DC) plays a key role in the development of allergic contact dermatitis (ACD), we have chosen the pro-monocytic human line THP-1. We have studied as initial events (KE1), reactive oxygen species (ROS) and glutathione (GSH), Nrf2-Keap1 pathway (central detoxification pathway) and gene expression for KE2 as well as phenotypic modifications for KE3.We have shown that strong allergens are correlated with early production of FRO associated with GSH reduction. They also activate the Nrf2-Keap1 pathway and induce the expression of CD54 and CD86 cell surface markers as well as production of specific cytokines (IL-8, IL-18, etc.).To conclude, this work propose a new assay integrating all the biological measures as different KEs within the same cell.

Skin sensitization resulting for allergic contact dermatitis (ACD) is an occupational and environmental health issue. The allergic hazard for workers and consumers is a serious problem for individuals, employers and marketing certain products. Consequently, it is necessary to accurately identify chemicals skin sensitization potential. According to the new EU chemical regulation REACH (Registration, Evaluation, Authorization and Restriction of Chemicals), information of skin sensitization of chemicals manufactured or imported at or above 1 ton/year should be available. Currently, valid approaches assessing skin sensitization rely on animal testing, such as local lymph node assay (LLNA). However, it now ultimately eliminates using animals for this purpose. Based on the fact that a key step in the skin sensitization process is formatting a covalent adduct between allergic sensitizers and proteins and/or peptides in skin, a lot of additional approaches are proposed and developed for replacing or reducing animal used. In this research, three bioassays, 24 h growth inhibition toward Tetrahymena pyriformis, long term (24 h) and short term (30 min) bacterial toxicity (to Vibrio fischeri), and a kinetic glutathione chemoassay are applied for predicting the organic chemicals’ skin sensitization potential. The major results and conclusions obtained are listed as follows: 1. Toxicity enhancement (Te) of 55 chemicals comprising different sensitization potencies were determined and compared with their narcotic toxicity to predict their skin sensitization. Three linear regressions yielded for all allergic sensitizer without nonsensitizers for each bioassay. The linear regressions are improved after classifying sensitizers into five different reaction mechanistic domains. Correspondingly, five different slopes from various reaction mechanisms indicate a decreased sensitivity of toxicity enhancement to skin sensitization potential with order SNAr > SN2 > acylation ≈ Schiff base > aromatic Michael addition. Based on the fact that a key step in the skin sensitization process is forming a covalent adduct between allergic sensitizers and proteins and/or peptides, Te > 10 as a threshold is applied to discriminate these allergic sensitizers, with 100% accuracy for strong (with extreme) and weaker sensitizers, up to 72% accuracy for moderate sensitizers and less than 69% accuracy for nonsensitizers. Compared with these bioassays, a decreasing order of sensitivities is 24 h growth inhibition (Tetrahymena pyriformis) > 24 h growth inhibition (Vibrio fischeri) > 30 min bioluminescence inhibition (Vibrio fischeri). These three bioassays are useful tools for screening sensitization potency of allergic chemicals, and the toxicity enhancement (Te) can be used to discriminate sensitizers from weak or nonsensitizers. However, in this context we should separate aromatic from aliphatic Mas (Michael acceptors). Moreover, metabolic biotransformation should be considered during predicting nonsensitizers’ skin sensitization. 2. Chemical reactivity of selected 55 compounds measuring through kinetic glutathione chemoassay applies to predict their skin sensitization. This chemoassay confirms the fact that the key step of sensitizers eliciting skin sensitization is formatting a covalent adduct between sensitizers and skin proteins or peptides. The chemical reactivity of tested sensitizers strongly relates with their sensitization potential, with strong (extreme) sensitizers presenting the highest reactivity as followed with moderate sensitizers, weak sensitizers as well as nonsensitizers. Moreover, an integrated platform of this chemoassay data and three bioassays data is performed, and this performance shows good sensitivity for monitoring skin sensitization potency, with more rational accuracy for each sensitizing classifications. 3. Thiol reactivity (kGSH) as well as toxicity enhancement (Te) of additional 21 aliphatic α,β-unsaturated compounds are determined for predicting their skin sensitization potential. The linear regressions of skin sensitization versus thiol reactivity and skin sensitization versus toxicity enhancement are significantly improved after classifying these 21 compounds to four chemical subgroups (acrylates, other esters, ketones and aldehydes). Thiol reactivity of these subgroups presented different sensitivity to skin sensitization, with a decreasing order as acrylates (－2.05) > other esters (－1.26) > ketones (－0.43) > aldehydes (－0.21). Moreover, thiol reactivity is confirmed to be a more sensitive tool for predicting skin sensitization, compared with toxicity enhancement. Although the datasets are probably too small to give a definite decision, hydrophobicity reveals contribution to skin sensitization for aliphatic MAs, which is different with literature report. This study suggests that aliphatic MAs should be treated separately into different chemical subgroups for analysis, and their skin sensitization potency can be predicted using kinetic glutathione chemoassay as well as toxicity enhancement bioassay.