Literature DB >> 17400584

Quantification of chemical peptide reactivity for screening contact allergens: a classification tree model approach.

G Frank Gerberick1, Jeffrey D Vassallo, Leslie M Foertsch, Brad B Price, Joel G Chaney, Jean-Pierre Lepoittevin.   

Abstract

In the interest of reducing animal use, in vitro alternatives for skin sensitization testing are under development. One unifying characteristic of chemical allergens is the requirement that they react with proteins for the effective induction of skin sensitization. The majority of chemical allergens are electrophilic and react with nucleophilic amino acids. To determine whether and to what extent reactivity correlates with skin sensitization potential, 82 chemicals comprising allergens of different potencies and nonallergenic chemicals were evaluated for their ability to react with reduced glutathione (GSH) or with two synthetic peptides containing either a single cysteine or lysine. Following a 15-min reaction time with GSH, or a 24-h reaction time with the two synthetic peptides, the samples were analyzed by high-performance liquid chromatography. UV detection was used to monitor the depletion of GSH or the peptides. The peptide reactivity data were compared with existing local lymph node assay data using recursive partitioning methodology to build a classification tree that allowed a ranking of reactivity as minimal, low, moderate, and high. Generally, nonallergens and weak allergens demonstrated minimal to low peptide reactivity, whereas moderate to extremely potent allergens displayed moderate to high peptide reactivity. Classifying minimal reactivity as nonsensitizers and low, moderate, and high reactivity as sensitizers, it was determined that a model based on cysteine and lysine gave a prediction accuracy of 89%. The results of these investigations reveal that measurement of peptide reactivity has considerable potential utility as a screening approach for skin sensitization testing, and thereby for reducing reliance on animal-based test methods.

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Year:  2007        PMID: 17400584     DOI: 10.1093/toxsci/kfm064

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  41 in total

Review 1.  T-cell recognition of chemicals, protein allergens and drugs: towards the development of in vitro assays.

Authors:  Stefan F Martin; Philipp R Esser; Sonja Schmucker; Lisa Dietz; Dean J Naisbitt; B Kevin Park; Marc Vocanson; Jean-Francois Nicolas; Monika Keller; Werner J Pichler; Matthias Peiser; Andreas Luch; Reinhard Wanner; Enrico Maggi; Andrea Cavani; Thomas Rustemeyer; Anne Richter; Hermann-Josef Thierse; Federica Sallusto
Journal:  Cell Mol Life Sci       Date:  2010-08-18       Impact factor: 9.261

2.  Probabilistic hazard assessment for skin sensitization potency by dose-response modeling using feature elimination instead of quantitative structure-activity relationships.

Authors:  Thomas Luechtefeld; Alexandra Maertens; James M McKim; Thomas Hartung; Andre Kleensang; Vanessa Sá-Rocha
Journal:  J Appl Toxicol       Date:  2015-06-05       Impact factor: 3.446

3.  Predicting full thickness skin sensitization using a support vector machine.

Authors:  Serom Lee; David Xu Dong; Rohit Jindal; Tim Maguire; Bhaskar Mitra; Rene Schloss; Martin Yarmush
Journal:  Toxicol In Vitro       Date:  2014-07-12       Impact factor: 3.500

4.  Fragment-based prediction of skin sensitization using recursive partitioning.

Authors:  Jing Lu; Mingyue Zheng; Yong Wang; Qiancheng Shen; Xiaomin Luo; Hualiang Jiang; Kaixian Chen
Journal:  J Comput Aided Mol Des       Date:  2011-09-20       Impact factor: 3.686

5.  Mechanistic understanding of molecular initiating events (MIEs) using NMR spectroscopy.

Authors:  Paul N Sanderson; Wendy Simpson; Richard Cubberley; Maja Aleksic; Stephen Gutsell; Paul J Russell
Journal:  Toxicol Res (Camb)       Date:  2015-09-15       Impact factor: 3.524

Review 6.  Application of proteomics in the elucidation of chemical-mediated allergic contact dermatitis.

Authors:  Tessa Höper; Franz Mussotter; Andrea Haase; Andreas Luch; Tewes Tralau
Journal:  Toxicol Res (Camb)       Date:  2017-06-13       Impact factor: 3.524

7.  Substituent effects on the reactivity of benzoquinone derivatives with thiols.

Authors:  Wilbes Mbiya; Itai Chipinda; Paul D Siegel; Morgen Mhike; Reuben H Simoyi
Journal:  Chem Res Toxicol       Date:  2012-12-27       Impact factor: 3.739

8.  Prediction of skin sensitization potency using machine learning approaches.

Authors:  Qingda Zang; Michael Paris; David M Lehmann; Shannon Bell; Nicole Kleinstreuer; David Allen; Joanna Matheson; Abigail Jacobs; Warren Casey; Judy Strickland
Journal:  J Appl Toxicol       Date:  2017-01-10       Impact factor: 3.446

9.  The modified IL-8 Luc assay, an in vitro skin sensitisation test, can significantly improve the false-negative judgment of lipophilic sensitizers with logKow values > 3.5.

Authors:  Yutaka Kimura; Chizu Fujimura; Setsuya Aiba
Journal:  Arch Toxicol       Date:  2020-10-17       Impact factor: 5.153

10.  In silico prediction of pesticide aquatic toxicity with chemical category approaches.

Authors:  Fuxing Li; Defang Fan; Hao Wang; Hongbin Yang; Weihua Li; Yun Tang; Guixia Liu
Journal:  Toxicol Res (Camb)       Date:  2017-07-31       Impact factor: 3.524

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