Bioinformatics analyses of 10 allergen proteins in peanuts [abstract]

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Bioinformatics analyses of 10 allergen proteins in peanuts [abstract]

Please use this identifier to cite or link to this item: http://hdl.handle.net/10355/925

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Title: Bioinformatics analyses of 10 allergen proteins in peanuts [abstract]
Author: Yu, Sarah
Contributor: University of Missouri-Columbia. Office of Undergraduate Research
Keywords: food allergies
peanuts
Date: 2006
Publisher: University of Missouri--Columbia. Office of Undergraduate Research
Abstract: Food allergies affect up to 8% of children and 2% of adults, and peanut allergies are one of the most prevalent and enduring. To understand the mechanisms and how they interact with antibodies it is important to analyze their sequence and structural features at the molecular and atomic levels. By using web-based and publicly available protein prediction tools it is possible to gain a better understanding of how these proteins function as allergens. Analysis shows that these 10 allergens are variable in length and does not show any collectively conserved regions. They contain a variety of functional domains and have homologous hits in many other legume plants, most notably soybean and pea. Furthermore, intracellular localization predictions show a range of locations such as nuclear, cytoplasmic, or part of a secretory pathway. Three allergens (Ara h 1, Ara h 2, and Ara h 3) had a total of 37 known epitopes, with sequences of 6-10 amino acids that are responsible for the allergenicity of the protein, which reveals no significant conserved amino acid regions or properties. Short sequence alignment of epitopes shows exact matches in other organisms including viruses and mammals. This could provide information about what makes epitopes so durable as an allergen and during digestion. The epitopes occur in diverse conformations, such as coils, helices, and ? sheets or a combination of these. Because of the diversity in structure of the allergens and their epitopes, continuing research will focus on unique structural features of these regions and how they interact with their surroundings. From this knowledge better and more effective methods can be applied to genomic engineering of nonallergenic peanut.
URI: http://hdl.handle.net/10355/925

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