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Identification of putative and potential cross-reactive chickpea (Cicer arietinum) allergens through an in silico approach
AnujaKulkarni, LaxmiAnanthanarayan,
Published in Elsevier Ltd
2013
PMID: 24099701
Volume: 47
   
Pages: 149 - 155
Abstract
Background Allergy has become a key cause of morbidity worldwide. Although many legumes (plants in the Fabaceae family) are healthy foods, they may have a number of allergenic proteins. A number of allergens have been identified and characterized in Fabaceae family, such as soybean and peanut, on the basis of biochemical and molecular biological approaches. However, our understanding of the allergens from chickpea (Cicer arietinum L.), belonging to this family, is very limited. Objective In this study, we aimed to identify putative and cross-reactive allergens from Chickpea (C. arietinum) by means of in silico analysis of the chickpea protein sequences and allergens sequences from Fabaceae family. Methods We retrieved known allergen sequences in Fabaceae family from the IUIS Allergen Nomenclature Database. We performed a protein BLAST (BLASTp) on these sequences to retrieve the similar sequences from chickpea. We further analyzed the retrieved chickpea sequences using a combination of in silico tools, to assess them for their allergenicity potential. Following this, we built structure models using FUGUE: Sequence-structure homology; these models generated by the recognition tool were viewed in Swiss-PDB viewer. Results Through this in silico approach, we identified seven novel putative allergens from chickpea proteome sequences on the basis of similarity of sequence, structure and physicochemical properties with the known reported legume allergens. Four out of seven putative allergens may also show cross reactivity with reported allergens since potential allergens had common sequence and structural features with the reported allergens. Conclusion The in silico proteomic identification of the allergen proteins in chickpea provides a basis for future research on developing hypoallergenic foods containing chickpea. Such bioinformatics approaches, combined with experimental methodology, will help delineate an efficient and comprehensive approach to assess allergenicity and pave the way for a better understanding of the biological and medical basis of the same. © 2013 Elsevier Ltd. All rights reserved.
About the journal
JournalData powered by TypesetComputational Biology and Chemistry
PublisherData powered by TypesetElsevier Ltd
ISSN14769271
Open AccessNo
Concepts (63)
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    Bioinformatics
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    Molecular biology
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    Proteins
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    Tools
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    BIOLOGICAL APPROACH
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    CHICKPEA
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    CHICKPEA (CICER ARIETINUM L.)
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    EXPERIMENTAL METHODOLOGY
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    Physicochemical property
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    PROTEOMIC IDENTIFICATION
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    Proteomics
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    Structural feature
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    Allergens
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    ARACHIS HYPOGAEA
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    CICER ARIETINUM
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    Fabaceae
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    Glycine max
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    ALLERGEN
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    IMMUNOGLOBULIN E
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    VEGETABLE PROTEIN
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    ALLERGEN PREDICTION
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    Amino acid sequence
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    Article
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    BASIC LOCAL ALIGNMENT SEARCH TOOL
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    BLASTP
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    Chemical structure
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    Chemistry
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    CHICKPEA
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    CICER
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    Computer simulation
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    CROSS REACTION
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    FOOD AND AGRICULTURAL ORGANIZATION
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    FOOD AND AGRICULTURE ORGANIZATION
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    Immunology
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    INTERNATIONAL UNION OF IMMUNOLOGICAL SOCIETIES
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    IUIS
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    Molecular genetics
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    PFAM
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    PRESSURE WAVE
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    PROTEIN FAMILIES' DATABASE
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    PROTEIN-PROTEIN BLAST
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    Sequence alignment
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    World health organization
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    ALLERGEN PREDICTION
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    BASIC LOCAL ALIGNMENT SEARCH TOOL
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    BLAST
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    BLASTP
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    CHICKPEA
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    FAO
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    FOOD AND AGRICULTURE ORGANIZATION
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    IGE
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    IMMUNOGLOBULIN E
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    INTERNATIONAL UNION OF IMMUNOLOGICAL SOCIETIES
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    IUIS
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    PFAM
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    PROTEIN FAMILIES' DATABASE
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    PROTEIN-PROTEIN BLAST
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    WHO
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    CICER
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    CROSS REACTIONS
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    Models, molecular
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    Molecular sequence data
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    PLANT PROTEINS