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14. Allergen Databases

Author

Sircar, Gaurab, primary, Sarkar, Debasree, additional, Bhattacharya, Swati Gupta, additional, and Saha, Sudipto, additional

Published
2014
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24. Mining Novel Allergens from Coconut Pollen Employing Manual De NovoSequencing and Homology-Driven Proteomics

Author

Saha, Bodhisattwa, Sircar, Gaurab, Pandey, Naren, and Gupta Bhattacharya, Swati

Abstract

Coconut pollen, one of the major palm pollen grains is an important constituent among vectors of inhalant allergens in India and a major sensitizer for respiratory allergy in susceptible patients. To gain insight into its allergenic components, pollen proteins were analyzed by two-dimensional electrophoresis, immunoblotted with coconut pollen sensitive patient sera, followed by mass spectrometry of IgE reactive proteins. Coconut being largely unsequenced, a proteomic workflow has been devised that combines the conventional database-dependent analysis of tandem mass spectral data and manual de novosequencing followed by a homology-based search for identifying the allergenic proteins. N-terminal acetylation helped to distinguish “b” ions from others, facilitating reliable sequencing. This led to the identification of 12 allergenic proteins. Cluster analysis with individual patient sera recognized vicilin-like protein as a major allergen, which was purified to assess its in vitroallergenicity and then partially sequenced. Other IgE-sensitive spots showed significant homology with well-known allergenic proteins such as 11S globulin, enolase, and isoflavone reductase along with a few which are reported as novel allergens. The allergens identified can be used as potential candidates to develop hypoallergenic vaccines, to design specific immunotherapy trials, and to enrich the repertoire of existing IgE reactive proteins.

Published
2015
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25. In silico prediction of allergenic proteins.

Author

Sircar G, Saha B, Bhattacharya SG, and Saha S

Subjects
Allergens chemistry, Amino Acid Sequence, Animals, Computer Simulation, Databases, Protein, Epitopes chemistry, Epitopes immunology, Humans, Immunoglobulin E immunology, Internet, Molecular Sequence Data, Proteins chemistry, Sequence Alignment, Allergens immunology, Artificial Intelligence, Computational Biology methods, Proteins immunology, Software
Abstract

Currently, the prediction of new allergens is becoming important due to use of genetically modified (GM) foods and biopharmaceuticals. In this chapter, we describe how to use four popular allergenic prediction servers: (1) Structural Database of Allergenic Proteins (SDAP), (2) Allermatch, (3) Evaller 2, and (4) AlgPred. The first two prediction servers are based on traditional approaches, whereas Evaller 2 and AlgPred use sophisticated machine learning techniques.

Published
2014
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26. Allergen databases.

Author

Sircar G, Sarkar D, Bhattacharya SG, and Saha S

Subjects
Allergens chemistry, Humans, Internet, Molecular Conformation, Allergens immunology, Computational Biology methods, Databases, Factual, Hypersensitivity, Immediate immunology
Abstract

In this chapter, five popular allergen databases have been described: (1) Allergome is based on basic and clinical information on allergens causing an IgE-mediated disease; (2) AllergenOnline allows online search of peer-reviewed allergen list; (3) International Union of Immunological Societies Allergen nomenclature subcommittee database contains systematic nomenclature and molecular details of well-characterized allergens; (4) AllFam allows classifying allergens into protein families based on domain information; and (5) SDAP provides in detail structural information of the allergens.

Published
2014
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