ArticleNucleic acids research2019
SPADE web service for prediction of allergen IgE epitopes.
Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Review
- Advances of computational methods enhance the development of multi-epitope vaccines.Briefings in bioinformatics · 2024Review
- A systematic review of allergen cross-reactivity: Translating basic concepts into clinical relevance.The journal of allergy and clinical immunology. Global · 2024Review
- Assessing the predictive ability of computational epitope prediction methods on Fel d 1 and other allergens.PloS one · 2024Article
- Structure and IgE Cross-Reactivity among Cashew, Pistachio, Walnut, and Peanut Vicilin-Buried Peptides.Journal of agricultural and food chemistry · 2023Article
- Structure, Immunogenicity, and IgE Cross-Reactivity among Walnut and Peanut Vicilin-Buried Peptides.Journal of agricultural and food chemistry · 2022Article
- Antibody Class(es) Predictor for Epitopes (AbCPE): A Multi-Label Classification Algorithm.Frontiers in bioinformatics · 2021Article
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2 authors.
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Abstract
The specific interaction of allergens with IgE antibodies and the allergen mediated cross-linking of receptor-bound IgE are key events of allergic diseases. The elucidation of the IgE binding sites (the epitopes) on the allergen surface is an important goal of allergy research. Only few allergen-specific IgE epitopes have been determined experimentally to date. Epitope prediction methods represent a viable alternative to experimental methods and have worked well with linear epitopes. However, as most IgE epitopes are of conformational and/or discontinuous nature sequence based prediction methods have had limited success in these cases. Here, we present the web server of the program SPADE (https://spade.uni-graz.at), which is the server implementation of a previously published program (1). In this approach we utilize the structural homology of cross-reactive allergens combined with the immunological cross-reactivity data for the discrimination of putative IgE-binding sites from non-cross-reactive surface patches. The method, although predictive, does not rely on machine-learning algorithms and does not require training data. The SPADE server features an easy-to-use interface, an automated pipeline consisting of third-party, as well as own, newly developed routines and a comprehensive output page.
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