Abstract
An increasing number of studies on allergenic molecules have been published during the past 20 years, and the number of proteins reported as allergens is close to 1500 (http://www.allergome.org). Collecting, organizing, and displaying data reported in the scientific literature is becoming the major commitment of Web-based databases that organize this knowledge in heterogeneous ways. This heterogeneity prevents the databases from being connected to each other, something that has been done in several other biomedical fields. This review reports on the current status of allergen databases and available tools to study the allergenicity of new compounds. An analysis of what has been done by applying bioinformatics in other medical fields is presented. Suggestions on how to create a common platform in which experimental, clinical, and epidemiologic data could be merged are offered. The model of the Allergome platform and its modules and tools (eg, InterAll, ReTiME, RefArray, and AllergomeBlaster) are used to exemplify interconnectivity and data integration.
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References and Recommended Reading
Cohen SG, King JR: Skin tests: a historic trail. Immunol Allergy Clin North Am 2001, 21:191–249.
Kamble S, Bharmal M: Incremental direct expenditure of treating asthma in the United States. J Asthma 2009, 46:73–80.
Ferreira F, Hawranek T, Gruber P, et al.: Allergic cross-reactivity: from gene to the clinic. Allergy 2004, 59:243–267.
Radauer C, Bublin M, Wagner S, et al.: Allergens are distributed into few protein families and possess a restricted number of biochemical functions. J Allergy Clin Immunol 2008, 121:847–852.
Thomas K, Macintosh S, Bannon G, et al.: Scientific advancement of novel protein allergenicity evaluation: an overview of work from the HESI Protein Allergenicity Technical Committee (2000-2008). Food Chem Toxicol 2009, 47:1041–1050.
Li X, Zhang Y: Bioinformatics data distribution and integration via Web Services and XML. Genomics Proteomics Bioinformatics 2003, 1:299–303.
Madsen CB, Hattersley S, Buck J, et al.: Approaches to risk assessment in food allergy: report from a workshop “Developing a framework for assessing the risk from allergenic foods.” Food Chem Toxicol 2009, 47:480–489.
Miotto O, Tan TW, Brusic V: Supporting the curation of biological databases with reusable text mining. Genome Inform 2005, 16:32–44.
Mari A, Scala E, Palazzo P, et al.: Bioinformatics applied to allergy: allergen databases, from collecting sequence information to data integration. The Allergome platform as a model. Cell Immunol 2007, 244:97–100.
Galperin MY, Cochrane GR: Nucleic Acids Research annual Database Issue and the NAR online Molecular Biology Database Collection in 2009. Nucleic Acids Res 2009, 37:D1–D4.
Boutet E, Lieberherr D, Tognolli M, et al.: UniProtKB/Swiss-Prot. Methods Mol Biol 2007, 406:89–112.
Kanz C, Aldebert P, Althorpe N, et al.: The EMBL Nucleotide Sequence Database. Nucleic Acids Res 2005, 33:D29–D33.
Berman HM, Westbrook J, Feng Z, et al.: The Protein Data Bank. Nucleic Acids Res 2000, 28:235–242.
King TP, Hoffman D, Lowenstein H, et al.: Allergen nomenclature. J Allergy Clin Immunol 1995, 96:5–14.
Gendel SM: Assessing the potential allergenicity of new food proteins. Food Biotechnol 1998, 12:175–185.
Sayers EW, Barrett T, Benson DA, et al.: Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 2009, 37:5–15.
Hileman RE, Silvanovich A, Goodman RE, et al.: Bioinformatic methods for allergenicity assessment using a comprehensive allergen database. Int Arch Allergy Immunol 2002, 128:280–291.
Ivanciuc O, Schein CH, Braun W: SDAP: database and computational tools for allergenic proteins. Nucleic Acids Res 2003, 31:359–362.
Altschul SF, Gish W, Miller W, et al.: Basic local alignment search tool. J Mol Biol 1990, 215:403–410.
Pearson WR, Lipman DJ: Improved tools for biological sequence comparison. Proc Natl Acad Sci U S A 1988, 85:2444–2448.
Smith TF, Waterman MS: Identification of common molecular subsequences. J Mol Biol 1981, 147:195–197.
Pearson WR: Comparison of methods for searching protein sequence databases. Protein Sci 1995, 4:1145–1160.
Silvanovich A, Nemeth MA, Song P, et al.: The value of short amino acid sequence matches for prediction of protein allergenicity. Toxicol Sci 2006, 90:252–258.
Aalberse RC: Structural biology of allergens. J Allergy Clin Immunol 2000, 106:228–238.
Stadler MB, Stadler BM: Allergenicity prediction by protein sequence. FASEB J 2003, 17:1141–1143.
Marti P, Truffer R, Stadler MB, et al.: Allergen motifs and the prediction of allergenicity. Immunol Lett 2007, 109:47–55.
Rasi C, Palazzo P, Carabella G, Mari A: AllergomeBlaster: Auto-collecting new potential in silico allergens for the Allergome platform. Allergy 2008, 63:S400.
Hiller R, Laffer S, Harwanegg C, et al.: Microarrayed allergen molecules: diagnostic gatekeepers for allergy treatment. FASEB J 2002, 16:414–416.
Barrett T, Suzek TO, Troup DB, et al.: NCBI GEO: mining millions of expression profiles—database and tools. Nucleic Acids Res 2005, 33:D562–D566.
Brazma A, Parkinson H, Sarkans U, et al.: ArrayExpress—a public repository for microarray gene expression data at the EBI. Nucleic Acids Res 2003, 31:68–71.
Loewe L: Global computing for bioinformatics. Brief Bioinform 2002, 3:377–388.
Pappalardo F, Halling-Brown MD, Rapin N, et al.: ImmunoGrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization. Brief Bioinform 2009, 10:330–340.
Matsson PNJ, Hamilton RG, Esch RE, et al.: Analytical Performance Characteristics and Clinical Utility of Immunological Assays for Human Immunoglobulin E (IgE) Antibodies and Defined Allergen Specificities; Approved Guideline, edn 2. Wayne, PA: Clinical and Laboratory Standards Institute; 2009.
Donaldson I, Martin J, de Bruijn B, et al.: PreBIND and Textomy—mining the biomedical literature for protein-protein interactions using a support vector machine. BMC Bioinformatics 2003, 4:11.
Cheng D, Knox C, Young N, et al.: PolySearch: a web-based text mining system for extracting relationships between human diseases, genes, mutations, drugs and metabolites. Nucleic Acids Res 2008, 36:W399–W405.
Valarakos AG, Karkaletsis V, Alexopoulou D, et al.: Building an allergens ontology and maintaining it using machine learning techniques. Comput Biol Med 2006, 36:1155–1184.
Gendel SM: Allergen databases and allergen semantics. Regul Toxicol Pharmacol 2008 Dec 6 (Epub ahead of print).
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Mari, A., Rasi, C., Palazzo, P. et al. Allergen databases: Current status and perspectives. Curr Allergy Asthma Rep 9, 376–383 (2009). https://doi.org/10.1007/s11882-009-0055-9
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DOI: https://doi.org/10.1007/s11882-009-0055-9