Search for Author, Title, Keyword
Databases and Associated Bioinformatic Tools in Studies of Food Allergens, Epitopes and Haptens – a Review
More details
Hide details
Publication date: 2018-06-30
Pol. J. Food Nutr. Sci. 2018;68(2):103-113
Allergies and/or food intolerances are a growing problem of the modern world. Difficulties associated with the correct diagnosis of food allergies result in the need to classify the factors causing allergies and allergens themselves. Therefore, internet databases and other bioinformatic tools play a special role in deepening knowledge of biologically-important compounds. Internet repositories, as a source of information on different chemical compounds, including those related to allergy and intolerance, are increasingly being used by scientists. Bioinformatic methods play a significant role in biological and medical sciences, and their importance in food science is increasing. This study aimed at presenting selected databases and tools of bioinformatic analysis useful in research on food allergies, allergens (11 databases), epitopes (7 databases), and haptens (2 databases). It also presents examples of the application of computer methods in studies related to allergies.
Ahsan N., Rao R.S.P., Gruppuso P.A., Ramratnam B., Salomon A.R., Targeted proteomics: Current status and future perspectives for quantification of food allergens. J. Proteom., 2016, 143, 15-23.
Ameratunga R., Crooks C., Simmons G., Woon S.T., Health risks and adverse reactions to functional foods. Crit. Rev. Food Sci. Nutr., 2016, 56, 318-325.
Arnon R., Van Regenmortel M.H.V., Structural basis of antigenic specificity and design of new vaccines. FASEB J., 1992, 6, 3265-3274.
Atwood T.K., Bongcam-Rudloff E., Brazas M.E., Corpas M., Gaudet P., Lewitter F., Mulder N., Palagi P.M., Schneider M.V., van Gelder C.W.G., GOBLET Consortium, GOBLET: The Global Organisation for Bioinformatics Learning. Education and Training. PLoS Comput. Biol., 2015, 11, Article No e1004143.
Bhasin M., Singh H., Raghava G.P.S., MHCBN: a comprehensive database of MHC binding and non-binding peptides. Bioinformatics, 2003, 19, 665-666.
Blythe M.J., Doytchinova I.A., Flower D.R., JenPep: a database of quantitative functional peptide data for immunology. Bioinformatics, 2002, 18, 434-439.
Borchers A., Teuber S.S., Keen C.L., Gershwin M.E., Food safety. Clin. Rev. Allergy Immunol., 2010, 39, 95-141.
Boulesteix A.L., Over-optimism in bioinformatics research. Bioinformatics, 2010, 26, 437–439.
Boulesteix A.L., Ten simple rules for reducing overoptimistic reporting in methodological computational research. PLoS Comput. Biol., 2015, 11, Article No e1004191.
Brazas M.D., Ouellette B.F.F., Continuing education workshops in bioinformatics positively impact research and careers. PLoS Comput. Biol., 2016, 12, Article No e1004916.
Breiteneder H., Chapman M.D., Allergen nomenclature, 2014, in: Allergens and Allergen Immunotherapy, 5th edition (eds. R.F. Lockey, D.K. Ledford). CRC Press: Boca Raton, FL, USA, pp. 37–49.
Brusic V., Information management for the study of allergies. Inflamm. Allergy – Drug Targets, 2006, 5, 35–42.
Brusic V., Millot M., Petrovsky N., Gendel S.M., Gigonzac O., Stelman S.J., Allergen databases. Allergy, 2003, 58, 1093-1100.
Bucholska J., Minkiewicz P., The use of peptide markers of carp and herring allergens as an example of detection of sequenced and non-sequenced proteins. Food Technol. Biotech., 2016, 54, 266-274.
Carrera M., Cañas B., Piñeiro C., Vázquez J., Gallardo J.M., Identification of commercial hake and grenadier species by proteomic analysis of the parvalbumin fraction. Proteomics, 2006, 6, 5278–5287.
de la Iglesia D., García-Remesal M., de la Calle G., Kulikowski C., Sanz F., Maojo V., The impact of computer science in molecular medicine: Enabling high-throughput research. Curr. Top. Med. Chem., 2013, 13, 526-575.
Di Costanzo M., Paparo L., Cosenza L., Di Scala C., Nocerino R., Aitoro R., Berni Canani R., Food allergies: novel mechanisms and therapeutic perspectives. Methods Mol. Biol., 2016, 1371, 215-221.
Ding Y., Wang M., He Y., Ye A.Y., Yang X., Liu F., Meng Y., Gao G., Wei L., "Bioinformatics: introduction and methods’’, a bilingual Massive Open Online Course (MOOC) as a new example for global bioinformatics education. PLoS Comput. Biol., 2014, 10, Article No e1003955.
Dziuba M., Minkiewicz P., Dąbek M., Peptides, specific proteolysis products as molecular markers of allergenic proteins – in silico studies. Acta Sci. Polon. Technol. Aliment., 2013, 12, 101-112.
Erhardt G., Shuiep E.T.S., Lisson M., Weimann C., Wang Z., Zubeir I.E.Y.M., Pauciullo A., Alpha S1-casein polymorphisms in camel (Camelus dromedarius) and descriptions of biological active peptides and allergenic epitopes. Tropical Anim. Health Prod., 2016, 48, 879–887.
Ertl P., Molecular structure input on the web. J. Cheminform., 2010, 2, Article No 1.
Finn R.D., Mistry J., Tate J., Coggill P., Heger A., Pollington J.E., Gavin O.L., Gunesekaran P., Ceric G., Forslund K., Holm L., Sonnhammer E.L., Eddy S.R., Bateman A., The Pfam protein families database. Nucleic Acids Res., 2010, 38, D211-D222.
García B.E., Lizaso M.T., Cross-reactivity syndromes in food allergy. J. Investig. Allergol. Clin. Immunol., 2011, 21, 162-170.
Garino C., Coïsson J.D., Arlorio M., In silico allergenicity prediction of several lipid transfer proteins. Comput. Biol. Chem., 2016, 60, 32–42.
Gendel S.M., Allergen databases and allergen semantics. Regul. Toxicol. Pharm., 2009, 54, S7–S10.
Gołąb J., Jakóbisiak M., Lasek W., Stokłosa T. (Ed.), Immunology, 2010, PWN Scientific Publishing House, Warsaw, pp. 1-3, ISBN 978-83-01-15154-6 (in Polish).
Goodman R.E., Ebisawa M., Ferreira F., Sampson H.U., van Ree R., Vieths S., Baumert J.L., Bohle B., Lalithambika S., Wise J., Taylor S.L., AllergenOnline: A peer-reviewed, curated allergen database to access novel food proteins for potential cross-reactivity. Mol. Nutr. Food Res., 2016, 60, 1183-1198.
Goodman R.E., Wise J., Bioinformatic analysis of proteins in Golden Rice 2 to assess potential allergenic cross-reactivity. Food Allergy Research and Resource Program, University of Nabraska, expertise nr BIO-02-2006, 2006, 1-24. available on-line: [], December 2016.
Goodrow M.H., Harrison R.O., Hammock B.D., Hapten synthesis, antibody development and competitive inhibition enzyme immunoassay for s-triazine herbicides. J. Agric. Food Chem., 1990, 38, 990-996.
Gowthaman U., Agrewala J.N., In Silico tools for predicting peptides binding to HLA-class II molecules: more confusion than conclusion. J. Proteome Res., 2008, 7, 154-163.
Gűnther S., Hempel D., Dunkel M., Rother K., Preissner R., SuperHapten: a comprehensive database for small immunogenic compounds. Nucleic Acids Res., 2007, 35, D906-D910.
Harzing A.W., Alakangas S., Google Scholar, Scopus and the Web of Science: a longitudinal and cross-disciplinary comparison. Scientometrics, 2016, 106, 787-804.
Hayes M., Rougé P., Barre A., Herouet-Guicheney C., Roggen E.L., In silico tools for exploring potential human allergy to proteins. Drug Discovery Today, Disease Models, 2015, 17-18, 3-11.
Henry V.J., Bandrowski A.E., Pepin A.S., Gonzalez B.J., Desfeux A., OMICtools: an informative directory for multi-omic data analysis. Database, 2014, Article No bau069.
Holton T.A., Vijayakumar V., Khaldi N., Bioinformatics: Current perspectives and future directions for food and nutritional research facilitated by a Food-Wiki database. Trends Food Sci. Technol., 2013, 34, 5-17.
Ivanciuc O., Schein C.H., Garcia T., Oezguen N., Negi S.S., Braun W., Structural analysis of linear and conformational epitopes of allergens. Regul. Toxicol. Pharm., 2009, 54 (3 Suppl.), S11–S19.
Jędrychowski L., Wróblewska B., Szymkiewicz A., State of the art on food allergens – a review. Pol. J. Food Nutr. Sci., 2008, 58, 165–175.
Jiménez-Saiz R., Benedé S., Molina E., López-Expósito I., Effect of processing technologies on the allergenicity of food products. Crit. Rev. Food Sci. Nutr., 2015, 55, 1902-1917.
Juhász A., Haraszi R., Maulis C., ProPepper: a curated database for identification and analysis of peptide and immune-responsive epitope composition of cereal grain protein families. Database, 2015, Article No bav100.
Kadam K., Sawant S., Jayaraman V.K., Kulkarni-Kale U., Databases and Algorithm in Allergen Informatics. Bioinformatics - Updated Features and Applications, Abdurakhmonov I. (Ed.), InTech, 2016, DOI: 10.5772/63083.
King T.P., Hoffmann D., Loewenstein H., Marsh D.G., Platts-Mills T.A.E., Thomas W., WHO/IUS Allergen Nomenclature Subcommittee, 1994, ACI News 6/2:38-44.
Koeberl M., Clarke D., Lopata A.L., Next generation of food allergen quantification using mass spectrometric systems. J. Proteome Res., 2014, 13, 3499–3509.
Lata S., Bhasin M., Raghava G.P.S., MHCBN 4.0, A database of MHC/TAP binding peptides and T-cell epitopes. BMC Res. Notes, 2009, 2, Article No 61.
Leung N.Y.H., Wai C.Y.Y., Shu S., Wang J., Kenny T.P., Chu K.H., Leung P.S.C., Current immunological and molecular biological perspectives on seafood allergy: a comprehensive review. Clin. Rev. Allerg. Immunol., 2014, 46, 180-197.
Liu Z.P., Wu L.Y., Wang Y., Zhang X.S., Chen L., Bridging protein local structures and protein functions. Amino Acids, 2008, 35, 627–650.
Mari A., Rasi C., Palazzo P., Scala E., Allergen databases: current status and perspectives. Curr. Allergy Asthma Rep., 2009, 9, 376-383.
Mari A., Scala E., Palazzo P., Ridolfi S., Zennaro D., Carabella G., Bioinformatics applied to allergy: Allergen databases, from collecting sequence information to data integration. The Allergome platform as a model. Cell Immunol., 2006, 244, 97-100.
Marti P., Truffer R., Stadler M.B., Keller-Gautschi E., Crameri R., Mari A., Schmid-Grendelmeier P., Miescher S.M., Stadler B.M., Vogel M., Allergen motifs and the prediction of allergenicity. Immunol. Lett., 2007, 109, 47–55.
McSparron H., Blythe M.J., Zygouri C., Doytchinova I.A., Flower D.R., JenPep: A novel computational information resource for immunobiology and vaccinology. J. Chem. Inf. Comput. Sci., 2003, 43, 1276-1287.
Minkiewicz P., Darewicz M., Iwaniak A., Bucholska J., Starowicz P., Czyrko E., Internet databases of the properties, enzymatic reactions, and metabolism of small molecules-search options and applications in food science. Int. J. Mol. Sci., 2016, 17, Article No 2039.
Minkiewicz P., Darewicz M., Iwaniak A., Sokołowska J., Starowicz P., Bucholska J., Hrynkiewicz M., Common amino acid subsequences in a universal proteome-relevance for food science. Int. J. Mol. Sci., 2015, 16, 20748-20773.
Minkiewicz P., Dziuba J., Darewicz M., Iwaniak A., Michalska J., Online programs and databases of peptides and proteolytic enzymes – a brief update for 2007-2008. Food Technol. Biotech., 2009, 47, 345-355.
Minkiewicz P., Miciński J., Darewicz M., Bucholska J., Biological and chemical databases for research into the composition of animal source foods. Food Rev. Int., 2013, 29, 321-351.
Nakamura R., Teshima R., Talagi K., Sawada J.I., Development of Allergen Database for Food Safety (ADFS): an integrated database to search allergens and predict allergenicity. Bull. Nat. Inst. Health Sci., 2005, 123, 32–36.
Ortea I., O'Connor G., Maquet A., Review on proteomics for food authentication. J. Proteom., 2016, 147, 212-225.
Pearson W.R., Lipman D.J., Improved tools for biological sequence comparison. Proc. Natl. Acad. Sci., 1988, 85, 2440-2448.
Pfiffner P., Truffer R., Matsson P., Rasi C., Mari A., Stadler B.M., Allergen cross reactions: a problem greater than ever thought? Allergy, 2010, 65, 1536–1544.
Radauer C., Nandy A., Ferreira F., Goodman R.E., Larsen J.N., Lidholm J., Pomés A., Raulf-Heimsoth M., Rozynek P., Thomas W.R., Breiteneder H., Update of the WHO/IUIS Allergen Nomenclature Database based on analysis of allergen sequences. Allergy, 2014, 69, 413-419.
Radauer C., Bublin M., Wagner S., Mari A., Breiteneder H., Allergens are distributed into few protein families and possess a restricted number of biochemical functions. J. Allergy Clin Immun., 2008, 121, 847-852.
Saeed H., Gagnon C., Cober E., Gleddie S., Using patient serum to epitope map soybean glycinins reveals common epitopes shared with many legumes and tree nuts. Mol. Immunol., 2016, 70, 125–133.
Saha S., Bhasin M., Raghava G.P.S., Bcipep: A database of B-cell epitopes. BMC Genomics, 2005, 6, Article No 79.
Saha S., Raghava G.P.S., AlgPred: prediction of allergenic proteins and mapping of IgE epitopes. Nucleic Acids Res., 2006, 34, W202-W209.
Scalbert A., Andres-Lacueva C., Arita M., Kroom P., Manach C., Urpi-Sarda M., Wishart D., Databases on food phytochemicals and their health-promoting effects. J. Agric. Food Chem., 2011, 59, 4331-4348.
Sharma O.P., Das A.A., Krishna R., Suresh Kumar M., Mathur P.P., Structural Epitope Database (SEDB): A Web-based Database for the epitope, and its intermolecular interaction along with the tertiary structure information. J. Proteom. Bioinform., 2012, 5, 3, 084-089.
Shreder K., Synthetic haptens as probes of antibody response and immunorecognition. Methods, 2000, 20, 372–379.
Sicherer S.H., Leung D.Y.M., Advances in allergic skin disease, anaphylaxis, and hypersensitivity reactions to foods, drugs and insects in 2014. J Allergy Clin. Immunol., 2015, 135, 357-367.
Sicherer S.H., Epidemiology of food allergy. J. Allergy Clin. Immunol., 2011, 127, 594-602.
Singh M.K., Srivastava S., Raghava G.P.S., Varshney G.C., HaptenDB: a comprehensive database of haptens, carrier proteins and anti- hapten antibodies, Bioinformatics, 2006, 22, 253-255.
Singh K.V., Kaur J., Varshney G.C., Raje M., Suri C.R., Synthesis and characterisation of hapten–protein conjugates for antibody production against small molecules. Bioconjug. Chem., 2004, 15, 168-173.
Sircar G., Sarkar D., Bhattacharya S.G., Saha S., Allergen databases. Methods Mol. Biol., 2014, 1184, 165-181.
Siruguri V., Bharatraj D.K., Vankudavath R.N., Rao Mendu V.V., Gupta V., Goodman R.E., Evaluation of Bar, Barnase, and Barstar recombinant proteins expressed in genetically engineered Brassica juncea (Indian mustard) for potential risks of food allergy using bioinformatics and literature searches. Food Chem. Toxicol., 2015, 83, 93-102.
Tapal A., Vegarud G.E., Sreedhara A., Hegde P., Inamdar S., Kaul Tiku P., In vitro human gastro-intestinal enzyme digestibility of globulin isolate from oil palm (Elaeis guineensis var. Tenera) kernel meal and the bioactivity of the digest. RSC Adv., 2016, 6, 20219-20229.
The UniProt Consortium, UniProt: a hub for protein information. Nucl. Acids Res., 2015, 43, D204–D212.
Tong J.Ch., Song Ch.M., Tan P.T.J., Ren E.Ch., Sinha A.A., BEID: Database for sequence- structure-function information on antigen-antibody interactions. Bioinformation, 2008, 3, 58-60.
Trapp J., Web of Science, Scopus, and Google Scholar citation rates: a case study of medical physics and biomedical engineering: what gets cited and what doesn’t? Australas. Phys. Eng. Sci. Med., 2016, 39, 817-823.
Vita R., Overton J.A., Greenbaum J.A., Ponomarenko J., Clark J.D., Cantrell J.R., Wheeler D.K., Gabbard J.L., Hix D., Sette A., Peters B., The immune epitope database (IEDB) 3.0. Nucleic Acids Res., 2015, 43, D405–D412.
Wróblewska B., Szymkiewicz A., Jędrychowski L., Impact of technological processes on changes in food allergies. Żywn. Nauk. Technol. Jakość, 2007, 6, 55, 7-19 (in Polish).
Literature review in support of adjuvanticity/immunogenicity assessment of proteins
Marco Parenti, Aurelia Santoro, Rio Del, Claudio Franceschi
EFSA Supporting Publications
Hybrid Approach in the Analysis of Bovine Milk Protein Hydrolysates as a Source of Peptides Containing Di- and Tripeptide Bitterness Indicators
Anna Iwaniak, Piotr Minkiewicz, Monika Hrynkiewicz, Justyna Bucholska, Małgorzata Darewicz
Polish Journal of Food and Nutrition Sciences
In-silico evaluation of fungal and bacterial L-asparaginases allergenicity
Tekeba Sisay, Naomi Mainal, Sabina Wachira, Victor Mobegi
Informatics in Medicine Unlocked
Anna Iwaniak, Piotr Minkiewicz, Małgorzata Darewicz
Journals System - logo
Scroll to top