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Enables prediction of cross-reactivity between distantly related allergenic proteins using their X-ray or homology modeled structures in combination with epitope analysis. Cross-React uses a patch analysis, solvent accessible surface area of amino acids, and structural similarity between amino acids in the epitope region of a query allergen and allergens in the SDAP database. The search results are ranked based on the calculated Pearson correlation coefficient (PCC) between the amino acid composition in the query epitope and the accessible surface patches on the target allergens. Cross-React can be used as a predictive tool to assess protein allergenicity and cross-reactivity.

SDAP / Structural Database of Allergenic Proteins

A web server that provides rapid, cross-referenced access to the sequences, structures and IgE epitopes of allergenic proteins. SDAP contains information about the allergen name, source, sequence, structure, IgE epitopes and literature references and easy links to the major protein (PDB, SWISS-PROT/TrEMBL, PIR-ALN, NCBI Taxonomy Browser) and literature (PubMed, MEDLINE) on-line servers. The computational component in SDAP uses an original algorithm based on conserved properties of amino acid side chains to identify regions of known allergens similar to user supplied peptides or selected from the SDAP database of IgE epitopes. This and other bioinformatics tools can be used to rapidly determine potential cross-reactivities between allergens and to screen novel proteins for the presence of IgE epitopes they may share with known allergens.


forum (1)
A fast and accurate sequence-based allergen prediction tool that models protein sequences as text documents and uses support vector machine in text classification for allergen prediction. Test results on multiple highly skewed datasets demonstrated that Allerdictor predicted allergens with high precision over high recall at fast speed. For example, Allerdictor only took approximately 6 min on a single core PC to scan a whole Swiss-Prot database of approximately 540 000 sequences and identified <1% of them as allergens.

AllergenFP / Allergen FingerPrint

An alignment-free method for allergenicity prediction, based on amino acid principal properties as hydrophobicity, size, relative abundance, helix and β-strand forming propensities. AllergenFP transforms proteins into descriptor-based fingerprints and compares them by Tanimoto coefficient. The algorithm was optimized in terms of lag length and resolution step and cross-validated by a set of 2427 known allergens and 2427 non-allergens. It recognized 87% of the allergens and 89% of the non-allergens. AllergenFP was compared with five freely available web servers for allergenicity prediction and showed the highest predictive ability.


A bioinformatics tool for allergenicity prediction. AllerTOP is based on amino acid descriptors, accounting for residue hydrophobicity, size, abundance, helix- and β-strand forming propensities. The protein strings were transformed into uniform vectors by auto- and cross-covariance and a machine learning method using k nearest neighbours was used to classify allergens and non-allergens. The comparison between several servers for allergen prediction indicates that AllerTOP v.2 has the highest accuracy. AllerTOP v.2 offers a useful, robust, and strongly complimentary approach to allergen prediction that should provide researchers with important and persuasive new approach to identifying allergens in both existing and newly developed materials.

AllergenPro / NABIC AllergenPro database

An integrated web-based system providing information about allergen in foods, microorganisms, animals and plants. AllergenPro has the three main features namely, (1) allergen list with epitopes, (2) searching of allergen using keyword, and (3) methods for allergenicity prediction. AllergenPro outputs the search based allergen information through a user-friendly web interface, and users can run tools for allergenicity prediction using three different methods namely, (1) FAO/WHO, (2) motif-based and (3) epitope-based methods.


A web server with essential tools for the assessment of predicted as well as published cross-reactivity patterns of allergens. AllerTool includes graphical representation of allergen cross-reactivity information; a local sequence comparison tool that displays information of known cross-reactive allergens; a sequence similarity search tool for assessment of cross-reactivity in accordance to FAO/WHO Codex alimentarius guidelines; and a method based on support vector machine (SVM).


A cross-reactive allergen prediction program built on a combination of support vector machine (SVM) and pairwise sequence similarity. Cross-reactivity is based on similarity of proteins to allergens. However, not all proteins with similar sequence or structure to known allergens are cross-reactive allergens. AllerHunter aims to predict allergens and non-allergens with high sensitivity and specificity, without compromising efficiency at classification of proteins with similar sequence to known allergens.