An Allergen Portrait Gallery: Representative Structures and an Overview of IgE Binding Surfaces

Identifying Similar Allergens and Potentially Cross-Reacting Areas Using Structural Database of Allergenic Proteins (SDAP) Tools and D-Graph

The Structural Database of Allergenic Proteins (SDAP) provides rapid search tools to identify similarities among allergens, their IgE epitopes, and to determine the potential allergenicity of any novel protein. Many labs have identified IgE-binding proteins and their antibody binding or T cell epitopes using dotspots or microarrays. This chapter describes how to determine the relationship of these proteins and peptides to known allergens using the tools implemented in SDAP. One can also search with these smaller peptide similarity search tool implemented in SDAP to find similar sequences with low property distance (PD) values in the over 1500 sequences of allergens. The sequences can be compared by mapping on the surface of the protein structures provided for nearly all the allergens in SDAP. Once the user has a unique list of similar sequences, they can be graphed in 2D according to interpeptide PD values calculated automatically by the D-graph program. This chapter provides a step-by-step description of how to do this, starting from a protein similar to the Ole e 1 (olive pollen) allergen family.

The updated Structural Database of Allergenic Proteins (SDAP 2.0) provides 3D models for allergens and incorporated bioinformatics tools

Background

Allergenic proteins can cause IgE-mediated adverse reactions in sensitized individuals. Although the sequences of many allergenic proteins have been identified, bioinformatics data analysis with advanced computational methods and modeling is needed to identify the basis for IgE binding and cross-reactivity.

Objective

We aim to present the features and use of the updated Structural Database of Allergenic Proteins 2.0 (SDAP 2.0) webserver, a unique, publicly available resource to compare allergens using specially designed computational tools and new high-quality 3-D models for most known allergens.

Methods

Previously developed and novel software tools for identifying cross-reactive allergens using sequence and structure similarity are implemented in SDAP 2.0. A comprehensive set of high-quality 3-D models of most allergens was generated with the state-of-the-art AlphaFold 2 software. A graphics tool enables the interactive visualization of IgE epitopes on experimentally determined and modeled 3-D structures.

Results

A user can search for allergens similar to a given input sequence with the FASTA algorithm or the window-based World Health Organization/International Union of Immunological Societies (WHO/IUIS) guidelines on safety concerns of novel food products. Peptides similar to known IgE epitopes can be identified with the property distance tool and conformational epitopes by the Cross-React method. The updated database contains 1657 manually curated sequences including all allergens from the IUIS database, 334 experimentally determined X-ray or NMR structures, and 1565 3-D models. Each allergen/isoallergen is classified according to its protein family.

Conclusions

SDAP provides access to the steadily increasing information on allergenic structures and epitopes with integrated bioinformatics tools to identify and analyze their similarities. In addition to serving the research and regulatory community, it provides clinicians with tools to identify potential coallergies in a sensitive patient and can help companies to design hypoallergenic foods and immunotherapies.

Allergenicity of peanut allergens and its dependence on the structure

Food allergies are a global food safety problem. Peanut allergies are common due, in part, to their popular utilization in the food industry. Peanut allergy is typically an immunoglobulin E-mediated reaction, and peanuts contain 17 allergens belonging to different families in peanut. In this review, we first introduce the mechanisms and management of peanut allergy, followed by the basic structures of associated allergens. Subsequently, we summarize methods of epitope localization for peanut allergens. These methods can be instrumental in speeding up the discovery of allergenicity-dependent structures. Many attempts have been made to decrease the allergenicity of peanuts. The structures of hypoallergens, which are manufactured during processing, were analyzed to strengthen the desensitization process and allergen immunotherapy. The identification of conformational epitopes is the bottleneck in both peanut and food allergies. Further, the identification and modification of such epitopes will lead to improved strategies for managing and preventing peanut allergy. Combining traditional wet chemistry research with structure simulation studies will help in the epitopes' localization.

Epitopes with similar physicochemical properties contribute to cross reactivity between peanut and tree nuts

Many individuals with peanut (PN) allergy have severe reactions to tree nuts (TN) such as walnuts or cashews. Although allergenic proteins in TN and PN have overall low identity, they share discrete sequences similar in physicochemical properties (PCP) to known IgE epitopes. Here, PCP-consensus peptides (cp, 13 aa and 31 aa) were identified from an alignment of epitope rich regions of walnut vicilin, Jug r 2, leader sequence (J2LS) and cross-reactive epitopes in the 2S albumins of peanut and synthesized. A peptide similarity search in the Structural Database of Allergenic Proteins (SDAP) revealed a network of peptides similar (low property distance, PD) to the 13 aa cp (13cp) in many different plant allergens. Peptides similar to the 13cp in PN and TN allergens bound IgE from sera of patients allergic to PN and TN in peptide microarray analysis. The 13cp was used to produce a rabbit consensus peptide antibody (cpAB) that detected proteins containing repeats similar to the 13cp in western blots of various nut extracts, in which reactive proteins were identified by mass spectrometry. The cpAB bound more specifically to allergens and nut extracts containing multiple repeats similar to the 13 cp, such as almond (Pru du 6), peanut (Ara h 2) and walnut (Jug r 2). IgE binding to various nut extracts is inhibited by recombinant J2LS sequence and synthetic 31cp. Thus, several repeated sequences similar to the 13cp are bound by IgE. Multiple similar repeats in several allergens could account for reaction severity and clinically relevant cross-reactivity to PN and TN. These findings may help improve detection, diagnostic, and therapeutic tools.

Distinguishing allergens from non-allergenic homologues using Physical-Chemical Property (PCP) motifs

Quantitative guidelines to distinguish allergenic proteins from related, but non-allergenic ones are urgently needed for regulatory agencies, biotech companies and physicians. In a previous study, we found that allergenic proteins populate a relatively small number of protein families, as characterized by the Pfam database. However, these families also contain non-allergenic proteins, meaning that allergenic determinants must lie within more discrete regions of the sequence. Thus, new methods are needed to discriminate allergenic proteins within those families. Physical-Chemical Properties (PCP)-motifs specific for allergens within a Pfam class were determined for 17 highly populated protein domains. A novel scoring method based on PCP-motifs that characterize known allergenic proteins within these families was developed, and validated for those domains. The motif scores distinguished sequences of allergens from a large selection of 80,000 randomly selected non-allergenic sequences. The motif scores for the birch pollen allergen (Bet v 1) family, which also contains related fruit and nut allergens, correlated better than global sequence similarities with clinically observed cross-reactivities among those allergens. Further, we demonstrated that the average scores of allergen specific motifs for allergenic profilins are significantly different from the scores of non-allergenic profilins. Several of the selective motifs coincide with experimentally determined IgE epitopes of allergenic profilins. The motifs also discriminated allergenic pectate lyases, including Jun a 1 from mountain cedar pollen, from similar proteins in the human microbiome, which can be assumed to be non-allergens. The latter lacked key motifs characteristic of the known allergens, some of which correlate with known IgE binding sites.

Conformational IgE epitopes of peanut allergens Ara h 2 and Ara h 6

BACKGROUND

Cross-linking of IgE antibody by specific epitopes on the surface of mast cells is a prerequisite for triggering symptoms of peanut allergy. IgE epitopes are frequently categorized as linear or conformational epitopes. Although linear IgE-binding epitopes of peanut allergens have been defined, little is known about conformational IgE-binding epitopes.

OBJECTIVE

To identify clinically relevant conformational IgE epitopes of the two most important peanut allergens, Ara h 2 and Ara h 6, using phage peptide library.

METHODS

A phage 12mer peptide library was screened with allergen-specific IgE from 4 peanut-allergic patients. Binding of the mimotopes to IgE from a total of 29 peanut-allergic subjects was measured by ELISA. The mimotope sequences were mapped on the surface areas of Ara h 2 and Ara h 6 using EpiSearch.

RESULTS

Forty-one individual mimotopes were identified that specifically bind anti- Ara h 2/Ara h 6 IgE as well as rabbit anti-Ara h 2 and anti-Ara h 6 IgG. Sequence alignment showed that none of the mimotope sequences match a linear segment of the Ara h 2 or Ara h 6 sequences. EpiSearch analysis showed that all the mimotopes mapped to surface patches of Ara h 2 and Ara h 6. Eight of the mimotopes were recognized by more than 90% of the patients, suggesting immunodominance. Each patient had distinct IgE recognition patterns but the recognition frequency was not correlated to the concentration of peanut specific IgE or to clinical history.

CONCLUSIONS

The mimotopes identified in this study represent conformational epitopes. Identification of similar surface patches on Ara h 2 and Ara h 6 further underscores the similarities between these two potent allergens.

Molecular Dynamics of Major Allergens from Alternaria, Birch Pollen and Peach

In the search for factors that make a protein allergenic (an issue that remains so far elusive) some common features of allergens such as small size, high stability and lipid binding are recognized in spite of their structural diversity. Other relevant but still poorly understood feature is their capability to form homodimers. We investigated by means of Molecular Dynamics (MD) calculations the stability in solution of several dimers of three major allergens from Alternaria mold, birch pollen, and peach fruit known to play essential roles in allergic disease. By running 20 ns MD simulations we found essential properties on solution that provide information of interest on their dimerization, stability of their epitopes and dynamical features of ligand binding cavities. Our results show that three essential allergen proteins display a distinct behavior on their trends to form homodimers in solution.

Food allergy: a practice parameter update-2014

This parameter was developed by the Joint Task Force on Practice Parameters, representing the American Academy of Allergy, Asthma & Immunology (AAAAI); the American College of Allergy, Asthma & Immunology (ACAAI); and the Joint Council of Allergy, Asthma & Immunology (JCAAI). The AAAAI and the ACAAI have jointly accepted responsibility for establishing "Food Allergy: A practice parameter update-2014." This is a complete and comprehensive document at the current time. The medical environment is a changing one, and not all recommendations will be appropriate for all patients. Because this document incorporated the efforts of many participants, no single individual, including those who served on the Joint Task Force, is authorized to provide an official AAAAI or ACAAI interpretation of these practice parameters. Any request for information about or an interpretation of these practice parameters by the AAAAI or ACAAI should be directed to the Executive Offices of the AAAAI, ACAAI, and JCAAI. These parameters are not designed for use by pharmaceutical companies in drug promotion.

Stabilization of the dimeric birch pollen allergen Bet v 1 impacts its immunological properties

Many allergens share several biophysical characteristics, including the capability to undergo oligomerization. The dimerization mechanism in Bet v 1 and its allergenic properties are so far poorly understood. Here, we report crystal structures of dimeric Bet v 1, revealing a noncanonical incorporation of cysteine at position 5 instead of genetically encoded tyrosine. Cysteine polysulfide bridging stabilized different dimeric assemblies, depending on the polysulfide linker length. These dimers represent quaternary arrangements that are frequently observed in related proteins, reflecting their prevalence in unmodified Bet v 1. These conclusions were corroborated by characteristic immunologic properties of monomeric and dimeric allergen variants. Hereby, residue 5 could be identified as an allergenic hot spot in Bet v 1. The presented results refine fundamental principles in protein chemistry and emphasize the importance of protein modifications in understanding the molecular basis of allergenicity.

Sequence microheterogeneity of parvalbumin, the major fish allergen

The microheterogeneity of amino acid sequence observed in various allergens may affect immune response, but incidence of sequence microheterogeneity in allergens and its relation to their allergenicity are unclear. The occurrence of sequence microheterogeneity in major fish allergen, parvalbumin (PA), has been explored using bioinformatics approaches. 44% of 111 species with known PA sequence have PA isoforms. 41% of these species exhibit from 1 to 4 cases of PA sequence microheterogeneity, i.e. unique pairs of PA isoforms with sequence identity above 90%. 29% of 210 PA sequences studied are characterized by microheterogeneity. The occurrence of allergens among them is 2.5-fold higher than among other PAs. The incidence of sequence microheterogeneity within more allergenic β isoform of PA is 2.0-fold lower than that for its less allergenic α isoform. 39 residues affected by PA microheterogeneity are concentrated in the region of helices A, B, F, while helices D and E are the most conservative region. 44% and 11% of the microheterogeneous substitutions are located in the species-specific and cross-reactive IgE-binding epitopes of PAs, respectively. 45% and 48% of the substitution cases are predicted to cause notable changes in protein disorder propensity and protein stability, respectively. Hence, the increased allergenicity rate among PAs having microheterogeneous isoforms can be related to differences in their IgE-binding caused directly or in an allosteric manner. Overall, sequence microheterogeneity is shown to be inherent to many of PAs and likely contributes to PA allergenicity.

Assessment of 3D models for allergen research

Allergenic proteins must crosslink specific IgE molecules, bound to the surface of mast cells and basophils, to stimulate an immune response. A structural understanding of the allergen-IgE interface is needed to predict cross-reactivities between allergens and to design hypoallergenic proteins. However, there are less than 90 experimentally determined structures available for the approximately 1500 sequences of allergens and isoallergens cataloged in the Structural Database of Allergenic Proteins. To provide reliable structural data for the remaining proteins, we previously produced more than 500 3D models using an automated procedure, with strict controls on template choice and model quality evaluation. Here, we assessed how well the fold and residue surface exposure of 10 of these models correlated with recently published experimental 3D structures determined by X-ray crystallography or NMR. We also discuss the impact of intrinsically disordered regions on the structural comparison and epitope prediction. Overall, for seven allergens with sequence identities to the original templates higher than 27%, the backbone root-mean square deviations were less than 2 Å between the models and the subsequently determined experimental structures for the ordered regions. Further, the surface exposure of the known IgE epitopes on the models of three major allergens, from peanut (Ara h 1), latex (Hev b 2), and soy (Gly m 4), was very similar to the experimentally determined structures. For the three remaining allergens with lower sequence identities to the modeling templates, the 3D folds were correctly identified. However, the accuracy of those models is not sufficient for a reliable epitope mapping.

Group 10 allergens (tropomyosins) from house-dust mites may cause covariation of sensitization to allergens from other invertebrates

Group 10 allergens (tropomyosins) have been assumed to be a major cause of cross-reactivity between house-dust mites (HDMs) and other invertebrates. Despite all of the published data regarding the epidemiology, percent IgE binding and level of sensitization in the population, the role of tropomyosin as a cross-reactive allergen in patients with multiple allergy syndrome still remains to be elucidated. Homology between amino acid sequences reported in allergen databases of selected invertebrate tropomyosins was determined with Der f 10 as the reference allergen. The 66.9 and 54.4% identities were found with selected crustacean and insect species, respectively, whereas only 20.4% identity was seen with mollusks. A similar analysis was performed using reported B-cell IgE-binding epitopes from Met e1 (shrimp allergen) and Bla g7 (cockroach allergen) with other invertebrate tropomyosins. The percent identity in linear sequences was higher than 35% in mites, crustaceans, and cockroaches. The polar and hydrophobic regions in these groups were highly conserved. These findings suggest that tropomyosin may be a major cause of covariation of sensitization between HDMs, crustaceans, and some species of insects and mollusks.

AllerML: markup language for allergens

Many concerns have been raised about the potential allergenicity of novel, recombinant proteins into food crops. Guidelines, proposed by WHO/FAO and EFSA, include the use of bioinformatics screening to assess the risk of potential allergenicity or cross-reactivities of all proteins introduced, for example, to improve nutritional value or promote crop resistance. However, there are no universally accepted standards that can be used to encode data on the biology of allergens to facilitate using data from multiple databases in this screening. Therefore, we developed AllerML a markup language for allergens to assist in the automated exchange of information between databases and in the integration of the bioinformatics tools that are used to investigate allergenicity and cross-reactivity. As proof of concept, AllerML was implemented using the Structural Database of Allergenic Proteins (SDAP; http://fermi.utmb.edu/SDAP/) database. General implementation of AllerML will promote automatic flow of validated data that will aid in allergy research and regulatory analysis.

Bioinformatics and the allergy assessment of agricultural biotechnology products: industry practices and recommendations

Bioinformatic tools are being increasingly utilized to evaluate the degree of similarity between a novel protein and known allergens within the context of a larger allergy safety assessment process. Importantly, bioinformatics is not a predictive analysis that can determine if a novel protein will ''become" an allergen, but rather a tool to assess whether the protein is a known allergen or is potentially cross-reactive with an existing allergen. Bioinformatic tools are key components of the 2009 CodexAlimentarius Commission's weight-of-evidence approach, which encompasses a variety of experimental approaches for an overall assessment of the allergenic potential of a novel protein. Bioinformatic search comparisons between novel protein sequences, as well as potential novel fusion sequences derived from the genome and transgene, and known allergens are required by all regulatory agencies that assess the safety of genetically modified (GM) products. The objective of this paper is to identify opportunities for consensus in the methods of applying bioinformatics and to outline differences that impact a consistent and reliable allergy safety assessment. The bioinformatic comparison process has some critical features, which are outlined in this paper. One of them is a curated, publicly available and well-managed database with known allergenic sequences. In this paper, the best practices, scientific value, and food safety implications of bioinformatic analyses, as they are applied to GM food crops are discussed. Recommendations for conducting bioinformatic analysis on novel food proteins for potential cross-reactivity to known allergens are also put forth.