Structural Database Of Allergenic Proteins Research Articles

In silico approaches for the identification of potential allergens among hypothetical proteins from Alternaria alternata and its functional annotation

Direct exposure to the fungal species Alternaria alternata is a major risk factor for the development of asthma, allergic rhinitis, and inflammation. As of November 23rd 2020, the NCBI protein database showed 11,227 proteins from A. alternata genome as hypothetical proteins (HPs). Allergens are the main causative of several life-threatening diseases, especially in fungal infections. Therefore, the main aim of the study is to identify the potentially allergenic inducible proteins from the HPs in A. alternata and their associated functional assignment for the complete understanding of the complex biological systems at the molecular level. AlgPred and Structural Database of Allergenic Proteins (SDAP) were used for the prediction of potential allergens from the HPs of A. alternata. While analyzing the proteome data, 29 potential allergens were predicted by AlgPred and further screening in SDAP confirmed the allergic response of 10 proteins. Extensive bioinformatics tools including protein family classification, sequence-function relationship, protein motif discovery, pathway interactions, and intrinsic features from the amino acid sequence were used to successfully predict the probable functions of the 10 HPs. The functions of the HPs are characterized as chitin-binding, ribosomal protein P1, thaumatin, glycosyl hydrolase, and NOB1 proteins. The subcellular localization and signal peptide prediction of these 10 proteins has further provided additional information on localization and function. The allergens prediction and functional annotation of the 10 proteins may facilitate a better understanding of the allergenic mechanism of A. alternata in asthma and other diseases. The functional domain level insights and predicted structural features of the allergenic proteins help to understand the pathogenesis and host immune tolerance. The outcomes of the study would aid in the development of specific drugs to combat A. alternata infections.

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

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

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.

New, Structural Database of Allergenic Proteins (SDAP) Provides 3D models with Incorporated Bioinformatics Tools

The 3D structures of allergenic proteins are needed to determine conformational epitopes contributing to allergen cross-reactivity. SDAP now includes new models and bioinformatics tools for predicting allergenic propensity and epitopes.

The Identification and Characterization of Immunoreactive Fungal Proteins Recognized by Sera from Zimbabweans Sensitized to Fungi

Background: Exposure to fungal allergens poses a serious threat to human health, especially to mould-allergic individuals. The prevalence of fungal allergic disease is increasing globally but is poorly studied in Africa. Here, we aimed to identify and characterize fungal proteins that were immunoreactive against serum samples from fungal-sensitized Zimbabweans from Shamva district to inform the development of diagnostics and therapeutics. Methods: Crude protein extracts of the Ascomycota Aspergillus fumigatus, Alternaria alternata, Cladosporium herbarum, Epicoccum nigrum, Penicillium chrysogenum, and Saccharomyces cerevisiae as well as mucoromycota Rhizopus nigricans were individually separated by one-dimensional gel electrophoresis for protein staining and immunoblotting. A pool of eight sera from fungi-sensitive Zimbabwean children aged 3–5 years was used to screen the crude extracts to determine their immunoreactivity. Protein bands recognized by the sera were subjected to mass spectrometry to identify the individual proteins reactive with the sera. Results: The pooled serum sample reacted with 20 bands, which resolved to 34 distinct proteins, most of which were novel immunogens. The pool was most reactive to A. alternata. The proteins identified included peptidases (8/34), hydrolases (6/34), oxidoreductases (5/34), and glucosidases (4/34), while 11/34 were unknown. Eight of the proteins were predicted to be allergens using the Structural Database of Allergenic Proteins (SDAP). Conclusions: We identified novel immunogens from fungi expanding the number of known fungal allergens. These form a potential basis for diagnostics specific for the Zimbabwean population. Validation assays will now need to be carried out to further evaluate the cross-reactivity of the identified allergen candidates as well as investigate their potential recognition in a larger cohort of patients. Furthermore, there is now a need to conduct studies relating sensitization to these immunogens and clinical diseases in the population.

Still SDAPing Along: 20 Years of the Structural Database of Allergenic Proteins.

The introduction of plant extracts to mitigate the symptoms of “hay fever”, about a century ago, led to discoveries beginning sixty years ago on determining the sequences and eventually structures of allergenic proteins. As more proteins were cloned, there was a need to rapidly identify and categorize those with significant similarity to known allergens. The Structural Database of Allergenic Proteins (SDAP) was created at the beginning of the 21st century as the first cross-referenced website to allow rapid overview of the structures and sequences of allergenic proteins. SDAP provides a way to identify sequence and functional similarities between these proteins, despite the complex nomenclature system based on the Latin names of their different sources. A rapid FASTA search simplifies grouping allergens from the same structural or functional family. SDAP also provides an overview of the rapidly expanding literature on the sequence, structure and epitopes of allergenic proteins and a way to estimate the potential allergenicity of novel proteins based on rules provided by the IUIS. Twenty years and a pandemic later, the list of allergenic proteins and their attributes continues to grow. SDAP is expanding and improving to allow rapid access to all this information.

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.

Proteomic Analysis and Identification of Possible Allergenic Proteins in Mature Pollen of Populus tomentosa.

Pollen grains from Populus tomentosa, a widely cultivated tree in northern area of China, are considered to be an important aeroallergen causing severe allergic diseases. To gain insight into their allergenic components, mature Populus tomentosa pollen proteins were analyzed by two-dimensional gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF/TOF MS). A total of 412 spots from mature pollen were resolved on pH 4–7 immobilized pH gradient (IPG) strips and 159 distinct proteins were identified from 242 spots analyzed. The identified proteins were categorized based on their functional role in the pollen, which included proteins involved in energy regulation, protein fate, protein synthesis and processing, metabolism, defense/stress responses, development and other functional categories. Moreover, among the identified proteins, 27 proteins were identified as putative allergens using the Structural Database of Allergenic Proteins (SDAP) tool and Allergen Online. The expression patterns of these putative allergen genes indicate that several of these genes are highly expressed in pollen. The identified putative allergens have the potential to improve specific diagnosis and can be used to develop vaccines for immunotherapy against poplar pollen allergy.

In Vitro Evaluation of the Allergic Potential of Antibacterial Peptides: Camel and Citropin.

Peptide-based drugs are promising group of compounds which are characterized by specificity to their in vivo targets and high potency of action (antineoplastic, immunoregulatory, antibacterial). The peptides, however, involve a relatively high risk of allergic reactions that are not predictable on the basis of their sequence and chemical properties. In this study, peripheral blood was obtained from 53 patients including 38 hypersensitive patients and 15 control patients. Basophil activation stimulated by two antibacterial peptides (camel, citropin 1.1), and acetylsalicylic acid was assessed by means of BAT (basophil activation test). Basophil activation stimulated by camel occurred in 7 of 38 patients with hypersensitivity (18.42%) as well as in 2 of 15 control patients (13.33%). Basophils were activated by citropin 1.1 in 7 of 38 hypersensitive patients (18.42%) and in none of the control patients. Using the Structural Database of Allergenic Proteins, we confirmed that the examined peptides share some structural similarities with common environmental allergens. Therefore, the cross-reactivity between potentially present anti-allergen IgE with examined peptides cannot be excluded. Our study proved that BAT, together with other biological tests and specific databases of allergenic compounds, may serve as an initial selection of new active peptides and proteins.

Absolute quantification of protein NP24 in tomato fruit by liquid chromatography/tandem mass spectrometry using stable isotope-labelled tryptic peptide standard

Protein NP24 is a thaumatin-like protein contained in tomato (Lycopersicon esculentum Mill.). This protein is reported to be a putative tomato allergen and is listed as a food allergen in Structural Database of Allergenic Proteins (SDAP). In this research, we developed the quantitative analysis of NP24 by employing the protein absolute quantification (AQUA) technology composed of stable isotope-labelled internal standard (SIIS) peptide (GQTWVINAPR[13C6,15N4]) and liquid chromatography/tandem mass spectrometry (LC/MS/MS). A linear relationship (r2>0.99) was found throughout the concentration range (2.0–500fmol/μL). The coefficients of variation (CVs) measured on each of the five days when NP24 contained in the tomato skin was analysed did not exceed 13%. Our developed assay of NP24 will contribute to the allergological examination of tomato and its derived products.

In silico prediction of allergenic proteins.

Currently, the prediction of new allergens is becoming important due to use of genetically modified (GM) foods and biopharmaceuticals. In this chapter, we describe how to use four popular allergenic prediction servers: (1) Structural Database of Allergenic Proteins (SDAP), (2) Allermatch, (3) Evaller 2, and (4) AlgPred. The first two prediction servers are based on traditional approaches, whereas Evaller 2 and AlgPred use sophisticated machine learning techniques.

The analysis of specific allergenicity of food allergens families

Classification of food allergens based on protein's structure and function contributes to the study of the relationship between bioinformatics and potential allergenicity of allergens, as well as the evaluation of novel proteins' allergenicity. Some researches were focused on classification within plant or animal food allergens respectively, but there is not any classification of the wholefood allergens. In this article, we classified all the food allergens included in the SDAP into different food allergen families and analysed their specific allergenicity. According to allergen families in AllFam Database, food allergens taken from SDAP (Structural Database of Allergenic Proteins) are classified into different allergen families. Moreover, Protean of DNAStar was applied to analyzing the allergenicity of food allergens. 60% of food allergens are included in the five allergen families: Prolamin superfamily, EF hand domain, Cupin superfamily Profilin and Bet v 1-related protein. Besides, three other cross-food allergen families are found: EF hand domain, Serpin serine protease inhibitor and Triose phosphate isomerase, which include food allergens from both plants and animals. Common characters of food allergens from the same family were easy to find. For instance, they share the same specific peptides and potential T lymphocyte antigen epitope. This classification and characterization of allergen allergenicity in different food allergen families provide foundation for studying the structure and function of novel food allergens as well as the data for the assessment of potential allergenicity.

In silico Identification of IgE-Binding Epitopes of Osmotin Protein

The identification of B-cell epitopes is an important step to study the antigen- antibody interactions for diagnosis and therapy. The present study aimed to identify B- cell epitopes of osmotin using bioinformatic tools and further modify these regions to study the allergenic property. B-cell epitopes were predicted based on amino acid physicochemical properties. Three single point mutations M1, M2, and M3 and a multiple point mutant (M123) were selected to disrupt the IgE binding. These mutants were cloned, expressed and proteins purified to homogeneity. The IgE binding of the purified proteins was evaluated by ELISA and ELISA inhibition with patients' sera. Three regions of osmotin M1 (57–70 aa), M2 (72–85 aa) and M3 (147–165 aa) were identified as potential antibody recognition sites using in silico tools. The sequence similarity search of the predicted epitopes of osmotin using Structural Database of Allergenic proteins (SDAP) showed similarity with known allergens from tomato, kiwifruit, bell pepper, apple, mountain cedar and cypress. Mutants M1, M2 and M3 showed up to 72%, 60% and 76% reduction, respectively in IgE binding whereas M123 showed up to 90% reduction with patients' sera. The immunoblot of M123 mutant showed 40% reduction in spot density as compared to osmotin. All mutants showed decreased inhibition potency with M123 exhibiting lowest potency of 32% with osmotin positive pooled patients' sera. The three B- cell epitopes of osmotin predicted by in silico method correlated with the experimental approach. The mutant M123 showed a reduction of 90% in IgE binding. The present method may be employed for prediction of B- cell epitopes of allergenic proteins.

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.

Computationally predicted IgE epitopes of walnut allergens contribute to cross-reactivity with peanuts

Cross-reactivity between peanuts and tree nuts implies that similar immunoglobulin E (IgE) epitopes are present in their proteins. To determine whether walnut sequences similar to known peanut IgE-binding sequences, according to the property distance (PD) scale implemented in the Structural Database of Allergenic Proteins, react with IgE from sera of patients with allergy to walnut and/or peanut. Patient sera were characterized by western blotting for IgE binding to nut protein extracts and to peptides from walnut and peanut allergens, similar to known peanut epitopes as defined by low PD values, synthesized on membranes. Competitive enzyme-linked immunosorbent assay (ELISA) was used to show that peanut and predicted walnut epitope sequences compete with purified Ara h 2 for binding to IgE in serum from a cross-reactive patient. Sequences from the vicilin walnut allergen Jug r 2, which had low PD values to epitopes of the peanut allergen Ara h 2, a 2S albumin, bound to IgE in sera from five patients who reacted to either walnut or peanut or both. A walnut epitope recognized by sera from six patients mapped to a surface-exposed region on a model of the N-terminal pro-region of Jug r 2. This predicted walnut epitope competed for IgE binding to Ara h 2 in serum as well as the known IgE epitope from Ara h 2. Sequences with low PD value (< 8.5) to known IgE epitopes could contribute to cross-reactivity between allergens. This further validates the PD scoring method for predicting cross-reactive epitopes in allergens.

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.

Structural analysis of linear and conformational epitopes of allergens

In many countries regulatory agencies have adopted safety guidelines, based on bioinformatics rules from the WHO/FAO and EFSA recommendations, to prevent potentially allergenic novel foods or agricultural products from reaching consumers. We created the Structural Database of Allergenic Proteins (SDAP, http://fermi.utmb.edu/SDAP/) to combine data that had previously been available only as flat files on Web pages or in the literature. SDAP was designed to be user friendly, to be of maximum use to regulatory agencies, clinicians, as well as to scientists interested in assessing the potential allergenic risk of a protein. We developed methods, unique to SDAP, to compare the physicochemical properties of discrete areas of allergenic proteins to known IgE epitopes. We developed a new similarity measure, the property distance ( PD) value that can be used to detect related segments in allergens with clinical observed cross-reactivity. We have now expanded this work to obtain experimental validation of the PD index as a quantitative predictor of IgE cross-reactivity, by designing peptide variants with predetermined PD scores relative to known IgE epitopes. In complementary work we show how sequence motifs characteristic of allergenic proteins in protein families can be used as fingerprints for allergenicity.

Characteristic motifs for families of allergenic proteins

The identification of potential allergenic proteins is usually done by scanning a database of allergenic proteins and locating known allergens with a high sequence similarity. However, there is no universally accepted cut-off value for sequence similarity to indicate potential IgE cross-reactivity. Further, overall sequence similarity may be less important than discrete areas of similarity in proteins with homologous structure. To identify such areas, we first classified all allergens and their subdomains in the Structural Database of Allergenic Proteins (SDAP, http://fermi.utmb.edu/SDAP/) to their closest protein families as defined in Pfam, and identified conserved physicochemical property motifs characteristic of each group of sequences. Allergens populate only a small subset of all known Pfam families, as all allergenic proteins in SDAP could be grouped to only 130 (of 9318 total) Pfams, and 31 families contain more than four allergens. Conserved physicochemical property motifs for the aligned sequences of the most populated Pfam families were identified with the PCPMer program suite and catalogued in the webserver MotifMate (http://born.utmb.edu/motifmate/summary.php). We also determined specific motifs for allergenic members of a family that could distinguish them from non-allergenic ones. These allergen specific motifs should be most useful in database searches for potential allergens. We found that sequence motifs unique to the allergens in three families (seed storage proteins, Bet v 1, and tropomyosin) overlap with known IgE epitopes, thus providing evidence that our motif based approach can be used to assess the potential allergenicity of novel proteins.

The property distance index PD predicts peptides that cross-react with IgE antibodies

Similarities in the sequence and structure of allergens can explain clinically observed cross-reactivities. Distinguishing sequences that bind IgE in patient sera can be used to identify potentially allergenic protein sequences and aid in the design of hypo-allergenic proteins. The property distance index PD, incorporated in our Structural Database of Allergenic Proteins (SDAP, http://fermi.utmb.edu/SDAP/), may identify potentially cross-reactive segments of proteins, based on their similarity to known IgE epitopes. We sought to obtain experimental validation of the PD index as a quantitative predictor of IgE cross-reactivity, by designing peptide variants with predetermined PD scores relative to three linear IgE epitopes of Jun a 1, the dominant allergen from mountain cedar pollen. For each of the three epitopes, 60 peptides were designed with increasing PD values (decreasing physicochemical similarity) to the starting sequence. The peptides synthesized on a derivatized cellulose membrane were probed with sera from patients who were allergic to Jun a 1, and the experimental data were interpreted with a PD classification method. Peptides with low PD values relative to a given epitope were more likely to bind IgE from the sera than were those with PD values larger than 6. Control sequences, with PD values between 18 and 20 to all the three epitopes, did not bind patient IgE, thus validating our procedure for identifying negative control peptides. The PD index is a statistically validated method to detect discrete regions of proteins that have a high probability of cross-reacting with IgE from allergic patients.

Comprehensive 3D-modeling of allergenic proteins and amino acid composition of potential conformational IgE epitopes

Similarities in sequences and 3D structures of allergenic proteins provide vital clues to identify clinically relevant immunoglobulin E (IgE) cross-reactivities. However, experimental 3D structures are available in the Protein Data Bank for only 5% (45/829) of all allergens catalogued in the Structural Database of Allergenic Proteins (SDAP, http://fermi.utmb.edu/SDAP). Here, an automated procedure was used to prepare 3D-models of all allergens where there was no experimentally determined 3D structure or high identity (95%) to another protein of known 3D structure. After a final selection by quality criteria, 433 reliable 3D models were retained and are available from our SDAP Website. The new 3D models extensively enhance our knowledge of allergen structures. As an example of their use, experimentally derived “continuous IgE epitopes” were mapped on 3 experimentally determined structures and 13 of our 3D-models of allergenic proteins. Large portions of these continuous sequences are not entirely on the surface and therefore cannot interact with IgE or other proteins. Only the surface exposed residues are constituents of “conformational IgE epitopes” which are not in all cases continuous in sequence. The surface exposed parts of the experimental determined continuous IgE epitopes showed a distinct statistical distribution as compared to their presence in typical protein–protein interfaces. The amino acids Ala, Ser, Asn, Gly and particularly Lys have a high propensity to occur in IgE binding sites. The 3D-models will facilitate further analysis of the common properties of IgE binding sites of allergenic proteins.