Lol p Epitopes in Cutting Edge : Identification of Novel T Cell (original) (raw)
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Cutting edge: identification of novel T cell epitopes in Lol p5a by computational prediction
The Journal of …, 1999
Although atopic allergy affects <20% of the total population, the relationship between the protein structure and immunogenic activity of the allergens is still largely unknown. We observed that group 5 grass allergens are characterized by repeated structural motifs. Using a new algorithm, TEPITOPE, we predicted promiscuous HLA-DR ligands within the repeated motifs of the Lol p5a allergen from rye grass. In vitro binding studies confirmed the promiscuous binding characteristics of these peptides. Moreover, most of the predicted ligands were novel T cell epitopes that were able to stimulate T cells from atopic patients. We generated a panel of Lol p5a-specific T cell clones, the majority of which recognized the peptides in a crossreactive fashion. The computational prediction of DR ligands might thus allow the design of T cell epitopes with potential useful application in novel immunotherapy strategies.
Molecular Determinants of T Cell Epitope Recognition to the Common Timothy Grass Allergen
The Journal of Immunology, 2010
We investigated the molecular determinants of allergen-derived T cell epitopes in humans utilizing the Phleum pratense (Timothy grass) allergens (Phl p). PBMCs from allergic individuals were tested in ELISPOT assays with overlapping peptides spanning known Phl p allergens. A total of 43 distinct antigenic regions were recognized, illustrating the large breadth of grass-specific T cell epitopes. Th2 cytokines (as represented by IL-5) were predominant, whereas IFN-γ, IL-10, and IL-17 were detected less frequently. Responses from specific immunotherapy treatment individuals were weaker and less consistent, yet similar in epitope specificity and cytokine pattern to allergic donors, whereas nonallergic individuals were essentially nonreactive. Despite the large breadth of recognition, nine dominant antigenic regions were defined, each recognized by multiple donors, accounting for 51% of the total response. Multiple HLA molecules and loci restricted the dominant regions, and the immunodominant epitopes could be predicted using bioinformatic algorithms specific for 23 common HLA-DR, DP, and DQ molecules. Immunodominance was
Immunoinformatics Based Study of T Cell Epitopes in Zea m 1 Pollen Allergen
Medicina, 2019
Background and Objectives: Zea m 1 is a pollen allergen, which is present in maize, is accountable for a type I hypersensitivity reaction in all over the world. Several effective medications are available for the disorder with various side effects. Design and verification of a peptide-based vaccine is a state-of-art technology which is more cost effective than conventional drugs. Materials and Methods: Using immunoinformatic methods, the T cell epitopes from the whole structure of this allergenic protein can be predicted. Worldwide conserved region study among the other pollen allergens has been performed for T cell predicted epitopes by using a conservancy tool. This analysis will help to identify completely conserved HLA (human leukocyte antigen) binding epitopes. Lastly, molecular docking study and MHC-oligopeptide complex binding energy calculation data are applied to determine the interacting amino acids and the affinity of the epitopes to the class II MHCmolecule. Results: The...
Structure of allergens and structure based epitope predictions
Methods, 2014
The structure determination of major allergens is a prerequisite for analyzing surface exposed areas of the allergen and for mapping conformational epitopes. These may be determined by experimental methods including crystallographic and NMR-based approaches or predicted by computational methods. In this review we summarize the existing structural information on allergens and their classification in protein fold families. The currently available allergen-antibody complexes are described and the experimentally obtained epitopes compared. Furthermore we discuss established methods for linear and conformational epitope mapping, putting special emphasis on a recently developed approach, which uses the structural similarity of proteins in combination with the experimental cross-reactivity data for epitope prediction.
Enlarging the Toolbox for Allergen Epitope Definition with an Allergen-Type Model Protein
PLoS ONE, 2014
Background: Birch pollen-allergic subjects produce polyclonal cross-reactive IgE antibodies that mediate pollen-associated food allergies. The major allergen Bet v 1 and its homologs in plant foods bind IgE in their native protein conformation. Information on location, number and clinical relevance of IgE epitopes is limited. We addressed the use of an allergenrelated protein model to identify amino acids critical for IgE binding of PR-10 allergens.
The identification of potentially pathogenic and therapeutic epitopes from common human allergens
2013
Objectives: To outline the processes involved in large-scale T-cell epitope identification from common allergens and illustrate their relevance to development of allergy specific immunotherapy. Data Sources: A set of studies recently published by our laboratory illustrating high-throughput identification of allergen specific T-cell epitopes. Study Selection: T-cell responses contribute both directly and indirectly to allergy-related disease. However, the molecular targets (epitopes) recognized by allergen-specific T cells are largely undefined. We review several different studies in the last 2 years that identified novel T-cell epitopes from a panel of 32 different allergen sources. Results: Allergen-specific T-cell responses are highly heterogeneous. Epitopes prevalently recognized in allergic patients are often capable of binding to multiple HLA class II molecules. This feature can be used to predict these promiscuous epitopes by bioinformatic predictions. This approach was validated in the Timothy grass system and then applied to a panel of 31 other allergen sources. Conclusion: T-cell epitopes for common allergens have been identified, and a general method to identify epitopes from additional allergens has been validated. Characterization of epitopes for common allergens might enable new diagnostics and immunotherapy regimens. These data will also allow the study of T-cell responses in different patient populations and throughout disease progression.
Objectives: The identification of B-cell epitopes is a challenging approach to explore the antigen-antibody interactions for diagnosis and therapy of hypersensitivity reaction. In our present study, an in-silico approach is used to investigate the interaction of pollen allergen EXPB1 (Zea m 1), pollen allergen from maize with IgE molecules of human. Material and Methods: Paratope of human immunoglobulin E is identified using site-specific proABC predictor method. Phylogenetic analysis of Zea m 1 reveals that 13 pollen allergens from different grasses, maize, timothy grass, velvet grass, Bermuda grass, canary grass, rice and perennial rye grass are close homologs to our query allergen EXPB1. Among them Phl p 1 pollen allergen from Phleum pratense is identified with 60% identity with Zea m 1. Experimental B cell epitopes of Phl p 1 are known and we have verified those epitopes with PIPER, molecular docking software. Thus, interacting amino acids present both in epitopes and paratopes are visualized and confirmed with predicted paratopes. For all homologous allergens, the interacting amino acids i.e. epitopes and paratopes have been identified using the two docking programs, DOT and ZDOCK. Results and Conclusions: Negative binding energies of all pollen allergens with immunoglobulin E confirm their allergenicity. Thus, all allergens become cross reactive with maize allergen. The multiple sequence alignment for all homologous sequences reveals that the positions of antigenic peptide of Zea m 1 sequence are well conserved in its homologs and responsible for cross-reactivity. This cross-reactivity identification will help us to identify the immunotheraputics e.g. vaccine designing for these β expansin family protein allergens during pollinosis. Kumar et al., 2015[6]in their in-silico work, have mapped sequential and conformational B-cell epitopes from the crystal structure of LipL32, the most abundant surfaceassociated protein of Leptospira and identified the order of antigenicity of four B cell epitopes. Radauer et al. [7]
Journal of immunology (Baltimore, Md. : 1950), 2012
A panel of 133 allergens derived from 28 different sources, including fungi, trees, grasses, weeds, and indoor allergens, was surveyed utilizing prediction of HLA class II-binding peptides and ELISPOT assays with PBMC from allergic donors, resulting in the identification of 257 T cell epitopes. More than 90% of the epitopes were novel, and for 14 allergen sources were the first ever identified to our knowledge. The epitopes identified in the different allergen sources summed up to a variable fraction of the total extract response. In cases of allergens in which the identified T cell epitopes accounted for a minor fraction of the extract response, fewer known protein sequences were available, suggesting that for low epitope coverage allergen sources, additional allergen proteins remain to be identified. IL-5 and IFN-γ responses were measured as prototype Th2 and Th1 responses, respectively. Whereas in some cases (e.g., orchard grass, Alternaria, cypress, and Russian thistle) IL-5 pro...
Characteristic motifs for families of allergenic proteins
Molecular Immunology, 2009
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 Motif-Mate (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.