Epitope-based Vaccine Design Against Common Tree Allergens Using Computational Approaches
-
Mina Noroozbeygi
,
Mina Mohammad-rezaei
,
Mohammad Hossein Shams
,
Armaghan Nikoosokhan
,
Viana Dayhimi
,
Mohammad-Ali Assarehzadegan
Abstract
Allergy-related diseases, driven by type I hypersensitivity reactions, affect over 20% to 25% of the global population and continue to rise. Pollen grains may have allergens that cause hypersensitivity reactions. Pla or 3, Fra e 1, and Bet v 1 are major allergens of pollen grains from the common allergenic trees Platanus orientalis, Fraxinus excelsior, and Betula pendula, respectively, and are employed in this study to design a multi-epitope allergy vaccine using immunoinformatics methods.
The steps after finding the main allergenic epitopes include sequences retrieval, T-cell epitopes selection by IEDB and NetMHCIIpan, B-cell epitopes selection by IEDB, addition of linkers and adjuvant, and construction of multi-epitope vaccine, evaluating antigenicity, allergenicity, and toxicity of vaccine construct, secondary structure prediction, 3-dimensional structure modeling and refinement by GalaxyTBM, validation of the model by ProSA-web, ERRAT, and PROCHECK, and exploring the interaction of the designed molecule with receptor by ClusPro.
The designed vaccine demonstrated favorable properties, including high antigenicity, lack of allergenicity and toxicity, and stable secondary and tertiary structures.
These results suggest that this vaccine has the potential to mitigate allergic responses effectively. However, experimental validation is required to confirm its efficacy and safety.
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31. Karplus PA, Schulz GE. Prediction of chain flexibility in proteins. Naturwissenschaften. 1985;72(4):212-3.
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34. Kolaskar AS, Tongaonkar PC. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett. 1990;276(1-2):172-4.
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42. Ko J, Park H, Heo L, Seok C. GalaxyWEB server for protein structure prediction and refinement. Nucleic Acids Res. 2012;40(W1):W294-W297.
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47. Saha S, Raghava GPS. AlgPred: prediction of allergenic proteins and mapping of IgE epitopes. Nucleic Acids Res. 2006;34(Web Server issue):W202-W209.
48. Gupta S, Kapoor P, Chaudhary K, Gautam A, Kumar R, Raghava GPS. In silico approach for predicting toxicity of peptides and proteins. PLoS One. 2013;8(9):e73957.
49. Desta IT, Porter KA, Xia B, Kozakov D, Vajda S. Performance and its limits in rigid body protein-protein docking. Structure. 2020;28(9):1071-1081.e3.
50. Vajda S, Yueh C, Beglov D, Bohnuud T, Mottarella SE, Xia B, et al. New additions to the ClusPro server motivated by CAPRI. Proteins. 2017;85(3):435-44.
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52. Kozakov D, Beglov D, Bohnuud T, Mottarella SE, Xia B, Hall DR, et al. How good is automated protein docking? Proteins. 2013;81(12):2159-66.
53. Lee TH. Allergy: the unmet need. Clin Med (Lond). 2003;3(4):303-305.
54. Jutel M, Kosowska A, Smolinska S. Allergen immunotherapy: past, present, and future. Allergy Asthma Immunol Res. 2016;8(3):191-7.
55. Bousquet J, Lockey R, Malling HJ. Allergen immunotherapy: therapeutic vaccines for allergic diseases. A WHO position paper. J Allergy Clin Immunol. 1998;102(4 Pt 1):558-62.
56. Canonica GW, Cox L, Pawankar R, Baena-Cagnani CE, Blaiss M, Bonini S, et al. Sublingual immunotherapy: World Allergy Organization position paper 2013 update. World Allergy Organ J. 2014;7(1):6.
57. Cox L, Nelson H, Lockey R, Calabria C, Chacko T, Finegold I, et al. Allergen immunotherapy: a practice parameter third update. J Allergy Clin Immunol. 2011;127(1 Suppl):S1-S55.
58. Fathollahi M, Kazemi T, Amani J, Asadi A, Nazarian S, Rezaei N, et al. In silico vaccine design and epitope mapping of New Delhi metallo-beta-lactamase (NDM): an immunoinformatics approach. BMC Bioinformatics. 2021;22(1):458.
59. Shamji MH, Kappen JH, Akdis M, Jensen-Jarolim E, Knol EF, Kleine-Tebbe J, et al. The role of allergen-specific IgE, IgG and IgA in allergic disease. Allergy. 2021;76(12):3627-3641.
60. Naeimi R, Bahmani A, Afshar S. Investigating the role of peptides in effective therapies against cancer. Cancer Cell Int. 2022;22(1):139.
61. Luchner M, Reinke S, Milicic A. TLR agonists as vaccine adjuvants targeting cancer and infectious diseases. Pharmaceutics. 2021;13(2):142.
62. Duan T, Du Y, Xing C, Wang HY, Wang RF. Toll-like receptor signaling and its role in cell-mediated immunity. Front Immunol. 2022;13:812774.
63. Tamaș TP, Ciurariu E. Allergen immunotherapy: pitfalls, perks and unexpected allies. Int J Mol Sci. 2025;26(8):3535.
64. Chen X, Zaro JL, Shen WC. Fusion protein linkers: property, design and functionality. Adv Drug Deliv Rev. 2013;65(10):1357-69.
65. Livingston B, Crimi C, Newman M, Higashimoto Y, Appella E, Sidney J, et al. A rational strategy to design multiepitope immunogens based on multiple Th lymphocyte epitopes. J Immunol. 2002;168(11):5499-5506.
66. Aurora R, Srinivasan R, Rose GD. Local interactions in protein folding: lessons from the alpha-helix. J Biol Chem. 1997;272(3):1413-16.
67. Mosaheb MM, Reiser ML, Wetzler LM. Toll-like receptor ligand-based vaccine adjuvants require intact MyD88 signaling in antigen-presenting cells for germinal center formation and antibody production. Front Immunol. 2017;8:225.
68. Kawai T, Akira S. The role of pattern-recognition receptors in innate immunity: update on Toll-like receptors. Nat Immunol. 2010;11(5):373-84.
69. Vaure C, Liu Y. A comparative review of toll-like receptor 4 expression and functionality in different animal species. Front Immunol. 2014;5:316.
70. Ciesielska A, Matyjek M, Kwiatkowska K. TLR4 and CD14 trafficking and its influence on LPS-induced pro-inflammatory signaling. Cell Mol Life Sci. 2021;78:1233-1261.
71. Lu YC, Yeh WC, Ohashi PS. LPS/TLR4 signal transduction pathway. Cytokine. 2008;42(2):145-51.
72. Carter D, Reed SG, Fox CB, Baldwin SL, Vedvick TS, Coler RN, et al. The success of toll-like receptor 4 based vaccine adjuvants. Vaccine. 2025;61:127413.
73. Baldwin SL, Bertholet S, Kahn M, Zharkikh I, Ireton GC, Vedvick TS, et al. Enhanced humoral and type 1 cellular immune responses with Fluzone adjuvanted with a synthetic TLR4 agonist formulated in an emulsion. Vaccine. 2009;27:5956-63.
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2. Dbouk T, Drikakis D. Risk assessment of pollen allergy in urban environments. Sci Rep. 2022;12(1):21076.
3. Zhang Y, Lan F, Zhang L. Advances and highlights in allergic rhinitis. Allergy. 2021;76(11):3383-3389.
4. Asam C, Hofer H, Wolf M, Aglas L, Wallner M, Ferreira F, et al. Tree pollen allergens—an update from a molecular perspective. Allergy. 2015;70(10):1201-11.
5. Mansouritorghabeh H, Jabbari Azad F, Sankian M, Varasteh A, Farid Hosseini R, Shakeri MT, et al. The most common allergenic tree pollen grains in the Middle East: a narrative review. Iran J Med Sci. 2019;44(2):87-98.
6. Barderas R, Villalba M, Pascual CY, Batanero E, Rodríguez R. Cloning, expression, and clinical significance of the major allergen from ash pollen, Fra e 1. J Allergy Clin Immunol. 2005;115(2):351-7.
7. Sedghy F, Varasteh A, Sankian M, Moghadam M, Moghadam A. Quantification of Pla or 3, a Platanus orientalis allergen, grown under different environmental conditions, by sandwich ELISA. Rep Biochem Mol Biol. 2016;5(1):40-5.
8. Pazouki N, Sankian M, Nejadsattari T, Khavari-Nejad RA, Varasteh A. Oriental plane pollen allergy: identification of allergens and cross-reactivity between relevant species. Allergy Asthma Proc. 2008;29(6):622-8.
9. Biedermann T, Winther L, Till SJ, Panzner P, Knulst A, Valovirta E, et al. Birch pollen allergy in Europe. Allergy. 2019;74(7):1237-48.
10. Ipsen H, Løwenstein H. Isolation and immunochemical characterization of the major allergen of birch pollen (Betula verrucosa). J Allergy Clin Immunol. 1983;72(2):150-159.
11. Mujtaba M, Akyuz L, Koc B, Kaya M, Ilk S, Cakmak YS, et al. Newly isolated sporopollenin microcages from Platanus orientalis pollens as a vehicle for controlled drug delivery. Mater Sci Eng C Mater Biol Appl. 2017;77:263-270.
12. Diethart B, Halbritter H. Fraxinus excelsior. In: PalDat – A Palynological Database. Vienna: PalDat; 2020.
13. Halbritter H, Diethart B, Heigl H. Betula pendula. In: PalDat – A Palynological Database. Vienna: PalDat; 2020.
14. Jarvis C. Linnaean Plant Names and Their Types (Part P). In: Order Out of Chaos: Linnaean Plant Names and Their Types. London: Linnean Society of London; 2007.
15. Parr CS, Wilson N, Leary P, Schulz K, Lans K, Walley L, et al. The Encyclopedia of Life v2: providing global access to knowledge about life on Earth. Biodivers Data J. 2014;(2):e1079.
16. Plants of the World Online (POWO). Kew: Royal Botanic Gardens, Kew; 2024.
17. GBIF Secretariat. Betula pendula Roth. GBIF Backbone Taxonomy. 2023.
18. GBIF Secretariat. Platanus orientalis L. GBIF Backbone Taxonomy. 2023.
19. GBIF Secretariat. Fraxinus excelsior L. GBIF Backbone Taxonomy. 2023.
20. Molinari G, Colombo G, Celenza C. Respiratory allergies: a general overview of remedies, delivery systems, and the need to progress. ISRN Allergy. 2014;2014:326980.
21. Novakova P, Tiotiu A, Baiardini I, Krčmová I, Kowal K, Mokros M, et al. Allergen immunotherapy in asthma: current evidence. J Asthma. 2021;58(2):223-30.
22. Raith M, Nair A, Johnson M, Schmetterer K, Valenta R, Campana R, et al. Rational design of a hypoallergenic Phl p 7 variant for immunotherapy of polcalcin-sensitized patients. Sci Rep. 2019;9(1):7802.
23. Dorofeeva Y, Shilovskiy I, Tulaeva I, Focke-Tejkl M, Flicker S, Kudlay D, et al. Past, present, and future of allergen immunotherapy vaccines. Allergy. 2021;76(1):131-49.
24. Skwarczynski M, Toth I. Peptide-based synthetic vaccines. Chem Sci. 2016;7(2):842-54.
25. Schneble E, Clifton GT, Hale DF, Peoples GE. Peptide-Based Cancer Vaccine Strategies and Clinical Results. Methods Mol Biol. 2016;1403:797-817.
26. Larché M. T cell epitope-based allergy vaccines. Curr Top Microbiol Immunol. 2011;352:107-19.
27. Valenta R, Campana R, Niederberger V. Recombinant allergy vaccines based on allergen-derived B cell epitopes. Immunol Lett. 2017;189:19-26.
28. Parvizpour S, Pourseif MM, Razmara J, Rafi MA, Omidi Y. Epitope-based vaccine design: a comprehensive overview of bioinformatics approaches. Drug Discov Today. 2020;25(6):1034-42.
29. Kardani K, Bolhassani A, Namvar A. An overview of in silico vaccine design against different pathogens and cancer. Expert Rev Vaccines. 2020;19(8):699-726.
30. Jespersen MC, Peters B, Nielsen M, Marcatili P. BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes. Nucleic Acids Res. 2017;45(W1):W24-W29.
31. Karplus PA, Schulz GE. Prediction of chain flexibility in proteins. Naturwissenschaften. 1985;72(4):212-3.
32. Parker JM, Guo D, Hodges RS. New hydrophilicity scale derived from high-performance liquid chromatography peptide retention data: correlation of predicted surface residues with antigenicity and X-ray-derived accessible sites. Biochemistry. 1986;25(19):5425-32.
33. Emini EA, Hughes JV, Perlow DS, Boger J. Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptide. J Virol. 1985;55(3):836-9.
34. Kolaskar AS, Tongaonkar PC. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett. 1990;276(1-2):172-4.
35. Chou PY, Fasman GD. Prediction of the secondary structure of proteins from their amino acid sequence. In: Meister A, editor. Advances in enzymology and related areas of molecular biology. Vol. 47. John Wiley & Sons; 1979. p. 45–148.
36. Wang P, Sidney J, Kim Y, Sette A, Lund O, Nielsen M, et al. Peptide binding predictions for HLA-DR, DP and DQ molecules. BMC Bioinformatics. 2010;11:568.
37. Wang P, Sidney J, Dow C, Mothé B, Sette A, Peters B. A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLoS Comput Biol. 2008;4(4):e1000048.
38. Nielsen M, Lundegaard C, Lund O. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method. BMC Bioinformatics. 2007;8:238.
39. Jensen KK, Andreatta M, Marcatili P, Buus S, Greenbaum JA, Yan Z, et al. Improved methods for predicting peptide binding affinity to MHC class II molecules. Immunology. 2018;154(3):394-406.
40. Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins MR, Appel RD, et al. Protein Identification and Analysis Tools on the ExPASy Server. In: Walker JM, editor. The Proteomics Protocols Handbook. Totowa (NJ): Humana Press; 2005. p. 571-607.
41. McGuffin LJ, Bryson K, Jones DT. The PSIPRED protein structure prediction server. Bioinformatics. 2000;16(4):404-5.
42. Ko J, Park H, Heo L, Seok C. GalaxyWEB server for protein structure prediction and refinement. Nucleic Acids Res. 2012;40(W1):W294-W297.
43. Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 2007;35(Web Server issue):W407-W410.
44. Colovos C, Yeates TO. Verification of protein structures: patterns of nonbonded atomic interactions. Protein Sci. 1993;2(9):1511-9.
45. Laskowski RA, MacArthur MW, Moss DS, Thornton JM. PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Crystallogr. 1993;26(2):283-91.
46. Laskowski RA, Rullmannn JA, MacArthur MW, Kaptein R, Thornton JM. AQUA and PROCHECK-NMR: programs for checking the quality of protein structures solved by NMR. J Biomol NMR. 1996;8(4):477-86.
47. Saha S, Raghava GPS. AlgPred: prediction of allergenic proteins and mapping of IgE epitopes. Nucleic Acids Res. 2006;34(Web Server issue):W202-W209.
48. Gupta S, Kapoor P, Chaudhary K, Gautam A, Kumar R, Raghava GPS. In silico approach for predicting toxicity of peptides and proteins. PLoS One. 2013;8(9):e73957.
49. Desta IT, Porter KA, Xia B, Kozakov D, Vajda S. Performance and its limits in rigid body protein-protein docking. Structure. 2020;28(9):1071-1081.e3.
50. Vajda S, Yueh C, Beglov D, Bohnuud T, Mottarella SE, Xia B, et al. New additions to the ClusPro server motivated by CAPRI. Proteins. 2017;85(3):435-44.
51. Kozakov D, Hall DR, Xia B, Porter KA, Padhorny D, Yueh C, et al. The ClusPro web server for protein-protein docking. Nat Protoc. 2017;12(2):255-278.
52. Kozakov D, Beglov D, Bohnuud T, Mottarella SE, Xia B, Hall DR, et al. How good is automated protein docking? Proteins. 2013;81(12):2159-66.
53. Lee TH. Allergy: the unmet need. Clin Med (Lond). 2003;3(4):303-305.
54. Jutel M, Kosowska A, Smolinska S. Allergen immunotherapy: past, present, and future. Allergy Asthma Immunol Res. 2016;8(3):191-7.
55. Bousquet J, Lockey R, Malling HJ. Allergen immunotherapy: therapeutic vaccines for allergic diseases. A WHO position paper. J Allergy Clin Immunol. 1998;102(4 Pt 1):558-62.
56. Canonica GW, Cox L, Pawankar R, Baena-Cagnani CE, Blaiss M, Bonini S, et al. Sublingual immunotherapy: World Allergy Organization position paper 2013 update. World Allergy Organ J. 2014;7(1):6.
57. Cox L, Nelson H, Lockey R, Calabria C, Chacko T, Finegold I, et al. Allergen immunotherapy: a practice parameter third update. J Allergy Clin Immunol. 2011;127(1 Suppl):S1-S55.
58. Fathollahi M, Kazemi T, Amani J, Asadi A, Nazarian S, Rezaei N, et al. In silico vaccine design and epitope mapping of New Delhi metallo-beta-lactamase (NDM): an immunoinformatics approach. BMC Bioinformatics. 2021;22(1):458.
59. Shamji MH, Kappen JH, Akdis M, Jensen-Jarolim E, Knol EF, Kleine-Tebbe J, et al. The role of allergen-specific IgE, IgG and IgA in allergic disease. Allergy. 2021;76(12):3627-3641.
60. Naeimi R, Bahmani A, Afshar S. Investigating the role of peptides in effective therapies against cancer. Cancer Cell Int. 2022;22(1):139.
61. Luchner M, Reinke S, Milicic A. TLR agonists as vaccine adjuvants targeting cancer and infectious diseases. Pharmaceutics. 2021;13(2):142.
62. Duan T, Du Y, Xing C, Wang HY, Wang RF. Toll-like receptor signaling and its role in cell-mediated immunity. Front Immunol. 2022;13:812774.
63. Tamaș TP, Ciurariu E. Allergen immunotherapy: pitfalls, perks and unexpected allies. Int J Mol Sci. 2025;26(8):3535.
64. Chen X, Zaro JL, Shen WC. Fusion protein linkers: property, design and functionality. Adv Drug Deliv Rev. 2013;65(10):1357-69.
65. Livingston B, Crimi C, Newman M, Higashimoto Y, Appella E, Sidney J, et al. A rational strategy to design multiepitope immunogens based on multiple Th lymphocyte epitopes. J Immunol. 2002;168(11):5499-5506.
66. Aurora R, Srinivasan R, Rose GD. Local interactions in protein folding: lessons from the alpha-helix. J Biol Chem. 1997;272(3):1413-16.
67. Mosaheb MM, Reiser ML, Wetzler LM. Toll-like receptor ligand-based vaccine adjuvants require intact MyD88 signaling in antigen-presenting cells for germinal center formation and antibody production. Front Immunol. 2017;8:225.
68. Kawai T, Akira S. The role of pattern-recognition receptors in innate immunity: update on Toll-like receptors. Nat Immunol. 2010;11(5):373-84.
69. Vaure C, Liu Y. A comparative review of toll-like receptor 4 expression and functionality in different animal species. Front Immunol. 2014;5:316.
70. Ciesielska A, Matyjek M, Kwiatkowska K. TLR4 and CD14 trafficking and its influence on LPS-induced pro-inflammatory signaling. Cell Mol Life Sci. 2021;78:1233-1261.
71. Lu YC, Yeh WC, Ohashi PS. LPS/TLR4 signal transduction pathway. Cytokine. 2008;42(2):145-51.
72. Carter D, Reed SG, Fox CB, Baldwin SL, Vedvick TS, Coler RN, et al. The success of toll-like receptor 4 based vaccine adjuvants. Vaccine. 2025;61:127413.
73. Baldwin SL, Bertholet S, Kahn M, Zharkikh I, Ireton GC, Vedvick TS, et al. Enhanced humoral and type 1 cellular immune responses with Fluzone adjuvanted with a synthetic TLR4 agonist formulated in an emulsion. Vaccine. 2009;27:5956-63.
74. Sharma E, Vitte J. A systematic review of allergen cross-reactivity: translating basic concepts into clinical relevance. J Allergy Clin Immunol Glob. 2024;3(2):100230.
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How to Cite
1.
Noroozbeygi M, Mohammad-rezaei M, Shams MH, Nikoosokhan A, Dayhimi V, Assarehzadegan M-A. Epitope-based Vaccine Design Against Common Tree Allergens Using Computational Approaches. Iran J Allergy Asthma Immunol. 2026;:1-22.
