Peptit Temelli Aşı Üretim Stratejileri
Yıl: 2022 Cilt: 27 Sayı: 2 Sayfa Aralığı: 189 - 195 Metin Dili: Türkçe DOI: 10.5578/flora.20229801 İndeks Tarihi: 10-08-2022
Peptit Temelli Aşı Üretim Stratejileri
Öz: Sentetik peptitler proteinlerin bağlama kapasiteleri, proteolitik aktiviteleri, immünojeniteleri gibi özelliklerinin kolaylıkla çalışılabildiği sistemlerdir. Patojenlere ait nükleotid/aminoasit sekans verisini temel alarak belirlenen B ve T hücre epitopları ile hem hücresel hem de humoral immüniteyi uyararak spesifik koruyucu bağışıklık yanıtı oluşturabilen aşı adaylarının geliştirilmesine olanak sağlarlar. Güvenli, biyouyumlu ve fiyat efektif olmalarına rağmen immünojenite kapasiteleri düşüktür ve enzimatik bozulmaya karşı hassaslardır. Multiepitop yaklaşımı ve uygun bir adjuvan/taşıyıcı sistem ile sentetik peptitlerin immünojenite kapasiteleri artırılarak etkili ve kararlı aşılar geliştirilebilir.
Anahtar Kelime: Peptide Based Vaccine Strategies
Öz: Synthetic peptides are easy tool to investigate binding capacities, proteolytic activities and immunogenicity properties of proteins. They enable the development of vaccine candidates that can create a specific protective immune response by stimulating both cellular and humoral immunity with the B and T cell epitopes determined based on the nucleotide/amino acid sequence data of the pathogens. Although they are safe, biocompatible, and cost-effective, they have low immunogenicity capacities and are susceptible to enzymatic degradation. Effective and stable vaccines can be developed by increasing the immunogenicity capacities of synthetic peptides with a multiepitope approach and an appropriate adjuvant/carrier system.
Anahtar Kelime: Belge Türü: Makale Makale Türü: Derleme Erişim Türü: Erişime Açık
- 1. Cable J, Srikantiah P, Crowe JE, Pulendran B, Hill A, Ginsberg A, et al. Vaccine innovations for emerging infectious diseases- A symposium report. Ann N Y Acad Sci 2020;1462:14- 26. https://doi.org/10.1111/nyas.14235
- 2. Vetter V, Denizer G, Friedland LR, Krishnan J, Shapiro M, Understanding modern-day vaccines: What you need to know, Ann Med 2018;50:110-20. https://doi.org/10.108 0/07853890.2017.1407035
- 3. O’Neill CL, Shrimali PC, Clapacs ZP, Files MA, Rudra JS. Peptide-based supramolecular vaccine systems. Acta Biomater 2021;133:153-67. https://doi.org/10.1016/j.actbio. 2021.05.003
- 4. Global Vaccine Action Plan 2011-2020; World Health Organization, Available from: https://www.who.int/immunization/ global_vaccine_action_plan/GVAP_doc_2011_2020/ en/; (Accessed date: 14/01/22).
- 5. Tang D, Kang R, Coyne CB, Zeh HJ, Lotze MT. PAMPs and DAMPs: Signal 0s that spur autophagy and immunity. Immunol Rev 2012;249(1):158-75. https://doi.org/ 10.1111/j.1600-065X.2012.01146.x
- 6. Slifka MK, Amanna I. How advances in immunology provide insight into improving vaccine efficacy. Vaccine 2014;23;32(25):2948-57. https://doi.org/10.1016/j.vaccine. 2014.03.078
- 7. Rappuoli R, Aderem AA. vision for vaccines against HIV, tuberculosis and malaria. Nature 2020;2011:463-69. https:// doi.org/10.1038/nature10124
- 8. Paladino A, Marchetti F, Rinaldi S, Colombo G. Protein design: From computer models to artificial intelligence. Wiley Interdiscip Rev: Comput Mol Sci 2017;7:e1318. https://doi. org/10.1002/wcms.1318
- 9. Moisa AA, Kolesanova EF. Synthetic peptide vaccines. Biochemistry (Moscow) Supplement Series B: Biomedical Chemistry 2010;4(4):321-32. https://doi.org/10.1134/ S1990750810040025
- 10. Soria-Guerra RE, Nieto-Gomez R, Govea-Alonso DO, Rosales Mendoza S. An overview of bioinformatics tools for epitope prediction: implications on vaccine development. J Biomed Inform 2015;53:405-14. https://doi.org/10.1016/j. jbi.2014.11.003
- 11. Sherman AC, Mehta A, Dickert NW, Anderson EJ, Rouphael N. The future of flu: A review of the human challenge model and systems biology for advancement of influenza vaccinology. Front Cell Infect Microbiol 2019;9:107. https://doi. org/10.3389/fcimb.2019.00107
- 12. Pyclik M, Gorska S, Brzozowska E, Dobrut A, Ciekot J, Gamian A, Brzychczy-Włoch M. Epitope mapping of streptococcus agalactiae elongation factor tu protein recognized by human sera. Front Microbiol 2018;9:125. https://doi. org/10.3389/fmicb.2018.00125
- 13. Araújo CL, Alves J, Nogueira W, Pereira LC, Gomide AC, Ramos R, et al. Prediction of new vaccine targets in the core genome of Corynebacterium pseudotuberculosis through omics approaches and reverse vaccinology. Gene 2019;702:36-45. https://doi.org/10.1016/j. gene.2019.03.049
- 14. Davies MN, Flower DR. Harnessing bioinformatics to discover new vaccines. Drug Discov Today 2007;12:389-95. https://doi.org/10.1016/j.drudis.2007.03.010
- 15. Odorico M, Pellequer JL. BEPITOPE: Predicting the location of continuous epitopes and patterns in proteins. J Mol Recognit 2003;16:20-2. https://doi.org/10.1002/jmr.602
- 16. Alix AJ. Predictive estimation of protein linear epitopes by using the program PEOPLE. Vaccine 1999;18:311-4. https:// doi.org/10.1016/S0264-410X(99)00329-1
- 17. Saha S, Raghava GP. Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Proteins 2006;65:40-8. https://doi.org/10.1002/prot.21078
- 18. Malonis RJ, Lai JR, Vergnolle O. Peptide-based vaccines: Current progress and future challenges. Chem Rev 2020;120(6):3210-29. https://doi.org/10.1021/acs. chemrev.9b00472
- 19. Schenck RO, Lakatos E, Gatenbee C, Graham TA, Anderson ARA. NeoPredPipe: high-throughput neoantigen prediction and recognition potential pipeline. BMC Bioinformatics 2019;20:264.
- 20. Bjerregaard AM, Nielsen M, Hadrup SR, Szallasi Z, Eklund AC. MuPeXI: Prediction of neo-epitopes from tumor sequencing data. Cancer Immunol Immunother 2017;66:1123- 30. https://doi.org/10.1007/s00262-017-2001-3
- 21. Bais P, Namburi S, Gatti DM, Zhang X, Chuang J. H. Cloud- Neo: A cloud pipeline for identifying patient-specific tumor neoantigens. Bioinformatics 2017;33:3110-2. https://doi. org/10.1093/bioinformatics/btx375
- 22. Bijker MS, van den Eeden SJF, Franken KL, Melief CJM, Offringa R, van der Burg SH. CD8+ CTL priming by exact peptide epitopes in incomplete Freund’s adjuvant induces a vanishing CTL response, whereas long peptides induce sustained CTL reactivity. Immunol 2007;179:5033-40.
- 23. Nelde A, Rammensee HG, Walz JS. The Peptide Vaccine of the Future. Mol Cell Proteomics 2021;20:100022. https:// doi.org/10.1074/mcp.R120.002309
- 24. Azmi F, Fuaad AHA, Skwarczynski M, Toth I. Recent progress in adjuvant discovery for peptide-based subunit vaccines, Human Vaccines & Immunotherapeutics 2014;10:778-96. https://doi.org/10.4161/hv.27332
- 25. Di Natale C, La Manna S, De Benedictis I, Brandi P, Marasco D. Perspectives in peptide-based vaccination strategies for syndrome coronavirus 2 pandemic. Front Pharmacol 2020;11:578382. https://doi.org/10.3389/ fphar.2020.578382
- 26. Raponi A, Brewer JM, Garside P, Laera D. Nanoalum adjuvanted vaccines: Small details make a big difference. Semin Immunol 2021;56:101544. https://doi.org/10.1016/j. smim.2021.101544
- 27. O’Hagan DT. MF59 is a safe and potent vaccine adjuvant that enhances protection against influenza virus infection. Expert Rev Vaccines 2007;6(5):699-710. https://doi. org/10.1586/14760584.6.5.699
- 28. Cohet C, van der Most R, Bauchau V, Bekkat-Berkani R, Doherty TM, Schuind A, et al. Safety of AS03-adjuvanted influenza vaccines: A review of the evidence. Vaccine 2019;37(23):3006-21. https://doi.org/10.1016/j.vaccine. 2019.04.048
- 29. Colavecchia SB, Jolly A, Fernández B, Fontanals AM, Fernández E, Mundo SL. Effect of lipoarabinomannan from Mycobacterium avium subsp avium in Freund’s incomplete adjuvant on the immune response of cattle. Braz J Med Biol Res 2012;45(2):139-46. https://doi.org/10.1590/S0100- 879X2012007500012
- 30. Sun HX, Xie Y, Ye YP. ISCOMs and ISCOMATRIX. Vaccine 2009;27(33):4388-401. https://doi.org/10.1016/j.vaccine. 2009.05.032
- 31. de Groot C, Müller-Goymann CC. saponin ınteractions with model membrane systems - langmuir monolayer studies, hemolysis and formation of ISCOMs. Planta Med 2016;82(18):1496-512. https://doi.org/ 10.1055/s-0042-118387
- 32. Curtidor H, Reyes C, Bermúdez A, Vanegas M, Varela Y, Patarroyo ME. Conserved binding regions provide the clue for peptide-based vaccine development: A chemical perspective. Molecules 2017;22(12):2199. https://doi. org/10.3390/molecules22122199
- 33. Holenya P, Lange PJ, Reimer U, Woltersdorf W, Panterodt T, Glas M, et al. Peptide microarray-based analysis of antibody responses to SARS-CoV-2 identifies unique epitopes with potential for diagnostic test development. Eur J Immunol 2021;51(7):1839-49. https://doi.org/10.1002/ eji.202049101
- 34. Zhang BZ, Hu YF, Chen LL, Yau T, Tong YG, Hu JC, et al. Mining of epitopes on spike protein of SARS-CoV-2 from COVID-19 patients. Cell Res 2020;(8):702-4. https://doi. org/10.1038/s41422-020-0366-x
- 35. Bijker MS, van den Eeden SJ, Franken KL, Melief CJ, Offringa R, van der Burg SH. CD8+ CTL priming by exact peptide epitopes in incomplete Freund’s adjuvant induces a vanishing CTL response, whereas long peptides induce sustained CTL reactivity. J Immunol 2007;179:5033-40.
- 36. Ghaffari-Nazari H, Tavakkol-Afshari J, Jaafari MR, Tahaghoghi Hajghorbani S, Masoumi E, Jalali SA. Improving multi-epitope long peptide vaccine potency by using a strategy that enhances CD4+ T help in BALB/c Mice. PLoS One 2015;10:e0142563. https://doi.org/10.1371/journal. pone.0142563
- 37. Pishraft Sabet L, Taheri T, Memarnejadian A, Azad TM, Asgari F, Rahimnia R, et al. Immunogenicity of multi-epitope DNA and peptide vaccine candidates based on core, E2, NS3 and NS5B HCV Epitopes in BALB/c Mice. Hepat Mon 2014;14:e22215. https://doi.org/10.5812/hepatmon. 22215
- 38. Bae J, Smith R, Daley J, Mimura N, Tai YT, Anderson KC, et al. Myeloma-specific multiple peptides able to generate cytotoxic T lymphocytes: A potential therapeutic application in multiple myeloma and other plasma cell disorders. Clin Cancer Res 2012;18(17):4850-60. https://doi. org/10.1158/1078-0432.CCR-11-2776
- 39. Suzuki H, Fukuhara M, Yamaura T, Mutoh S, Okabe N, Yaginuma H, et al. Multiple therapeutic peptide vaccines consisting of combined novel cancer testis antigens and anti-angiogenic peptides for patients with non-small cell lung cancer. J Transl Med 2013;11:97. https://doi. org/10.1186/1479-5876-11-97
| APA | AYDIN S, Varan G, Unal S (2022). Peptit Temelli Aşı Üretim Stratejileri. , 189 - 195. 10.5578/flora.20229801 |
| Chicago | AYDIN Semra,Varan Gamze,Unal Serhat Peptit Temelli Aşı Üretim Stratejileri. (2022): 189 - 195. 10.5578/flora.20229801 |
| MLA | AYDIN Semra,Varan Gamze,Unal Serhat Peptit Temelli Aşı Üretim Stratejileri. , 2022, ss.189 - 195. 10.5578/flora.20229801 |
| AMA | AYDIN S,Varan G,Unal S Peptit Temelli Aşı Üretim Stratejileri. . 2022; 189 - 195. 10.5578/flora.20229801 |
| Vancouver | AYDIN S,Varan G,Unal S Peptit Temelli Aşı Üretim Stratejileri. . 2022; 189 - 195. 10.5578/flora.20229801 |
| IEEE | AYDIN S,Varan G,Unal S "Peptit Temelli Aşı Üretim Stratejileri." , ss.189 - 195, 2022. 10.5578/flora.20229801 |
| ISNAD | AYDIN, Semra vd. "Peptit Temelli Aşı Üretim Stratejileri". (2022), 189-195. https://doi.org/10.5578/flora.20229801 |
| APA | AYDIN S, Varan G, Unal S (2022). Peptit Temelli Aşı Üretim Stratejileri. Flora İnfeksiyon Hastalıkları ve Klinik Mikrobiyoloji Dergisi, 27(2), 189 - 195. 10.5578/flora.20229801 |
| Chicago | AYDIN Semra,Varan Gamze,Unal Serhat Peptit Temelli Aşı Üretim Stratejileri. Flora İnfeksiyon Hastalıkları ve Klinik Mikrobiyoloji Dergisi 27, no.2 (2022): 189 - 195. 10.5578/flora.20229801 |
| MLA | AYDIN Semra,Varan Gamze,Unal Serhat Peptit Temelli Aşı Üretim Stratejileri. Flora İnfeksiyon Hastalıkları ve Klinik Mikrobiyoloji Dergisi, vol.27, no.2, 2022, ss.189 - 195. 10.5578/flora.20229801 |
| AMA | AYDIN S,Varan G,Unal S Peptit Temelli Aşı Üretim Stratejileri. Flora İnfeksiyon Hastalıkları ve Klinik Mikrobiyoloji Dergisi. 2022; 27(2): 189 - 195. 10.5578/flora.20229801 |
| Vancouver | AYDIN S,Varan G,Unal S Peptit Temelli Aşı Üretim Stratejileri. Flora İnfeksiyon Hastalıkları ve Klinik Mikrobiyoloji Dergisi. 2022; 27(2): 189 - 195. 10.5578/flora.20229801 |
| IEEE | AYDIN S,Varan G,Unal S "Peptit Temelli Aşı Üretim Stratejileri." Flora İnfeksiyon Hastalıkları ve Klinik Mikrobiyoloji Dergisi, 27, ss.189 - 195, 2022. 10.5578/flora.20229801 |
| ISNAD | AYDIN, Semra vd. "Peptit Temelli Aşı Üretim Stratejileri". Flora İnfeksiyon Hastalıkları ve Klinik Mikrobiyoloji Dergisi 27/2 (2022), 189-195. https://doi.org/10.5578/flora.20229801 |
