Design of a new structure of immunogenic chimeric polytope against human various cancers using immunoinformatics and structural methods
Abstract
Cancer is one of the deadliest diseases in recent decades. Which has different types. Despite advances in the treatment of cancer, they are still the most critical threat to public health. Although conventional therapies have played a major role in the treatment or eradication of the disease, the emergence of emerging diseases requires new therapies such as vaccine design. Significant challenges in cancer drug treatment such as drug resistance and side effects of drug toxicity and high cost have made the treatment process more difficult. The aim of this study was to design a new and effective strategy for preparing a vaccine against cancer using some antigenic proteins in this disease. After preparing appropriate epitopes of antigenic protein compounds in cancers and examining their antigenic and immunogenic properties, the process of fusion vaccine composition was performed with the help of various bioinformatics tools to study the physicochemical properties and two-dimensional and three-dimensional structures and Their validation as well as immunological and simulation properties were investigated and finally the codons of vaccine constructs were optimized to increase the translation rate of its cloning process in the expression vector pET28a (+) to evaluate the expression of protein in prokaryotic cells in E. coli K12 system. Finally, the docking process was performed with some receptors that are effective in immunological processes in the body, such as TLRs, MHCI, and MHCII. Selected epitopes of physiologically important cancer proteins theoretically cover a high percentage of the world's population. The vaccine was designed with a stable, antigenic, and non-sensitizing composition. Structural analysis of the TRL5/vaccine binding complex and its simulation process reveal sufficiently stable critical with the prospect of receptor recognition. The dynamics of the immune response, having the potential to stimulate and produce active and memory B cells, and the production of CD8+T, and CD4+T cells show a favorable role in stimulating and creating effective immune responses by Th2 and Th1 cells. Computational results using bioinformatics tools showed that our designed immunogenic structure has the potential to stimulate cellular and humoral immune responses against cancer properly. Therefore, based on these data and after evaluating the effectiveness of the candidate vaccine through in vivo and in vitro immunological tests, it can be suggested as a candidate vaccine against cancer.
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17. Dimitrov I, Naneva L, Doytchinova I, Bangov I. AllergenFP: allergenicity prediction by descriptor fingerprints. Bioinformatics. 2014 Mar 15;30(6):846-51.
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22. Ashokan KV, Pillai M. In silico characterization of silk fibroin protein using computational tools and servers. Asian J Exp Sci. 2008;22:265-74.
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24. Skwarczynski M, Toth I. Peptide-based synthetic vaccines. Chemical science. 2016;7(2):842-54.
25.Shirota H, Tross D, Klinman DM. CpG oligonucleotides as cancer vaccine adjuvants. Vaccines. 2015 Jun;3(2):390-407.
26. Zininga T, Ramatsui L, Shonhai A. Heat shock proteins as immunomodulants. Molecules. 2018 Nov;23(11):2846.
27. Nold-Petry CA, Nold MF, Levy O, Kliger Y, Oren A, Borukhov I, Becker C, Wirtz S, Sandhu MK, Neurath M, Dinarello CA. Gp96 peptide antagonist gp96-II confers therapeutic effects in murine intestinal inflammation. Frontiers in immunology. 2017 Dec 11;8:1531.
28. Argos P. An investigation of oligopeptides linking domains in protein tertiary structures and possible candidates for general gene fusion. Journal of molecular biology. 1990 Feb 20;211(4):943-58.
29.Gasteiger E, Hoogland C, Gattiker A, Wilkins MR, Appel RD, Bairoch A. Protein identification and analysis tools on the ExPASy server. The proteomics protocols handbook. 2005:571-607.
30. Pihlasalo S, Auranen L, Hanninen P, Härmä H. Method for estimation of protein isoelectric point. Analytical chemistry. 2012 Oct 2;84(19):8253-8.
31 Sen Gupta PS, Mandal B, Bandyopadhyay AK. In silico characterization of human cyclooxygenase using computational tools and servers. Int J Institutional Pharmacy Life Sci. 2013;3:111.
32. Ansari HR, Raghava GP. Identification of conformational B-cell Epitopes in an antigen from its primary sequence. Immunome research. 2010 Dec;6(1):1-9.
33. Zheng J, Lin X, Wang X, Zheng L, Lan S, Jin S, Ou Z, Wu J. In silico analysis of epitope-based vaccine candidates against hepatitis B virus polymerase protein. Viruses. 2017 May;9(5):112.
34. Zhao W, Sher X. Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes. PLoS computational biology. 2018 Nov 8;14(11):e1006457.
35. Ozturk OG. HLA alleles in breast cancer. Pathology & Oncology Research. 2012 Oct;18(4):1099-.
36. Baloria U, Akhoon BA, Gupta SK, Sharma S, Verma V. In silico proteomic characterization of human epidermal growth factor receptor 2 (HER-2) for the mapping of high affinity antigenic determinants against breast cancer. Amino acids. 2012 Apr;42(4):1349-60.
37. Ali M, Pandey RK, Khatoon N, Narula A, Mishra A, Prajapati VK. Exploring dengue genome to construct a multi-epitope based subunit vaccine by utilizing immunoinformatics approach to battle against dengue infection. Scientific reports. 2017 Aug 23;7(1):1-3.
38. Corporate Comms. "New data on MAGE-A3 cancer immunotherapy support potential novel options of treating non-small cell lung cancer and melanoma". Us.gsk.com. Archived from the original on 2012-06-27. Retrieved 2012-10-16.
39. Jungbluth AA, Chen YT, Stockert E, Busam KJ, Kolb D, Iversen K, Coplan K, Williamson B, Altorki N, Old LJ. Immunohistochemical analysis of NY‐ESO‐1 antigen expression in normal and malignant human tissues. International Journal of Cancer. 2001 Jun 15;92(6):856-60.
40.Theurillat JP, Ingold F, Frei C, Zippelius A, Varga Z, Seifert B, Chen YT, Jäger D, Knuth A, Moch H. NY‐ESO‐1 protein expression in primary breast carcinoma and metastases—correlation with CD8+ T‐cell and CD79a+ plasmacytic/B‐cell infiltration. International journal of cancer. 2007 Jun 1;120(11):2411-7.
2. Arnon R, Ben-Yedidia T. Old and new vaccine approaches. International immunopharmacology. 2003 Aug 1;3(8):1195-204.
3. Davies MN, Flower DR. Harnessing bioinformatics to discover new vaccines. Drug discovery today. 2007 May 1;12(9-10):389-95.
4. Morera Y, Bequet-Romero M, Ayala M, Lamdán H, Agger EM, Andersen P, Gavilondo JV. Anti-tumoral effect of active immunotherapy in C57BL/6 mice using a recombinant human VEGF protein as antigen and three chemically unrelated adjuvants. Angiogenesis. 2008 Dec;11(4):381-93.
5. Jasinska J, Wagner S, Radauer C, Sedivy R, Brodowicz T, Wiltschke C, Breiteneder H, Pehamberger H, Scheiner O, Wiedermann U, Zielinski CC. Inhibition of tumor cell growth by antibodies induced after vaccination with peptides derived from the extracellular domain of Her‐2/neu. International journal of cancer. 2003 Dec 20;107(6):976-83.
6.Mahler M, Blüthner M, Pollard KM. Advances in B-cell epitope analysis of autoantigens in connective tissue diseases. Clinical Immunology. 2003 May 1;107(2):65-79.
7. Parvizpour S, Razmara J, Omidi Y. Breast cancer vaccination comes to age: impacts of bioinformatics. BioImpacts: BI. 2018;8(3):223.
8. Das, N.C., Patra, R., Gupta, P.S. Sen, Ghosh, P., Bhattacharya, M., Rana, M.K.,Mukherjee, S., 2020. Designing of a novel multi-epitope peptide based vaccine against Brugia malayi: an in silico approach. Infect. Genet. Evol. 104633 https://doi.org/10.1016/j.meegid.2020.104633.
9. Duthie MS, Windish HP, Fox CB, Reed SG. Use of defined TLR ligands as adjuvants within human vaccines. Immunological reviews. 2011 Jan;239(1):178-96.
10. Zheng W, Zhang C, Li Y, Pearce R, Bell EW, Zhang Y. Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations. Cell reports methods. 2021 Jul 26;1(3):100014.
11. Robinson J, Guethlein LA, Cereb N, Yang SY, Norman PJ, Marsh SG, Parham P. Distinguishing functional polymorphism from random variation in the sequences of> 10,000 HLA-A,-B and-C alleles. PLoS genetics. 2017 Jun 26;13(6):e1006862.
12. Kozakov D, Hall DR, Xia B, Porter KA, Padhorny D, Yueh C, Beglov D, Vajda S. The ClusPro web server for protein–protein docking. Nature protocols. 2017 Feb;12(2):255-78.
13. Rapin N, Lund O, Bernaschi M, Castiglione F. Computational immunology meets bioinformatics: the use of prediction tools for molecular binding in the simulation of the immune system [PLoS]. PLoS One.2010; 5(4): e9862. https://doi.org/10.1371/journal.pone.0009862 PMID: 20419125.
14.Nielsen M, Andreatta M. NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets. Genome medicine. 2016 Dec;8(1):1-9.
15. Andreatta M, Karosiene E, Rasmussen M, Stryhn A, Buus S, Nielsen M. Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification. Immunogenetics. 2015 Nov;67(11):641-50.
16. Hurley CK, Hou L, Lazaro A, Gerfen J, Enriquez E, Galarza P, Rodriguez Cardozo MB, Halagan M, Maiers M, Behm D, Ng J. Next generation sequencing characterizes the extent of HLA diversity in an Argentinian registry population. Hla. 2018 Mar;91(3):175-86.
17. Dimitrov I, Naneva L, Doytchinova I, Bangov I. AllergenFP: allergenicity prediction by descriptor fingerprints. Bioinformatics. 2014 Mar 15;30(6):846-51.
18.Thévenet P, Shen Y, Maupetit J, Guyon F, Derreumaux P, Tuffery P. PEP-FOLD: an updated de novo structure prediction server for both linear and disulfide bonded cyclic peptides. Nucleic acids research. 2012 May 11;40(W1):W288-93.
19 . Shen Y, Maupetit J, Derreumaux P, Tufféry P. Improved PEP-FOLD approach for peptide and miniprotein structure prediction. Journal of chemical theory and computation. 2014 Oct 14;10(10):4745-58.
20. Doytchinova IA, Flower DR. In silico prediction of cancer immunogens: current state of the art. BMC immunology. 2018 Dec;19(1):1-9.
21. Pandey RK, Bhatt TK, Prajapati VK. Novel immunoinformatics approaches to design multi-epitope subunit vaccine for malaria by investigating anopheles salivary protein. Scientific reports. 2018 Jan 18;8(1):1-1.
22. Ashokan KV, Pillai M. In silico characterization of silk fibroin protein using computational tools and servers. Asian J Exp Sci. 2008;22:265-74.
23. Nezafat N, Eslami M, Negahdaripour M, Rahbar MR, Ghasemi Y. Designing an efficient multi-epitope oral vaccine against Helicobacter pylori using immunoinformatics and structural vaccinology approaches. Molecular BioSystems. 2017;13(4):699-713.
24. Skwarczynski M, Toth I. Peptide-based synthetic vaccines. Chemical science. 2016;7(2):842-54.
25.Shirota H, Tross D, Klinman DM. CpG oligonucleotides as cancer vaccine adjuvants. Vaccines. 2015 Jun;3(2):390-407.
26. Zininga T, Ramatsui L, Shonhai A. Heat shock proteins as immunomodulants. Molecules. 2018 Nov;23(11):2846.
27. Nold-Petry CA, Nold MF, Levy O, Kliger Y, Oren A, Borukhov I, Becker C, Wirtz S, Sandhu MK, Neurath M, Dinarello CA. Gp96 peptide antagonist gp96-II confers therapeutic effects in murine intestinal inflammation. Frontiers in immunology. 2017 Dec 11;8:1531.
28. Argos P. An investigation of oligopeptides linking domains in protein tertiary structures and possible candidates for general gene fusion. Journal of molecular biology. 1990 Feb 20;211(4):943-58.
29.Gasteiger E, Hoogland C, Gattiker A, Wilkins MR, Appel RD, Bairoch A. Protein identification and analysis tools on the ExPASy server. The proteomics protocols handbook. 2005:571-607.
30. Pihlasalo S, Auranen L, Hanninen P, Härmä H. Method for estimation of protein isoelectric point. Analytical chemistry. 2012 Oct 2;84(19):8253-8.
31 Sen Gupta PS, Mandal B, Bandyopadhyay AK. In silico characterization of human cyclooxygenase using computational tools and servers. Int J Institutional Pharmacy Life Sci. 2013;3:111.
32. Ansari HR, Raghava GP. Identification of conformational B-cell Epitopes in an antigen from its primary sequence. Immunome research. 2010 Dec;6(1):1-9.
33. Zheng J, Lin X, Wang X, Zheng L, Lan S, Jin S, Ou Z, Wu J. In silico analysis of epitope-based vaccine candidates against hepatitis B virus polymerase protein. Viruses. 2017 May;9(5):112.
34. Zhao W, Sher X. Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes. PLoS computational biology. 2018 Nov 8;14(11):e1006457.
35. Ozturk OG. HLA alleles in breast cancer. Pathology & Oncology Research. 2012 Oct;18(4):1099-.
36. Baloria U, Akhoon BA, Gupta SK, Sharma S, Verma V. In silico proteomic characterization of human epidermal growth factor receptor 2 (HER-2) for the mapping of high affinity antigenic determinants against breast cancer. Amino acids. 2012 Apr;42(4):1349-60.
37. Ali M, Pandey RK, Khatoon N, Narula A, Mishra A, Prajapati VK. Exploring dengue genome to construct a multi-epitope based subunit vaccine by utilizing immunoinformatics approach to battle against dengue infection. Scientific reports. 2017 Aug 23;7(1):1-3.
38. Corporate Comms. "New data on MAGE-A3 cancer immunotherapy support potential novel options of treating non-small cell lung cancer and melanoma". Us.gsk.com. Archived from the original on 2012-06-27. Retrieved 2012-10-16.
39. Jungbluth AA, Chen YT, Stockert E, Busam KJ, Kolb D, Iversen K, Coplan K, Williamson B, Altorki N, Old LJ. Immunohistochemical analysis of NY‐ESO‐1 antigen expression in normal and malignant human tissues. International Journal of Cancer. 2001 Jun 15;92(6):856-60.
40.Theurillat JP, Ingold F, Frei C, Zippelius A, Varga Z, Seifert B, Chen YT, Jäger D, Knuth A, Moch H. NY‐ESO‐1 protein expression in primary breast carcinoma and metastases—correlation with CD8+ T‐cell and CD79a+ plasmacytic/B‐cell infiltration. International journal of cancer. 2007 Jun 1;120(11):2411-7.
| Files | ||
| Issue | Vol 15 No 1 (2023) | |
| Section | Original Articles | |
| Keywords | ||
| cancer,Vaccine, Immunoinformatics, Antigenicity | ||
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How to Cite
1.
Pirmoradi S. Design of a new structure of immunogenic chimeric polytope against human various cancers using immunoinformatics and structural methods. Basic Clin Cancer Res. 2024;15(1):18-35.
