Designing a Multi-epitope Peptide Vaccine Against COVID-19 Variants Utilizing In-silico Tools

Dariushnejad, Hassan; Ghorbanzadeh, Vajihe; Akbari, Soheila; Hashemzadeh, Pejman

doi:10.30699/ijmm.15.5.592

year 15, Issue 5 (September - October 2021) Iran J Med Microbiol 2021, 15(5): 592-605 | Back to browse issues page

‎ 10.30699/ijmm.15.5.592

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Dariushnejad H, Ghorbanzadeh V, Akbari S, Hashemzadeh P. Designing a Multi-epitope Peptide Vaccine Against COVID-19 Variants Utilizing In-silico Tools. Iran J Med Microbiol 2021; 15 (5) :592-605
URL: http://ijmm.ir/article-1-1390-en.html

Designing a Multi-epitope Peptide Vaccine Against COVID-19 Variants Utilizing In-silico Tools

Hassan Dariushnejad¹

, Vajihe Ghorbanzadeh²

, Soheila Akbari³

, Pejman Hashemzadeh

⁴

1- Department of Medical Biotechnology, Faculty of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran
2- Razi Herbal Medicines Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran
3- Department of Obstetrics and Gynecology, Lorestan University of Medical Sciences, Khorramabad, Iran
4- Department of Medical Biotechnology, Faculty of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran , pejman7genetian@gmail.com

Abstract: (2713 Views)

Background and Aim: SARS-CoV-2 is the causative agent of Coronavirus 2019 or COVID-19 in the world. Novel coronavirus disease is a respiratory disease. To date, there have been challenges in the treatment for COVID-19 and emerged new variants like UK B1.1.7. Accordingly, an effective prevention regime is needed for this infection, which covers most variants. The purpose of this research was to predict the conserved epitopes of Spike and Nucleocapsid proteins from SARS-CoV-2 for the design of a novel coronavirus 2019 multi-epitope vaccine using in silico tools.
Materials and Methods: Computational analysis and immunoinformatics approaches include identification of potential conserve epitopes and selection of epitopes based on allergenicity, toxicity, antigenicity, and molecular docking were used for epitope prediction and screening. In the next step, selected segments of the epitopes were attached by the suitable linkers. Finally, Maltese-bound protein (MBP) as an adjuvant was added to the novel vaccine structure. The secondary and third structures of the designed multi-epitope vaccine were predicted via immunoinformatics algorithms. Predicted structure refined and validated for attaining best stability. In the end, immunoinformatics evaluation, molecular docking, and molecular dynamics were performed to confirm vaccine efficiency. Codon optimization and in silico cloning were done to ensure the expression yield of the novel multi-epitope vaccine in the target host.
Results: This study showed that our data support the suggestion that the designed vaccine could induce immune responses against SARS-CoV-2 variants.
Conclusion: The structure designed had acceptable quality with software reviews. Further in vitro and in vivo experiments are needed to confirm the safety and immunogenicity of the candidate vaccine.

Keywords: B1.1.7 variant, COVID-19, Immunoinformatics, SARS-CoV-2, Vaccine

Full-Text [PDF 1284 kb] (1200 Downloads) | | Full-Text (HTML) (1761 Views)

Type of Study: Original Research Article | Subject: Microbial Bioinformatics
Received: 2021/07/11 | Accepted: 2021/09/1 | ePublished: 2021/09/28

References

1. Payne S. Family Coronaviridae. Viruses. 2017:149. [DOI:10.1016/B978-0-12-803109-4.00017-9]

2. Al-Rohaimi AH, Al Otaibi F. Novel SARS-CoV-2 outbreak and COVID19 disease; a systemic review on the global pandemic. GENES DIS. 2020. [DOI:10.1016/j.gendis.2020.06.004] [PMID] [PMCID]

3. Ye Z-W, Yuan S, Yuen K-S, Fung S-Y, Chan C-P, Jin D-Y. Zoonotic origins of human coronaviruses. Int. J. Biol. Sci. 2020;16(10):1686. [DOI:10.7150/ijbs.45472] [PMID] [PMCID]

4. Sun P, Lu X, Xu C, Sun W, Pan B. Understanding of COVID‐19 based on current evidence. J. Med. Virol. 2020;92(6):548-51. [DOI:10.1002/jmv.25722] [PMID] [PMCID]

5. Song Y, Liu P, Shi X, Chu Y, Zhang J, Xia J, et al. SARS-CoV-2 induced diarrhoea as onset symptom in patient with COVID-19. Gut. 2020;69(6):1143-4. [DOI:10.1136/gutjnl-2020-320891] [PMID]

6. Bouaziz J, Duong T, Jachiet M, Velter C, Lestang P, Cassius C, et al. Vascular skin symptoms in COVID‐19: a french observational study. J. Eur. Acad. Dermatol. Venereol. 2020. [DOI:10.1111/jdv.16544] [PMCID]

7. Struyf T, Deeks JJ, Dinnes J, Takwoingi Y, Davenport C, Leeflang MM, et al. Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID‐19 disease. Cochrane Database Syst. Rev. 2020(7). [DOI:10.1002/14651858.CD013665] [PMID] [PMCID]

8. Yang Z, Bogdan P, Nazarian S. An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study. Sci. Rep. 2021;11(1):1-21. [DOI:10.1038/s41598-021-81749-9] [PMID] [PMCID]

9. Jebril N. World Health Organization declared a pandemic public health menace: A systematic review of the coronavirus disease 2019 "COVID-19", up to 26th March 2020. Available at SSRN 3566298. 2020. [DOI:10.2139/ssrn.3566298]

10. Tang JW, Tambyah PA, Hui DS. Emergence of a new SARS-CoV-2 variant in the UK. J. Infect. 2020. [DOI:10.1016/j.jinf.2020.12.024] [PMID] [PMCID]

11. Boopathi S, Poma AB, Kolandaivel P. Novel 2019 coronavirus structure, mechanism of action, antiviral drug promises and rule out against its treatment. J. Biomol. Struct. Dyn. 2020:1-10. [DOI:10.1080/07391102.2020.1758788] [PMID] [PMCID]

12. Pathak SK. General Details of Structural Proteins of Coronaviruses with Special Reference of SARS-COV-2 or COVID-19. Bull. Env. Pharmacol. Life Sci. 2020;9:34-8.

13. Tai W, He L, Zhang X, Pu J, Voronin D, Jiang S, et al. Characterization of the receptor-binding domain (RBD) of 2019 novel coronavirus: implication for development of RBD protein as a viral attachment inhibitor and vaccine. Cell. Mol. Immunol. 2020;17(6):613-20. [DOI:10.1038/s41423-020-0400-4] [PMID] [PMCID]

14. Chen W-H, Hotez PJ, Bottazzi ME. Potential for developing a SARS-CoV receptor-binding domain (RBD) recombinant protein as a heterologous human vaccine against coronavirus infectious disease (COVID)-19. Hum. Vaccines Immunother. 2020:1-4. [DOI:10.1080/21645515.2020.1740560] [PMID] [PMCID]

15. Choi J-H, Woo H-M, Lee T-y, Lee S-y, Shim S-M, Park W-J, et al. Characterization of a human monoclonal antibody generated from a B-cell specific for a prefusion-stabilized spike protein of Middle East respiratory syndrome coronavirus. PLoS One. 2020;15(5):e0232757. [DOI:10.1371/journal.pone.0232757] [PMID] [PMCID]

16. Chen X, Li R, Pan Z, Qian C, Yang Y, You R, et al. Human monoclonal antibodies block the binding of SARS-CoV-2 spike protein to angiotensin converting enzyme 2 receptor. Cell. Mol. Immunol. 2020:1-3. [DOI:10.1038/s41423-020-0426-7] [PMID] [PMCID]

17. Kumar S. Drug and vaccine design against Novel Coronavirus (2019-nCoV) spike protein through Computational approach. Preprints. 2020. [DOI:10.20944/preprints202002.0071.v1]

18. Thieme C, Anft M, Paniskaki K, Blázquez Navarro A, Doevelaar A, Seibert FS, et al. The SARS-CoV-2 T-cell immunity is directed against the spike, membrane, and nucleocapsid protein and associated with COVID 19 severity. Cell Rep Med. 2020. [DOI:10.2139/ssrn.3606763]

19. Dutta NK, Mazumdar K, Gordy JT. The nucleocapsid protein of SARS-CoV-2: a target for vaccine development. J. Virol. 2020;94(13). [DOI:10.1128/JVI.00647-20]

20. Hashemzadeh P, Ghorbanzadeh V, Lashgarian HE, Kheirandish F, Dariushnejad H. Harnessing Bioinformatic Approaches to Design Novel Multi-epitope Subunit Vaccine Against Leishmania infantum. nt J Pept Res Ther. 2019:1-12. [DOI:10.1007/s10989-019-09949-6]

21. Pruitt KD, Tatusova T, Maglott DR. NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. . Nucleic Acids Res. 2007;35(suppl_1):D61-D5. [DOI:10.1093/nar/gkl842] [PMID] [PMCID]

22. Larsen JEP, Lund O, Nielsen M. Improved method for predicting linear B-cell epitopes. Immunome Res. 2006;2(1):2. [DOI:10.1186/1745-7580-2-2] [PMID] [PMCID]

23. Ponomarenko JV, Bourne PE. Antibody-protein interactions: benchmark datasets and prediction tools evaluation. BMC Struct. Biol. 2007;7(1):64. [DOI:10.1186/1472-6807-7-64] [PMID] [PMCID]

24. Reche PA, Glutting J-P, Zhang H, Reinherz EL. Enhancement to the RANKPEP resource for the prediction of peptide binding to MHC molecules using profiles. Immunogenetics. 2004;56(6):405-19. [DOI:10.1007/s00251-004-0709-7] [PMID]

25. Dimitrov I, Flower DR, Doytchinova I, editors. AllerTOP-a server for in silico prediction of allergens. BMC Bioinform. 2013. [DOI:10.1186/1471-2105-14-S6-S4] [PMID] [PMCID]

26. Gupta S, Kapoor P, Chaudhary K, Gautam A, Kumar R, Raghava GP, et al. In silico approach for predicting toxicity of peptides and proteins. PloS one. 2013;8(9). [DOI:10.1371/journal.pone.0073957] [PMID] [PMCID]

27. Doytchinova IA, Flower DR. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinform. 2007;8(1):4. [DOI:10.1186/1471-2105-8-4] [PMID] [PMCID]

28. Schneidman-Duhovny D, Inbar Y, Nussinov R, Wolfson HJ. PatchDock and SymmDock: servers for rigid and symmetric docking. Nucleic Acids Res. 2005;33(suppl_2):W363-W7. [DOI:10.1093/nar/gki481] [PMID] [PMCID]

29. Duhovny D, Nussinov R, Wolfson H. Efficient unbound docking of rigid molecules, p 185-200. Algorithms in bioinformatics Lecture notes in computer science. 2002;2452. [DOI:10.1007/3-540-45784-4_14]

30. Afzali F, Ghahremanifard P, Ranjbar MM, Salimi M. Exploring PLAC1 Structure and Underlying Mechanisms to Design a Derivative Vaccine Against Breast Cancer Progression; In-Silico Study. Curr. Proteom. 2020;17(5):379-91. [DOI:10.2174/1570164617666191203111451]

31. 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: Springer; 2005. p. 571-607. [DOI:10.1385/1-59259-890-0:571]

32. Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJ. The Phyre2 web portal for protein modeling, prediction and analysis. Nat. Protoc. 2015;10(6):845. [DOI:10.1038/nprot.2015.053] [PMID] [PMCID]

33. Lovell SC, Davis IW, Arendall III WB, De Bakker PI, Word JM, Prisant MG, et al. Structure validation by Cα geometry: ϕ, ψ and Cβ deviation. Proteins: Struct. Funct. Bioinform. 2003;50(3):437-50. [DOI:10.1002/prot.10286] [PMID]

34. 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(suppl_2):W407-W10. [DOI:10.1093/nar/gkm290] [PMID] [PMCID]

35. Pierce BG, Wiehe K, Hwang H, Kim B-H, Vreven T, Weng Z. ZDOCK server: interactive docking prediction of protein-protein complexes and symmetric multimers. Bioinformatics. 2014;30(12):1771-3. [DOI:10.1093/bioinformatics/btu097] [PMID] [PMCID]

36. 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. [DOI:10.1038/nprot.2016.169] [PMID] [PMCID]

37. López-Blanco JR, Aliaga JI, Quintana-Ortí ES, Chacón P. iMODS: internal coordinates normal mode analysis server. Nucleic Acids Res. 2014;42(W1):W271-W6. [DOI:10.1093/nar/gku339] [PMID] [PMCID]

38. Liu C, Zhou Q, Li Y, Garner LV, Watkins SP, Carter LJ, et al. Research and development on therapeutic agents and vaccines for COVID-19 and related human coronavirus diseases. ACS Cent. Sci. 2020. [DOI:10.1021/acscentsci.0c00272] [PMID] [PMCID]

39. Kibria K, Ullah H, Miah M. The multi-epitope vaccine prediction to combat Pandemic SARS-CoV-2, an immunoinformatic approach. Preprints 2020. [DOI:10.21203/rs.3.rs-21853/v1]

40. De Groot AS, Sbai H, Aubin CS, McMurry J, Martin W. Immuno‐informatics: Mining genomes for vaccine components. Immunol. Cell Biol. 2002;80(3):255-69. [DOI:10.1046/j.1440-1711.2002.01092.x] [PMID]

41. Purcell AW, McCluskey J, Rossjohn J. More than one reason to rethink the use of peptides in vaccine design. Nat. Rev. Drug Discov. 2007;6(5):404-14. [DOI:10.1038/nrd2224] [PMID]

42. Christie JM, Chapel H, Chapman RW, Rosenberg WM. Immune selection and genetic sequence variation in core and envelope regions of hepatitis C virus. Hepatology. 1999;30(4):1037-44. [DOI:10.1002/hep.510300403] [PMID]

43. Twiddy SS, Holmes EC, Rambaut A. Inferring the rate and time-scale of dengue virus evolution. Mol. Biol. Evol. 2003;20(1):122-9. [DOI:10.1093/molbev/msg010] [PMID]

44. Shen Z, Xiao Y, Kang L, Ma W, Shi L, Zhang L, et al. Genomic Diversity of Severe Acute Respiratory Syndrome-Coronavirus 2 in Patients With Coronavirus Disease 2019. Clin. Infect. Dis. 2020;71(15):713-20. [DOI:10.1093/cid/ciaa203] [PMID] [PMCID]

45. Lan J, Ge J, Yu J, Shan S, Zhou H, Fan S, et al. Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor. Nature. 2020;581(7807):215-20. [DOI:10.1038/s41586-020-2180-5] [PMID]

46. Cong Y, Ulasli M, Schepers H, Mauthe M, V'kovski P, Kriegenburg F, et al. Nucleocapsid protein recruitment to replication-transcription complexes plays a crucial role in coronaviral life cycle. J. Virol. 2020;94(4). [DOI:10.1128/JVI.01925-19]

47. Leung DTM, Chi Hang TF, Chun Hung M, Sheung Chan PK, Cheung JLK, Niu H, et al. Antibody response of patients with severe acute respiratory syndrome (SARS) targets the viral nucleocapsid. The Journal of infectious diseases. 2004;190(2):379-86. [DOI:10.1086/422040] [PMID] [PMCID]

48. Kim PS, Reicin AS. Discontinuation of VIOXX. Lancet. 2005;365(9453):23. [DOI:10.1016/S0140-6736(04)17652-6]

49. Okada M, Takemoto Y, Okuno Y, Hashimoto S, Yoshida S, Fukunaga Y, et al. The development of vaccines against SARS corona virus in mice and SCID-PBL/hu mice. Vaccine. 2005;23(17-18):2269-72. [DOI:10.1016/j.vaccine.2005.01.036] [PMID] [PMCID]

50. Hofmeyr SA. An interpretative introduction to the immune system. Design principles for the immune system and other distributed autonomous systems. 2001;3:28-36.

51. Tritto E, Mosca F, De Gregorio E. Mechanism of action of licensed vaccine adjuvants. Vaccine. 2009;27(25-26):3331-4. [DOI:10.1016/j.vaccine.2009.01.084] [PMID]

52. Buonaguro FM, Tornesello ML, Buonaguro L. New adjuvants in evolving vaccine strategies. Expert Opin Biol Ther. 2011;11(7):827-32. [DOI:10.1517/14712598.2011.587802] [PMID]

53. Yuzawa S, Kurita-Ochiai T, Hashizume T, Kobayashi R, Abiko Y, Yamamoto M. Sublingual vaccination with fusion protein consisting of the functional domain of hemagglutinin A of Porphyromonas gingivalis and Escherichia coli maltose-binding protein elicits protective immunity in the oral cavity. FEMS Immunol Med Microbiol. 2012;64(2):265-72. [DOI:10.1111/j.1574-695X.2011.00895.x] [PMID]

54. Fang F, Ma J, Ni W, Wang F, Sun X, Li Y, et al. MUC1 and maltose‑binding protein recombinant fusion protein combined with Bacillus Calmette‑Guerin induces MUC1‑specific and nonspecific anti‑tumor immunity in mice. Mol. Med. Rep. 2014;10(2):1056-64. [DOI:10.3892/mmr.2014.2306] [PMID]

55. Zhao X, Ma J, Fang F, Zhou J, Song X, Liu Z, et al. Effect of Escherichia coli maltose-binding protein on mouse Th1 cell activation. Chin. J. Microbiol. Immunol. 2009;25(6):504-7.

56. Fernandez S, Palmer DR, Simmons M, Sun P, Bisbing J, McClain S, et al. Potential role for Toll-like receptor 4 in mediating Escherichia coli maltose-binding protein activation of dendritic cells. Infect. Immun. 2007;75(3):1359-63. [DOI:10.1128/IAI.00486-06] [PMID] [PMCID]

57. Routzahn KM, Waugh DS. Differential effects of supplementary affinity tags on the solubility of MBP fusion proteins. J. Struct. Funct. Genomics. 2002;2(2):83-92. [DOI:10.1023/A:1020424023207] [PMID]

58. Chen X, Zaro JL, Shen W-C. Fusion protein linkers: property, design and functionality. Adv. Drug Deliv. Rev. 2013;65(10):1357-69. [DOI:10.1016/j.addr.2012.09.039] [PMID] [PMCID]

59. Terpe K. Overview of tag protein fusions: from molecular and biochemical fundamentals to commercial systems. Appl. Microbiol. Biotechnol. 2003;60(5):523-33. [DOI:10.1007/s00253-002-1158-6] [PMID]

60. Jie J, Zhang Y, Zhou H, Zhai X, Zhang N, Yuan H, et al. CpG ODN1826 as a promising mucin1-maltose-binding protein vaccine adjuvant induced DC maturation and enhanced antitumor immunity. Int. J. Mol. Sci. 2018;19(3):920. [DOI:10.3390/ijms19030920] [PMID] [PMCID]