Volume 24, Issue 1 (4-2025)                   JRUMS 2025, 24(1): 19-46 | Back to browse issues page

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Ehsasatvatan M, Baghban Kohnehrouz B, Nejad Iran Nejad F. Immunoinformatics Design of a Multi-Epitope Vaccine Candidate via Poxin-Schlafen Protein of Monkeypox Virus. JRUMS 2025; 24 (1) :19-46
URL: http://journal.rums.ac.ir/article-1-7594-en.html
University of Tabriz
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Immunoinformatics Design of a Multi-Epitope Vaccine Candidate via Poxin-Schlafen Protein of Monkeypox Virus
Maryam Ehsasatvatan[1], Bahram Baghban Kohnehrouz[2], Fedra Nejad Iran Nejad[3]

Received: 15/12/24       Sent for Revision: 19/01/25       Received Revised Manuscript: 01/03/25   Accepted: 04/03/25

Background and Objectives: Monkeypox virus, a DNA-enveloped virus of the orthopoxvirus family, causes monkeypox infection in humans. Poxviruses have a distinctive nuclease called poxin, which cleaves cyclic dinucleotide 2'-3'-cGAMP, a crucial secondary messenger in the cGAS-STING (Cyclic GMP-AMP Synthase-Stimulator of Interferon Genes) signaling pathway. Despite existing drugs and vaccines for orthopoxvirus infections, the recent spread of monkeypox has raised global concerns. This study investigated the poxin-schlafen protein of monkeypox virus as a potential target for a novel multi-epitope vaccine.
Materials and Methods: This study was conducted using bioinformatic data analysis. Epitopes of this protein were evaluated for non-allergenicity, non-toxicity, and the ability to elicit T and B cell responses. The interaction between the vaccine and toll-like receptor-4 (TLR-4) was assessed using Cluspro 2.0. Immune, and MD simulations were performed to confirm the reliability of the docked complexes.
Results: The designed vaccine candidate was highly antigenic, non-allergenic, soluble, and had acceptable physicochemical properties. The three-dimensional structure of the vaccine and its interaction with TLR-4 were elucidated. Molecular dynamics simulations corroborated the high stability of the vaccine-TLR-4 complex. Immune simulation indicated that the vaccine candidate effectively elicited robust protective immune responses in the human body.
Conclusion: This study identified the most efficacious epitopes from the poxin-schlafen protein of the monkeypox virus. These findings demonstrate the potential efficacy of this vaccine candidate in eliciting immune responses. This study could significantly advance the development of an antiviral vaccine against monkeypox viruses. However, further in vitro and in vivo studies are required.
Keywords: Monkeypox, Immunoinformatic, Poxin-schlafen, Vaccine candidate

Funding: The study was funded by Tabriz University, Tabriz, Iran.
Conflict interest: None declared.
Ethical considerations: Not applicable.
Authors’ contributions:
-Conceptualization: Bahram Baghban Kohnehrouz
-Methodology: Bahram Baghban Kohnehrouz, Maryam Ehsasatvatan
- Data collection: Maryam Ehsasatvatan, Fedra Nejad Iran Nejad
-Formal analysis: Maryam Ehsasatvatan
-Supervision: Bahram Baghban Kohnehrouz
-Project administration: Bahram Baghban Kohnehrouz
-Writing - original draft: Maryam Ehsasatvatan
-Writing - review & editing: Bahram Baghban Kohnehrouz
Citation: Ehsasatvatan M, Baghban Kohnehrouz B, Nejad Iran Nejad F. Immunoinformatics Design of a Multi-Epitope Vaccine Candidate via Poxin-Schlafen Protein of Monkeypox Virus. J Rafsanjan Univ Med Sci 2025; 24 (1): 19-46. [Farsi]
 

[1]- Post Doctoral Researcher in Plant Biotechnology, Dept. of Plant Breeding & Biotechnology, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
[2]- Associate Prof., Dept. of Plant Breeding & Biotechnology, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
[3]- MSc Graduate in Plant Biotechnology, Dept. of Plant Breeding & Biotechnology, Faculty of Agriculture, University of Tabriz, Tabriz, Iran, ORCID: 0009-0003-5258-1011
(Corresponding Author) Tel: (041) 33356003, E-mail: nejadiran.f@gmail.com
Type of Study: Research | Subject: ايمونولوژي
Received: 2024/12/10 | Accepted: 2025/03/4 | Published: 2025/04/21

References
1. Alakunle EF, Okeke MI. Monkeypox virus: a neglected zoonotic pathogen spreads globally. Nat Rev Microbiol 2022; 20(9): 507-8.
2. Happi C, Adetifa I, Mbala P, Njouom R, Nakoune E, Happi A, et al. Urgent need for a non-discriminatory and non-stigmatizing nomenclature for monkeypox virus. PLoS Biol 2022; 20(8): 3001769.
3. Earl PL, Americo JL, Moss B. Lethal monkeypox virus infection of CAST/EiJ mice is associated with a deficient gamma interferon response. J Virol 2012; 86(17): 9105-12.
4. Grothe JH, Cornely OA, Salmanton-García J. Monkeypox diagnostic and treatment capacity at epidemic onset: A VACCELERATE online survey. J Infect Public Health 2022; 15(10): 1043-6.
5. WHO. Multi-country monkeypox outbreak: situation update. 2022.
6. Choudhary G, Prabha PK, Gupta S, Prakash A, Medhi B. Monkeypox infection: A quick glance. Indian J Pharmacol 2022 54(3); 161-4.
7. Bunge EM, Hoet B, Chen L, Lienert F, Weidenthaler H, Baer LR, et al. The changing epidemiology of human monkeypox—A potential threat? A systematic review. PLoS Negl Trop Dis 2022; 16(2): 0010141.
8. Plotkin SA, Orenstein W, Offit PA. Vaccines. E-book, Elsevier Health Sciences. 2012; 1570.
9. Grosenbach DW, Honeychurch K, Rose EA, Chinsangaram J, Frimm A, Maiti B, et al. Oral tecovirimat for the treatment of smallpox. NEJM 2018; 379(1): 44-53.
10. Chittick G, Morrison M, Brundage T, Nichols WG. Short-term clinical safety profile of brincidofovir: A favorable benefit–risk proposition in the treatment of smallpox. Antiviral Res 2017; 143: 269-77.
11. Delany I, Rappuoli R, Seib KL. Vaccines, reverse vaccinology, and bacterial pathogenesis. Cold Spring Harb Perspect Med 2013; 3(5): 012476.
12. Albekairi TH, Alshammari A, Alharbi M, Alshammary AF, Tahir ul Qamar M, Ullah A, et al. Designing of a novel multi-antigenic epitope-based vaccine against E. hormaechei: an intergraded reverse vaccinology and immunoinformatics approach. Vaccines 2022; 10(5): 665.
13. Seib KL, Dougan G, Rappuoli R. The key role of genomics in modern vaccine and drug design for emerging infectious diseases. PLoS Genet 2009; 5(10): 1000612.
14. Goumari MM, Farhani I, Nezafat N, Mahmoodi S. Multi-epitope vaccines (MEVs), as a novel strategy against infectious diseases. Curr Proteomics 2020; 17(5): 354-64.
15. Negahdaripour M, Nezafat N, Eslami M, Ghoshoon MB, Shoolian E, Najafipour S, et al. Structural vaccinology considerations for in silico designing of a multi-epitope vaccine. Infect Genet Evol 2018; 58: 96-109.
16. Eaglesham JB, Pan Y, Kupper TS, Kranzusch PJ. Viral and metazoan poxins are cGAMP-specific nucleases that restrict cGAS–STING signalling. Nature 2019; 566(7743): 259-63.
17. Maluquer de Motes C. Poxvirus cGAMP nucleases: Clues and mysteries from a stolen gene. PLoS Pathog 2021; 17(3): 1009372.
18. Eaglesham JB, McCarty KL, Kranzusch PJ. Structures of diverse poxin cGAMP nucleases reveal a widespread role for cGAS-STING evasion in host–pathogen conflict. Elife 2020; 9: 59753.
19. Ablasser A, Goldeck M, Cavlar T, Deimling T, Witte G, Röhl I, et al. cGAS produces a 2′-5′-linked cyclic dinucleotide second messenger that activates STING. Nature 2013; 498(7454): 380-4.
20. Phelan T, Little MA, Brady G. Targeting of the cGAS-STING system by DNA viruses. Biochem Pharmacol 2020; 174: 113831.
21. Liu F, Zhou P, Wang Q, Zhang M, Li D. The Schlafen family: complex roles in different cell types and virus replication. Cell Bio Int 2018; 42(1): 2-8.
22. Sievers F, Higgins DG. Clustal Omega for making accurate alignments of many protein sequences. Protein Sci 2018; 27(1): 135-45.
23. Clifford JN, Høie MH, Deleuran S, Peters B, Nielsen M, Marcatili P. BepiPred‐3.0: Improved B‐cell epitope prediction using protein language models. Protein Sci 2022; 31(12): 4497.
24. Saha S, Raghava GPS. Prediction of continuous B‐cell epitopes in an antigen using recurrent neural network. Proteins:Struct., Funct., Bioinf 2006; 65(1): 40-8.
25. Reynisson B, Alvarez B, Paul S, Peters B, Nielsen M. NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data. Nucleic Acids Res 2020; 48(1): 449-54.
26. Ehsasatvatan M, Kohnehrouz BB. Designing and immunomolecular analysis of a new broad-spectrum multiepitope vaccine against divergent human papillomavirus types. PLoS One 2024; 19(12): 0311351.
27. 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 Comp Biol 2008; 4(4): 1000048.
28. 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. Immunol 2018; 154(3): 394-406.
29. Doytchinova IA, Flower DR. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics 2007; 8: 4.
30. Calis JJ, Maybeno M, Greenbaum JA, Weiskopf D, De Silva AD, Sette A, et al. Properties of MHC class I presented peptides that enhance immunogenicity. PLoS Comput Biol 2013; 9(10): 1003266.
31. Dimitrov I, Naneva L, Doytchinova I, Bangov I. AllergenFP: allergenicity prediction by descriptor fingerprints. Bioinformatics 2014; 30(6): 846-51.
32. Dimitrov I, Flower DR, Doytchinova I. AllerTOP--a server for in silico prediction of allergens. BMC Bioinformatics 2013; 14: 4.
33. Sharma N, Naorem LD, Jain S, Raghava GP. ToxinPred2: An improved method for predicting toxicity of proteins. Brief Bioinform 2022; 23(5): 174.
34. Mahram A, Herbordt MC. NCBI BLASTP on high-performance reconfigurable computing systems. TRETS 2015; 7(4): 1-20.
35. Bui H-H, Sidney J, Dinh K, Southwood S, Newman MJ, Sette A. Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinformatics 2006; 7(1): 1-5.
36. Cepeda MS, Katz EG, Blacketer C. Microbiome-gut-brain axis: probiotics and their association with depression. J Neuropsychiatry Clin Neurosci 2017; 29(1): 39-44.
37. Dong R, Chu Z, Yu F, Zha Y. Contriving multi-epitope subunit of vaccine for COVID-19: immunoinformatics approaches. Front Immunol 2020; 11: 1784.
38. Hajighahramani N, Nezafat N, Eslami M, Negahdaripour M, Rahmatabadi SS, Ghasemi Y. Immunoinformatics analysis and in silico designing of a novel multi-epitope peptide vaccine against Staphylococcus aureus. Infect Genet Evol 2017; 48: 83-94.
39. Pandey RK, Ojha R, Aathmanathan VS, Krishnan M, Prajapati VK. Immunoinformatics approaches to design a novel multi-epitope subunit vaccine against HIV infection. Vaccine 2018; 36(17): 2262-72.
40. Saadi M, Karkhah A, Nouri HR. Development of a multi-epitope peptide vaccine inducing robust T cell responses against brucellosis using immunoin_ formatics based approaches. Infect Genet Evol 2017; 51: 227-34.
41. Hebditch M, Carballo-Amador MA, Charonis S, Curtis R, Warwicker J. Protein–Sol: a web tool for predicting protein solubility from sequence. Bioinformatics 2017; 33(19): 3098-100.
42. Garnier J, Gibrat J-F, Robson B. [32] GOR method for predicting protein secondary structure from amino acid sequence. In Methods in enzymology. 266, Elsevier, Academic Press 1996; 540-53.
43. McGuffin LJ, Bryson K, Jones DT. The PSIPRED protein structure prediction server. Bioinformatics 2000; 16(4): 404-5.
44. Tunyasuvunakool K, Adler J, Wu Z, Green T, Zielinski M, Žídek A, et al. Highly accurate protein structure prediction for the human proteome. Nature 2021; 596(7873): 590-6.
45. Ko J, Park H, Heo L, Seok C. GalaxyWEB server for protein structure prediction and refinement. Nucleic Acids Res 2012; 40(1): 294-7.
46. Laskowski R, MacArthur M, Thornton J. PROCHECK: validation of protein-structure coordinates. International Table for Crystallography 2012; 684-8.
47. Colovos C, Yeates T. ERRAT: an empirical atom-based method for validating protein structures. Protein Sci 1993; 2(9): 1511-9.
48. 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: 407-10.
49. Potocnakova L, Bhide M, Pulzova LB. An introduction to B-cell epitope mapping and in silico epitope prediction. J Immunol Res 2016; 2016.
50. 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): 255-78.
51. Xue LC, Rodrigues JP, Kastritis PL, Bonvin AM, Vangone A. PRODIGY: a web server for predicting the binding affinity of protein-protein complexes. Bioinformatics 2016; 32(23): 3676-8.
52. Wallace AC, Laskowski RA, Thornton JM. LIGPLOT: a program to generate schematic diagrams of protein-ligand interactions. Protein Eng 1995; 8(2): 127-34.
53. Van Der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJ. GROMACS: fast, flexible, and free. J Comput Chem 2005; 26(16): 1701-18.
54. Lindquist JM, Sulewski CA. Microsoft Excel: The Universal Tool of Analysis. In Handbook of Military and Defense Operations Research. Chapman and Hall/CRC, Taylor & Francis. 2020; 19-54.
55. DeWitt ME, Polk C, Williamson J, Shetty AK, Passaretti CL, McNeil CJ, et al. Global monkeypox case hospitalisation rates: a rapid systematic review and meta-analysis. EClinicalMedicine 2022; 54.
56. Gruber MF. Current status of monkeypox vaccines. NPJ Vaccines 2022; 7(1): 94.
57. Owens LE. JYNNEOS vaccination coverage among persons at risk for mpox—United States, May 22, 2022–January 31, 2023. MMWR Morb Mortal Wkly Rep 2023; 72: 342-7.
58. Grosenbach DW, Jordan R, King DS, Berhanu A, Warren TK, Kirkwood-Watts DL, et al. Immune responses to the smallpox vaccine given in combination with ST-246, a small-molecule inhibitor of poxvirus dissemination. Vaccine 2008; 26(7): 933-46.
59. Cheng P, Gong W. In silico analysis of peptide-based biomarkers for the diagnosis and prevention of latent tuberculosis infection. Front Microbiol 2022; 13: 947852.
60. Mahapatra SR, Dey J, Kushwaha GS, Puhan P, Mohakud NK, Panda SK, et al. Immunoinformatic approach employing modeling and simulation to design a novel vaccine construct targeting MDR efflux pumps to confer wide protection against typhoidal Salmonella serovars. J Biomol Struct Dyn 2022; 40(22): 11809-21.
61. Beikzadeh B. Immunoinformatics design of multi-epitope vaccine using OmpA, OmpD and enterotoxin against non-typhoidal salmonellosis. BMC Bioinformatics 2023; 24(1): 63.
62. Maleki A, Russo G, Parasiliti Palumbo GA, Pappalardo F. In silico design of recombinant multi-epitope vaccine against influenza A virus. BMC Bioinformatics 2021; 22: 617.
63. Sarvmeili J, Baghban Kohnehrouz B, Gholizadeh A, Ofoghi H, Shanehbandi D. Introduction of an Efficient Multiepitopic Vaccine Against Different SARS-CoV-2 Strains: Reverse Vaccinology. Journal of Health and Biomedical Informatics 2023; 10(3): 269-93.
64. Sarvmeili J, Baghban Kohnehrouz B, Gholizadeh A, Shanehbandi D, Ofoghi H. Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer. Sci Rep 2024; 14(1): 10297.
65. He R, Yang X, Liu C, Chen X, Wang L, Xiao M, et al. Efficient control of chronic LCMV infection by a CD4 T cell epitope-based heterologous prime-boost vaccination in a murine model. Cell Mol Immunol 2018; 15(9): 815-26.
66. Jiang P, Cai Y, Chen J, Ye X, Mao S, Zhu S, et al. Evaluation of tandem Chlamydia trachomatis MOMP multi-epitopes vaccine in BALB/c mice model. Vaccine 2017; 35(23): 3096-103.
67. Lu I-N, Farinelle S, Sausy A, Muller CP. Identification of a CD4 T-cell epitope in the hemagglutinin stalk domain of pandemic H1N1 influenza virus and its antigen-driven TCR usage signature in BALB/c mice. Cell Mol Immunol 2017; 14(6): 511-20.
68. Hoque SF, Bappy MNI, Chowdhury AT, Parvez MSA, Ahmed F, Imran MAS, et al. Scrutinizing surface glycoproteins and poxin-schlafen protein to design a heterologous recombinant vaccine against monkeypox virus. bioRxiv 2020; 919332.
69. Sandrini A, Rolland JM, O’Hehir RE. Current developments for improving efficacy of allergy vaccines. Expert Rev Vaccines 2015; 14(8): 1073-87.
70. Jasenosky LD, Scriba TJ, Hanekom WA, Goldfeld AE. T cells and adaptive immunity to Mycobacterium tuberculosis in humans. Immunolo Rev 2015; 264(1): 74-87.
71. Papaleo E, Saladino G, Lambrughi M, Lindorff-Larsen K, Gervasio FL, Nussinov R. The role of protein loops and linkers in conformational dynamics and allostery. Chem Rev 2016; 116(11): 6391-423.
72. Marciani DJ. Vaccine adjuvants: role and mechanisms of action in vaccine immunogenicity. Drug Discov Today 2003; 8(20): 934-43.
73. Mizel SB, Bates JT. Flagellin as an adjuvant: cellular mechanisms and potential. J Immunol 2010; 185(10): 5677-82.
74. Lester SN, Li K. Toll-like receptors in antiviral innate immunity. J Mol Biol 2014; 426(6): 1246-64.
75. Mantegazza AR, Magalhaes JG, Amigorena S, Marks MS. Presentation of phagocytosed antigens by MHC class I and II. Traffic 2013; 14(2): 135-52.
76. Alakunle E, Kolawole D, Diaz-Canova D, Alele F, Adegboye O, Moens U, et al. A comprehensive review of monkeypox virus and mpox characteristics. Front Cell Infect Microbiol 2024; 14: 1360586.
77. Adcock SA, McCammon JA. Molecular dynamics: survey of methods for simulating the activity of proteins. Chem Rev 2006; 106(5): 1589-615.
78. Machado MR, Pantano S. Split the charge difference in two! A rule of thumb for adding proper amounts of ions in MD simulations. J Chem Theory Comput 2020; 16(3): 1367-72.
79. Pang J, Cui J-a, Hui J. The importance of immune responses in a model of hepatitis B virus. Nonlinear Dyn 2012; 67: 723-34.
80.  

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