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. 2022 Dec 6;16(1):107–116. doi: 10.1016/j.jiph.2022.11.033

Designing multi-epitope monkeypox virus-specific vaccine using immunoinformatics approach

Sumera Zaib a,⁎, Nehal Rana a, Areeba a, Nadia Hussain e,f, Hamad Alrbyawi c, Ayed A Dera b,d, Imtiaz Khan b,⁎, Mohammad Khalid g, Ajmal Khan h, Ahmed Al-Harrasi h,⁎
PMCID: PMC9724569  PMID: 36508944

Abstract

Background

Monkeypox virus is an enveloped DNA virus that belongs to Poxviridae family. The virus is transmitted from rodents to primates via infected body fluids, skin lesions, and respiratory droplets. After being infected with virus, the patients experience fever, myalgia, maculopapular rash, and fluid-filled blisters. It is necessary to differentiate monkeypox virus from other poxviruses during diagnosis which can be appropriately envisioned via DNA analysis from swab samples. During small outbreaks, the virus is treated with therapies administered in other orthopoxviruses infections and does not have its own specific therapy and vaccine. Consequently, in this article, two potential peptides have been designed.

Methods

For the purpose of designing a vaccine, protein sequences were retrieved followed by the prediction of B- and T-cell epitopes. Afterward, vaccine structures were predicted which were docked with toll-like receptors. The docked complexes were analyzed with iMODS. Moreover, vaccine constructs nucleotide sequences were optimized and expressed in silico.

Results

COP-B7R vaccine construct (V1) has antigenicity score of 0.5400, instability index of 29.33, z-score of − 2.11-, and 42.11% GC content whereas COP-A44L vaccine construct (V2) has an antigenicity score of 0.7784, instability index of 23.33, z-score of − 0.61, and 48.63% GC content. It was also observed that COP-A44L can be expressed as a soluble protein in Escherichia coli as compared to COP-B7R which requires a different expression system.

Conclusion

The obtained results revealed that both vaccine constructs show satisfactory outcomes after in silico investigation and have significant potential to prevent the monkeypox virus. However, COP-A44L gave better results.

Abbreviations: MPXV, Monkeypox virus; IID, Initial Intrusion Duration; CDC, Centers for Disease Control and Prevention; VIG, Vaccinia Immunoglobulins; IEDB, Immune Epitope Database; TLR3, Toll-like receptor 3; NMA, Normal Mode Analysis; CAI, Codon Adaptation Index; II, Instability Index

Keywords: Monkeypox virus, Vaccine, Codon optimization, Epitope prediction, Molecular docking, Expression analysis

Graphical Abstract

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1. Introduction

The monkeypox is a zoonotic infection caused by a brick-shaped enveloped monkeypox virus (MPXV) that belongs to the family of ancient viruses, namely Poxviridae, characterized by a linear double-stranded DNA genome [1], [2]. It was first reported in 1959 as a pox-like disease in monkey colonies that were confined for study in Denmark. Subsequently, several outbreaks were also reported in countries of Central and West Africa and even in the United States (U.S.) with mortality rates ranging from 1% to 10% [3], [4]. Moreover, several cases have also been reported across the borders of Africa in Singapore, and South Korea, together with the most recently reported in Taiwan (June 24, 2022) [5]. The virus is primarily transmitted from wild animals (rodents and primates) to humans; however, human-to-human transmission is frequent. The major routes of transmission of MPXV among humans involve contact with contaminated items, infected body fluids, skin lesions on body of patients, and respiratory droplets [1], [3]. Furthermore, sexual route of transmission among bisexuals has also been revealed in the recent outbreak [6].

The transmission of MPXV is followed by an entry into cells which depends on its ability to evade antiviral immune responses and on the presence of ten viral accessory genes [7]. These viral accessory genes are also known as host range genes, and determine divergence in the host range and impede various aspects of cellular innate responses [8], [9]. The induction of type I interferon-mediated antiviral signaling is suppressed by viral protein B16. Moreover, Tumor Necrosis Factor alpha (TNF-α) and interferon-stimulated genes remain silent and are not expressed during infection with MPXV [10]. Inside the host, MPXV undergoes an incubation period of 5–21 days among which the first five days depict initial intrusion duration (IID). During IID, the patient experiences fever, lymph node inflammation, myalgia, severe headache, asthenia, and backache as the main symptoms. After 1–3 days of fever, the patient also experiences maculopapular rashes which subsequently develop into pus-containing fluid-filled blisters and burst in ten subsequent days [11].

Analysis of viral DNA extracted from swab samples obtained from the crust of vesicles represents the most suitable diagnosis procedure for the identification of monkeypox infection [12]. To date, no particular treatment for MPXV is available according to the Centers for Disease Control and Prevention (CDC). However, patients are being treated with other orthopoxvirus therapies such as cidofovir, brincidofovir and tecovirimat [6], [13]. Moreover, until now, small outbreaks are controlled by administering vaccinia immunoglobulins (VIG), and smallpox vaccines such as jynneos and LC16 m8, although not specific for MPXV [6], [14].

Therefore, the fundamental aim of this research centers around the design of multi-epitope MPXV-specific vaccine using immunoinformatics approach that can help in the eradication of viral infection. Two virulent genes, namely COP-A44L and COP-B7R, have been selected for vaccine development. COP-B7R is absent in variola virus but present in MPXV; whereas, COP-A44L encodes a protein comprising 140 amino acids shorter in variola virus as compared to MPXV [15]. COP-A44L protein product (3-β-hydroxysteroid dehydrogenase) catalyzes the conversion of pregnenalone to androstendione and is mandatory for the formation of immunosuppressive steroid hormones [16]. Similarly, COP-B7R is endoplasmic reticulum residing viral protein whose virulence mechanism is unknown. However, it may affect apoptotic mechanisms or may be expressed on cell surface and is involved in immune responses [17].

2. Methodology

2.1. Retrieval of protein sequences

The genome of poxvirus is around 200 Kb in size and contains 200 proteins. It has a linear double-stranded DNA genome having covalently closed hairpin end and 10 Kb inverted terminal repeats at each end. The protein selected was COP-A44L, a full length protein encoding 140 amino acids while other protein was COP-B7R, a resistant protein in monkeypox virus. The whole genome sequence was retrieved from GenBank (NCBI) (https://www.ncbi.nlm.nih.gov/). In addition, the protein sequence was taken from GenBank. However, Expasy (https://www.expasy.org/) and PSIPRED tools (http://bioinf.cs.ucl.ac.uk/psipred/) were used to determine the physiochemical properties, and secondary structure [18]. The number of amino acid and cysteine residues were accessed through DiANNA 1.1 web server (http://clavius.bc.edu/∼clotelab/DiANNA/) [19]. The online server VaxiJen v2.0 (http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html) was used to retrieve antigenicity score whereas number of TM helices was determined using TMHMM v2.0 server (https://services.healthtech.dtu.dk/service.php?TMHMM-2.0) [20], [21]. The prediction of allergenicity was determined through AllerTOP v. 2.0 (https://ddgpharmfac.net/AllergenFP/) [22].

2.2. B- and T-cell epitope prediction

For B- and T-cell epitope prediction of COP-A44L and COP-B7R, the immune epitope database (IEDB) (https://www.iedb.org/) analysis resource was used [23], [24], [25]. For this purpose, protein sequence was retrieved from the NCBI (https://www.ncbi.nlm.nih.gov/) and their epitopes were predicted separately. Subsequently, the same epitopes with IC50 value ≤ 100 based on their antigenicity and allergenicity were extracted and analyzed for population coverage using Population Coverage – IEDB Analysis Resource [26].

2.3. Prediction of 2D and 3D structures

A 2D structure represents covalent bonds in the molecule and PSIPRED tools (http://bioinf.cs.ucl.ac.uk/psipred/) were used for analysis [18]. However, 3D structures are three-dimensional coordinates of a molecule determined by an appropriate approach. The 3D structures for COP-A44L and COP-B7R were determined through SCRATCH Protein Predictor (https://scratch.proteomics.ics.uci.edu/) and I-TASSER (https://zhanggroup.org/I-TASSER/), respectively [27], [28]. Furthermore, refinement of the best model was achieved through Galaxy web server (https://galaxy.seoklab.org/) which showed the five models with Ramachandran plot, MolProbity, clash score RMSD and GDT-HA [29], [30]. Furthermore, the Ramachandran plot for the first model was predicted via RAMPAGE (https://zlab.umassmed.edu/bu/rama/) [31].

2.4. Molecular docking of designed chimeric protein with toll-like receptor

The interaction between antigenic molecule and specific immune receptor leads to the immune response. Toll-like receptor 3 (TLR3) was used as a receptor for determining the interaction of refined protein through a ClusPro server (https://cluspro.bu.edu/) [32]. This server is used to find the native sites within the protein and helps in protein-protein docking by providing various results. Molecular docking of multi-epitope vaccine peptide with TLR3 receptor was determined using ClusPro server to obtain the best docked model. Later, iMODS server (https://imods.iqfr.csic.es/) was used to perform the normal mode analysis (NMA) in internal coordinates of nucleic acid and protein atomic structure [33].

2.5. In silico cloning optimization of designed vaccine candidate

To perform reverse translation and codon optimization, EMBOSS Backtranseq (https://www.ebi.ac.uk/Tools/st/emboss_backtranseq/), and NovoPro (https://www.novoprolabs.com/tools/codon-optimization) were used. The acquired results showed output of codon adaptation index (CAI) and percentage of GC content, used to access protein expression level [34]. CAI helps to provide codon information and> 0.8 is considered as a good score, while GC content should be in the range of 30–70%. Furthermore, restriction enzyme cloning was performed via SnapGene that ensures the expression of vaccine construct. Vectors pET-28c (+) and pET-21a (+) were used to clone optimized gene sequences of final vaccine constructs [35]. A brief overview of the implemented methodology is shown in Fig. 1.

Fig. 1.

Fig. 1

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Diagrammatic illustration of envisioned methodology. All steps and software used for vaccine construction are shown in the flow chart.

3. Results and discussion

3.1. Analysis of protein sequence

Two protein sequences of COP-A44L and COP-B7R were retrieved from the NCBI and were used for the preparation of multi-epitope vaccine against the MPXV. Expasy-ProtParam (https://www.expasy.org/) was used for the physicochemical analysis. The physicochemical analysis of COP-B7R suggested the presence of 182 amino acids in the structure with molecular weight of 21,390.08 Da and theoretical pI of 5.65. Additionally, the half-life of the protein was 30 h (mammalian reticulocytes, in vitro),> 20 h (yeast, in vivo) and> 10 h (Escherichia coli, in vivo), whereas, for COP-A44L, whose molecular weight was found to be 39,338.36 Da with a sequence length of 346 amino acids, theoretical pI of 7.06, and stability index of 34.74 (stable protein). Furthermore, the estimated half-life was 30 h,> 20 h and> 10 h in mammalian reticulocytes (in vitro), yeast (in vivo) and E. coli (in vivo), respectively.

VaxiJen v2.0 online server (http://www.ddgpharmfac.net/vaxijen/VaxiJen/VaxiJen.html) showed that both the protein sequence were probable ANTIGEN (COP-B7R: 0.4395; COP-A44L: 0.4016), while, AllerTOP v. 2.0 (https://www.ddg-pharmfac.net/AllerTOP/) rendered both as non-allergic. Later, the functional sequence of the protein was subjected to linear B- and T-cell epitope prediction.

3.2. B- and T-cell epitope prediction analysis

Immune Epitope Database (IEDB) Analysis Resource (https://www.iedb.org/) is a repository website of computational tools used for analysis and prediction of B- and T-cell epitopes. B-cell epitopes can be linear or non-linear (discontinuous). The prediction of linear B-cell epitopes is more advanced and practical as compared to discontinuous B-cell epitopes. It is because linear B-cell epitopes are derived from the sequence of proteins and consist of sequential residues which instantly displace antigens for the formation of antibodies. Contrarily, discontinuous B-cell epitopes are derived from various patches of input protein in a non-sequential method and require three-dimensional structure of the protein. Additionally, the production of a selective antibody requires a suitable scaffold for grafting epitopes, which is feasible when linear B-cell epitopes are utilized [36]. Therefore, BepiPred-2.0 which is a web server for predicting linear B-cell epitopes from antigen sequences, is used in this research. BepiPred-2.0 is based on a random forest algorithm trained on epitope data derived from Protein Data Bank (PDB) and shows improved prediction of linear B-cell epitopes [37]. Subsequent to the retrieval of peptide sequences from the IEDB (http://tools.iedb.org/bcell/), epitopes having antigenicity score> 0.5 for COP-B7R and> 0.7 for COP-A44L were selected and subjected to vaccine construction. Additionally, these epitopes were also accessed by Population Coverage – IEDB Analysis Resource (http://tools.iedb.org/population/) to analyze percentage of the world population and was predicted to be 68.44% (MHC-I) and 50.93% (MHC-II) for COP-A44L.

3.3. Construction of multi-epitope subunit vaccine

For COP-B7R, the total number of predicted epitopes used to design chimera was 9 B-cell epitopes, 19 MHC-I epitopes, and 14 MHC-II epitopes while vaccine construct for COP-A44L constitutes 14 B-cell epitopes, 18 MHC-I epitopes and 8 MHC-II epitopes as shown in Fig. 2. These predicted epitopes were merged to form a continuous sequence via specific linkers. Both B- and T-cells were joined through a linker GPGPG and AAV. The adjuvant used was the TLR3 (PDB ID: 1ZIW) agonist, 50 S ribosomal L7/L12 (Locus RL7_MYCTU) with accession number P9WHE3 and added to amino terminus of vaccine peptide through EAAAK linker for specific immune response. Lastly, a 6xHis-tag was added to the C-terminal for protein purification and identification. Peptides with 494 amino acids (COP-B7R) and 366 amino acids (COP-A44L) were generated at the end. The COP-B7R vaccine construct will be denoted as V1 while vaccine construct of COP-A44L will be denoted as V2 throughout the article.

Fig. 2.

Fig. 2

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Vaccine constructs. A represents the V1 while V2 structure is depicted in B. The vaccine construct consists of B-cell epitopes, HTL and CTL epitopes, linkers and adjuvant.

3.4. Prediction of the antigenicity and allergenicity of the vaccine candidate

The allergenicity and antigenicity of final sequence of COP-B7R vaccine construct (V1) (with adjuvant sequence) was predicted by VaxiJen v2.0 and AllerTOP v. 2.0 that showed 0.5400 (antigenicity) and non-allergen. The results showed that the generated sequence was antigenic and non-allergic in nature. The COP-A44L vaccine construct (V2) was likely to be non-allergic with an antigenic score of 0.7784. The predicted antigenic scores are higher than that of the reported vaccine constructs (in silico) which were 0.44–0.47 [38] and 0.5311 [39].

3.5. Physicochemical properties and solubility prediction

The predicted molecular weight of the final protein of V1 was 57,803.24 Dalton with theoretical isoelectric point value of 6.06. Additionally, the protein half-life was 1 h (mammalian reticulocytes, in vitro), 30 min (yeast, in vivo) and> 10 h (Escherichia coli, in vivo). However, solubility of V1 was determined through SOLUPROT (https://loschmidt.chemi.muni.cz/soluprot/) which showed that V1 cannot be expressed in E. coli. The instability index was 29.33 which classified the protein as stable. Furthermore, the predicted aliphatic index was 79.90 with a grand average of hydropathicity of − 0.416. The corresponding negative sign indicates the hydrophilic nature of protein and ability to interact with other water molecules.

After physicochemical evaluation, the molecular weight of V2 was predicted to be 41,377.02 Dalton having 366 residues. Furthermore, the solubility of V2 was predicted to be 0.522 by SOLUPROT, indicating soluble expression in E. coli. Moreover, its theoretical pI, instability index (II) and hydropathicity were 9.14, 23.23 and − 0.277, respectively.

3.6. 2D and 3D structure analysis

3.6.1. Secondary structure prediction

According to PSIPRED results, V1 encompasses 3 helices in the secondary structure with a number of strands and coils. Similarly, V2 constitutes six helical conformations and numerous strands and coils in the predicted secondary structure. Moreover, MEMSAT analysis predicts the extracellular, transmembrane, and cytoplasmic domains of constructed vaccine peptide sequences. The V2 contains a pore lining domain from 173 to 188 amino acids while the N-terminal domain is designated as extracellular domain and the C-terminal domain as intracellular domain (Fig. S1).

3.6.2. Tertiary structure modeling

I-TASSER was used for the prediction of 3D structure of the V1 final proteins. The results showed 10 threading template with five best models of 1d2pA, 7w6bA, 3holA, 7w7iA and 5nxkA. All the 10 templates showed good alignment and z-score, ranging from 1.1 to 1.4. Among the five models, the one with high C-score was selected for refinement ( Fig. 3A) as the C score ranges from − 2.53 to − 4.76. The selected model had an estimated TM-score of 0.42 ± 0.14 and RMSD of 13.5 ± 4.0 Å.

Fig. 3.

Fig. 3

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Modeling and refinement of 3-dimensional (3D) structure of V1 and V2. (A) V1 3D model has been generated by homology modeling via I-TASSER. (3B) V2 3D model is generated by SCRATCH Protein Predictor as the amino acid sequence was less than 400 residues. (C) represents the refined model obtained by GalaxyRefine. (D) GalaxyRefine generated 3D model having Rama favored score of 96.4.

SCRATCH Protein Predictor was used for the prediction of 3D structure of the V2. It was used because SCRATCH Protein Predictor only predicts the protein sequence less than 400 amino acids with high authenticity in less time (Fig. 3B).

3.6.3. Tertiary structure refinement

The term refinement is used for the vaccine model to refine 3D predicted structure of the I-TASSER and SCRATCH Protein Predictor. In this case, Galaxy web server was used to refine model 1 retrieved from I-TASSER and SCRATCH Protein Predictor. GalaxyRefine server showed the five models with Ramachandran plot, MolProbity, RMSD and GDT-HA. Model 4 was found to be the best among all models due to its parameters, including GDT-HA (0.9160), RMSD (0.516), and MolProbity (3.034). In addition, the clash score was 37.5 with poor rotamers score of 2.2, and the Ramachandran plot score of 80.9. This model was further analyzed for vaccine construction (Fig. 3C). Contrarily, model 1 obtained via GalaxyRefine having GDT-HA 0.8854, RMSD 0.561, MolProbity 1.854, clash score 12.8, poor rotamers 0.6 and 96.4 Rama favored score was selected for further predictions and analyses of V2 (Fig. 3D).

The Ramachandran plot for V1 showed highly preferable area as green crosses with a percentage of 90.6. However, preferred observations are shown as brown triangles (7.3%) and red spots show questionable observation (1.9%) ( Fig. 4A). Subsequently, the Ramachandran plot predicted for V2 showed 100% residues (328 amino acids) in highly preferred region which are represented as green crosses, with no residues in additional preferred and questionable regions (Fig. 4B). The refined models of V1 and V2 were further validated via ProSA-web (https://prosa.services.came.sbg.ac.at/prosa.php) which showed a z-score of − 2.11 and − 0.61, respectively (Fig. 4C and D). The higher the z-score, the higher will be the model quality.

Fig. 4.

Fig. 4

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Validation of V1 and V2. (A) Ramachandran plot of V1 for the refined model. The green crosses are the amino acid residues in most favored/allowed region, the brown triangles are the amino acid residues in favored region and the red dots are the residues in disallowed region. (B) Ramachandran plot of V2 shows all the amino acid residues in highly preferred region with green crosses (100%). There are no brown triangles (0.0%) as well as no questionable observations (red circles). (C) This graph is generated by ProSA-web for V1 showing the quality of 3D model on the basis of z-score. (D) This graph predicts the quality of 3D refined model of V2 generated via ProSA-web on the basis of z-score (z-score = −0.61).

3.7. Molecular docking and dynamics simulation of subunit vaccine with immune receptor (TLR3)

The ClusPro was used for determining the protein binding and hydrophobic interaction sites on the proteins surface ( Fig. 5). iMODS server was used for the analysis of protein-protein docking and explains the deformability in the main chain and the deformed nature of each residue. According to the graphs as shown in Fig. 6A and B, the peaks are quite higher in 6 A depicting greater deformation in V1 as compared to V2 for which only few peaks are higher. Moreover, the eigenvalue is also predicted which is linked to the normal mode representing the stiffness of the model. It represents energy value needed to deform the structure. The lower eigenvalue causes the easy deformation. So according to the graphs in Fig. 6C and D, the eigenvalues of V1 and V2 are 7.088347e-06 and 8.277109e-07, respectively. These values interpret that the complex of V2 with TLR3 is easier to deform.

Fig. 5.

Fig. 5

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Molecular docking. (A) Docking complex of V1 with TLR3. (B) Docking complex of V2 (blue) with TLR3 (pink color). Here the red colored regions show the active site of TLR3 with which the vaccine construct interacts.

Fig. 6.

Fig. 6

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iMODS analysis of V1 and V2. (A) This graph represents the deformability potential of each residue in V1. Higher the peak, the higher will be the deformability. (B) This graph is visual representation of deformability potential of atoms in V2. In this graphical representation, most of the peaks have lower deformability. (C) This graph shows the eigenvalue for V1 which interprets the ease to deform the structure. Lower the eigenvalue, the higher the chance of deformation. (D) This graph for V2 interprets the susceptibility of a molecule to deform based on the eigenvalue. Here the eigenvalue is 8.277109e-07.

The covariance matrix showed interaction between the different pair of residues explained in Fig. 7A and B. The motion of atoms in V1 are not very correlated because blue and white regions are more obvious.On the other hand, the covariance matrix for V2 contains more red region, less blue region and nearly no white region showing correlated motion of atoms. However, Fig. 7C and D explain the elastic network model representing the atom pairs connected by strings. Each dot in graph exhibits the one spring between the corresponding atom pairs. These dots represent the stiffness and darker gray shows the stiffer spring.

Fig. 7.

Fig. 7

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V1 and V2 analysis using iMODS. (A) This graph elucidates covariance for V1. As most of the region is red so it shows correlated motion of residues; whereas, blue region shows uncorrelated motion between residues. (B) For V2, most of the colored region in graph is red so most of the residues have correlated motion; others (blue) have uncorrelated motion, while fewer have anti-correlated motion. (C) This is the elastic model network for V1 which illustrates spring formation between corresponding pair of atoms. The gray color dots show spring formation; the thicker the gray color, stronger is the spring between corresponding pairs. In this graph, most of the atoms form stronger springs. (D) According to elastic model network for V2, the atoms up to 600 are showing more strong spring formation as evident from the stronger gray color. Other atoms are also forming spring but they are not as dense as the former.

3.8. Optimization of the codon of final vaccine construct

For maximum protein expression, NovoPro was used to optimize the codon sequence generated by EMBOSS Backtranseq which converts the protein residues into a nucleotide sequence. The length of the optimized codon sequence for V1 was 1482 base pairs with a codon adaptation index (CAI) of 0.84 and average GC content of 42.11% that exhibited the good possibility of showing expression in the E. coli (strain K12) vector. Finally, adapted codon sequence was inserted into pET-21a (+) vector for designing a recombinant plasmid using SnapGene software.

For in silico restriction enzyme cloning of V2, the gene sequence generated by EMBOSS Backtranseq was optimized by NovoPro to be expressed in E. coli (strain K12). Consequently, the codon optimization index (CAI) was improved from 0.65 to 0.80 with 48.63% GC content in optimized sequence (1098 base pairs). Subsequently, the analysis for restriction fragments indicates PpuMI (at 18 bp) and ClaI (at 1040 bp) as the most favorable restriction sites. Resultantly, the optimized sequence was auspiciously ligated in pET-28c (+) plasmid for obtaining expression in E. coli (Figs. S2-S5).

After analysis of results and comparison between V1 and V2 as shown in Table 1, COP-A44L was found to possess more antigenic score and stable tertiary structure (predicted by higher z-score and Rama favored score).

Table 1.

A comparison between V1 and V2 based on their significant attributes.

Significant Attributes COP-B7R Vaccine Construct (V1) COP-A44L Vaccine Construct (V2)
Allergenicity Non-Allergic Non-Allergic
Antigenicity Score 0.5400 0.7784
Expression inEscherichia coli No Yes (as soluble protein)
Instability Index (II) 29.33 23.23
Hydropathicity -0.416 -0.277
Number of helical conformations in secondary structure 3 6
Rama favored score of tertiary structure 80.9 96.4
z-score -2.11 -0.61
Codon Optimization Index (CAI) 0.84 0.80
GC content 42.11% 48.63%
Expression Vector pET-21a (+) pET-28c (+)
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4. Conclusion

Monkeypox virus outbreak have been reported number of times in Central and West African countries. Recently, these outbreaks have also occurred in countries outside Africa. In the present study, we have developed two novel vaccine constructs for providing specific immunity against the virus. The vaccine constructs were analyzed for physicochemical properties, allergenicity, antigenicity, molecular dynamic simulation and cloning via restriction enzymes. Both the vaccine constructs namely, V1 (COP-B7R) and V2 (COP-A44L), contained epitopes with high population coverage, linked with stable linkers and adjuvant, showed antigenic potential and were found as non-allergic. The construct V2 can be expressed in E. coli and shows higher z-score than V1. In a nutshell, V2 showed better results than V1 by applying bioinformatics approaches.

Future perspectives

Owing to the frequent outbreaks of MPXV, the development of preventive measures is the need of time. In this article, two potential vaccine constructs have been designed by in silico methods, however, both the vaccines have to be validated by in vivo research and clinical trials before its commercialization.

Ethics approval

Not applicable because there are no animals and human used in this study.

Funding

The project was supported by grant from the Oman Research Council (TRC) through the funded project (BFP/RGP/EBR/22/021).

Competing interests

There are no conflicts to declare.

Acknowledgments

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Large Groups under grant number (RGP.2/244/43).

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Authors’ contributions

The manuscript was written through contribution of all authors. All authors have given approval to the final version of the manuscript.

Footnotes

Appendix A

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.jiph.2022.11.033.

Appendix A. Supplementary material

Supplementary material

mmc1.xlsx (1.1MB, xlsx)

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Supplementary material

mmc2.xlsx (688.7KB, xlsx)

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Supplementary material

mmc3.docx (1.4MB, docx)

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mmc1.xlsx (1.1MB, xlsx)

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mmc2.xlsx (688.7KB, xlsx)

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mmc3.docx (1.4MB, docx)

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