Monkeypox is a viral zoonotic illness resembling smallpox. It was a national epidemic, primarily in Africa, but has lately spread around the world, and as a result, it could evolve into a global pandemic in a relatively short amount of time. So, a multi-epitope vaccine capable of eliciting an immune response against MPXV by exploiting cell envelope protein as a target was therefore designed and created to generate a novel vaccination that is both effective and nearly devoid of adverse effects. The constructed vaccine has T-cell and B-cell epitopes from A30L protein that are highly antigenic, non-allergenic, non-toxic, conserved, and non-homologous. Consequently, they should be able to offer robust protection against the virus. Protein-protein docking was used to foretell the most effective vaccine design by docking with Toll-like receptors (TLR) 2, 3, 4, 6, and 8. In the end, the MD simulation and the immune simulation of the ideal vaccine construct both predicted positive outcomes. Ultimately, In Silico cloning will be employed to construct a vaccine in a large-scale production approach. Additionally, if in vivo and in vitro experiments yield positive results, our results provide an epitope-based peptide fragment that might be a promising entrant for the creation of a vaccine against the monkeypox virus.
Research Article
Computer-Aided Multi-Epitope based Vaccine Design against Monkeypox Virus Surface Protein A30L: An Immunoinformatics Approach
https://doi.org/10.21203/rs.3.rs-2250867/v1
This work is licensed under a CC BY 4.0 License
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MPXV
MHC
Vaccines
Peptide synthesis
A30L
The outbreak of monkeypox in 2022, which affected numerous countries located in both endemic and non-endemic zones, has sparked a tremendous amount of interest on a global scale. The monkeypox virus (MPXV) is a double-stranded DNA virus that is closely related to the Vaccinia and cowpox viruses. The core of its structure is typically dumbbell-shaped and ranges in size from 200 to 250 nm. It is a member of the Poxviridae family, subfamily Chordopoxvirinae, and the genus "Orthopoxvirus". Viruses such as the Vaccinia virus, Cowpox virus, Camelpox virus, Rabbitpox virus, Horsepox virus, Ectromelia virus, and Variola virus are all members of the genus Orthopoxvirus[1].
A pathogenic virus that had been overlooked for quite some time was found in cynomolgus monkeys in 1959 as they were being transported from Singapore to Denmark. Squirrels, rodents, mice, monkeys, dogs, and people have all contracted infections [2]. But, the very first case of monkeypox in the history of mankind was identified in 1970 in the Basankusu Territory of the Democratic Republic of the Congo, which is located in Central Africa. This case included a new-born who had not been vaccinated and was only nine months old
[3]. Two genetically different clades have been recognized. The first is the West African clade, while the second is the Central African clade, which inhabits the Congo basin [4]. In the last half-century, there have been isolated cases, most frequently in countries located in Africa. Multiple thousands of individual cases have been documented to date. Due to tourism and the importation or exportation of livestock carrying the virus, there have been sporadic instances and minor breakouts of the virus in areas where it is not usually found [5]. Theoretically, the monkeypox virus and other zoonotic poxviruses could slowly take over the role that the highly related variola virus used to play in the binomial niche. The mortality rate from monkeypox infections has traditionally ranged from 1–10%, with the majority of victims being children [36]. Although the symptoms of monkeypox are similar to those of smallpox, its contagiousness and severity of sickness are less severe. Monkeypox virus has become the most significant orthopoxvirus exhibiting persistent infection in various life forms since smallpox was eradicated in 1980 and the vaccinations were later stopped for smallpox [6]. In rural regions close to tropical rainforests, nations in west and central Africa have recorded occasional occurrences of monkeypox. The onset of monkeypox was identified in the United States in 2003, this was the first occasion that monkeypox in people was found off the perimeter of Africa. The infection has traditionally been found in central and western Africa, but in recent times, cases of human-to-human and contagious diseases have occurred, making monkeypox another possible global hazard while the world continues to deal with the fallout from the spread of COVID [7].
In the UK, monkeypox is declared a "High Consequence Infectious Disease" (HCID), and people suffering are administered peculiarly concerned treatments [36]. The European Center for Disease Prevention and Control announces that as of July 22, 2022, around 18 thousand infections of monkeypox have been reported across the globe, notably in France, Germany, India, Spain, the United States of America, and the United Kingdom. This assures the recurrence of monkeypox. Considering monkeypox's rapid proliferation and its presence in more than 70 locations, it seems like the infection has already been spreading at elevated levels, which have eluded detection by monitoring systems until now [8]. Because overseas travel is being linked to the disease's transmission and because the number of cases is rising slowly around the world, precautions need to be taken to avoid a recurrence of past errors, and enhanced inspections of foreign travellers are required to stop further pandemics. In the past two decades, the likelihood of this happening has increased as a result of several factors, including rising human migration, expanding human populations, intrusion on animal reservoir ecosystems, and an increased level of global connectivity.
Due to the virus's pathogenicity to cause disease, the virus first enters the lymph nodes and thereafter spreads to other organs, causing a wide range of symptoms such as swollen lymph nodes, flu, and the development of lesions that manifest first in the oropharynx and progress to other portions of the skin, including that of the palms and soles [1]. The onset of symptoms associated with monkeypox typically occurs within three weeks of infection with the virus. If an individual experiences flu-like conditions, one to four days later they will typically get a rash that can at first resemble acne or blisters, which lasts for the next two to four weeks. While curing, the rash goes through several stages, including scabs, and it may appear on or close to the genitalia and other places, including the feet, chest, and face. It is contagious from the time the first symptoms show up until the rash is completely gone, all scabs have dropped off, and a new layer of skin has grown. The complications include microbial contagion, hypopigmentation or hyperpigmentation of perpetual scars on the skin; scarring of the cornea; pneumonia, sepsis, and morbidity [9].
Several observational studies have shown that getting a smallpox vaccine helps prevent monkeypox about 85% of the time. In 2019, a vaccine against monkeypox based on a modified attenuated vaccinia virus (Ankara strain) was approved. This immunization must be in two separate doses, and access to it is still limited. Vaccines against smallpox and monkeypox are typically created using compositions that are dependent on the vaccinia virus. This is due to the fact that orthopoxviruses provide cross-protection [10]. A30L is an envelope protein present in monkeypox viruses which is responsible for virus that into a host and also for cell-cell fusion (a conserved cellular structure formed by the multiple cell fusions of mononuclear cells) and is analogous to the Vaccinia virus variant Copenhagen A28L [11]. It is being eyed as a prime research and development target in the monkeypox virus vaccine development field.
Scientists worldwide should improve their understanding of this pox virus, including its prophylactic measures, medication diagnosis, and the fundamentals of infection control, to understand the significant ramifications of the current outbreak, given the rising case statistics observed in the outbreak. In the current research, an immunoinformatics-based strategy was intended to be used in order to create a multi-epitope against monkeypox.
2.1 Protein sequence retrieval
The FASTA sequence of A30L envelope protein from Monkeypox virus Zaire-96-I-16 NCBI Reference Sequence NP_536567.1 was acquired from the National Center of Biotechnology the Information (NCBI) database (https://www.ncbi.nlm.nih.gov/). A30L is also considered an important target in monkeypox virus research as an envelope protein for virus entry into a host and cell-cell fusion (syncytial formation).
2.2 Physiochemical analysis
The ProtParam server is available at (https://web.expasy.org/protparam/)[37]. The physicochemical characteristics of the protein under research were predicted using Protparam, which was also employed to comprehend the core makeup of the vaccine. ProtParam computes grand average hydropathicity parameters (GRAVY), estimated half-life, molecular weight, instability and aliphatic index, theoretical pI, amino acid and atomic composition, and extinction coefficient. The GRAVY value and of a peptide or protein is calculated by adding up the hydropathy values of all of the amino acids, dividing that total by the number of residues in the sequence, and then rounding up to the nearest whole number.
2.3 Antigenicity and Toxicity prediction
The Vaxijen 2.0 server (httpredictiondg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html) was used to predict the immunogenic nature of each epitope fragment (antigenicity). It is predicated on the alignment independence technique, which estimates antigenicity by making use of physiochemical characteristics without recourse to sequence alignment [12]. Vaxigen works by transforming protein sequences using a technique called auto-cross covariance (ACC), which results in uniform vectors of the key amino acid characteristics. Fragments of peptides having a threshold score higher than 0.4 were identified as possibly antigenic [13]. The toxicity of the epitopes was predicted using the ToxinPred webserver (http://crdd.osdd.ntheet/raghava/toxinpred/)[14]. The epitopes with the half maximal inhibitory concentration (ic50) value less than 70 nM are chosen.
2.4 Allergenicity analysis
Using the AllerTop 2.0 server (https://www.ddg-pharmfac.net/AllerTOP/index.html), the allergenicity of the predicted peptides was evaluated. For the categorization of allergies, AllerTOP makes use of the amino acid E-descriptors, auto- and cross-covariance transformation of protein sequences into uniform equal-length vectors, and several machine learning techniques [15].
2.5 B-cell epitope prediction
The IEDB (The immune epitope database) server (http://tools.iedb.org/main/bcell/) has a set of tools that may be used to locate regions of proteins that have a high probability of being identified as epitopes in the context of a B cell response. B-cells need to have their immune response triggered by a specific antigen or epitope in order to produce antibodies that composed. The BepiPred 2.0 server (http://tools.iedb.org/bcell/help/#Bepipred-2.0) was employed for the prediction of B-cell epitope of the Monkeypox virus protein (A30L Monkeypox virus Zaire-96-I-16). BepiPred-2.0 is able to discover B-cell epitopes based on a sequence by using a Random Forest algorithm that has been trained on non-epitope and epitopes amino acids that have been found based on crystal structures [16].
2.6 T cell MHC class I binding predictions
Major Histocompatibility Complex class I (MHC I) binding prediction tool that is available on the IEDB (http://tools.iedb.org/mhci) was utilized to predict the interaction with the MHC I alleles. It services distinct approaches to measure the binding affinity of selected sequences to definite MHC class I molecule sequences artificial neural network (ANN) method was used to determine the values of the half maximum inhibitory concentration ic50 for peptide binding to the MHC class I molecule. For further study, alleles with binding affinities of ic50 below 70 nM were chosen [17–19].
2.7 T cell MHC class II binding predictions
In order to make the MHCII peptide predict protein sequence was sent to the IEDB server (http://tools.iedb.org/mhcii/) with the NN-align2.3 algorithm selected as the prediction technique. Peptides were selected on IC50 values less than 70 Nm [20].
2.8 Population coverage
To check whether the constructed multi-epitope vaccine is effective in different populations around the world to fight monkeypox catastrophe population coverage analysis is essential. Through the study of population coverage, we are able to determine their potential use of successful application for the development of promising vaccines in a variety of populations. Population coverage was performed for the selected MHC class I and II epitopes for the overall world population affected by the death and infection of monkeypox virus using the IEDB population the overage analysis tool (http://tools.iedb.org/population/) [21].
2.9. Multi-epitope vaccine construction
Epitopes which possess properties of antigenic, non-allergenic, and nontoxic were segregated and used to construct a multi-epitope vaccine. In order to develop the multi-epitope construction, T-Cell and MHC I and MHC II were connected together using linkers. The vaccine sequence was linked to the adjuvant sequence by an EAAAK linker. Linkers like CPGPG were used to connect the B-cell and MHC I epitopes, whereas AAY was used to connect the MHC II epitopes. In order to ease protein identification and epitope prediction, a 6xHis tag was attached to the C-terminal end of the vaccine [22–24].
2.10. Prediction of secondary structure
The secondary structure of a protein is an essential component in determining the folding properties of the protein as well as its physicochemical properties. Thus, for the prediction of the constructed multi-epitope vaccine’s secondary structure and to assess its structural properties and elements. We used the Prabi server (https://npsa-prb i.ibcp.fr/cgi-bin/ npsa_automat.pl?page=/NPSA/npsa_gor4.html) [25].
2.11. Modeling of tertiary structure
The 3D Modeling multi-epitope vaccination was predicted using the I-TASSER (Iterative Threading Assembly Refinement) server, which is accessible at (https://zhanglab.ccmb.med.umich.edu/I-TASSER/) [26].Discovery Studio 2020 was used to visualize the vaccine-building models that showed the prevaccine-building (https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-discovery-studio/visualization/).
2.12 Disulphide engineering
Disulfide engineering was done using the webserver DiANNA (bc.edu). The server rapidly assessed for proximity and geometry of the amino acid residues consistent with disulfide formation [27].
2.13 Molecular Docking
Toll-like receptors, often known as TLRs, are recognition molecules that can recognize a variety of antigens, and their activation triggers an intracellular signaling pathway. Using the HDOCK (httsignalingphys.hust.edu.cn/) [28, 29] molecular docking of the multi-epitope vaccine construct with the TLR2 (PDB ID: 6NIG), TLR3 (PDB ID: 2A0Z), TLR4 (PDB ID: 4G8A), TLR5 (PDB ID: 3J0A), and TLR8 (PDB ID: 4R0A) receptor was carried out in order to assess the interaction between receptor and the binding affinity of selected potential vaccine candidates.
2.14. Molecular dynamics simulation
All the Toll-Like receptors and peptide vaccine complex were subjected to dynamic studies to monitor the stability of the compound followed by the Root mean square deviation and Root mean square fluctuation graphs. In our study, we performed protein-protein dynamic simulation using GROMOS96 54a7 force field through the GROMACS 2022.4 package (Abraham et al., 2015) for molecular dynamic simulation in Linux operating system with a command-line interface. The salt concentration was kept at 0.15M according to the box size (2 nm) and the number of water molecules. The simulation run was for 50 nanoseconds to prepare the graph ratio followed by SASA (Solvent Accessible Surface Area) for the last 50ns to get the accuracy of the results.
2.14.1 Equilibration
The complex was equilibrated at 310 K and 1bar pressure and simulated with 2 fs step size. At the NVT ensemble, the system was continuously heated up by employing a Berendsen thermostat with the standard constant at 0.1 Ps to reach the 310 K temperature. In the NVT ensemble, using the Parinello-Rahman barostat algorithm, the system was pressurized and initiated the position restrain.
2.15. Codon optimization
Codon optimization is a necessary procedure that is utilized to promote gene expression and raise the efficiency of translation of a gene of interest by adapting the codon bias of the host organism. This is accomplished through the use of codon bias [30]. Codon optimization of the designed multi-epitope vaccine construct was done in vectorbuilder (https://en.vectorbuilder.com/tovector buildertimization for gene expression in the E. coli (strain K12) host. During the process of codon optimization, cleavage sites for restriction enzymes were avoided. GC content percentage and Codon adaptation index (CAI) results were also obtained.
13. Immune simulation and in silico cloning
Through the use of the Web prediction tool C-ImmSim (http://150.146.2.1/C-IMMSIM/), it was possible to simulate the immunogenicity and immune response profile of the designed multi-epitope vaccine construct in the human immune system. The prediction of the immsim response is accomplished through the use of this server. The position-specific scoring matrix (PSSM) and several machine learning algorithms. The in-silico cloning SnapGene (version 5.2.3) (www.snapgene.com) program was utilized in order to include the modified DNA sequence into the pET-28a (+) vector. This was done between the restriction sites for EcoR1 and BamHI introduced at the 5′and 3′ ends of the vaccine construct.
14.1 Characterization of A30L protein sequence
The total number of amino acids in the A30L protein sequence is 146, and its molecular weight is 16403.68 kDa. The protein is classified as stable because the instability score is 29.97. The grand average of hydropathicity (GRAVY) score is anticipated to be 0.057 and the aliphatic index is calculated to be 86.78, indicating that protein is hydrophilic by nature.
The VaxiJen server was then used to test for Antigenicity. Since viruses have a score threshold of 0.4, proteins with a score greater than 0.5 are considered to be Antigenic, whereas proteins with a score lower than 0.5 are considered to be non-Antigenic. The overall prediction score for this protein's Antigenicity is 0.6212 and the threshold for this protein is 0.4, making it a probable Antigen. The toxinpred server and the allertop server both demonstrate that the protein sequence is non-allergenic and non-toxic.
Table 1: Assesstion of Antigenicity allergeni8city and toxicity of A30L Protein Sequence
14.2 B cell and T cell prediction
B-cell and T cell epitopes of different lengths were predicted for A30L protein of the monkeypox virus. Using IEDB conservation methods, the BCPRED of B cell proposed 4 epitopes, all of which were shown to be 100% conserved and capable of inducing an immune response. With the aid of bioinformatics web tools, the predicted peptides were tested for Antigenicity, allergenicity, and toxicity.
|
No |
Start |
End |
Peptide |
Length |
Antigenicity |
Allergenicity |
Toxicity |
|---|---|---|---|---|---|---|---|
|
1 |
30 |
72 |
YGNIKEFNATHAAFEYSKSIGGTPALDRRVQDVNDTISDVKQK |
43 |
0.8069 (Antigen) |
Non- allergen |
Non-Toxic |
|
2 |
93 |
112 |
AEVGPNNTRSIRKFNTMRQC |
20 |
0.1312 (Non-Antigen) |
Non- allergen |
Non-Toxic |
|
3 |
116 |
122 |
TFSDVIN |
7 |
-0.1316 (Non-Antigen) |
Non- allergen |
Non-Toxic |
|
4 |
130 |
138 |
IAPNINNTE |
9 |
1.2654 (Antigen) |
Allergen |
Non-Toxic |
The peptides and accompanying MHC I and MHC II alleles were obtained from the IEDB server. Because IC50 values higher than 70 may be dangerous, the peptides with IC50 values less than 70 were chosen. After that the predicted peptides were tested for Antigenicity, allergenicity, and toxicity. The Antigenicity value should be between 0.5-1.0 so the vaccine construct will have peptide sequences that are Antigenic, non-allergenic, and non-toxic. The following list of the 22 peptides cleared all of the tests and are suitable to be used in vaccine construction and have the appropriate alleles in both MHC I and MHC II.
|
Position |
Peptide |
Alleles |
IC50 |
Antigenicity |
Allergenicity |
Toxicity |
|---|---|---|---|---|---|---|
|
38–47 |
ATHAAFEYSK |
HLA-A*11:01 HLA-A*30:01 HLA-A*68:01 |
14.86 |
0.8034 (Antigen) |
Non- allergen |
Non-Toxic |
|
7–16 |
FFIVVATAAV |
HLA-A*02:03 HLA-A*02:06 |
28.22 |
0.7002 (Antigen) |
Non- allergen |
Non-Toxic |
|
1–10 |
MNSLSIFFIV |
HLA-A*02:06 |
66.65 |
0.6003 (Antigen) |
Non- allergen |
Non-Toxic |
|
14–28 |
AAVCLLFIQSYSIYE |
HLA-DRB1*15:01 HLA-DRB1*04:05 HLA-DRB1*13:02 HLA-DRB1*07:01 HLA-DPA1*01:03/DPB1*02:01 |
7.8 |
0.5630 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
86–100 |
ASIFGFQAEVGPNNT |
HLA-DRB1*01:01 |
63.8 |
0.7911 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
12–26 |
ATAAVCLLFIQSYSI |
HLA-DRB1*15:01 HLA-DRB1*07:01 HLA-DRB1*13:02 HLA-DPA1*01:03/DPB1*02:01 |
27 |
0.6073 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
38–52 |
ATHAAFEYSKSIGGT |
HLA-DRB1*07:01 |
24.1 |
0.6296 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
114–128 |
DFTFSDVINIDIYNP |
HLA-DRB1*07:01 |
44.5 |
0.9114 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
35–49 |
EFNATHAAFEYSKSI |
HLA-DRB1*09:01 |
37.5 |
0.9701 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
82–96 |
GFVSASIFGFQAEVG |
HLA-DRB1*09:01 |
37 |
0.7075 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
40–54 |
HAAFEYSKSIGGTPA |
HLA-DRB1*07:01 HLA-DRB1*01:01 |
24 |
0.5284 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
123–137 |
IDIYNPCIAPNINNT |
HLA-DRB1*01:01 |
64.3 |
0.7641 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
6–20 |
IFFIVVATAAVCLLF |
HLA-DRB1*01:01 HLA-DRB1*07:01 |
69 |
0.7146 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
88–102 |
IFGFQAEVGPNNTRS |
HLA-DRB1*01:01 |
47.8 |
0.9802 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
4–18 |
LSIFFIVVATAAVCL |
HLA-DRB1*07:01 |
57.6 |
0.7394 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
37–51 |
NATHAAFEYSKSIGG |
HLA-DRB1*07:01 |
26.5 |
0.6238 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
122–136 |
NIDIYNPCIAPNINN |
HLA-DRB1*01:01 |
65.5 |
0.5798 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
107–121 |
NTMRQCIDFTFSDVI |
HLA-DRB1*07:01 |
57.5 |
0.9812 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
5–19 |
SIFFIVVATAAVCLL |
HLA-DRB1*01:01 HLA-DRB1*07:01 |
61.7 |
0.5982 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
13–27 |
TAAVCLLFIQSYSIY |
HLA-DRB1*15:01 HLA-DRB1*13:02 HLA-DRB1*07:01 HLA-DPA1*01:03/DPB1*02:01 |
12.1 |
0.5496 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
39–53 |
THAAFEYSKSIGGTP |
HLA-DRB1*07:01 |
23.9 |
0.6116 (Probable Antigen) |
Non- allergen |
Non-toxin |
|
126–140 |
YNPCIAPNINNTECQ |
HLA-DRB1*13:02 |
63.9 |
0.9808 (Probable Antigen) |
Non- allergen |
Non-toxin |
14.3 Population coverage
By providing the promiscuous epitopic core sequences (Class I and Class II) which are listed in the table with their matching HLA alleles to the IEDB population coverage analysis tool, the population coverage rate of the anticipated epitopes of the A30L protein was analysed.
|
MHC Class |
Coverage hit |
Avg. hit |
PC90 |
|
I |
68.63% |
1.22 |
0.32 |
|
MHC Class |
Coverage hit |
Avg. hit |
PC90 |
|
II |
55.6% |
5.56 |
0.23 |
14.4 Construction of vaccine and their physiochemical properties
The adjuvant and linkers between the B cell and T cell predicted peptides, which are Antigenic, non-allergenic, and non-toxic, were used to create the vaccine. The constructed vaccine has a predicted molecular weight of 55692.38 kDa. The construct's theoretical pI value of 5.0 indicates that the protein has a mildly acidic nature. The vaccine design has an estimated half-life of 30 hours in human reticulocytes in vitro, >20 hours in yeast in vivo, and >10 hours in E. coli in vivo. The protein is categorised as stable by the instability index, which was calculated to be 25.18. Grand average of hydropathicity (GRAVY) score is anticipated to be 0.338 and the aliphatic index is calculated to be 92.66, indicating that protein is hydrophilic by nature.
14.5 Antigenicity, Allergenicity and Toxicity Prediction of Vaccine Construct
The multi epitope constructed vaccine was checked for Antigenicity, allergenicity and toxicity with the help of bioinformatics online tool such as Vaxigen, allertop and toxinpred. The predicted results were the constructed vaccine is an Antigenic with a score of 0.6286 and their threshold is 0.4. It has been determined that this vaccine does not produce allergens and does not cause toxicity; hence, it is suitable for use as a preventative measure against the disease for which it was developed.
14.6 Secondary structure prediction
Using the Psipred server, a computation was performed to determine the percentage of the multi-epitope vaccine's secondary structure components. The structure that was anticipated for it consisted of an alpha-helix (55.74%) with a count of 291, an beta strand (9.19%) with a count of 48, and a random coil (35.05%) with a count of 183. The Psipred server gives the sequence plot and psipred cartoon results.
14.7 Tertiary structure prediction of the vaccine construct
Tertiary structure was predicted using the I TASSER sever, the server predicted the top 5 models for this multi-epitope constructed vaccine. The five anticipated models computed
C-scores range from − 1.00 to -4.29(-1.00, -1.59, -2.53, -2.59 and − 4.29). The typical C-score range is between − 5 and 2, and a higher value denotes greater confidence. The model with the greatest C-score was therefore chosen for more research. The Ramachandran plot was also visualized for the vaccine construct model in Biovia Discovery studio.
14.8 Molecular Docking
Using the H Dock server, molecular docking between the designed vaccine and the TLRs (TLR2, TLR3, TLR4, TLR5 and TLR8) was performed. The first model in each docking that was predicted by the HDOCK server was selected for further study. The docking scores for the TLR2-, TLR3-, TLR4-, TLR5-, and TLR8- vaccines were respectively − 287.79, -408.81, -369.01, -361.81, and − 363.03. It demonstrates that as compared to other TLRs, the TLR3 and TLR4 have a higher docking score.
14.9 Molecular Dynamic Simulation
The molecular dynamic simulation was subjected to all best-docked TLR (Toll-like receptors) against our designed peptide structure. The steepest Descent algorithm was employed for the energy minimization step followed by NVT and NPT Equilibration for 50000 steps each. The simulation was run for 50 nanoseconds to analyze the stability with each other and to analyze the solvent accessibility. RMSD, RG, and SASA were calculated based on the simulation run and protein-peptide stability and observed to be more stable in the last 30ns. TLR2, TLR3, and TLR5 were observed more stable during the full stack 50ns trajectories and can be seen in Figure 9-11.
14.9 Codon Optimization
In order to maximize the amount of protein that can be expressed from the vaccine construct in E. coli (strain K12), codon optimization was performed. The length of the codon sequence that was optimized was 1569 nucleotides. The optimized nucleotide sequence had a CAI of 0.92, which means it was made up of the most commonly occurring codons. The optimized sequence has a GC content of 51.82% on average. The higher the GC concentration, the greater the protein expression in prokaryotes. Employing the SnapGene tool, the nucleotide sequence that had been optimized was cloned into the pET28a (+) vector.
The viral zoonotic illness known as monkeypox has features that are similar to those observed in outbreaks of smallpox in the past, however it is physiologically less severe. It is caused by the monkeypox virus and poses a risk to human health, which has been observed primarily in Africa. However, cases of it have lately been found in other regions of the world, and as a result, it has the potential to evolve into a worldwide public health hazard in a very short span of time. In this project, a multi-epitope subunit vaccine was constructed. This vaccine can cause an immune response against MPXV by using cell envelope protein (A30L) as a target. The goal is to make a new vaccine that is fully secure and has almost no negative complexity. Envelope protein is important for essential bioactivities for MPXV, including viral entry into host, cell-cell fusion, and interaction between the host and the virus.
The provided epitopes need to be associated with the vast majority of ethnically polymorphic MHC I and MHC II alleles and have high population coverage scores for the vaccine to be accepted globally. In this context, the population coverage of projected T lymphocyte-reacting epitopes was assessed. The hypothesized epitopes were associated very significantly with MHC I and MHC II alleles and therefore associated with a variety of different sets of alleles that had high population coverage scores. The envelope polyprotein is observed to have many known epitopes that interact with MHC I and MHC II alleles in T lymphocytes. Antigenic, non-allergic, and nontoxic peptides were selected for use as potential candidates for vaccination. In this study, we found that the proposed epitopes as vaccine candidates might efficiently interact with human common alleles around the globe, which might help in protecting a huge proportion of the global population.
The prediction of MHC class I epitopes is an essential part of vaccine development. In brief, the designated viral constituents of MPXV were put through their paces on a number of different web-based MHC I and II epitope prediction tools. The T cell epitopes were evaluated by internal standards before being proposed for further study. There are two main selection criteria: the candidate antigen or antigens should be sufficiently immunogenic and they should also be topographically accessible to membrane-bound or free antibodies. Hence, we evaluated IC50 values lower than 70 because this substance has significant immunogenicity. As a conclusion of promising results, constructing a vaccine based on the proposed peptides seems to be a high priority, with the potential to be extensively deployed as a universal epitope-based peptide vaccine against MPXV. The humoral immune system's B-lymphocytes play a crucial role in fighting against monkeypox virus antigens as they generate a variety of pathogen-specific and eventually aid in reducing the viral load. The BCPRED service of the IEDB server was employed for the prediction of B-cell epitope of the Monkeypox virus protein (A30L Monkeypox virus Zaire-96-I-16) into the vaccine design. Four conserved epitopes with significant scores were obtained. In this research, T cell MHC I and MHCII epitopes were fused using AAY linkers, whereas MHC I and B cell epitopes were linked using CPGPG linkers. While promoting epitope presentation, CPGPG and AAY linkers also inhibit the development of junctional epitopes. The EAAAK linker increases stability while reducing the linkage with other protein regions. Mycobacterium tuberculosis derived 50S ribosomal protein L7/L12 has been used as an adjuvant to improve the vaccine’s immunogenicity [31, 32] .
According to the secondary structure analysis, the vaccine design contains alpha helices (55.74%), beta strands (9.19%), and random coiled (35.05%) structures. The structural templates from the PDB are first identified by I-TASSER using a multiple-threading technique using LOMETS (Local Meta-Threading Server, version 3), and full-length atomic models are then built using iterative simulations of fragment assembly depending on templates. Additionally, it determines the C-score to assess the predictive models accuracy [33–35]..Molecular docking was performed in HDOCK server. The vaccine complexes TLR4, TLR5, and TLR8 almost have similar docking scores. Based on docking score, TLR3- vaccine construct complex is predicted to be the best complex. For expression and purification, the vaccine construct was cloned into the appropriate vector. The vector pET28a (+) is appropriate for expressing proteins. Codon biasness is a common problem when eukaryotic proteins are expressed on prokaryotic vectors. Therefore, codon optimization was carried out to prevent codon bias. The average GC content of the optimised sequence is 51.82%, while the CAI of the nucleotide sequence was 0.92. These two parameters shows that the vaccine construct will be highly expressed in the vector.
The monkeypox virus has had a detrimental impact on the health of millions of individuals all over the world. It has been responsible for the loss of many lives across several countries. There is not yet a viable therapeutic vaccination that is successful in treating MKXP infections at this time. The current outbreak of MPXV has brought renewed attention to the significance of the vaccine. In this study, we have designed a multi-epitope vaccine that can evoke an immunological response against this vicious MPXV using in silico based immunoinformatic approaches, utilizing A30L envelope protein as a target in order to develop a novel vaccine that is both safe and almost free of side effects. B and T cell epitopes of the A30L protein of MKXP were identified. After determining the Antigenicity, toxicity, and allergenicity of the anticipated epitopes, the epitopes with the best characteristics were combined with the help of suitable linkers and adjuvants. The binding affinity of the vaccine construct with the TLR2, TLR3, TLR4, TLR5, and TLR8 complex was evaluated using molecular docking as well. It was determined that the vaccine that had been designed was not allergic while also being Antigenic, and its physicochemical properties were satisfactory. Through the use of MD simulation, we were able to validate the candidate vaccine's stability. The last step was an analysis of the multi-epitope vaccine's level of expression as well as its translation efficiency. This study revealed a multi-epitope design that demonstrated promising results through in silico steps. These results could be further studied through in vitro and in vivo experiments. Our research will be helpful in the creation of appropriate therapies and will motivate the development of future vaccines against MPXV. This might be a significant step toward the production of an antiviral vaccine against MPXV. Therefore, it is anticipated that the vaccine construct will stimulate the host immune system to produce antibodies against the A30L protein and inhibit the entry of the viral genome into host cells. It is possible that this multi-epitope vaccine will assist in the enhancement of the host immune system’s defenses against MPXV.
Funding
Not Applicable
Conflicts of interest/Competing interests
There is no conflict of interest.
Availability of data and material
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Code availability
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Acknowledgement
The authors would like to acknowledge the Bioinformatics lab facility, BioNome, Bangalore, 560043, India, during the work. The help from Dr. Sameer Sharma and his team, Bioinformatics lab, is also of great importance, particularly during the MD simulation analysis via Desmond Schrodinger part in the manuscript for simulation studies.
- Shafi, A., Wani, A. A., Ul Islam, J., & Peerzada, K. (2022). Monkey pox: What we need to know. Acta Scientific Microbiology, 40–44. https://doi.org/10.31080/asmi.2022.05.1095
- Magnus, P. von, Andersen, E. K., Petersen, K. B., & Birch-Andersen, A. (2009). A pox-like disease in Cynomolgus monkeys. Acta Pathologica et Microbiologica Scandinavica, 46(2), 156–176. https://doi.org/10.1111/j.1699-0463.1959.tb00328.x
- Nih.gov. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2480792/pdf/bullwho00192-0028.pdf
- Likos, A. M., Sammons, S. A., Olson, V. A., Frace, A. M., Li, Y., Olsen-Rasmussen, M., Davidson, W., Galloway, R., Khristova, M. L., Reynolds, M. G., Zhao, H., Carroll, D. S., Curns, A., Formenty, P., Esposito, J. J., Regnery, R. L., & Damon, I. K. (2005). A tale of two clades: monkeypox viruses. The Journal of General Virology, 86(Pt 10), 2661–2672. https://doi.org/10.1099/vir.0.81215-0
- Multi-country monkeypox outbreak: situation update. (n.d.). Who.int. Retrieved September 28, 2022, from https://www.who.int/emergencies/disease-outbreak-news/item/2022-DON390
- Titanji, B. K., Tegomoh, B., Nematollahi, S., Konomos, M., & Kulkarni, P. A. (2022). Monkeypox: A contemporary review for healthcare professionals. Open Forum Infectious Diseases, 9(7), ofac310. https://doi.org/10.1093/ofid/ofac310
- Ashby, K. A. (2022). Monkeypox: Fact or Fiction. Independently Published.
- Kumar, R., Nagar, S., Haider, S., Sood, U., Ponnusamy, K., Dhingra, G. G., Anand, S., Dua, A., Singh, M., Sengar, M., Singh, I. K., & Lal, R. (2022). Monkey pox virus (MPXV): Phylogenomics, host-pathogen interactome, and mutational cascade. In bioRxiv. https://doi.org/10.1101/2022.07.25.501367
- CDC. (2022, August 29). Signs and symptoms. Centers for Disease Control and Prevention. https://www.cdc.gov/poxvirus/monkeypox/symptoms/index.html
- Islam, M. R., Hossain, M. J., Roy, A., Hasan, A. H. M. N., Rahman, M. A., Shahriar, M., & Bhuiyan, M. A. (2022). Repositioning potentials of smallpox vaccines and antiviral agents in monkeypox outbreak: A rapid review on comparative benefits and risks. Health Science Reports, 5(5), e798. https://doi.org/10.1002/hsr2.798
- Shchelkunov, S. N., Totmenin, A. V., Safronov, P. F., Mikheev, M. V., Gutorov, V. V., Ryazankina, O. I., Petrov, N. A., Babkin, I. V., Uvarova, E. A., Sandakhchiev, L. S., Sisler, J. R., Esposito, J. J., Damon, I. K., Jahrling, P. B., & Moss, B. (2002). Analysis of the monkeypox virus genome. Virology, 297(2), 172–194. https://doi.org/10.1006/viro.2002.1446
- Doytchinova, I. A., & Flower, D. R. (2007a). Identifying candidate subunit vaccines using an alignment-independent method based on principal amino acid properties. Vaccine, 25(5), 856–866. https://doi.org/10.1016/j.vaccine.2006.09.032
- Doytchinova IA, Flower DR. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics [Internet]. 2007;8(1):4. Available from: http://dx.doi.org/10.1186/1471-2105-8-4
- Gupta, S., Kapoor, P., Chaudhary, K., Gautam, A., Kumar, R., Open Source Drug Discovery Consortium, & Raghava, G. P. S. (2013). In silico approach for predicting toxicity of peptides and proteins. PloS One, 8(9), e73957. https://doi.org/10.1371/journal.pone.0073957
- Dimitrov, I., Bangov, I., Flower, D. R., & Doytchinova, I. (2014). AllerTOP v.2--a server for in silico prediction of allergens. Journal of Molecular Modeling, 20(6), 2278. https://doi.org/10.1007/s00894-014-2278-5
- Jespersen, M. C., Peters, B., Nielsen, M., & Marcatili, P. (2017). BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes. Nucleic Acids Research, 45(W1), W24–W29. https://doi.org/10.1093/nar/gkx346
- Nielsen, M., Lundegaard, C., Worning, P., Lauemøller, S. L., Lamberth, K., Buus, S., Brunak, S., & Lund, O. (2003). Reliable prediction of T-cell epitopes using neural networks with novel sequence representations. Protein Science: A Publication of the Protein Society, 12(5), 1007–1017. https://doi.org/10.1110/ps.0239403
- Lundegaard, C., Lamberth, K., Harndahl, M., Buus, S., Lund, O., & Nielsen, M. (2008). NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11. Nucleic Acids Research, 36(Web Server issue), W509-12. https://doi.org/10.1093/nar/gkn202
- Kolaskar, A. S., & Tongaonkar, P. C. (1990). A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Letters, 276(1–2), 172–174. https://doi.org/10.1016/0014-5793(90)80535-q
- Jensen, K. K., Andreatta, M., Marcatili, P., Buus, S., Greenbaum, J. A., Yan, Z., Sette, A., Peters, B., & Nielsen, M. (2018). Improved methods for predicting peptide binding affinity to MHC class II molecules. Immunology, 154(3), 394–406. https://doi.org/10.1111/imm.12889
- Bui, H.-H., Sidney, J., Dinh, K., Southwood, S., Newman, M. J., & Sette, A. (2006). Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinformatics, 7(1), 153. https://doi.org/10.1186/1471-2105-7-153
- Kar, T., Narsaria, U., Basak, S., Deb, D., Castiglione, F., Mueller, D. M., & Srivastava, A. P. (2020). A candidate multi-epitope vaccine against SARS-CoV-2. Scientific Reports, 10(1), 10895. https://doi.org/10.1038/s41598-020-67749-1
- Naz, A., Shahid, F., Butt, T. T., Awan, F. M., Ali, A., & Malik, A. (2020). Designing multi-Epitope vaccines to combat emerging Coronavirus disease 2019 (COVID-19) by employing immuno-informatics approach. Frontiers in Immunology, 11, 1663. https://doi.org/10.3389/fimmu.2020.01663
- Samad, A., Ahammad, F., Nain, Z., Alam, R., Imon, R. R., Hasan, M., & Rahman, M. S. (2022). Designing a multi-epitope vaccine against SARS-CoV-2: an immunoinformatics approach. Journal of Biomolecular Structure & Dynamics, 40(1), 14–30. https://doi.org/10.1080/07391102.2020.1792347
- Buchan, D. W. A., & Jones, D. T. (2019). The PSIPRED Protein Analysis Workbench: 20 years on. Nucleic Acids Research, 47(W1), W402–W407. https://doi.org/10.1093/nar/gkz297
- Roy, A., Kucukural, A., & Zhang, Y. (2010). I-TASSER: a unified platform for automated protein structure and function prediction. Nature Protocols, 5(4), 725–738. https://doi.org/10.1038/nprot.2010.5
- Ferrè, F., & Clote, P. (2005). DiANNA: a web server for disulfide connectivity prediction. Nucleic Acids Research, 33(Web Server issue), W230-2. https://doi.org/10.1093/nar/gki412
- Yan, Y., Tao, H., He, J., & Huang, S.-Y. (2020). The HDOCK server for integrated protein-protein docking. Nature Protocols, 15(5), 1829–1852. https://doi.org/10.1038/s41596-020-0312-x
- Yan, Y., Zhang, D., Zhou, P., Li, B., & Huang, S.-Y. (2017). HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy. Nucleic Acids Research, 45(W1), W365–W373. https://doi.org/10.1093/nar/gkx407
- Mauro, V. P. (2018). Codon optimization in the production of recombinant biotherapeutics: Potential risks and considerations. BioDrugs: Clinical Immunotherapeutics, Biopharmaceuticals and Gene Therapy, 32(1), 69–81. https://doi.org/10.1007/s40259-018-0261-x
- Arai, R., Ueda, H., Kitayama, A., Kamiya, N., & Nagamune, T. (2001). Design of the linkers which effectively separate domains of a bifunctional fusion protein. Protein Engineering, 14(8), 529–532. https://doi.org/10.1093/protein/14.8.529
- Pandey, R. K., Narula, A., Naskar, M., Srivastava, S., Verma, P., Malik, R., Shah, P., & Prajapati, V. K. (2017). Exploring dual inhibitory role of febrifugine analogues against Plasmodium utilizing structure-based virtual screening and molecular dynamic simulation. Journal of Biomolecular Structure & Dynamics, 35(4), 791–804. https://doi.org/10.1080/07391102.2016.1161560
- Zheng, W., Zhang, C., Li, Y., Pearce, R., Bell, E. W., & Zhang, Y. (2021). Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations. Cell Reports Methods, 1(3), 100014. https://doi.org/10.1016/j.crmeth.2021.100014
- Yang, J., Yan, R., Roy, A., Xu, D., Poisson, J., & Zhang, Y. (2015). The I-TASSER Suite: protein structure and function prediction. Nature Methods, 12(1), 7–8. https://doi.org/10.1038/nmeth.3213
- Yang, J., & Zhang, Y. (2015). I-TASSER server: new development for protein structure and function predictions. Nucleic Acids Research, 43(W1), W174-81. https://doi.org/10.1093/nar/gkv342
- Adler, H., Gould, S., Hine, P., Snell, L. B., Wong, W., Houlihan, C. F., Osborne, J. C., Rampling, T., Beadsworth, M. B., Duncan, C. J., Dunning, J., Fletcher, T. E., Hunter, E. R., Jacobs, M., Khoo, S. H., Newsholme, W., Porter, D., Porter, R. J., Ratcliffe, L., … NHS England High Consequence Infectious Diseases (Airborne) Network. (2022). Clinical features and management of human monkeypox: a retrospective observational study in the UK. The Lancet Infectious Diseases, 22(8), 1153–1162. https://doi.org/10.1016/S1473-3099(22)00228-6
- Gasteiger, E., Hoogland, C., Gattiker, A., Duvaud, S., Wilkins, M. R., Appel, R. D., & Bairoch, A. (2005). Protein identification and analysis tools on the ExPASy server. In The Proteomics Protocols Handbook (pp. 571–607). Humana Press.
No competing interests reported.