In Silico Prediction of a Novel Universal Multi-epitope Peptide Vaccine in the Whole Spike Glycoprot...

Marwan Mustafa Badawi, Maryam Atif SalahEldin, Marwa Mustafa Suliman, Samah Awad AbduRahim, Alaa Abd elghafoor Mohammed, Alaa Salah Aldein SidAhmed, Marwa Mohamed Osman, Mohamed Ah...

American Journal of Microbiological Research

In Silico Prediction of a Novel Universal Multi-epitope Peptide Vaccine in the Whole Spike Glycoprotein of MERS CoV

Marwan Mustafa Badawi1,,#, Maryam Atif SalahEldin2,#, Marwa Mustafa Suliman3,#, Samah Awad AbduRahim2,##, Alaa Abd elghafoor Mohammed1,##, Alaa Salah Aldein SidAhmed1, Marwa Mohamed Osman1, Mohamed Ahmed Salih1

1Department of Biotechnology, Africa city of Technology- Khartoum, Sudan

2Department of medical microbiology, Faculty of Medical Laboratory Sciences, University of Khartoum-Khartoum, Sudan

3Sudan Armed forces hospital- Khartoum, Sudan

#contributed equally.

##contributed equally.

Abstract

Middle East Respiratory Syndrome (MERS) is a new viral emergent human disease caused by a novel strain of Coronavirus. First known case of MERS occurred in Jordan in April 2012, by December 2015, the disease had already struck 1,621 persons of whom 584 died. Despite of the high mortality rate of the infection, there are no clinically approved vaccines or antiviral drugs, thus, the aim of this study is to analyze Spike glycoprotein strains using in silico approaches looking for conservancy, which is further studied to predict all potential epitopes that can be used after in vitro and in vivo confirmation as a therapeutic peptide vaccine. Total of 255 Spike glycoprotein variants retrieved from NCBI database were aligned, to select the conserved regions for epitopes prediction. By means of IEDB analysis resource B and T cell epitopes were predicted and population coverage was calculated. Two epitopes were proposed for international therapeutic peptide vaccine for B cell (GTPPQVY and LTPRSVRSVP). Regarding T cell, FSFGVTQEY epitope was highly recommended as therapeutic peptide vaccine to interact with MHC class I along with eight other epitopes that showed good population coverage against the whole world population. Four epitopes showed high affinity to interact with MHC class II alleles (FNLTLLEPV, FAAIPFAQS, SFAAIPFAQ and FYVYKLQPL) with excellent population coverage throughout the world and Saudi Arabia. Herd immunity protocols can be conducted in countries with low population coverage to minimize the active transmission of the virus especially among people contacting camels and other groups at risk.

Cite this article:

  • Marwan Mustafa Badawi, Maryam Atif SalahEldin, Marwa Mustafa Suliman, Samah Awad AbduRahim, Alaa Abd elghafoor Mohammed, Alaa Salah Aldein SidAhmed, Marwa Mohamed Osman, Mohamed Ahmed Salih. In Silico Prediction of a Novel Universal Multi-epitope Peptide Vaccine in the Whole Spike Glycoprotein of MERS CoV. American Journal of Microbiological Research. Vol. 4, No. 4, 2016, pp 101-121. http://pubs.sciepub.com/ajmr/4/4/2
  • Badawi, Marwan Mustafa, et al. "In Silico Prediction of a Novel Universal Multi-epitope Peptide Vaccine in the Whole Spike Glycoprotein of MERS CoV." American Journal of Microbiological Research 4.4 (2016): 101-121.
  • Badawi, M. M. , SalahEldin, M. A. , Suliman, M. M. , AbduRahim, S. A. , Mohammed, A. A. E. , SidAhmed, A. S. A. , Osman, M. M. , & Salih, M. A. (2016). In Silico Prediction of a Novel Universal Multi-epitope Peptide Vaccine in the Whole Spike Glycoprotein of MERS CoV. American Journal of Microbiological Research, 4(4), 101-121.
  • Badawi, Marwan Mustafa, Maryam Atif SalahEldin, Marwa Mustafa Suliman, Samah Awad AbduRahim, Alaa Abd elghafoor Mohammed, Alaa Salah Aldein SidAhmed, Marwa Mohamed Osman, and Mohamed Ahmed Salih. "In Silico Prediction of a Novel Universal Multi-epitope Peptide Vaccine in the Whole Spike Glycoprotein of MERS CoV." American Journal of Microbiological Research 4, no. 4 (2016): 101-121.

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1. Introduction

Middle East respiratory syndrome (MERS) is a new viral emergent human disease caused by a novel coronavirus called Middle East Respiratory Syndrome Coronavirus (MERS-CoV) [1]. Although the disease was first reported in the Kingdom of Saudi Arabia (KSA) when the virus was isolated from a patient with fatal pneumonia and acute kidney injury in Jeddah in June 2012, however, through retrospective investigations, health officials later identified that the first known cases of MERS occurred in Jordan in April 2012 [2, 3, 4, 5, 6]. In September 2012 the World Health Organization (WHO) reported two cases of severe community-acquired pneumonia caused by MERS-CoV [7]. By December 2015, the disease had already struck 1,621 persons of whom 584 died from respiratory failure and diarrhea majority of them were reported from the Arabian Peninsula, with one large outbreak involving 186 cases in the Republic of Korea; infection is typically associated with considerable morbidity and mortality [8, 9, 10, 11].

Most infections were geographically linked to the Middle East, i.e., Jordan, Saudi Arabia, Qatar, and United Arab Emirates (UAE), but cases also occurred in the United Kingdom, Germany, France, and Italy [12]. As known cases have been directly or indirectly related to countries in the Arabian Peninsula, all cases of MERS have been linked through travel to or residence in countries in this region [6, 13]. Dromedary camels (Camelus dromedarius) were implicated for the first time as a possible source for human infection on the basis of the presence of MERS-CoV neutralizing antibodies in dromedaries from Oman and the Canary Islands of Spain. Since then, the presence of MERS-CoV antibodies in dromedaries has been reported in Jordan, Egypt, UAE and KSA [14]. MERS affects the respiratory system (lungs and breathing tubes). Most MERS patients developed severe acute respiratory illness with symptoms of fever, cough and shortness of breath. About 3-4 out of every 10 patients reported with MERS have died [6].

As all coronaviruses, MERS-CoV has a non segmented, single stranded, positive polarity RNA genome. It is an enveloped virus with a helical nucleocapsid. There is no virion polymerase. In the electron microscope, prominent club-shaped spikes in the form of a “corona” (halo) can be seen [15]. The MERS-CoV genome contains 30,119 nucleotides and contains at least 10 predicted open reading frames, 9 of which are predicted to be expressed from a nested set of seven subgenomic mRNAs [16].

Among the structural proteins of MERS-CoV, the spike (S) glycoprotein plays the most important roles in virus infection and pathogenesis as it uses a novel coronavirus receptor for entry and is targeted by neutralizing antibodies, thus, it is considered to be a promising target for effective MERS vaccine design [17, 18]. More importantly, T-cell-based cellular immunity is essential for cleaning MERS-CoV infection, yet the vaccine against the S protein mainly elicits neutralizing antibody response. Further, the high mutation rate of the S protein may result in the escape of neutralizing antibodies against MERS-CoV. Therefore, a highly conserved target that elicits both neutralizing antibody and cellular immunity against MERS-CoV is essential for an effective vaccine development [19].

Although the mortality of the infection is alarming (30-50%), as is its uncanny resemblance-at least in its clinical features to severe acute respiratory syndrome (SARS), there are no clinically approved vaccines or antiviral drugs available for either of these infections; thus, the development of effective therapeutic and preventive strategies that can be readily applied to new emergent strains is a research priority to save human lives and address the pandemic concerns [20, 21, 22, 23]. Past efforts to develop coronavirus vaccines have used whole-inactivated virus, live-attenuated virus, recombinant protein subunit or genetic approaches [24]. Although these methods are useful for vaccine development and successful in many cases, but they are time-consuming and fail when the pathogens cannot be cultivated in vitro, or when the most abundant antigens are variable in sequence. Now genomic approaches allow prediction of all antigens independent of their abundance and immunogenicity during infection, without the need to grow the pathogen in vitro [25]. The use of peptides as therapeutics is experiencing renewed enthusiasm owing to advances in delivery, stability and design. Moreover, there is a growing emphasis on the use of peptides in vaccine design as insights into tissue-specific processing of the immunogenic epitopes of proteins and the discovery of unusually long cytotoxic T-lymphocyte epitopes broaden the range of targets and give clues to enhancing peptide immunogenicity [26].

In this study, an immunoinformatics-driven genome-wide screening strategy of vaccine targets was adopted to identify a multi-epitope vaccine candidate against whole S glycoprotein of MERS-CoV that could be suitable to trigger a significant humoral and cellular immune response.

2. Materials and Methods

2.1. Protein Sequence Retrieval

A total of 255 Spike glycoprotein of MERS CoV were retrieved from NCBI (http://www.ncbi.nlm.nih.gov/protein/) database in April 2016, and collected from different parts of the world; 184 isolates were collected in Saudi Arabia, twenty-three in United Arab Emirates, twenty-two in South Korea, and the rest were isolated in different countries; Oman, China, USA, United Kingdom, Greece, Qatar, Egypt, Tunisia, France, Thailand and Nigeria. Retrieved strains, their accession numbers and date of collection are listed in supplementary table (S1).

2.2. Determination of Conserved Regions

The retrieved sequences were used as a platform to obtain conserved regions using multiple sequence alignment (MSA). Sequences aligned with the aid of ClustalW as implemented in the BioEdit program, version 7.0.9.0. [27]

2.3. B-cell Epitope Prediction:

B cell epitope is characterized by being hydrophilic, accessible and in a beta turn region. Thus, the classical propensity scale methods and hidden Markov model programmed softwares from IEDB analysis resource (http://www.iedb.org/), were used for the following aspects: [28, 29]

Prediction of linear B-cell Epitopes: BepiPred from immune epitope database (http://toolsiedb.ofg/bcell/) [30] was used as linear B-cell epitope prediction from the conserved region with a default threshold value of 0.350.

Prediction of surface accessibility: by using Emini surface accessibility prediction tool of the immune epitope database (IEDB) [31], the surface accessible epitopes were predicted from the conserved regions holding the default threshold value 1.000 or higher.

Prediction of Epitopes antigenicity sites: the kolaskar and tongaonker antigenicity method [32] was used to determine the antigenic sites with a default threshold value of 1.045.

Prediction of epitopes hydrophilicity: parker hydrophilicity prediction tool [33] was used to determine the hydrophilicity of the conserved regions; the threshold default value was 1.286.

Prediction of beta turns sites: Chou and Fasman beta turn prediction method was used with the default threshold 1.009 to determine the sites contain beta turns.

Thresholds of all tool were provided by IEDB and it is mainly calculated by the software as the average score of the tested protein for each corresponding tool.

2.4. MHC Class I Binding Predictions

Analysis of peptide binding to MHC class I molecules was assessed by the IEDB MHC I prediction tool http://tools.iedb.org/mhci/n, for MHC-I binding predication, several alleles were used including HLA-A*02, HLA-B*51, HLA-B*50, HLA-B*08, HLA-C*07 , HLA-C*06 and HLA-C*15 that have been reported as frequent among Saudis.[34, 35, 36, 37, 38] MHC-I peptide complex presentation to T lymphocytes undergo several steps. The attachment of cleaved peptides to MHC molecules step was predicted. prediction methods can be achieved by Artificial Neural Network (ANN), Stabilized Matrix Method (SMM), or Scoring Matrices derived from Combinatorial Peptide Libraries. Consensus method which combines ANN, SMM and comblib different methods was used [39, 40, 41, 42, 43]. Prior to prediction, all epitope lengths were set as 9mers, all internationally conserved epitopes that bind to alleles at score equal or less than 1.0 percentile rank were selected for further analysis. [44]

2.5. MHC Class II Binding Predictions

Analysis of peptide binding to MHC class II molecules was assessed by the IEDB MHC II prediction tool http://tools.immuneepitope.org/mhcii/ [45, 46]. For MHC-II binding predication, the reference set of alleles were used which include HLA-DQB1*02, HLA-DQB1*03, HLA-DQB1*06, HLA-DRB1*07, HLA-DRB1*04 and HLA-DRB1*03 that are reported to be frequent among Saudis [34, 35, 36, 37, 38]. MHC class II groove has the ability to bind to peptides with different lengths, this variability in binding makes prediction as difficult as less accurate [47]. There are four prediction methods for IEDB MHC II prediction tool: ARB, SMM_align, Sturniolo's method and a consensus method. ARB predict IC 50 values through combination of searches different peptide sizes and alleles into a single global prediction based on ARB matrices. SMM-align is a matrix-based method with extensions incorporating flanking residues outside of binding grooves. It also predicts the IC50 values of peptides. The consensus approach was used which combines the outcome of the three methods. Firstly, a random scan set of Swiss-Prot proteins and achieve scores for 2,000,000 random peptides, thereafter, act as reference to rank new predictions. The consensus method uses the median rank of the three approaches as the final prediction score [48]. All internationally conserved epitopes that bind to alleles at score equal or less than 10 percentile rank were selected for further analysis.

2.6. Population Coverage Calculation

All potential MHC I and MHC II binders from Spike glycoprotein were assessed for population coverage against the whole world population and Saudi Arabia, and other populations that had been reported MERS CoV cases. Calculations achieved using the selected MHC-I and MHC-II interacted alleles by the IEDB population coverage calculation tool http://tools.iedb.org/tools/population/iedb_input [49].

2.7. Homology Modeling

The complete 3D structure of Spike glycoprotein was obtained by phyre2, (http://www.sbg.bio.ic.ac.uk/phyre2) which uses advanced remote homology detection methods to build 3D models. UCSF Chimera (version 1.8) was used to visualize the 3D structure, which is currently available within the Chimera package and available from the chimera web site (http://www.cgl.ucsf.edu/cimera). Homology modeling was achieved for further verification of the service accessibility and hydrophilicity of B lymphocyte epitopes predicted, as well as visualization of all predicted T cell epitopes in the structural level [50, 51].

Figure 1. Prediction of B-cell epitopes by different scales

3. Results

3.1. Prediction of B-cell Epitopes

Spike glycoprotein was subjected to Bepipred linear epitope prediction, Emini surface accessibility, Kolaskar and Tongaonkar antigenicity, Parker hydrophobicity and Chou and Fasman beta turn prediction methods in IEDB, Figure 1.

In Bepipred Linear Epitope Prediction method; the average binders score of Spike glycoprotein to B cell was 0.35, all values equal or greater than the default threshold 0.35 were predicted to be potential B cell binders.

In Emini surface accessibility prediction; the average surface accessibility areas of the protein was scored as 1.000, all values equal or greater than the default threshold 1.0 were regarded potentially in the surface.

The default threshold of antigenicity of the protein was 1.045; all values greater than 1.045 were considered as potential antigenic determinants.

In Parker hydrophilicity prediction; the average hydrophilicity score of the protein was 1.286, all values equal or greater than the default threshold 1.286 were potentially hydrophilic.

Two internationally conserved epitopes had succeeded all prediction methods, epitope GTPPQVY from 391 to 397 was found to have the highest score, followed by LTPRSVRSVP from 745 to 754. The result is summarized in Table 1 and proposed epitopes are shown in Figure 2 at the structural level of the spike protein.

Table 1. list of B- cell epitopes predicted by different scales

The Chou and Fasman beta turn prediction method was used with the default threshold 1.009, for more confirmation of the prediction.

3.2. Prediction of Cytotoxic T-lymphocyte Epitopes and Interaction with MHC Class I

Based on Consensus (ann/smm/comblib_sidney2008) with percentile rank ≤1, 123 epitopes were predicted to interact with different MHC I alleles. The epitope FSFGVTQEY showed high affinity to interact with 9 alleles. All epitopes and their corresponding MHC-1 alleles are shown in Table 2. Figure 3 displays epitopes in the structural level.

Table 2. list of epitopes that have binding affinity with the MHC Class I alleles

Figure 3. proposed T-Cell epitopes that interact with MHC Class I
3.3. Prediction of T Helper Cell Epitopes and Interaction with MHC Class II

Based on Consensus (smm/nn/sturniolo) with percentile rank ≤10, there were 374 predicted epitopes found to interact with MHC-II alleles [data not shown] from which the peptide (core) FNLTLLEPV shows very high binding affinity to 26 alleles. The promiscuous epitopes and those which bind more than twelve different alleles are summarized in Table 3. Figure 4 displays epitopes in the structural level.

Table 3. list of epitopes that have binding affinity with ≥12 Class II alleles

Figure 4. proposed T-Cell epitopes that interact with MHC Class II
3.4. Analysis of the Population Coverage

Epitopes that are suggested interacting with MHC-I and II alleles especially high affinity binding epitopes and that can bind to different set of alleles were selected for population coverage analysis. The results of population coverage of proposed epitopes are listed in Table 4.

In MHC class I, three epitopes that interact with most frequent MHC class I alleles (ITYQGLFPY, FSFGVTQEY and KLQPLTFLL) gave high percentage against the whole world population by IEDB population coverage tool. The population coverage of FSFGVTQEY and IAFNHPIQV show good coverage among Saudis (60.35% and 54.70%) respectively, Table 5 represents the population coverage for the proposed epitopes and shows their corresponding coverage percentage.

Also in MHC class II, four epitopes that interact with most frequent MHC class II alleles (FNLTLLEPV, FAAIPFAQS, SFAAIPFAQ and FYVYKLQPL) gave high percentage against the whole world population by IEDB population coverage tool. The population coverage for these proposed epitopes is excellent internationally as (99.99%) as well as Saudi Arabia (99.62%) and (100%) in England. Table 5 represents the proposed epitopes. FNLTLLEPV which binds to DQB1*02:01 and DQB1*03:02 that is reported in high frequency in Saudi Arabia was found to definitely increase the population coverage in Saudi Arabia as seen in tables (5A, B and C).

Table 4. population coverage of all epitopes in both MHC class I and II in the world

Table (5A). population coverage for Class I proposed epitopes for selected regions

Table (5B). population coverage for Class II proposed epitopes for selected regions

Table (5C). population coverage for Class I proposed epitopes for selected regions

Table 6. population coverage for Class II proposed epitopes for selected regions

4. Discussion

Vaccination has proven to be the mainstay in prevention of various deadly infectious diseases. Historically, live-attenuated or inactivated forms of microbial pathogens (viruses, bacteria, etc.) have been used for induction of immune responses that protect the host against the subsequent infections, such vaccine might contain unnecessary proteins for the induction of protective immunity and may lead to allergenic responses, This has created an interest in peptide vaccines containing only epitopes capable of inducing positive, desirable T cell and B cell mediated immune responses. There are many peptide vaccines under development, such as vaccine for human immunodeficiency virus (HIV), hepatitis C virus (HCV), malaria, foot and mouth disease, swine fever, influenza, anthrax, human papilloma virus (HPV), therapeutic anti-cancer vaccines pancreatic cancer, melanoma, non-small cell lung cancer, advanced hepatocellular carcinoma cutaneous T-cell lymphoma and B-Cell chronic lymphocytic leukemia. [52-69][52]

In this study, we aimed to determine the highly potential immunogenic epitopes for B and T cells - the prime molecules of cell mediated and humoral immunity - as vaccine candidates for the highly lethal MERS coronaviral infection using the whole Spike glycoprotein as a target. Unlike previous studies and for better determination of the best candidate epitopes; all S protein was under investigation not only the receptor binding domain (RBD). Both complete S protein and RBD were in vitro and in vivo proven to elicit B lymphocyte to produce antibodies [12,70-75], therefore, we conducted this study to propose epitopes that would be enough to select out of these large non conserved domains to hopefully achieve the same result.

Conservancy in S protein in MERS CoV was found promising for peptide vaccine design, however, Tuhin ali et al found that a peptide region of 367-606 (which is the receptor binding domain) remained conserved, unlike our findings which showed that this region is no longer conserved, this region is no longer conserved, Tuhin ali et al,.2014 also found epitope CYSSLILDY interacting with 11 different MHC I alleles at threshold IC50 ≤ 100 and percentile rank ≤ 1, while we found this epitope only interacting with one allele as illustrated in Table 1, furthermore, this epitope was not predicted as B lymphocyte in our study [76].

To determine a potential and effective peptide antigen for B cell, epitopes should get above threshold scores in Bepipred linear epitope prediction, Emini surface accessibility, Parker hydrophobicity, Kolaskar and Tongaonkar antigenicity and Chou and Fasman beta turn prediction methods in IEDB. Epitopes illustrated in Table 1, are the only conserved regions from all retrieved strains of MERS coronavirus Spike glycoprotein that are available in NCBI database until 15th April 2016 and have high probability of activating humoral immune response. In the RBD, the only conserved epitope that was found activating B lymphocyte immune response was the 7mer epitope 391 GTPPQVY 397. LTPRSVRSVP epitope is located in S2 domain, and was the only conserved epitope that was found passing the thresholds in S2 domain of Spike glycoprotein.

Wang, L. et al had found important residues in RBD, that if mutated will affect the binding of RBD with the neutralizing antibody; 535W and 536E. 535W is conserved residue, the following 536E residue is not conserved as only one Spike glycoprotein retrieved in this study (gb/ALJ76286), collected from Taif - Saudi Arabia in 2014, is showing novel mutation in this residue. Although, these residues are no longer located in conserved peptide, a focus needs to be targeted to this region as they show high score in bepipred prediction tool [77].

Since the immune response of T cell is long lasting response comparing with B cell, where the antigen can easily escape the antibody memory response [54]. Additionally, CD8+ T and CD4+ T cell responses play a major role in antiviral immunity [55], designing of vaccine against T cell epitope is much more promising. For MHC Class I Alleles prediction, we chose the most common HLA-A and HLA-B alleles [56], and according to several studies in the allele frequencies among Saudis ( the most endemic area) the highest frequency of HLA-A was observed for A*02, followed by A*68, A*24, and A*26, for HLA-B locus, B*51, B*50, and B*08 represent very high frequency, the highest observed frequencies for HLA-C were C*07, C*06 , and C*15, whereas for MHC II, DQB1*02, DQB1*03, and DQB1*06 were representing the highly frequent alleles. The binding affinity of those alleles with all of the conserved epitopes of S protein was examined [34, 35, 36, 37, 38].

Among 123 internationally conserved T cell epitopes predicted to interact with MHC Class I as shown in Table 2, ITYQGLFPY and FSFGVTQEY were found to interact with 9 alleles (HLA-A*29:02, HLA-B*46:01, HLA-A*30:02, HLA-A*01:01, HLA-A*11:01, HLA-A*26:01, HLA-B*15:01, HLA-B*58:01, HLA-A*25:01) and (HLA-B*46:01, HLA-A*01:01, HLA-B*35:01, HLA-A*29:02, HLA-A*26:01, HLA-C*06:02, HLA-A*25:01, HLA-B*15:01, HLA-B*58:01) respectively. IAFNHPIQV was found to bind with the HLA-B*51:01, HLA-C*06:02 that are highly frequent among Saudis as well as AAIPFAQSI which interact with the HLA-C*15:02. (FSFGVTQEY, MEAAYTSSL, SVRNLFASV, KLQPLTFLL, IAFNHPIQV and GLYFMHVGY) among the proposed MHCI binders are located in S2 domain, and only LSMKSDLSV is found to be located in RBD.

We found that 374 internationally conserved epitopes in S glycoprotein interact with MHC-II alleles as represented in Table 3. Epitope FNLTLLEPV is showing very high binding affinity to 26 MHC II alleles (HLA-DPA1*03:01, HLA-DPB1*04:02, HLA-DPA1*02:01, HLA-DPB1*01:01, HLA-DRB1*04:05, HLA-DRB1*09:01, HLA-DQA1*01:01, HLA-DQB1*05:01, HLA-DPA1*01:03, HLA-DPB1*02:01, HLA-DQA1*03:01, HLA-DQB1*03:02, HLA-DRB5*01:01, HLA-DRB1*03:01, HLA-DRB1*11:01, HLA-DRB1*01:01, HLA-DRB1*12:01, HLA-DPA1*01:03, HLA-DPB1*02:01, HLA-DPA1*01, HLA-DPB1*04:01, HLA-DQA1*05:01, HLA-DQB1*02:01, HLA-DRB1*07:01, HLA-DRB3*01:01, HLA-DRB1*13:02) among which highly frequent alleles in Saudis, this epitope alone showed 99.79% coverage in the world, 98.92% in Saudi Arabia and 99.82% in England. FYVYKLQPL, FAAIPFAQS and SFAAIPFAQ also showed very high binding affinity. FNLTLLEPV, FAAIPFAQS and SFAAIPFAQ are all located in S2 domain. All proposed MHC I and MHC II epitopes as illustrated in Table 5, Table 6 were better chosen to serve the best population coverage percentage as well as the lowest number of peptides to be used as multi epitope vaccines against Middle East Respiratory Syndrome.

5. Conclusion

Conventional peptide vaccine development methods are costly, and time consuming, insilico prediction is highly appreciated as it selects specific peptides in protein, which then tested in vitro and in vivo to verify and prove the effectiveness of the proposed epitopes to induce an immune response, as well as to be used as a diagnostic screening test. Herd immunity protocols can be conducted in countries with low population coverage to minimize the active transmission of the virus, especially among people contacting camels and other groups at risk. Ultimately, a vaccine needs to target a broad set of zoonotic CoVs, because the emergence of two zoonotic CoV infections in 10 years suggests that this will happen repeatedly.

Acknowledgments

Authors would like to thank African City of Technology members for their cooperation.

Competing Interest

The authors declare that they have no competing interests.

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**Supplementary material**

Table (S1). Spike Glycoprotein strains retrieved, accession numbers and date of collection

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