Epitope‐based peptide vaccine design and target site depiction against Middle East Respiratory Syndrome Coronavirus: an immune-informatics study
Middle East Respiratory Syndrome Coronavirus (MERS-COV) is the main cause of lung and kidney infections in developing countries such as Saudi Arabia and South Korea. This infectious single-stranded, positive (+) sense RNA virus enters the host by binding to dipeptidyl-peptide receptors. Since no vaccine is yet available for MERS-COV, rapid case identification, isolation, and infection prevention strategies must be used to combat the spreading of MERS-COV infection. Additionally, there is a desperate need for vaccines and antiviral strategies.
The present study used immuno-informatics and computational approaches to identify conserved B- and T cell epitopes for the MERS-COV spike (S) protein that may perform a significant role in eliciting the resistance response to MERS-COV infection.
Many conserved cytotoxic T-lymphocyte epitopes and discontinuous and linear B-cell epitopes were predicted for the MERS-COV S protein, and their antigenicity and interactions with the human leukocyte antigen (HLA) B7 allele were estimated. Among B-cell epitopes, QLQMGFGITVQYGT displayed the highest antigenicity-score, and was immensely immunogenic. Among T-cell epitopes, MHC class-I peptide YKLQPLTFL and MHC class-II peptide YCILEPRSG were identified as highly antigenic. Furthermore, docking analyses revealed that the predicted peptides engaged in strong bonding with the HLA-B7 allele.
The present study identified several MERS-COV S protein epitopes that are conserved among various isolates from different countries. The putative antigenic epitopes may prove effective as novel vaccines for eradication and combating of MERS-COV infection.
KeywordsMERS-COV Spike protein T-and B-cell epitopes Computational approaches Vaccine design
Middle East Respiratory Syndrome Coronavirus
National Centre for Biotechnology Information
Protein Data Bank
major histocompatibility complex
Middle East Respiratory Syndrome-Coronavirus (MERS-COV), an extremely fatal respiratory infection was identified in 2012, when more than 90 cases were reported around the globe . Since then, MERS-COV keeps on being a danger to worldwide human health and reported in 27 other countries including Jordan, Qatar, Germany, United Kingdom, Italy, Tunisia and France . As of December-2018, total 2266 laboratory affirmed cases and 804 deaths with approximate 35.5% primitive–case casualty rate was accounted by world health organization (WHO). Solely Saudi Arabia were reported major figures of 1888 cases and 730 deaths .
The incubation period for MERS-COV is approximately 5 or 6 days and the fatality rate is ~ 30 to 40% . Patients with severe acute respiratory illness caused by MERS-COV infection exhibit symptoms like coughing, fever, shortness of breath, diarrhoea, nausea/vomiting, highly lethal pneumonia, and kidney infection in most severe forms . MERS-COV can create acute respiratory distress syndrome (ARDS) and have a higher chance of patient’s death from multi-organ failure, stubborn hypoxaemia and septic stun . According to recent research, people with comorbidities including chronic lung disease, heart and kidney disease, cancer and diabetes are more likely to become infected with MERS, people with a weakened immunity system are also at higher danger of infection [3, 7]. Various mammalian and avian hosts can be infected with coronaviruses causing respiratory, enteric, hepatic or neurological diseases , and animals exposure with MERS-COV include camels, marmosets and macaques .
At present, no specific therapeutic agent or vaccine is available on the market for the treatment of MERS infections . Inhibition of MERS-COV by type-I interferons (IFNα and especially IFNβ) has been proposed based on experiments on cultured cells; lung injury can be reduced by a combination of ribavirin and IFNα2b, and within 8 h of virus immunization the lung titre is decreased in rhesus macaques [9, 12]. Developing an effective treatment for MERS is therefore a research priority. To this end, immuno-informatics can be applied for deep analysis of viral antigens, forecast of conformational (discontinuous) and linear epitopes, evaluation of immunogenicity, and virulence of pathogens. Furthermore, an immuno-informatics approach may save time and cost when designing novel vaccines against viruses, and the use of kits and related antibodies can be reduced [13, 14]. Therefore, using this approach, the main aim of the current study was to identify potential B- and T-cell epitope(s) based on envelope and nucleocapsid proteins that could be used to develop promising vaccines . Extreme respiratory infection may also be recovered by T-cell and antibody reactions . In addition, fast recognition and isolation, disease prevention, and control steps are crucial for preventing the MERS-COV transmission in households, communities, and healthcare offices [16, 17]. The main aim of the current study was to identify the potential B-cell and T-cell epitope(s) from the envelope S protein that could be used as promising vaccines agents against MERS-COV.
Data retrieval and structural analysis
Primary sequence of Saudi Arabia isolate MERS-COVS protein was retrieved from NCBI database using accession number ALW82742.1 . Experimentally known 3D structure of MERS-COV S protein was retrieved by using PDB ID: 5X59 from Protein-Data-Bank . Protein sequence was analysed for its chemicals and physical properties including GRAVY (Grand average of hydropathicity), half-life, molecular weight, stability index and amino acid atomic composition via an online tool Protparam . Secondary structure of MERS-COV S protein was analysed through PSIPRED . TMHMM an online tool (http://www.cbs.dtu.dk/services/TMHMM/), used to examine the transmembrane topology of S protein. Existence of disulphide-bonds were examined through an online tool DIANNA v1.1. It makes prediction based on trained neural system . Antigenicity testing carried out through vaxijen v2.0 . Allergenicity of query sequence was checked through AllerTOP v2.0 .
B-cell epitope prediction
Freely online accessible servers IEDB (Immune-Epitope-Database And Analysis-Resource)  and BCPRED  were used to for B-cell epitopes forecast. Criteria was set to have 75% specificity and 14 residue lengthy epitopes were viewed as adequate to persuade defensive immune reaction. Only those epitopes were chosen that were visible on outer surface and other intracellular epitopes were eliminated. Vaxijen 2.0 server was utilized for antigenicity study of chosen epitopes . Recognition of B-cell epitopes was depended on; antigenicity, accessibility of surface, flexibility, hydrophilicity and predictions of linear epitope . Hydrophilicity, isolation of linear epitope, accessibility of surface and Flexibility analysis were performed through Bepipred linear epitope prediction and Parker hydrophilicity prediction algorithms, Kolaskar and Tongaonkar antigenicity scale, Emini surface accessibility prediction tool and Karplus and Schulz flexibility prediction tool . Forecast of beta turns in polyprotein was done by utilizing Chou and Fasman beta-turn prediction algorithm . As the discontinuous epitopes are increasingly explicit and have higher dominant attributes over linear epitopes [30, 31], so, the forecast of discontinuous epitopes have additionally been carried out via DiscoTope server . Parameter was set at ≥ 0.5 which indicated 90% specificity and 23% sensitivity. This method relies on surface accessibility and amino acid statistics in a collected form dataset of discontinuous epitopes found out by X-ray crystallography of antigen/antibody protein buildings. At last, position of predicted epitopes clusters (positional affirmation) on 3D structure of S protein was observed via PepSurf . Pymol was utilized to examine the positions of forecast epitopes on the 3D structure of MERS-COV S protein .
T-cell epitope prediction
Cytotoxic T-lymphocyte (CTL) epitopes play a crucial role in vaccine designation. Most significant, it decreases the cost and time as compared with wet lab experiments . By utilizing two distinctive online accessible tools Propred-1  and Propred tool , CTL epitopes of target protein of MHC class-I and MHC class-II were predicted respectively. The outcomes of these tools are quite substantial because they utilize vast number of alleles of HLAs (human-leukocyte-antigens) during computation. The sequence was given in plain format and all alleles were chosen for prediction. For propred-1 proteasome and Immuno-proteasome filters with a threshold value of 5% were kept on.
Eminent features profiling of selected T cells epitopes
After finalizing the epitopes of both MHC class-1 and MHC class-II alleles, their important features including digestion, mutation, toxicity, allergenicity, hydro and physiochemical were checked via vaxijen 2.0 , protein digest server (http://db.Systemsbiology.net:8080/proteomicsToolkit/proteinDigest.html), AllergenFP 1.0  server, Aller Hunter server (https://omictools.com/allerhunter-tool) and ToxinPred server (http://crdd.osdd.net/raghava/toxinpred/). AllergenFP 1.0 is generally utilized for the prediction of allergenicity of epitopes for vaccine development . Aller Hunter server compares peptide’s query sequences opposed to the database of previously reported allergens to give significant outcomes. An in silico method, ToxinPred is used to predict Non-Toxic/Toxic peptides. For further analysis, only NonToxic epitopes were chosen.
Conservation analysis of selected epitopes
S protein sequences of 8 distinctive countries were taken from an open access Genbank database . By utilizing CLC work bench, the multiple-sequence-alignment (MSA) was carried out to perceive the conservation of chosen epitopes . The aligned files (.aln) were additionally utilized to make phylogenetic tree via MEGA7 software . By analysing the multiple-sequence-alignment results and with IEDB conservation-analysis-tool, all the chosen epitopes were checked for their variability and conservation.
Structural modelling and molecular docking
All the predicted peptides 3D structures were modelled via PEPFOLD server at RPBS MOBYL portal , from Protein databank (PDB ID: 3VCL) at a resolution of 1.7 Å, the 3D structure of human HLA-B7 allele crystallized was taken  and utilized for further molecular docking purpose. Through Molecular Operating Environment (MOE) tool, the peptide models (antigenic determinants) were docked against their respective HLA-B7 allele to analyse their inhibitory potential. Procedure for molecular docking using MOE has already been described in various studies [13, 43, 44]. Docking procedure utilized in those studies include protonation, expulsion of already bound peptide and energy reduction followed by expulsion of water particles. Triangular matcher algorithm was applied as default peptide placement methods dependent on the receptor shape which without energy optimization rapidly produces 1000 best poses of docked peptide . By applying London-dG scoring function, the energy approximation of the imitated poses was rescored. For every peptide, top ten positioned poses of London-dG were additionally reduced by Force field refinement algorithm. Protein peptide connection were than examined via LigX tool of MOE. UCSF Chimera and Pymol tools were utilized to produce figures of docked complexes [33, 45].
The physiochemical properties of MERS-COV S protein computed via protparam demonstrates that it contained 1353 amino acids (aa) with molecular weight of 149,479.23 kDa, which reflects good antigenic nature. Theoretical isoelectric point (PI) of subject protein was 5.80 which indicate its negative in nature. An isoelectric point under 7 shows negatively charged protein. Briefly, out of 1353 residue, 112 aa were found as negatively charged whereas others found as positively charged. Protparam computed instability-index (II) 36.81, this categories protein as stable. Aliphatic-index 82.79, which devotes a thought of proportional volume hold by aliphatic side chain and GRAVY value for protein sequence is 0.078. Half-life of protein depicted as the total time taken for its vanishing after it has been synthesized in cell, which was computed as 30 h for mammalian-reticulocytes, > 20 h for yeast, > 10 h for Escherichia coli. Total number of Carbon (C), Oxygen (O), Nitrogen (N), Hydrogen (H) and Sulfur (S) were entitled by formulaC6687H10258N1740O2027S63. Protparam computed details of physiochemical properties enlisted in Additional file 2: Table S1.
Secondary and 3-D structure examination of S protein via PSIPRED , UCSF Chimera  and Pymol  respectively showed that (50%) Beta sheets, (10%) Helixes and (40%) Loops are present in structure as shown in Additional file 1: Figure S1. Two different conformations of structure of MERS-COVS protein shown in Additional file 1: Figure S2.
Furthermore in target protein, DiANNA1.1 tool  calculated 21 disulphides bond (S–S) positions and assign them a score given in Additional file 2: Table S2. Antigenicity of protein was evaluated via Vaxijen 2.0  by setting the threshold at ≥ 0.5, for higher specificity. Antigenicity analysis of full-length protein showed antigenicity 0.4808 for S protein showing it as an expected antigen. An online tool TMHMM used to checked the transmembrane protein topology (http://www.cbs.dtu.dk/services/TMHMM/) and it was found that residue from 1 to 1295 were exposed on the surface, while residue from 1296 to 1318 were inside transmembrane-region and residues from 1319 to 1353 were buried within the core-region of the S protein.
Recognition of B-cell epitopes
B-cell epitopes present on surface predicted via IEDB analysis resource and BCPRED are shown along with their starting positions and antigenicity scores
Discontinuous epitopes predicted through DISCOTOPE 2.0 Server
Number of contacts
Recognition of T-cell epitopes
MHC class-I allele binding peptides predicted via Propred-I with their antigenicity scores
MHC class-I alleles
MHC-Db, HLA-Cw*0301, HLA-B*51, HLA-B*5401, HLA-B*5301, HLA-B*3902, HLA-B*3901, HLA-B*3701, HLA-B14, HLA-A2.1, HLA-A20 Cattle, HLA-A2, HLA-A*0201, HLA-B7
MHC-Kk, MHC-Kd, HLA-B*5801, HLA-B*51, HLA-B*5103, HLA-B*5301, HLA-B7
MHC-Ld, HLA-Cw*0602, HLA-B60, HLA-B40, HLA-B*3902, HLA-A*3302, HLA-B7
MHC-Db revised, HLA-B8, HLA-B7, HLA-B60, HLA-B*5801, HLA-B*5103, HLA-B*5102, HLA-B*5101, HLA-B*3501
MHC-Dd, HLA-B7, HLA-B60, HLA-B*5401, HLA-B*5201, HLA-B*5103, HLA-B*5102, HLA-B*5101, HLA-B40, HLA-B*3901, HLA-B*3701, HLA-B*2705, HLA-A*0205, HLA-B14
HLA-A*1101, HLA-A3, HLA-A68.1, HLA-B*5301, HLA-B*5401, HLA-B*51, HLA-B*0702, HLA-B7
MHC class-II allele binding epitopes predicted using Propred with their antigenicity scores
MHC class-II alleles
DRB5_0105, DRB5_0101, DRB1_1328, DRB1_1327, DRB1_1323, DRB1_1307, DRB1_1305, DRB1_1302, DRB1_1301, DRB1_1128, DRB1_1120, DRB1_1114, DRB1_1101, DRB1_0802, DRB1_0101
DRB1_0301, DRB1_0802, DRB1_0806, DRB1_0817, DRB1_1104, DRB1_1106, DRB1_1128, DRB1_1305, DRB1_1311, DRB1_1321
DRB1_0301, DRB1_0306, DRB1_0307, DRB1_0308
DRB1_0311, DRB1_0405, DRB1_0410, DRB1_0423, DRB1_0801, DRB1_0802, DRB1_0804, DRB1_0806, DRB1_0817, DRB1_1101, DRB1_1102, DRB1_1104, DRB1_1106, DRB1_1107, DRB1_1114, DRB1_1120, DRB1_1121, DRB1_1128, DRB1_1301, DRB1_1302, DRB1_1304, DRB1_1305, DRB1_1307, DRB1_1311, DRB1_1321, DRB1_1322, DRB1_1323, DRB1_1327, DRB1_1328
DRB1_1321, DRB1_1307, DRB1_1305, DRB1_1128
DRB1_1101, DRB1_0801, DRB1_0426, DRB1_0421
DRB1_1328, DRB1_1327, DRB1_1322, DRB1_1301
DRB1_1121, DRB1_1107, DRB1_1102, DRB1_0426
DRB1_0402, DRB1_0401, DRB1_0311, DRB1_0308
DRB1_0307, DRB1_0306, DRB1_0301
DRB5_0101, DRB5_0105, DRB1_1327, DRB1_1328
DRB1_1128, DRB1_1301, DRB1_0102, DRB1_1101, DRB1_1104, DRB1_1106, DRB1_1305, DRB1_1311
Eminent features profiling of selected T cells epitopes
Digestion, Mutation, toxicity, allergenicity, hydro and physiochemical profiling of selected peptides
MHC class-I binding peptides
Trypsin R, Clostripain, IodosoBenzoate, AspN, Cyanogen Bromide, Staph Protease
Trypsin, Clostripain, AspN, Chymotrypsin, Cyanogen Bromide, IodosoBenzoate, Trypsin R, Trypsin K
Clostripain, Chymotrypsin, Cyanogen Bromide, AspN
Trypsin K, IodosoBenzoate, Proline Endopept, Trypsin R
Trypsin, Staph Protease, AspN, Chymotrypsin, Trypsin R, Clostripain, Trypsin K, CyanogenBromide, IodosoBenzoate, Proline Endopept
Clostripain, IodosoBenzoate, Staph Protease, AspN, Trypsin R, Cyanogen Bromide
Trypsin, Chymotrypsin (modified)Chymotrypsin, Cyanogen Bromide, Trypsin K, Trypsin R, Staph Protease
MHC class-II binding peptides
Cyanogen Bromide, Trypsin K, AspN, IodosoBenzoate
Trypsin, AspN, Clostripain, IodosoBenzoate, Staph Protease, Trypsin K, Trypsin R, Proline Endopept
IodosoBenzoate, Trypsin K, AspN, Staph Protease, Proline Endopept
Trypsin, AspN, Clostripain, Cyanogen Bromide, IodosoBenzoate, Trypsin R, Proline Endopept, Staph Protease, Trypsin K
Chymotrypsin, Trypsin K, IodosoBenzoate, Proline Endopept, Staph Protease, Cyanogen Bromide, AspN
AspN, Trypsin R, Clostripain, Staph Protease, Cyanogen Bromide, IodosoBenzoate
Conservation analyses of selected epitopes
The epitope-conservancy study through IEDB epitope conservancy analysis tool shows that all of selected B-cell and T-cell (MHC class-I and II) epitopes have 100% identity and conserved in all isolates of distinct countries (Additional file 2: Table S4).
Interaction study of predicted peptides with HLA alleles
3D structures of all 6 MHC class-I attaching peptides were predicted via PEPFOLD . It created 5 models of every peptide; one best model was chosen for every peptide (Additional file 1: Figure S4). At first models were refined via energy minimization in MOE and peptide library involved of 6 peptides was made to dock with explained structure of HLA-B7 allele.
Molecular docking results of HLA-B7 with MHC class-I binding peptides have been given
MHC class-I binding peptides
Tyr-9, Gln-70, Glu-76, Tyr-99
Arg-62, Glu-76, Arg-156
Arg-62, Asn-63, Gln-70, Glu-152, Gln-155
Arg-62, Glu-76, Ser-77, Arg-156
Asp-114, Gln-115, Lys-146, Glu-152, Arg-156
Arg-62, Glu-152, Glu-163, Trp-167
Emergence of new viral diseases in resource poor countries in Asia represent a huge global disease burden. The population of developing countries such as Saudi Arabia is facing a serious health threat from MERS-COV virus, and there is an urgent need for corresponding therapies and preventative measures. MERS syndrome is characterised by lung and kidney infections . This virus undergoes rapid evolution due to recombination between genomes of different viral particles after infecting host cells. At present, there are no reliable, specific drugs against MERS-COV infection available on the market .
Medical biotechnology is playing a significant role in the development of vaccines against these and similar viruses, but computer-based immune-informatics can be used for analysis of immunogenic data and vaccine development, and this approach can decrease time and cost. The specificity of epitope-based vaccines can be enhanced by only selecting the antigenic parts of proteins exposed on the surface, since these elicit strong immune responses [48, 49]. The viral S protein is considered a primary target for neutralising antibodies, and the S1 subunit of the S protein has been the focus of immunisation strategies to overcome MERS-COV disease . The MERS-COV S protein is an immunogenic protein that plays an important role in the attachment and entry of viral particles in host cells, characterised by high antigenicity and surface exposure .
Herein, we explored epitope-based vaccine development targeting S protein potential B- and T-cell S protein epitopes that may promote an immune response in the host were identified, analyses were performed at protein primary, secondary and tertiary structural levels. B-cell conserved epitopes (≥ 14 residues long) were predicted by IEDB analysis-resource and BCPRED. Other tools in IEDB were utilised to analyse antigenicity, flexibility, solvent accessibility and disulphide bonds. The ‘QLQMGFGITVQYGT’ yielded a higher immunogenicity score (1.5236) and may represent a potential B-cell epitope and vaccine candidate. In addition, several T-cell antigenic determinants possessing the ability to bind MHCI and/or MHCII were predicted using Propred-I and Propred, respectively. MHC-I (YKLQPLTFL) and MHC-II (YCILEPRSG) epitopes interact with numerous HLA alleles and are highly antigenic in nature . In addition, the positions of all predicted epitopes on the 3D structure were confirmed using Pepsurf. Discotope servers were used to predict discontinuous epitopes. Among MERS-COV strains, conservation of predicted epitopes from different countries was analysed to select epitopes common to all. The immune-informatics approach can identify highly conserved epitopes that may deliver wide protection against different strains. Conservation assessment revealed that all predicted epitopes were conserved between MERS-COV gene sequences reported from eight countries. Furthermore, allergenicity, toxicity, mutation and physiochemical properties of predicted antigen determinants were analysed to further increase specificity and selectivity. Digestion analysis confirmed that peptides identified in this study were stable and safe to use. On the basis of immunogenicity score and sequence conservation, it is clear that the conserved peptides are likely to be immunogenic. In addition, 3D structures of all six MHC class I binding peptides were predicted via PEPFOLD and docked with the human HLA-B7 allele by MOE to analyse binding specificity and defence response. Based on docking score, binding potential to HLA-B7, and immunogenicity score, peptides identified in the current study may prove highly immunogenic compared with previously reported peptides [51, 53, 54]. The predicted epitopes should be tested for therapeutic potency in future studies. We predict that the putative epitopes may have therapeutic potential with excellent scope. Our immune-informatics analysis identified potential strong T- and B-cell epitopes that may assist the development of potent peptide-based vaccines to address the imminent MERS-COV challenge.
In the present study, a reverse vaccinology approach was adopted to identify surface-exposed peptides, rather than focus on the whole pathogen, which is a less efficient and effective process. This approach can reduce time and cost, and increase specificity. Only immunogenic regions of antigenic epitopes of the S protein of MERS-COV were screened to identify potential vaccine candidates. Sequence, structure, conservation and interaction analyses were conducted to discover epitopes of B- and T-cells that are antigenic and conserved among MERS-COV isolates from eight different countries, that may serve as vaccine candidates. The small number of antigenic epitopes identified in this study might deliver a preliminary set of epitopes for future vaccines against MERS-COV, which may help to control this growing health threat.
Authors would like to acknowledge Huazhong Agricultural University, Wuhan, China and Prince Sattam bin Abdul Aziz University, Alkharj, Saudi Arabia for providing facilities for this study.
MTQ, UAA and SA conceived and designed this study; MTQ and SS performed the experiments; MTQ, SS, AB, and FA analyse the results; MTQ and SS wrote the manuscript; UAA, AB, FA and SA improved and revised the manuscript. All authors read and approved the final manuscript.
Ethics approval and consent to participate
Consent for publication
The authors declare that they have no competing interests.
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