key: cord-0929728-7qv3exy9
authors: Pourseif, Mohammad Mostafa; Parvizpour, Sepideh; Jafari, Behzad; Dehghani, Jaber; Naghili, Behrouz; Omidi, Yadollah
title: A domain-based vaccine construct against SARS-CoV-2, the causative agent of COVID-19 pandemic: development of self-amplifying mRNA and peptide vaccines
date: 2020-12-10
journal: Bioimpacts
DOI: 10.34172/bi.2021.11
sha: 23c7009024de59d2bd08664f0c71d83eacdeadd3
doc_id: 929728
cord_uid: 7qv3exy9

[Image: see text] Introduction: Coronavirus disease 2019 (COVID-19) is undoubtedly the most challenging pandemic in the current century with more than 293,241 deaths worldwide since its emergence in late 2019 (updated May 13, 2020). COVID-19 is caused by a novel emerged coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Today, the world needs crucially to develop a prophylactic vaccine scheme for such emerged and emerging infectious pathogens. Methods: In this study, we have targeted spike (S) glycoprotein, as an important surface antigen to identify its B- and T-cell immunodominant regions. We have conducted a multi-method B-cell epitope (BCE) prediction approach using different predictor algorithms to discover the most potential BCEs. Besides, we sought among a pool of MHC class I and II-associated peptide binders provided by the IEDB server through the strict cut-off values. To design a broad-coverage vaccine, we carried out a population coverage analysis for a set of candidate T-cell epitopes and based on the HLA allele frequency in the top most-affected countries by COVID-19 (update 02 April 2020). Results: The final determined B- and T-cell epitopes were mapped on the S glycoprotein sequence, and three potential hub regions covering the largest number of overlapping epitopes were identified for the vaccine designing (I(531)–N(711); T(717)–C(877); and V(883)–E(973)). Here, we have designed two domain-based constructs to be produced and delivered through the recombinant protein- and gene-based approaches, including (i) an adjuvanted domain-based protein vaccine construct (DPVC), and (ii) a self-amplifying mRNA vaccine (SAMV) construct. The safety, stability, and immunogenicity of the DPVC were validated using the integrated sequential (i.e. allergenicity, autoimmunity, and physicochemical features) and structural (i.e. molecular docking between the vaccine and human Toll-like receptors (TLRs) 4 and 5) analysis. The stability of the docked complexes was evaluated using the molecular dynamics (MD) simulations. Conclusion: These rigorous in silico validations supported the potential of the DPVC and SAMV to promote both innate and specific immune responses in preclinical studies.

Despite notable progress in medical sciences during the 20 th century, still, infectious diseases have significant consequences on the public health systems worldwide. Of these, emerging infectious diseases (EIDs) and re-emerging infectious diseases (RIDs) are always considered as striking threats to humans all around the world. 1 The majority of such infectious diseases are zoonotic and mostly originated from animals, including severe acute respiratory syndrome coronavirus (SARS-CoV), influenza A virus subtype H1N1, Middle East respiratory syndrome coronavirus (MERS-CoV), Ebola, and Zika virus.

Today, the world is confronting a novel coronavirus so officially named SARS-CoV-2, and World Health Organization (WHO) has named its relevant disease as "Coronavirus disease 2019 (COVID- 19) ". The first known SARS-CoV-2 was discovered in late December 2019 in Wuhan, Hubei province, China. Since then, it has become a global pandemic, in large part due to its rapid rate of human-to-human transmission, lack of vaccine, and delay in global functional protocols. 2 The infection of SARS-CoV-2 can lead to some severe respiratory damages with a different range of symptoms and complications -ranging from mild symptoms (e.g., fever, cough, myalgia or fatigue, and shortness of breath) to severe illness and death. 3 The SARS-CoV-2 belongs to the family Coronaviridae and the Betacoronavirus genus. 4 Coronaviruses (CoVs) are a large group of zoonotic viruses with unique features, including the crown-like surface projections with clubshaped spike proteins, and the enveloped positive-sense single-stranded RNA viruses with helical nucleocapsids. The structure of SARS-CoV-2 and its genome data is schematically illustrated in Fig. 1 .

Presently, along with the basic predictive measures and therapeutic modalities, the development of effective vaccine(s) is extremely vital for the controlling of the SARS-CoV-2. The empirical vaccinology against glycoprotein S due to its ability to trigger the most dominant and long-lasting neutralizing immune cells against SARS-CoV. 13, 14 Our main objective was to identify the immunodominant regions of the target antigen through the robust immunoinformatics approaches to accelerate the development process rationally. The regions of spike glycoprotein that cover the largest number of overlapping predicted B-and T-cell epitopes were used to logically design two different immunogenic constructs, including (i) an adjuvanted domain-based protein vaccine construct (DPVC), and (ii) a self-amplifying mRNA vaccine (SAMV). The immunizing efficiency of DPVC was validated through, (i) the analysis of the vaccine sequence and its three-dimensional (3D) structure, (ii) molecular docking between the vaccine structure and the human toll-like receptors (TLRs) 4 and 5, and (iii) the molecular dynamics (MD) simulations.

The whole-genome reference sequence of SARS-CoV-2 was retrieved from the National Center for Biotechnology Information (NCBI) genome database (accession no. NC_045512). The reference protein sequence of spike protein (accession no. YP_009724390.1) in FASTA format was used for BLAST against non-redundant protein sequences (nr) database through the blastp (proteinprotein BLAST) algorithm. The FASTA sequence of 100 spike protein of different countries and different dates of isolation with significant alignments (identity ≥ 75.80% and E-value 0.0) were taken and multiple-sequencealignment was carried out using the MUSCLE program of MEGA v10.0 software. 15, 16 The aligned sequences were then analyzed to find the best substitution model of amino acid evolution using MEGA 10 software. The phylogenetic tree of the protein S dataset was inferred by using the Maximum Likelihood (ML) method and JTT matrix-based model 17 and via bootstraps replications of 1000. 18 The putative spike protein isolated from Zaria Bat coronavirus (GenBank: ADY17911.1) was served as an outgroup.

In domain-based vaccine design, one important criterion is selecting epitopes that have an extracellular localization and are more accessible for the epitope-paratope interactions. In this regard, the spike protein was analyzed for the possible presence of signal peptide, transmembrane helices, and also intracellular regions. These structural features were predicted using the online web-servers, including TOPCONS, 19 CCTOP v2.0, 20 and TMHMM. 21 

The NCBI's Conserved Domain Database (CDD) v3. 16 tool with default E-value threshold was used to annotate the conserved domain(s) of SARS-CoV-2 S glycoprotein. 22 Besides, the aligned sequences of the protein S were imported to the BioEdit v7.2.5 to determine conserved regions of the S protein sequence by use of Shannon's entropy (Hx) plot. 23 This measure was also carried out to compare mutated regions of SARS-CoV-2 to SARS-CoV (Reference sequence accession no. NP_828851) using BioEdit v7.2.5 software and via Shannon entropy (Hx) analysis.

The secondary structure of S protein was predicted employing the PSIPRED web-server. 24 The 3D structure of S protein was homology modeled using the SWISS-MODEL online tool 25 and the newly reported crystal structures in Protein Data Bank (6LVN, 6LXT, 6VSB, 6VXX, and 6VYB).

To refine the 3D model for the hydrogen bonds and overall structural relaxation, it was subjected to the GalaxyRefine server processing. 26 To optimize the model's free energy, the refined model was subjected to an MD simulation recruiting GROMACS 5.0.7 software together with the GROMOS 96 force field. 27 The MD simulation procedure was carried out at 310 K by placing the model into a cubic box that had a suitable size and two Na+ ions to neutralize the environment. Subsequently, the RMSD graph was drawn for the analysis of the dynamic behavior of the constructed model. 28 The local and overall quality of the improved 3D model was checked using online webservers, including PROCHECK, 29 verify3D, 30 ERRAT. 31 In silico B-cell epitope mapping: a multi-method approach The potential B-cell epitopes (BCEs) were predicted by using the sequence-and structure-based tools. To predict linear and conformational BCEs with high accuracy, we implemented a multi-method approach based on the different currently available online BCE prediction web-servers. 32 We exploited the physicochemical and machine learning methods such as all the predictor tools of the Immune Epitope Database and Analysis Resource (IEDB) as a repository of curated epitope related information (http://tools.iedb.org/main/bcell/), BepiPred v2.0, 33 LBtope, 34 IgPred, 35 (https://webs.iiitd.edu.in/raghava/bcepred/ index.html). The energy minimized 3D structure of protein S was utilized to predict and map the potential discontinuous BCEs. The FASTA sequence of the protein was imported into the Excel program and any single amino acid was separated in a single cell as a set of consecutive cells using a user-defined function named "AddSpace" (the Excel VBA code is shown in Table S1 , see supplementary material). The scores of each of the twentyone prediction algorithms were normalized to have values between 0 and 1. Then, an average of all normalized scores for each residue was represented as a plot, in which the immunodominant regions of the S protein sequence were highlighted based on a strict threshold value of ≥ 0.6. For the residue-based comparison analysis of the final predicted BCEs, the pairwise sequence alignment was implemented employing Clustal Omega webserver 42 between the reference sequences of the spike proteins of SARS-CoV (accession ID: NP_828851.1) and SARS-CoV-2 (accession ID: YP_009724390.1). All the experimentally-determined spike glycoprotein SARS-CoV-derived BCEs were obtained from the NIAID Virus Pathogen Database and Analysis Resource (ViPR) (accessed on April 1 st , 2020) and IEDB web-server to have a comparative evaluation with SARS-CoV-2 dominant predicted BCEs (Table S2) . 43 

SARS coronavirus-associated T-cell epitopes are almost all correlated to the HLA complex antigen recognition. However, the HLA alleles are highly polymorphic among populations and there is no entire screening system to clarify the possible association between the occurrence of SARS-CoV-2 and the susceptibility/resistance of various HLA alleles. Therefore, in such diseases, it is logical to use the reference sets of HLA alleles with the maximal population coverage. The T-cell epitope prediction was performed using the reference isolate of SARS-CoV-2, i.e., spike protein sequence (NCBI: YP_009724390.1). Due to utilizing a vast number of the human leukocyte antigen (HLA) alleles during the calculation of peptide-MHC binding, the predicted output table might be quite substantial. Therefore, the prediction of peptide binders for class I and II MHC molecules was carried out based on the strict cut-offs to give more accurate and reliable peptide binders. To have a final set of the epitope for vaccine designing, those candidate epitopes that displayed overlap for multiple alleles were selected.

The cytotoxic T-lymphocyte (CTL) epitopes were predicted by utilizing the IEDB recommended v2.22 algorithm, 44 . To find the best consensus epitopes among a pool of peptide binders, we first sorted the IEDB's output table based on the rank of any binder in the three binding prediction methods (i.e., percentile rank, artificial neural network (ANN) IC 50 , and stabilized matrix method (SMM) IC 50 . Then, the sorted binders were filtered based on an MHC binding affinity (IC 50 ) value of ≤ 50 nM, and the percentile rank of ≤ 1.0, as strict thresholds. In the end, we selected the best candidate peptide binders via defining a ranking score, the so-called "consensus rank" (CR). This CR score was calculated by the following equation [i.e., CR = average rank of a mapped peptide binder/n], where, "n" refers to the total number of alleles covered by a peptide binder. Therefore, it provides a small list of candidate peptide binders that not only possess the highest prediction rank but also can bind to a wide range of MHC alleles.

To predict the most potential CD4 + helper T-cell epitopes, we used the IEDB recommended algorithm v2.22 (consensus approach) 46 based on the full HLA reference set that can cover > 99% of the global population. 47 The epitope length was specified on a variable-length option 12-18 that can cover 82.89% of epitope frequency. To generate a consensus list of CD4 + T cell epitopes, we selected the best peptides based on the adjusted percentile rank ≤ 1.0 (as a strict cut-off) and the number of MHC-II alleles covered by the candidate predicted peptide binders.

HLA molecules are extremely polymorphic, thus using multiple peptides with various HLA binding specificities will give more coverage of the population targeted by domain-based vaccines. Accordingly, in this study, we computed population coverage of the final T cell epitopes using the allele frequency net database 48 and the tool provided by the IEDB server. 49 The measured population coverage indicates the percentage of individuals within the population that are likely to stimulate an immune response to at least one T cell epitope from the set. We estimated the population coverage of T-cell epitopes for the top mostaffected countries by the COVID-19 pandemic (updated data on April 2 nd , 2020).

In this study, we designed two different vaccine constructs optimized based on the two different vaccine platforms and using the identified immunodominant B-and T-cell regions of SARS-CoV-2 spike glycoprotein. i. A DPVC for in vitro expression and purification as an injectable recombinant vaccine. ii. A self-amplifying mRNA vaccine (SAMV) construct for in vitro transcription and purification, and in vivo expression. The DPVC was designed based on the immunodominant B-and T-cell epitopes, intramolecular adjuvants, and different peptide linkers. The residues of the spike protein covering the largest number of overlapping predicted epitopes were used to design the DVC. Currently, it is known that the TLRs 4 and 5 are effectively contributed to the recognition and induction of immune responses against respiratory coronavirus infectious. 50, 51 Therefore, to potentially enhance the vaccine immunogenicity, we capitalized on two TLR agonist sequences as intramolecular adjuvants, including (i) a synthetic TLR4 agonist 7-mer peptide, named RS09 (APPHALS), 52 and (ii) Salmonella typhimurium Flagellin C (UniProtKB: P06179) as a bacterial ligand for binding to TLR5. 53 To improve the CD4 + T-cell immune responses, an invariant Pan HLA-DR reactive epitope (PADRE) was exploited in the vaccine construct. The intramolecular adjuvants (Flagellin C, and RS09) were linked to the PADRE sequence at the N-terminal site of the construct and joined each other using an in vivo cleavable linker (sequence: PPGVS). This peptide appears as the optimal cleavage site of matrix metalloproteinase-9 (MMP-9), which is a member of the metalloendopeptidase distributed in the human skin. 54, 55 The PADRE sequence was linked to the main domain of the vaccine construct using the Cathepsin S cleavable linker (PMGLP). In the human skin, the protease activity of cathepsin S has the main role in the antigen presentation pathways mediated by MHC class II molecules. [56] [57] [58] It is discussed before that signal peptides not only can improve vaccine immunogenicity but also have an intrinsic nature to direct the protein to the desired cellular compartment (e.g. secretion out of the cell or into cell membrane). 59 Here, according to the goal of vaccination, the final localization of the cytosolic expressed SAM vaccine can be engineered by antigen-specific signal sequences to be secreted extracellular or translocated into the host's cell membrane.

The second vaccine construct was designed as a selfamplifying mRNA (SAM) replicon vaccine. In this construct, we used the identified immunodominant regions of the glycoprotein S as a vaccine sequence. Further, to have a SAM construct we used the genes encoding non-structural proteins (nsp) of the Semliki Forest virus (NCBI reference sequence: NC_003215.1) as a genomic (+) single-strand RNA alphavirus. 60 The nsp1-4 region can improve properly the mRNA capping, stability, translational efficiency, and can form properly the RNAdependent RNA polymerase (RdRp) complex. 12 The SAMV construct was flanked between the newly designed 5' and 3' untranslated regions (UTRs) named as NASAR. 61 NCA-7d, as the 5' untranslated region (UTR), and S27a+R3U, as the 3' UTR. We propose a newly developed CleanCap TM method (by TriLink BioTechnologies, US) with base analogs Adenosine and Uridine for the mRNA capping process (cap residue: m 7 G(5')ppp(5')(2'OMeA) pU). This 5'-capping, as a co-transcriptional capping technology, is specialized for the high efficient production of the SAMVs with naturally creating Cap 1 structure.

The antigenicity analysis was varied out using the VaxiJen v2.0 server. 62 The potential allergenicity of the vaccine construct was evaluated in the AlgPred (using the hybrid method) 63 and AllerTOP v2.0 64 web-servers and based on the FAO/WHO allergenicity rules. To prevent possible autoimmunity of the designed vaccine, the vaccine amino acid sequence was blasted against non-redundant protein sequences of Homo sapiens using the blastp algorithm of the NCBI. The physicochemical properties of the designed vaccine such as molecular weight, theoretical isoelectric point (pI), half-life in vitro and in vivo, stability, aliphatic index, extinction coefficient, and grand average of hydropathicity (GRAVY) were predicted using the ProtParam tool of ExPASy web-server. 65

The tertiary and secondary structure of the vaccine construct was predicted using the I-TASSER and the Garnier Osguthorpe and Robson (GOR) version IV online servers. 66, 67 The highest quality 3D model was refined through the GalaxyRefine server 26 and then was executed for the energy minimization by the GROMACS 5.0.7 software package. 27 The structural quality of the optimized 3D model was validated using PROCHECK 29 web-server. The molecular docking was performed via ClusPro v2.0 online server 68 to assess the binding affinity between the DVC and extracellular regions of the human TLR4 (PDB ID: 4G8A), and TLR5 (PDB ID: 3J0A) molecules. The output of docking simulations was visualized and analyzed using the Chimera v1.14 69 and DIMPLOT schematic diagram of LigPlot + v2.2, 70 respectively.

Different features of the SARS-CoV-2 genome are categorized and presented in Table S3 (Supplementary file 1). To further assay the phylogenetic relationship between the SARS-CoV-2 genome and all other strains of CoVs, as shown in Fig. 2A , we built an evolutionary tree with the highest log likelihood (-11665.31). According to the phylogenetic analysis, among all known CoVs, the bat coronavirus RaTG13 (Accession no. QHR63300.2) showed the closest relation to the recent emergent human coronavirus (HCoV).

The conserved and variable regions of the spike glycoprotein among the hundred CoV strains are shown based on the Shannon entropy plot (Fig. 2B ). The most variable residues have entropy (Hx) values more than 1.0. According to the NCBI-CDD's output, there are two domain hits in the glycoprotein S sequence, including (i) a large polypeptide (CoV S2 protein, residues from 662 to 1270), and (ii) spike receptor-binding domain (residues from 331 to 583) that mediates the affinity binding of the virus to angiotensin-converting enzyme 2 (ACE2) (Fig.  3B ). The conserved regions have a higher probability to be as a part of functional domains of the protein, however, epitope escape mutations may be also a potential consequence to the emergence of such zoonotic EREI viruses.

In total, 28 immunodominant B-cell peptides were predicted. All the predicted peptides are located on the accessible surface of the S glycoprotein (Fig. 4C) . Therefore, those peptides, which have the highest prediction score, were selected for the vaccine design (Table 1) . Besides, the reference sequences of the S glycoproteins of SARS-CoV (accession ID: NP_828851.1) and SARS-CoV-2 (accession ID: YP_009724390.1) were used for pairwise sequence alignment, and the final predicted BCEs were marked for comparison with the experimentally-determined SARS-CoV-derived BCEs 71 ( Fig. S4 ; Table S4 ).

Cytotoxic T-cell epitope The IEDB server predicted a list of 2529 unique peptides of S glycoprotein binding to the 27 alleles of HLA class A and B as raw data (Table S5) . Of these, the consensus rank (CR) score of the peptide binders which had percentile rank ≤ 1.0, and ANN-and SMM-based IC 50 ≤ 50.0 were calculated. In this approach, peptide binders were sorted and then selected based on (i) their rank in terms of percentile rank, ANN-IC 50, and SMM-IC 50 measures (e.g., consensus rank or CR), and (ii) the number of the HLA alleles that are covered by these binders. As a result of the CR score-based screening, we plotted the most dominant peptide binders for both HLA-A and B alleles in Fig. 5A . The CR scores allow screening a subset of binder hits covering a large range of the human population. The most potent peptide binders of the SARS-CoV-2 spike glycoprotein sequence corresponding to the HLA-A and B alleles are shown in Fig. 5A .

The raw output table of IEDB's was contained 132195 peptides of different length binding to HLA-DRB alleles (Table S6 ). The predicted HLA-II peptide binders were filtered using a strict threshold (adjusted rank ≤ 1.0) to choose all the top-scoring peptides for each specific HLA-II allele. Of these, 24 most immunodominant peptides were chosen for more analysis (Fig. 5B) . The potentially effective CD4 + T-cell epitopes were selected based on the population coverage of each peptide and also the number of covered HLA-II alleles.

According to the announcement of the WHO on March 12 th , 2020, the COVID-19 outbreak was characterized as a pandemic, indicating that vaccinologists may confront with the broad-spectrum immunophenotypes that can complicate the vaccine design and development. 73 Therefore, in this study, we provided a list of most potent peptide binders associated with most frequent MHC alleles to design a broad coverage vaccine construct. The population coverage of the most potent T-cell epitopes in the countries that are impacted the most by SARS-CoV-2 is reported in Table S7 .

Among the pool of CD8 + T-cell peptide binders (Table  S5 ) we sought to found the most potent regions of S glycoprotein as the CTL epitope. Generally, we found 16 epitope sequences with the highest binding affinity to a maximum number of the most frequent HLA-I alleles.

The most dominant predicted CD8 + T-cell epitopes were selected based on their CR score, MHC allele coverage, and percentage of population coverage ( Table 2 ). As presented in Table 2 , the average population coverage for the eleven of the best CD8 + T-cell epitopes and their corresponding HLA-alleles were observed between 36.48% for the "SGWTAGAAAYYV" and 79.05% for the "GYLQPRTFLLKY" peptides. For details of the results of population coverage analysis of each of 16 predicted CD8 + T-cell epitopes in the most-affected countries by COVID-19, readers are directed to see Table S8 .

The selected HLA class II binders contain the most frequently occurring amino acids that have the highest capacity to attach different MHC class II alleles (Table  3) . Thereupon, they might have good potential to elicit effective cellular immunity in most human populations. The detailed results of population coverage analysis for all 16 predicted CD4 + T-cell epitopes in the most-affected countries by COVID-19 are presented in Table S9 .

For the rational design of the DPVC, we rendered the position of all final chosen B-and T-cell epitopes in the SARS-CoV-2 spike protein sequence (Fig. S5) . Consequently, we found three peptide fragments (100-280, 430-590, and 1060-1150) containing the largest number of the overlapping immunodominant B-and Tcell epitopes. These fragments can cover 7 BCEs, 7 CD4 + T-cell epitopes, and 4 CD8 + T-cell epitopes (Fig. S5 ). Here, we designed two vaccine constructs based on the two different platforms: (i) An adjuvanted DPVC, which needs to be produced, (ii) A self-adjuvanted SAMV construct, which needs to be synthesized, produced as in vitro transcription process, delivered by employing a designated non-viral delivery system such as liposomal nanoformulation, administrated intramuscularly, and expressed in vivo. The recombinant DPVC In this platform, we designed an adjuvanted vaccine construct with a full-length of 984 amino acid residues. The different components of the vaccine are schematically represented in Fig. 6A . The result of PSIPRED webserver showed among 984 amino acids, 257 (26.12%), 204 (20.73%), and 523 (53.15%) amino acids are involved in α-helix, extended strand, and random coil, respectively. The map of the predicted secondary structure is shown in Fig. S6 . The 3D structure of the MD-refined vaccine model is represented in Fig. 6B .

The C-and TM-scores, and RMSD of the initially modeled vaccine by the I-TASSER were calculated as -2.63, 0.41±0.14, and 13.6±3.1Å, respectively. The C-score is usually ranged from -5 to 2, where the C-score of higher values implies a model with higher confidence. 74 The TMscore and RMSD, as the standard metrics, are measured based on the C-score following the correlation observed between these qualities. 75 The TM-score threshold is independent of the size of proteins and values more than 0.5 are relevant to the correct model topology.

The energy level of the homology 3D modeled vaccine was minimized through the MD simulations for 50 ns to improve structural stability. The RMSD trajectory graph of the MD optimized vaccine model is shown in Fig. 6C . The RMSD of the structure reached 3.2Å after 5ns and remained approximately stable until the end of the simulations. This observation indicated the model expansion during the simulation and that the simulation duration was long enough to obtain an equilibrium structure for the constructed vaccine. Consequently, the extracted equilibrium structure at 310K was used for the subsequent evaluation of the vaccine-receptor binding affinity and interactions.

The backbone torsion angles (psi/phi) of the vaccine model and its overall quality before (i.e., initially modeled vaccine) and after MD simulation were analyzed based A) The receptor-binding domain (green), and S2 subunit (pink) of SARS-CoV-2 S glycoprotein. B) The dynamic root-mean-square deviation (RMSD) graph corresponding to all atoms of the modeled spike glycoprotein shows that the simulation time (40000 ps) was long enough to achieve convergence (or stability) for the protein. C) The position of the ten dominant predicted B-cell epitopes. Owing to the lack of crystallized template protein, some residues in the beginning and end of the 3D model (1-27, and 1021-1273, respectively) are missed. The 3D structures were visualized by UCSF Chimera v1.14 software. 72 on the validation plots obtained from the PROCHECK (Fig. S7) . The energy minimized vaccine model showed that 710 of all residues (82.8%) were in the most favored regions of the Ramachandran plot. Whereas in the initial DPVC model only 399 of residues (46.4%) were in these regions (Fig. S7) . The comparison assessments showed that the MD-minimized vaccine model can be reliable to predict the binding affinity between the vaccine and TLRs 4 and 5.

Based on the result of both AlgPred and AllerTOP webservers, the DPVC have no allergenic nature. The NCBI protein-protein BLAST against Homo sapiens showed the DPVC has no sequence similarity with the human proteome. This implies that the candidate vaccine should not trigger the autoimmune responses in the human body but activate the desired specific immunogenic reactions. The VaxiJen antigenicity score for the DPVC was 0.5097 indicating it as a probable antigen.

The molecular weight of the vaccine obtained from the ProtParam tool was about 105 kDa. The theoretical isoelectric point (pI) was calculated to be 5. 95 showing the vaccine is slightly neural. The total numbers of positively and negatively charged residues were computed to be 81 and 91, respectively. The extinction-coefficient was 83660 M -1 cm -1 at 280 nm measured in water, which means all Cys residues are reduced. The half-life of the vaccine construct in mammalian reticulocytes was estimated at 30 hours (in vitro), more than 20 hours in yeast (in vivo), and more than 10 hours in Escherichia coli (in vivo) obtained by ProtParam tool. The computed instability index (II) classified the vaccine construct as a stable protein with a score of 28.47. The aliphatic index and GRAVY were calculated to be 80.50, and -0.296, respectively. These measures indicate that the vaccine construct is highly thermostable and also hydrophilic. The safe, immunogenic, and stable nature of the designed vaccine makes it a good candidate for more structural analysis.

The protein-protein molecular docking between the MDoptimized DPVC and the immune receptors (TLR4 and TLR5) was performed using the ClusPro v2.0 tool (Fig. 7) . The best docked-complexes with the lowest energy scores were -1350.3 kcal/mol, and -1369.5 kcal/mol, for vaccine-TLR4, and vaccine-TLR5 complexes, respectively. The binding energies of the docked complexes were measured in the form of coefficient wattage using the formula E=0.40E rep +-0.40E att +600E elec +1.00E DARS in the Balanced model. 68 The complexes with the highest binding affinities were subjected to the MD simulations by the GROMCAS software to survey their conformational stability (Fig.  7) . The simulations were carried out in a 10 Å cubic box containing water molecules at 310K. The protein solvation was done using the spc216 template. The charges on the proteins were neutralized based on the Varlet cutoff scheme. Then, the system was subjected to energy minimization using the 1500 steps of steepest descent. The geometrical quality of the Cα backbone conformation was investigated using the root mean square deviation (RMSD) that is produced during MD simulation. According to the RMSD plots (Fig. 7) , both docked complexes are stable mostly during the simulation. Based on the RMSD plot of the vaccine-TLR4 complex (Fig. 7A) , the system reaches equilibrium at 15 ns (≈3.8 Å), whereas the RMSD values narrowly fluctuate between 3.5-4 Å. Nonetheless, the analysis of simulations for the vaccine-TLR5 reveals that it equilibrates much faster at 5 ns (≈3.8 Å) without significant fluctuations (Fig. 7B) . As represented in Figs. 7 and 8, the DPVC functional parts (spike glycoprotein domains 1, 2, and 3; TLR4 agonistic motif RS09; and TLR5 agonistic domain flagellin C (FlgC) have a high binding affinity to the extracellular domains of the TLR4 and TLR5. Of these, the vaccine domains 2, and 3 (Figs. 7 and 8) indicated a more binding affinity to the TLRs. Here, we observed that the domains of SARS-CoV-2 spike glycoprotein can interact with the TLRs 4 and TLR5 on the cell surface, possibly triggering the intracellular NF-κB pathway and subsequent production of cytokine. Wang et al demonstrated that the interaction between the SARS-CoV spike glycoprotein and the murine macrophages could elicit the NF-κB activation pathway and then upregulation of cytokines IL-6 and tumor necrosis factor alpha (TNF-α). 76 The H-bonds and hydrophobic interactions between the immune receptors (i.e., TLR4 and TLR5) and the DPVC are represented as a two-dimensional graph in Fig. 8 .

Having capitalized on the in vivo cleavable linker (PPGVS) between the PADRE sequence and intramolecular adjuvants, it is expected to have a high level of either TLR-dependent innate immunity by the in vivo cleaved intramolecular adjuvants (FlgC and RS09) and S glycoprotein domains, and also the adaptive immune responses by PADRE sequence and SARS-CoV-2 S glycoprotein domains.

The self-amplifying mRNA (replicon) vaccine construct In this approach, we designed a SAMV construct using the genes encoding the non-structural proteins (nsp1-4) of the positive-sense single-stranded RNA of Semliki Forest virus which are linked to the codon-optimized genes encoding the three identified immunodominant regions of the spike glycoprotein (I 531 -N 711 ; T 717 -C 877 ; V 883 -E 973 ) to support the translation machinery in human cells. The different compounds of the designed SAMV and its cap structure are represented in Fig. 9 . The designed SAMV consisted of the replication machinery of the Semliki Forest virus, therefore it might result in the injection-site intrinsic adjuvant reactions by the induction of pattern recognition receptors (PRRs), chemokines, cytokines (e.g., IL-12), and TNF. 77 These innate immune responses are critical for the maturation of dendritic cells (DCs) to boost up the subsequent direct adaptive immune responses. The mechanism of SAMV cellular uptake, activation of innate immunity, vaccine antigen's cellular processing, and the MHC presentation machinery in the injection site is projected in Fig. 10 .

Today, the sudden emergence with the quick spread of the novel zoonotic infectious agent, SARS-CoV-2 ( Fig.  1) , has led to a serious pandemic. Currently, several vaccine research teams in several countries are working to design, develop, and formulate an efficient prophylactic vaccine/adjuvant. 2, [78] [79] [80] However, the conventional vaccine platforms against such a high transmissible and less-known infectious agent is an extremely timeconsuming and risky task. Accordingly, among different vaccine platforms, self-amplifying mRNA vaccines as the next generation of mRNA vaccines provide a costeffective and time-efficient strategy for the development of vaccines compared to the traditional methods. 81 Conducting a rapid vaccine engineering approach during such a viral pandemic may need three important preliminary research steps, including (i) viral genome sequencing, (ii) bioinformatics and data analysis, and (iii) designing a gene-based vaccine construct. Under these circumstances, computational modeling and simulation methods can assist the vaccinologists to extrapolate close to real biological evidence for designing a promising recombinant vaccine with high accuracy, least cost, and minimal time. 32, 82 The in silico vaccinology, as a synergistic strategy is mainly based on (i) discovering of candidate vaccine antigens through the computer-aided data analysis approaches (e.g., reverse vaccinology), 83, 84 and (ii) identification of immunodominant epitopes by applying an immunoinformatics pipeline. [85] [86] [87] In this context, along with releasing multiple wholegenome sequences of SARS-CoV-2 together with our previous experience in designing and developing an epitope-based recombinant vaccine against Echinococcus granulosus through comprehensive field trials (National Patent number: 100538; IPC: C12R 32/1;A61P 00/33;C12N 00/15), we designed two domain-based vaccine constructs based on the two different vaccine production and delivery platforms (i.e. recombinant protein vaccine, and self-replicating mRNA vaccine) as candidate prophylactic treatment against COVID-19. In this line, we used the reference sequence of SARS-CoV-2 spike glycoprotein (accession ID: YP_009724390.1) to rationally design the vaccines. First, to find out the virus origin and its conserved/variable regions, we carried out a multiple sequence alignment and also phylogenetic analysis based on all the sequenced spike glycoprotein of SARS-related CoVs. According to our phylogenetic analysis, SARS-CoV-2 has a close genetic similarity to the bat-derived CoVs (Fig. 2) . A previous analysis using the haplotype network analysis announced that SARS-CoV-2 has emerged (or maybe emerging) due to the high frequently recurrent genetic recombination especially in the receptor-binding domain (RBD) of spike glycoprotein. 88 Theoretically, this natural occurrence has been likely affected in the virus transmissibility and pathogenicity through multiple amino acid alterations than SARS-CoV. 89 Based on the sequence variability analysis presented in the Shannon entropy plot (Fig. 2B) , the RBD was found to be 10 . A schematic illustration of the intracellular processing of LNPs formulated the SAM vaccine and the subsequent innate and pathogen-specific immune responses. The in vitro transcribed SAM vaccine is formulated as a targeted vaccine delivery system (VDS), which is internalized by the antigenpresenting cells through receptor-mediated endocytosis (1) . The targeted VDS is escaped from the endosomal compartment, and the initial endosomal RNA sensing by TLRs (mainly TLRs 3, 7, and 8) is activated (2) . Upon SAMV endosomal escape, two main pathways of innate and adaptive immune responses can be activated (3) . In the innate immune responses, steps 4' to 7' can occur. Both the SAM vaccine construct and the initial endosomal RNA sensing system activate the secondary RNA sensing system which is induced by cytosolic pathogen recognition receptors and then results in the production of type I interferons (INFα/β) (4', 5'). INFs are secreted (6'). The regulatory impacts of INFs are imposed on T-cell activity pathways (7'). In the Adaptive immune responses, steps 4-9 can occur. The in vivo translation of SAMV construct, the formation of RNA-dependent RNA polymerase (RdRp) complex, and the beginning a self-replication machinery for enhancement of the protein yield occur (4). The newly produced recombinant proteins have three possible destinies (5) . First, protein is released to the extracellular space and its TLR agonists (i.e. RS09, and FlgC) can activate both TLRs 4 and 5, respectively (6) . Second, protein is degraded by proteasomes to the small peptide fragments (7) . The peptide fragments are processed by the endoplasmic reticulum (8) . The MHC class I-epitope complexes are presented on the cell surface (9) . Third, the peptides enter the proteolytic endosomes (A) to form the MHC class II-epitope complexes (B) and to be presented on the cell surface (C). LNP: lipid-nanoparticle. SAMV: self-amplifying mRNA vaccine.

highly variable among different SARS-related CoVs. Tai et al represented a residue fragment (N 331 -V 524 ) in the RBD domain of spike protein which can significantly bound to human and bat ACE2 receptors with higher affinity than SARS-CoV. 80 They suggested this region as a candidate for the development of a prophylactic domain-based vaccine against SARS-CoV-2. Amino acid insertion or deletion can disrupt or make significant changes in the physiological function of an antigen. Ting et al observed the single amino acid substitutions in protein L1 of human papillomavirus 16 (HPV16) can change its susceptibility to neutralization by monoclonal antibodies or vaccinated sera. 90 It is newly reported that SARS-CoV and SARS-CoV-2 have either high binding capability to the ACE2 receptor but probably with different affinities. Walls et al and Zhang et al found a furin cleavage site (P 681 -V 687 ) of SARS-CoV-2 spike protein that is missed in the spike protein of all other SARS-related CoVs, and this insertion mutation has improved the mechanism of virus entry into the host cells. 91, 92 Existing knowledge about the SARS-CoV-2 is mainly based on the prediction and simulation algorithms derived from the experimental data of other SARS-related CoVs. Grifoni et al used SARS-CoV surface proteins (S, M, Orf 3a, Orf 1ab, and N) as a homolog model for SARS-CoV-2 to predict candidate B-and T-cell epitopes of SARS-CoV-2. 78 In a recent study, Ahmed et al utilized immunological data of SARS-CoV to predict the potential epitopes of SARS-CoV-2 spike and nucleocapsid proteins. 79 In another study, peptide binders to HLA-DR types of the Asia-pacific region were predicted based on the four surface proteins (S, E, M, and N) and five accessory proteins (ORF3a, ORF6, ORF7a, ORF8, and ORF10) of SARS-CoV-2. 93 Despite these homology-based methodologies for epitope mapping, we believe that an emerged virus may develop sparse peculiar epitopes. Especially, in the variable residues of the spike antigen, emerging probable neoepitopes may render different physicochemical features to form a stable complex with paratope site of antibodies and also binding groove of specific HLA molecules. 94, 95 At this stage, the prediction of SARS-CoV-2 epitopes by monitoring its homolog viruses (i.e. SARS-related CoVs) seems to be a reliable method for conserved epitopes. By the same token, we computed the S glycoprotein sequence based on a multi-method BCE prediction approach through various machine learning and physicochemical algorithms to find out the hub regions (not exact epitope sequence) with high potential for B-cell immune responses (Fig. 3A) . Then, through a stringent cut-off value (≥ 0.6) we identified a list of n=11 most immunodominant BCEs (Table 1) , which are almost compatible with the predicted BCEs by Bhattacharya et al. 96 As showed in the 3D structure of the spike protein, these immunodominant BCEs are in the surface accessible areas of the protein (Fig. 4) .

The currently developed methods for the T-cell epitope prediction are as a shortcut in epitope discovery; however, antigen processing and presentation in antigen-presenting cells (APCs) are followed through several complicated pathways. The T-cell epitope prediction servers specialized to provide widely dispersed dominant peptide binders with different lengths in a queried protein. Moreover, It is known that many of the cleaved peptides that are translocated into the endoplasmic reticulum (ER) have lengths of more than 8-10 amino acids, and some residues will be removed during processing by ER aminopeptidases. 97, 98 The structural studies verified that there are many different mechanisms whereby a long peptide binder originated from either structural and nonstructural antigens can proceed into the APCs, attached, and presented by MHC class I and II molecules. [99] [100] [101] [102] Currently, there is a lack of knowledge about the binding configuration/mechanism of SARS-CoV-2 epitopes and that how they make stable MHC-peptide complexes. In this regard, we used of online predictor tool IEDB to map potential high-rank T-cell peptide binders based on the reference set of HLA alleles covering > 97% (HLA-I) and > 99% (HLA-II) of the global population. To select candidate CD8 + T-cell epitopes, we defined a consensus ranking (CR) score to find out peptide binders with the lowest CR score and the highest HLA allele coverage (Fig. 5A) . To predict the most potential CD4 + T-cell binders, we selected peptide fragments with the lowest adjusted percentile rank (Fig.  5B) . The final T-cell epitopes were chosen based on the population coverage result of each predicted peptide fragment (Tables 2 and 3) .

Having considered the scaled map indicated in Fig. S6 , three hub domains of the spike glycoprotein covering the largest number of the best overlapping B-and T-cell epitopes were selected for the designing of the DVC (Fig.  6A ). Despite the high consistency between our predicted epitopes and the recently reported epitopes, 78, 79 we decided to target immunodominant domains of spike glycoprotein for vaccine designing, in large part due to the uncertainty about the exact sequence of B-and T-cell epitopes in different studies. This strategy allowed to have the optimal B-and T-cell epitopes through the natural humoral and cellular adaptive immune trafficking and APC-based proteolytic processing systems in the human body. We have joined the RS09 and S. typhimurium FlgC fragments at the N-terminal of the vaccine construct using an in vivo cleavable linker (Fig. 6A) . The RS09 and FlgC are agonists for TLR4 and TLR5, respectively. RS09 is an LPS peptide mimicking entity that can bind to TLR4 and stimulate it, resulting in the subsequent activation of NF-κB signaling pathways and secretion of chemokines. 103 FlgC is the structural unit of the bacterial flagellum, which can interact with TLR5-expressing cells (e.g., monocytes, neutrophils, DCs, lymphocytes, and macrophages) as an agonist of TLR5. 104, 105 Some studies reported the synergistic effects of the TLR4 and 5 signaling pathways; therefore, the use of FlgC might modulate initial innate and then the subsequent adaptive immune responses. 104, 106 We have validated the interaction of vaccine construct with the TLR4 and TLR5 using molecular docking and then MD simulations (Fig. 7) . Of note, as a strength, the self-amplifying mRNA vaccines have a high selfadjuvanted nature and both the endosomal and cytosolic RNA sensors (e.g., TLRs 3, 7, 8 and retinoic acid-inducible gene I (RIG-I) receptors, respectively) can recognize the viral derived agents and then trigger the innate immune signaling cascades (Fig. 10) . 107 The Pan-DR epitope (i.e. PADRE sequence), a 13mer synthetic T helper epitope, was also used to elicit more efficient adaptive immune responses (Fig. 6) . It is demonstrated that the linear PADRE epitope in conjugation with the carbohydrate BCE can stimulate specific IgG antibodies. 108 The PADRE sequence was added between the RS09 and spike glycoprotein's domains using the intracellular cleavable linker to facilitate its independent processing and presentation by APCs (Fig. 6) .

To produce the designed recombinant protein vaccine in a lab setting, a suitable expression host such as microalgae can be used to express the recombinant vaccine with the optimal post-translational modifications. 109, 110 In the case of SAMV construct, although both the non-viral delivery systems (e.g., lipid nanoparticles, 111 polymeric nanoparticles, 112 and cell-penetrating peptides 113 ), and in vivo transfection systems (e.g., injection, electroporation, and gene gun) can improve the stability and cellular uptake efficacy, however, the naked SAM vaccine can be taken up as well by significantly antigen-presenting cells without any additional required formulation. 114

Having capitalized on bioinformatics tools in the current study, for the first time, we designed two domain-based vaccine constructs against SARS-CoV-2 based on the two different vaccine production and delivery platforms including, (i) a recombinant protein vaccine, and (ii) a selfamplifying mRNA vaccine. We believe that the results of this study can be a step ahead in the vaccine development campaign against SARS-CoV-2. The methods used for the identification of the hub residue fragments of S glycoprotein were conducted based on the rational data filtering and also the precise multi-method analyses of various immunological datasets. The sequential and structural analysis of the DPVC showed that the vaccine is stable, safe, and immunogenic. In this context, these constructs are our urgent ongoing project to monitor the vaccine's potential to trigger properly both innate and specific B-and T-cell immune responses in animal models. Altogether, we have considered comprehensive key factors in the prediction of epitopes and the designing of both the DPVC and SAMV to ensure the proposed Designing a domain-based vaccine construct against SARS-CoV-2 BioImpacts, 2021, 11(1), 65- 84 81 vaccines can induce both innate and pathogen-specific immune responses. As a result, we proposed the designed vaccines are promising vaccines against SARS-CoV-2 after being further examined through accelerated animal studies and clinical trials.

Emerging and Reemerging Infectious Diseases: Global Overview

Epitopes for a 2019-nCoV vaccine

Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China

Coronaviridae Study Group of the International Committee on Taxonomy of V. The species Severe acute respiratory syndromerelated coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2

The cost and challenge of vaccine development for emerging and emergent infectious diseases

Systems Biology-Based Platforms to Accelerate Research of Emerging Infectious Diseases

Immunoinformatics guided rational design of a next generation multi epitope based peptide (MEBP) vaccine by exploring Zika virus proteome

Systems vaccinology and big data in the vaccine development chain

Epitopebased vaccine design: a comprehensive overview of bioinformatics approaches

The search for a promising cell factory system for production of edible vaccine

Current status and future prospective of vaccine development against Echinococcus granulosus

mRNA as a Transformative Technology for Vaccine Development to Control Infectious Diseases

Development of a SARS Coronavirus Vaccine from Recombinant Spike Protein Plus Delta Inulin Adjuvant

Understanding bat SARS-like coronaviruses for the preparation of future coronavirus outbreaks -Implications for coronavirus vaccine development

Molecular Evolutionary Genetics Analysis across Computing Platforms

MUSCLE: multiple sequence alignment with high accuracy and high throughput

The rapid generation of mutation data matrices from protein sequences

Estimating errors and confidence intervals for branch lengths in phylogenetic trees by a bootstrap approach

The TOPCONS web server for consensus prediction of membrane protein topology and signal peptides

CCTOP: a Consensus Constrained TOPology prediction web server

Secreted protein prediction system combining

CDD/SPARCLE: functional classification of proteins via subfamily domain architectures

BioEdit: A User-Friendly Biological Sequence Alignment Editor and Analysis Program for Windows 95/98/NT

The PSIPRED Protein Analysis Workbench: 20 years on

SWISS-MODEL: homology modelling of protein structures and complexes

GalaxyRefine: Protein structure refinement driven by side-chain repacking

5: a high-throughput and highly parallel open source molecular simulation toolkit

In silico design of a triple-negative breast cancer vaccine by targeting cancer testis antigens

AQUA and PROCHECK-NMR: programs for checking the quality of protein structures solved by NMR

VERIFY3D: assessment of protein models with three-dimensional profiles

Verification of protein structures: patterns of nonbonded atomic interactions

A multi-method and structure-based in silico vaccine designing against Echinococcus granulosus through investigating enolase protein

BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes

Improved method for linear B-cell epitope prediction using antigen's primary sequence

Open Source Drug Discovery C, Raghava GP. Identification of B-cell epitopes in an antigen for inducing specific class of antibodies

Identification of conformational B-cell Epitopes in an antigen from its primary sequence

BEPITOPE: predicting the location of continuous epitopes and patterns in proteins

Prediction of continuous B-cell epitopes in an antigen using recurrent neural network

SEPPA 3.0-enhanced spatial epitope prediction enabling glycoprotein antigens

Reliable B cell epitope predictions: impacts of method development and improved benchmarking

ElliPro: a new structure-based tool for the prediction of antibody epitopes

Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega

ViPR: an open bioinformatics database and analysis resource for virology research

A consensus epitope prediction approach identifies the breadth of murine T(CD8+)-cell responses to vaccinia virus

Reliable prediction of T-cell epitopes using neural networks with novel sequence representations

A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach

Functional classification of class II human leukocyte antigen (HLA) molecules reveals seven different supertypes and a surprising degree of repertoire sharing across supertypes

Allele frequency net 2015 update: new features for HLA epitopes, KIR and disease and HLA adverse drug reaction associations

The Immune Epitope Database (IEDB): 2018 update

Novel drugs targeting Toll-like receptors for antiviral therapy

Advances in Antiviral Therapies Targeting Toll-like Receptors

Synthetic Toll like receptor-4 (TLR-4) agonist peptides as a novel class of adjuvants

Salmonella flagellins are potent adjuvants for intranasally administered whole inactivated influenza vaccine

Substrate hydrolysis by matrix metalloproteinase-9

Designing a domain-based vaccine construct against SARS-CoV-2

Collagenolytic and gelatinolytic matrix metalloproteinases and their inhibitors in basal cell carcinoma of skin: comparison with normal skin

Upregulation of cathepsin S in psoriatic keratinocytes

Cathepsin S activity regulates antigen presentation and immunity

Engineered hybrid spider silk particles as delivery system for peptide vaccines

The use of signal peptide domains as vaccine candidates

Self-Replicating RNA

Leveraging mRNAs sequences to express SARS-CoV-2 antigens in vivo

VaxiJen Dataset of Bacterial Immunogens: An Update

AlgPred: prediction of allergenic proteins and mapping of IgE epitopes

AllerTOP v.2--a server for in silico prediction of allergens

Protein identification and analysis tools in the ExPASy server

GOR method for predicting protein secondary structure from amino acid sequence

I-TASSER server: new development for protein structure and function predictions

The ClusPro web server for protein-protein docking

UCSF Chimera--a visualization system for exploratory research and analysis

LigPlot+: multiple ligand-protein interaction diagrams for drug discovery

SARS corona virus peptides recognized by antibodies in the sera of convalescent cases

MODELLER, and IMP: an integrated modeling system

A community resource benchmarking predictions of peptide binding to MHC-I molecules

I-TASSER server for protein 3D structure prediction

Scoring function for automated assessment of protein structure template quality

Up-regulation of IL-6 and TNF-alpha induced by SARS-coronavirus spike protein in murine macrophages via NF-kappaB pathway

RNA sensors of the innate immune system and their detection of pathogens

A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2

Preliminary Identification of Potential Vaccine Targets for the COVID-19 Coronavirus (SARS-CoV-2) Based on SARS-CoV Immunological Studies

Characterization of the receptor-binding domain (RBD) of 2019 novel coronavirus: implication for development of RBD protein as a viral attachment inhibitor and vaccine

Next-generation vaccines and the impacts of state-of-the-art in-silico technologies

Preliminary bioinformatics studies on the design of a synthetic vaccine and a preventative peptidomimetic antagonist against the SARS-CoV-2 (2019-nCoV, COVID-19) coronavirus

Editorial: Reverse Vaccinology

Fundamentals and Methods for T-and B-Cell Epitope Prediction

A novel B-and helper T-cell epitopes-based prophylactic vaccine against Echinococcus granulosus

In-silico design of a multi-epitope vaccine candidate against onchocerciasis and related filarial diseases

A novel in silico minigene vaccine based on CD4(+) T-helper and B-cell epitopes of EG95 isolates for vaccination against cystic echinococcosis

novel coronavirus is undergoing active recombination

The proximal origin of SARS-CoV-2

Naturally Occurring Single Amino Acid Substitution in the L1 Major Capsid Protein of Human Papillomavirus Type 16: Alteration of Susceptibility to Antibody-Mediated Neutralization

Probable Pangolin Origin of SARS-CoV-2 Associated with the COVID-19 Outbreak

Antigenicity of the SARS-CoV-2 Spike Glycoprotein

Insights into Cross-species Evolution of Novel Human Coronavirus 2019-nCoV and Defining Immune Determinants for Vaccine Development

Level of neo-epitope predecessor and mutation type determine T cell activation of MHC binding peptides

Nanobody-based therapeutics against colorectal cancer: Precision therapies based on the personal mutanome profile and tumor neoantigens

Development of epitope-based peptide vaccine against novel coronavirus 2019 (SARS-COV-2): Immunoinformatics approach

Pathways of antigen processing

The Length Distribution of Class I-Restricted T Cell Epitopes Is Determined by Both Peptide Supply and MHC Allele-Specific Binding Preference

Human T Cell Response to Dengue Virus Infection

Selective CD4+ T cell help for antibody responses to a large viral pathogen: deterministic linkage of specificities

Have we cut ourselves too short in mapping CTL epitopes?

A long N-terminal-extended nested set of abundant and antigenic major histocompatibility complex class I natural ligands from HIV envelope protein

Intranasal Vaccination against HIV-1 with Adenoviral Vector-Based Nanocomplex Using Synthetic TLR-4 Agonist Peptide as Adjuvant

Bacterial flagellin-a potent immunomodulatory agent

Microneedle array delivered recombinant coronavirus vaccines: Immunogenicity and rapid translational development

TLR5 participates in the TLR4 receptor complex and promotes MyD88-dependent signaling in environmental lung injury

Enlisting the mRNA Vaccine Platform to Combat Parasitic Infections

Linear PADRE T helper epitope and carbohydrate B cell epitope conjugates induce specific high titer IgG antibody responses

Stable transformation of Spirulina (Arthrospira) platensis: a promising microalga for production of edible vaccines

Towards a new avenue for producing therapeutic proteins: Microalgae as a tempting green biofactory

Advances in mRNA Vaccines for Infectious Diseases

Overexpression of CFL1 in gastric cancer and the effects of its silencing by siRNA with a nanoparticle delivery system in the gastric cancer cell line

Peptidemediated drug delivery across the blood-brain barrier for targeting brain tumors

Self-Replicating RNA Viruses for RNA Therapeutics

The authors are very thankful to all the nurses, physicians, and every one of the workers in hospitals who have been being exposed to the SARS-CoV-2 infectious agent worldwide. Further, the authors are grateful to the Research Center for Pharmaceutical Nanotechnology (RCPN) at

The study protocol and research concept were designed by YO and MMP; The original draft, and the data analyses were performed by MMP; The molecular dynamics simulations were carried out by SP; The manuscript wrote by MMP; The manuscript was reviewed and edited by YO, BN, BJ and JD; The project was supervised by YO.What is the current knowledge? √ The B-and T-cell multi-epitope mapping provided versatile results for the immunodominant regions of SARS-CoV-2 spike protein. √ Using the consensus rank (CR) score and the approach used for T-cell epitope mapping, one can design a potentially immunogenic candidate vaccine with high population coverage. √ The self-amplifying mRNA (SAM) vaccine can be used as a nanoparticle-based vaccine (so-called nanovaccine) with an intrinsic adjuvanticity feature.What is new here? √ The multi-method approach for the prediction of spike protein B-cell epitopes improved the accuracy of the in silico epitope mapping. √ The CR score as a precise method could promote selection of best T-cell epitopes with highest binding affinity and population coverage. √ The designed SAM vaccine is a nanovaccine that offer both B-cell and T-cell immunity with an intrinsic adjuvanticity feature. Supplementary file 1 contains Figs. S1-S7 and Tables S1-S3.  Supplementary file 2 contains Table S4. Supplementary file 3 contains  Table S5. Supplementary file 4 contains Table S6. Supplementary file 5  contains Tables S7-S9.