Immunoinformatics-aided design of a new multi-epitope vaccine adjuvanted with domain 4 of pneumolysin against Streptococcus pneumoniae strains.

BACKGROUND: Streptococcus pneumoniae (Pneumococcus) has remained a leading cause of fatal infections such as pneumonia, meningitis, and sepsis. Moreover, this pathogen plays a major role in bacterial co-infection in patients with life-threatening respiratory virus diseases such as influenza and COVID-19. High morbidity and mortality in over one million cases, especially in very young children and the elderly, are the main motivations for pneumococcal vaccine development. Due to the limitations of the currently marketed polysaccharide-based vaccines, non-serotype-specific protein-based vaccines have received wide research interest in recent years. One step further is to identify high antigenic regions within multiple highly-conserved proteins in order to develop peptide vaccines that can affect various stages of pneumococcal infection, providing broader serotype coverage and more effective protection. In this study, immunoinformatics tools were used to design an effective multi-epitope vaccine in order to elicit neutralizing antibodies against multiple strains of pneumococcus. RESULTS: The B- and T-cell epitopes from highly protective antigens PspA (clades 1-5) and PhtD were predicted and immunodominant peptides were linked to each other with proper linkers. The domain 4 of Ply, as a potential TLR4 agonist adjuvant candidate, was attached to the end of the construct to enhance the immunogenicity of the epitope vaccine. The evaluation of the physicochemical and immunological properties showed that the final construct was stable, soluble, antigenic, and non-allergenic. Furthermore, the protein was found to be acidic and hydrophilic in nature. The protein 3D-structure was built and refined, and the Ramachandran plot, ProSA-web, ERRAT, and Verify3D validated the quality of the final model. Molecular docking analysis showed that the designed construct via Ply domain 4 had a strong interaction with TLR4. The structural stability of the docked complex was confirmed by molecular dynamics. Finally, codon optimization was performed for gene expression in E. coli, followed by in silico cloning in the pET28a(+) vector. CONCLUSION: The computational analysis of the construct showed acceptable results, however, the suggested vaccine needs to be experimentally verified in laboratory to ensure its safety and immunogenicity.

Exploiting reverse vaccinology approach for the design of a multiepitope subunit vaccine against the major SARS-CoV-2 variants.

The current COVID-19 pandemic, an infectious disease caused by the novel coronavirus (SARS-CoV-2), poses a threat to global health because of its high rate of spread and death. Currently, vaccination is the most effective method to prevent the spread of this disease. In the present study, we developed a novel multiepitope vaccine against SARS-CoV-2 containing Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (BA.1) variants. To this end, we performed a robust immunoinformatics approach based on multiple epitopes of the four structural proteins of SARS-CoV-2 (S, M, N, and E) from 475 SARS-CoV-2 genomes sequenced from the regions with the highest number of registered cases, namely the United States, India, Brazil, France, Germany, and the United Kingdom. To investigate the best immunogenic epitopes for linear B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL), we evaluated antigenicity, allergenicity, conservation, immunogenicity, toxicity, human population coverage, IFN-inducing, post-translational modifications, and physicochemical properties. The tertiary structure of a vaccine prototype was predicted, refined, and validated. Through docking experiments, we evaluated its molecular coupling to the key immune receptor Toll-Like Receptor 3 (TLR3). To improve the quality of docking calculations, quantum mechanics/molecular mechanics calculations (QM/MM) were used, with the QM part of the simulations performed using the density functional theory formalism (DFT). Cloning and codon optimization were performed for the successful expression of the vaccine in E. coli. Finally, we investigated the immunogenic properties and immune response of our SARS-CoV-2 multiepitope vaccine. The results of the simulations show that administering our prototype three times significantly increases the antibody response and decreases the amount of antigens. The proposed vaccine candidate should therefore be tested in clinical trials for its efficacy in neutralizing SARS-CoV-2.

In silico designing of a novel epitope-based candidate vaccine against Streptococcus pneumoniae with introduction of a new domain of PepO as adjuvant.

BACKGROUND: Streptococcus pneumoniae is the leading reason for invasive diseases including pneumonia and meningitis, and also secondary infections following viral respiratory diseases such as flu and COVID-19. Currently, serotype-dependent vaccines, which have several insufficiency and limitations, are the only way to prevent pneumococcal infections. Hence, it is plain to need an alternative effective strategy for prevention of this organism. Protein-based vaccine involving conserved pneumococcal protein antigens with different roles in virulence could provide an eligible alternative to existing vaccines. METHODS: In this study, PspC, PhtD and PsaA antigens from pneumococcus were taken to account to predict B-cell and helper T-cell epitopes, and epitope-rich regions were chosen to build the construct. To enhance the immunogenicity of the epitope-based vaccine, a truncated N-terminal fragment of pneumococcal endopeptidase O (PepO) was used as a potential TLR2/4 agonist which was identified by molecular docking studies. The ultimate construct was consisted of the chosen epitope-rich regions, along with the adjuvant role (truncated N-PepO) and suitable linkers. RESULTS: The epitope-based vaccine was assessed as regards physicochemical properties, allergenicity, antigenicity, and toxicity. The 3D structure of the engineered construct was modeled, refined, and validated. Molecular docking and simulation of molecular dynamics (MD) indicated the proper and stable interactions between the vaccine and TLR2/4 throughout the simulation periods. CONCLUSIONS: For the first time this work presents a novel vaccine consisting of epitopes of PspC, PhtD, and PsaA antigens which is adjuvanted with a new truncated domain of PepO. The computational outcomes revealed that the suggested vaccine could be deemed an efficient therapeutic vaccine for S. pneumoniae; nevertheless, in vitro and in vivo examinations should be performed to prove the potency of the candidate vaccine.

Molecular modelling on multiepitope-based vaccine against SARS-CoV-2 using immunoinformatics, molecular docking, and molecular dynamics simulation.

The pandemic of COVID-19 caused by SARS-CoV-2 has made a worldwide health emergency. Despite the fact that current vaccines are readily available, several SARSCoV-2 variants affecting the existing vaccine are to be less effective due to the mutations in the structural proteins. Furthermore, the appearance of the new variants cannot be easily predicted in the future. Therefore, the attempts to construct new vaccines or to modify the current vaccines are still pivotal works for preventing the spread of the virus. In the present investigation, the computational analysis through immunoinformatics, molecular docking, and molecular dynamics (MD) simulation is employed to construct an effective vaccine against SARS-CoV2. The structural proteins of SARS-CoV2 are utilized to create a multiepitope-based vaccine (MEV). According to our findings presented by systematic procedures in the current investigation, the MEV construct may be able to trigger a strong immunological response against the virus. Therefore, the designed MEV could be a potential vaccine candidate against SARS-CoV-2, and also it is expected to be effective for other variants.

Potential Immunogenic Activity of Computationally Designed mRNA- and Peptide-Based Prophylactic Vaccines against MERS, SARS-CoV, and SARS-CoV-2: A Reverse Vaccinology Approach.

The continued emergence of human coronaviruses (hCoVs) in the last few decades has posed an alarming situation and requires advanced cross-protective strategies against these pandemic viruses. Among these, Middle East Respiratory Syndrome coronavirus (MERS-CoV), Severe Acute Respiratory Syndrome coronavirus (SARS-CoV), and Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2) have been highly associated with lethality in humans. Despite the challenges posed by these viruses, it is imperative to develop effective antiviral therapeutics and vaccines for these human-infecting viruses. The proteomic similarity between the receptor-binding domains (RBDs) among the three viral species offers a potential target for advanced cross-protective vaccine designs. In this study, putative immunogenic epitopes including Cytotoxic T Lymphocytes (CTLs), Helper T Lymphocytes (HTLs), and Beta-cells (B-cells) were predicted for each RBD-containing region of the three highly pathogenic hCoVs. This was followed by the structural organization of peptide- and mRNA-based prophylactic vaccine designs. The validated 3D structures of these epitope-based vaccine designs were subjected to molecular docking with human TLR4. Furthermore, the CTL and HTL epitopes were processed for binding with respective human Lymphocytes Antigens (HLAs). In silico cloning designs were obtained for the prophylactic vaccine designs and may be useful in further experimental designs. Additionally, the epitope-based vaccine designs were evaluated for immunogenic activity through immune simulation. Further studies may clarify the safety and efficacy of these prophylactic vaccine designs through experimental testing against these human-pathogenic coronaviruses.

MPLA-Adjuvanted Liposomes Encapsulating S-Trimer or RBD or S1, but Not S-ECD, Elicit Robust Neutralization Against SARS-CoV-2 and Variants of Concern.

Safe and effective vaccines are the best method to defeat worldwide SARS-CoV-2 and its circulating variants. The SARS-CoV-2 S protein and its subunits are the most attractive targets for the development of protein-based vaccines. In this study, we evaluated three lipophilic adjuvants, monophosphoryl lipid A (MPLA), Toll-like receptor (TLR) 1/2 ligand Pam3CSK4, and α-galactosylceramide (α-GalCer), in liposomal and nonliposomal vaccines. The immunological results showed that the MPLA-adjuvanted liposomal vaccine induced the strongest humoral and cellular immunity. Therefore, we further performed a systematic comparison of S-trimer, S-ECD, S1, and RBD as antigens in MPLA-adjuvanted liposomes and found that, although these four vaccines all induced robust specific antibody responses, only S-trimer, S1, and RBD liposomes, but not S-ECD, elicited potent neutralizing antibody responses. Moreover, RBD, S-trimer, and S1 liposomes effectively neutralized variants (B.1.1.7/alpha, B.1.351/beta, P.1/gamma, B.1.617.2/delta, and B.1.1.529/omicron). These results provide important information for the subunit vaccine design against SARS-CoV-2 and its variants.

Immuno-informatics analysis predicts B and T cell consensus epitopes for designing peptide vaccine against SARS-CoV-2 with 99.82% global population coverage.

The current global pandemic due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has taken a substantial number of lives across the world. Although few vaccines have been rolled-out, a number of vaccine candidates are still under clinical trials at various pharmaceutical companies and laboratories around the world. Considering the intrinsic nature of viruses in mutating and evolving over time, persistent efforts are needed to develop better vaccine candidates. In this study, various immuno-informatics tools and bioinformatics databases were deployed to derive consensus B-cell and T-cell epitope sequences of SARS-CoV-2 spike glycoprotein. This approach has identified four potential epitopes which have the capability to initiate both antibody and cell-mediated immune responses, are non-allergenic and do not trigger autoimmunity. These peptide sequences were also evaluated to show 99.82% of global population coverage based on the genotypic frequencies of HLA binding alleles for both MHC class-I and class-II and are unique for SARS-CoV-2 isolated from human as a host species. Epitope number 2 alone had a global population coverage of 98.2%. Therefore, we further validated binding and interaction of its constituent T-cell epitopes with their corresponding HLA proteins using molecular docking and molecular dynamics simulation experiments, followed by binding free energy calculations with molecular mechanics Poisson-Boltzmann surface area, essential dynamics analysis and free energy landscape analysis. The immuno-informatics pipeline described and the candidate epitopes discovered herein could have significant impact upon efforts to develop globally effective SARS-CoV-2 vaccines.

In Silico Designing of a Multitope Vaccine against Rhizopus microsporus with Potential Activity against Other Mucormycosis Causing Fungi.

During the current era of the COVID-19 pandemic, the dissemination of Mucorales has been reported globally, with elevated rates of infection in India, and because of the high rate of mortality and morbidity, designing an effective vaccine against mucormycosis is a major health priority, especially for immunocompromised patients. In the current study, we studied shared Mucorales proteins, which have been reported as virulence factors, and after analysis of several virulent proteins for their antigenicity and subcellular localization, we selected spore coat (CotH) and serine protease (SP) proteins as the targets of epitope mapping. The current study proposes a vaccine constructed based on top-ranking cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes from filtered proteins. In addition to the selected epitopes, ß-defensins adjuvant and PADRE peptide were included in the constructed vaccine to improve the stimulated immune response. Computational tools were used to estimate the physicochemical and immunological features of the proposed vaccine and validate its binding with TLR-2, where the output data of these assessments potentiate the probability of the constructed vaccine to stimulate a specific immune response against mucormycosis. Here, we demonstrate the approach of potential vaccine construction and assessment through computational tools, and to the best of our knowledge, this is the first study of a proposed vaccine against mucormycosis based on the immunoinformatics approach.

Hydrogel-Based Slow Release of a Receptor-Binding Domain Subunit Vaccine Elicits Neutralizing Antibody Responses Against SARS-CoV-2.

The development of effective vaccines that can be rapidly manufactured and distributed worldwide is necessary to mitigate the devastating health and economic impacts of pandemics like COVID-19. The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein, which mediates host cell entry of the virus, is an appealing antigen for subunit vaccines because it is efficient to manufacture, highly stable, and a target for neutralizing antibodies. Unfortunately, RBD is poorly immunogenic. While most subunit vaccines are commonly formulated with adjuvants to enhance their immunogenicity, clinically-relevant adjuvants Alum, AddaVax, and CpG/Alum are found unable to elicit neutralizing responses following a prime-boost immunization. Here, it has been shown that sustained delivery of an RBD subunit vaccine comprising CpG/Alum adjuvant in an injectable polymer-nanoparticle (PNP) hydrogel elicited potent anti-RBD and anti-spike antibody titers, providing broader protection against SARS-CoV-2 variants of concern compared to bolus administration of the same vaccine and vaccines comprising other clinically-relevant adjuvant systems. Notably, a SARS-CoV-2 spike-pseudotyped lentivirus neutralization assay revealed that hydrogel-based vaccines elicited potent neutralizing responses when bolus vaccines did not. Together, these results suggest that slow delivery of RBD subunit vaccines with PNP hydrogels can significantly enhance the immunogenicity of RBD and induce neutralizing humoral immunity.

A Global Review on Short Peptides: Frontiers and Perspectives.

Peptides are fragments of proteins that carry out biological functions. They act as signaling entities via all domains of life and interfere with protein-protein interactions, which are indispensable in bio-processes. Short peptides include fundamental molecular information for a prelude to the symphony of life. They have aroused considerable interest due to their unique features and great promise in innovative bio-therapies. This work focusing on the current state-of-the-art short peptide-based therapeutical developments is the first global review written by researchers from all continents, as a celebration of 100 years of peptide therapeutics since the commencement of insulin therapy in the 1920s. Peptide "drugs" initially played only the role of hormone analogs to balance disorders. Nowadays, they achieve numerous biomedical tasks, can cross membranes, or reach intracellular targets. The role of peptides in bio-processes can hardly be mimicked by other chemical substances. The article is divided into independent sections, which are related to either the progress in short peptide-based theranostics or the problems posing challenge to bio-medicine. In particular, the SWOT analysis of short peptides, their relevance in therapies of diverse diseases, improvements in (bio)synthesis platforms, advanced nano-supramolecular technologies, aptamers, altered peptide ligands and in silico methodologies to overcome peptide limitations, modern smart bio-functional materials, vaccines, and drug/gene-targeted delivery systems are discussed.

Design of an epitope-based peptide vaccine against the SARS-CoV-2: a vaccine-informatics approach.

The recurrent and recent global outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has turned into a global concern which has infected more than 42 million people all over the globe, and this number is increasing in hours. Unfortunately, no vaccine or specific treatment is available, which makes it more deadly. A vaccine-informatics approach has shown significant breakthrough in peptide-based epitope mapping and opens the new horizon in vaccine development. In this study, we have identified a total of 15 antigenic peptides [including thymus cells (T-cells) and bone marrow or bursa-derived cells] in the surface glycoprotein (SG) of SARS-CoV-2 which is nontoxic and nonallergenic in nature, nonallergenic, highly antigenic and non-mutated in other SARS-CoV-2 virus strains. The population coverage analysis has found that cluster of differentiation 4 (CD4+) T-cell peptides showed higher cumulative population coverage over cluster of differentiation 8 (CD8+) peptides in the 16 different geographical regions of the world. We identified 12 peptides ((LTDEMIAQY, WTAGAAAYY, WMESEFRVY, IRASANLAA, FGAISSVLN, VKQLSSNFG, FAMQMAYRF, FGAGAALQI, YGFQPTNGVGYQ, LPDPSKPSKR, QTQTNSPRRARS and VITPGTNTSN) that are $80\hbox{--} 90\%$ identical with experimentally determined epitopes of SARS-CoV, and this will likely be beneficial for a quick progression of the vaccine design. Moreover, docking analysis suggested that the identified peptides are tightly bound in the groove of human leukocyte antigen molecules which can induce the T-cell response. Overall, this study allows us to determine potent peptide antigen targets in the SG on intuitive grounds, which opens up a new horizon in the coronavirus disease (COVID-19) research. However, this study needs experimental validation by in vitro and in vivo.

An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study.

The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over the world has led to over millions of deaths, and devastated the social, financial and political entities around the world. Without an existing effective medical therapy, vaccines are urgently needed to avoid the spread of this disease. In this study, we propose an in silico deep learning approach for prediction and design of a multi-epitope vaccine (DeepVacPred). By combining the in silico immunoinformatics and deep neural network strategies, the DeepVacPred computational framework directly predicts 26 potential vaccine subunits from the available SARS-CoV-2 spike protein sequence. We further use in silico methods to investigate the linear B-cell epitopes, Cytotoxic T Lymphocytes (CTL) epitopes, Helper T Lymphocytes (HTL) epitopes in the 26 subunit candidates and identify the best 11 of them to construct a multi-epitope vaccine for SARS-CoV-2 virus. The human population coverage, antigenicity, allergenicity, toxicity, physicochemical properties and secondary structure of the designed vaccine are evaluated via state-of-the-art bioinformatic approaches, showing good quality of the designed vaccine. The 3D structure of the designed vaccine is predicted, refined and validated by in silico tools. Finally, we optimize and insert the codon sequence into a plasmid to ensure the cloning and expression efficiency. In conclusion, this proposed artificial intelligence (AI) based vaccine discovery framework accelerates the vaccine design process and constructs a 694aa multi-epitope vaccine containing 16 B-cell epitopes, 82 CTL epitopes and 89 HTL epitopes, which is promising to fight the SARS-CoV-2 viral infection and can be further evaluated in clinical studies. Moreover, we trace the RNA mutations of the SARS-CoV-2 and ensure that the designed vaccine can tackle the recent RNA mutations of the virus.

Exploring the possible use of saponin adjuvants in COVID-19 vaccine.

There is an urgent need for a safe, efficacious, and cost-effective vaccine for the coronavirus disease 2019 (COVID-19) pandemic caused by novel coronavirus strain, severe acute respiratory syndrome-2 (SARS-CoV-2). The protective immunity of certain types of vaccines can be enhanced by the addition of adjuvants. Many diverse classes of compounds have been identified as adjuvants, including mineral salts, microbial products, emulsions, saponins, cytokines, polymers, microparticles, and liposomes. Several saponins have been shown to stimulate both the Th1-type immune response and the production of cytotoxic T lymphocytes against endogenous antigens, making them very useful for subunit vaccines, especially those for intracellular pathogens. In this review, we discuss the structural characteristics, mechanisms of action, structure-activity relationship of saponins, biological activities, and use of saponins in various viral vaccines and their applicability to a SARS-CoV-2 vaccine.

Techniques assisting peptide vaccine and peptidomimetic design. Sidechain exposure in the SARS-CoV-2 spike glycoprotein.

The aim of the present study is to discuss the design of peptide vaccines and peptidomimetics against SARS-COV-2, to develop and apply a method of protein structure analysis that is particularly appropriate to applying and discussing such design, and also to use that method to summarize some important features of the SARS-COV-2 spike protein sequence. A tool for assessing sidechain exposure in the SARS-CoV-2 spike glycoprotein is described. It extends to assessing accessibility of sidechains by considering several different three-dimensional structure determinations of SARS-CoV-2 and SARS-CoV-1 spike protein. The method is designed to be insensitive to a distance limit for counting neighboring atoms and the results are in good agreement with the physical chemical properties and exposure trends of the 20 naturally occurring sidechains. The spike protein sequence is analyzed with comment regarding exposable character. It includes studies of complexes with antibody elements and ACE2. These indicate changes in exposure at sites remote to those at which the antibody binds. They are of interest concerning design of synthetic peptide vaccines, and for peptidomimetics as a basis of drug discovery. The method was also developed in order to provide linear (one-dimensional) information that can be used along with other bioinformatics data of this kind in data mining and machine learning, potentially as genomic data regarding protein polymorphisms to be combined with more traditional clinical data.

Rapid Response Subunit Vaccine Design in the Absence of Structural Information.

Prior to 2020, the threat of a novel viral pandemic was omnipresent but largely ignored. Just 12 months prior to the Coronavirus disease 2019 (COVID-19) pandemic our team received funding from the Coalition for Epidemic Preparedness Innovations (CEPI) to establish and validate a rapid response pipeline for subunit vaccine development based on our proprietary Molecular Clamp platform. Throughout the course of 2019 we conducted two mock tests of our system for rapid antigen production against two potential, emerging viral pathogens, Achimota paramyxovirus and Wenzhou mammarenavirus. For each virus we expressed a small panel of recombinant variants of the membrane fusion protein and screened for expression level, product homogeneity, and the presence of the expected trimeric pre-fusion conformation. Lessons learned from this exercise paved the way for our response to COVID-19, for which our candidate antigen is currently in phase I clinical trial.

Epitope-Based Potential Vaccine Candidate for Humoral and Cell-Mediated Immunity to Combat Severe Acute Respiratory Syndrome Coronavirus 2 Pandemic.

The emergence of severe acute respiratory syndrome from novel Coronavirus (SARS-CoV-2) has put an immense pressure worldwide where vaccination is believed to be an efficient way for developing hard immunity. Herein, we employ immunoinformatic tools to identify B-cell, T-cell epitopes associated with the spike protein of SARS-CoV-2, which is important for genome release. The results showed that the highly immunogenic epitopes located at the stalk part are mostly conserved compared to the receptor binding domain (RDB). Further, two vaccine candidates were computationally modeled from the linear B-cell, T-cell epitopes. Molecular docking reveals the crucial interactions of the vaccines with immune-receptors, and their stability is assessed by MD simulation studies. The chimeric vaccines showed remarkable binding affinity toward the immune cell receptors computed by the MM/PBSA method. van der Waals and electrostatic interactions are found to be the dominant factors for the stability of the complexes. The molecular-level interaction obtained from this study may provide deeper insight into the process of vaccine development against the pandemic of COVID-19.

The PentaFOLD 3.0 Algorithm for the Selection of Stable Elements of Secondary Structure to be Included in Vaccine Peptides.

AIMS: The aim of this study was to create a new version of the PentaFOLD algorithm and to test its performance experimentally in several proteins and peptides. BACKGROUND: Synthetic vaccines can cause production of neutralizing antibodies only in case if short peptides form the same secondary structure as fragments of full-length proteins. The Penta- FOLD 3.0 algorithm was designed to check stability of alpha helices, beta strands, and random coils using several propensity scales obtained during analysis of 1730 3D structures of proteins. OBJECTIVE: The algorithm has been tested in the three peptides known to keep the secondary structure of the corresponding fragments of full-length proteins: the NY25 peptide from the Influenza H1N1 hemagglutinin, the SF23 peptide from the diphtheria toxin, the NQ21 peptide from the HIV1 gp120; as well as in the CC36 peptide from the human major prion protein. METHODS: Affine chromatography for antibodies against peptides accompanied by circular dichroism and fluorescence spectroscopy were used to check the predictions of the algorithm. RESULTS: Immunological experiments showed that all abovementioned peptides are more or less immunogenic in rabbits. The fact that antibodies against the NY25, the SF23, and the NQ21 form stable complexes with corresponding full-length proteins has been confirmed by affine chromatography. The surface of SARS CoV-2 spike receptor-binding domain interacting with hACE2 has been shown to be unstable according to the results of the PentaFOLD 3.0. CONCLUSION: The PentaFOLD 3.0 algorithm (http://chemres.bsmu.by/PentaFOLD30.htm) can be used with the aim to design vaccine peptides with stable secondary structure elements.

Design of novel multiepitope constructs-based peptide vaccine against the structural S, N and M proteins of human COVID-19 using immunoinformatics analysis.

The causative agent of severe acute respiratory syndrome (SARS) reported by the Chinese Center for Disease Control (China CDC) has been identified as a novel Betacoronavirus (SARS-CoV-2). A computational approach was adopted to identify multiepitope vaccine candidates against SARS-CoV-2 based on S, N and M proteins being able to elicit both humoral and cellular immune responses. In this study, the sequence of the virus was obtained from NCBI database and analyzed with in silico tools such as NetMHCpan, IEDB, BepiPred, NetCTL, Tap transport/proteasomal cleavage, Pa3P, GalexyPepDock, I-TASSER, Ellipro and ClusPro. To identify the most immunodominant regions, after analysis of population coverage and epitope conservancy, we proposed three different constructs based on linear B-cell, CTL and HTL epitopes. The 3D structure of constructs was assessed to find discontinuous B-cell epitopes. Among CTL predicted epitopes, S257-265, S603-611 and S360-368, and among HTL predicted epitopes, N167-181, S313-330 and S1110-1126 had better MHC binding rank. We found one putative CTL epitope, S360-368 related to receptor-binding domain (RBD) region for S protein. The predicted epitopes were non-allergen and showed a high quality of proteasomal cleavage and Tap transport efficiency and 100% conservancy within four different clades of SARS-CoV-2. For CTL and HTL epitopes, the highest population coverage of the world's population was calculated for S27-37 with 86.27% and for S196-231, S303-323, S313-330, S1009-1030 and N328-349 with 90.33%, respectively. We identified overall 10 discontinuous B-cell epitopes for three multiepitope constructs. All three constructs showed strong interactions with TLRs 2, 3 and 4 supporting the hypothesis of SARS-CoV-2 susceptibility to TLRs 2, 3 and 4 like other Coronaviridae families. These data demonstrated that the novel designed multiepitope constructs can contribute to develop SARS-CoV-2 peptide vaccine candidates. The in vivo studies are underway using several vaccination strategies.

Designing a multi-epitope peptide based vaccine against SARS-CoV-2.

COVID-19 pandemic has resulted in 16,114,449 cases with 646,641 deaths from the 217 countries, or territories as on July 27th 2020. Due to multifaceted issues and challenges in the implementation of the safety and preventive measures, inconsistent coordination between societies-governments and most importantly lack of specific vaccine to SARS-CoV-2, the spread of the virus that initially emerged at Wuhan is still uprising after taking a heavy toll on human life. In the present study, we mapped immunogenic epitopes present on the four structural proteins of SARS-CoV-2 and we designed a multi-epitope peptide based vaccine that, demonstrated a high immunogenic response with a vast application on world's human population. On codon optimization and in-silico cloning, we found that candidate vaccine showed high expression in E. coli and immune simulation resulted in inducing a high level of both B-cell and T-cell mediated immunity. The results predicted that exposure of vaccine by administrating three injections significantly subsidized the antigen growth in the system. The proposed candidate vaccine found promising by yielding desired results and hence, should be validated by practical experimentations for its functioning and efficacy to neutralize SARS-CoV-2.