Designing a Multi-epitope Vaccine against the SARS-CoV-2 Variant Based on an Immunoinformatics Approach.

BACKGROUND: SARS-CoV-2 is a life-threatening virus in the world. Scientific evidence indicates that this pathogen will emerge again in the future. Although the current vaccines have a pivotal role in the control of this pathogen, the emergence of new variants has a negative impact on their effectiveness. OBJECTIVE: Therefore, it is urgent to consider the protective and safe vaccine against all sub-coronavirus species and variants based on the conserved region of the virus. Multi-epitope peptide vaccine (MEV), comprised of immune-dominant epitopes, is designed by immunoinformatic tools and it is a promising strategy against infectious diseases. METHODS: Spike glycoprotein and nucleocapsid proteins from all coronavirus species and variants were aligned and the conserved region was selected. Antigenicity, toxicity, and allergenicity of epitopes were checked by a proper server. To robust the immunity of the multi-epitope vaccine, cholera toxin b (CTB) and three HTL epitopes of tetanus toxin fragment C (TTFrC) were linked at the N-terminal and C-terminal of the construct, respectively. Selected epitopes with MHC molecules and the designed vaccines with Toll-like receptors (TLR-2 and TLR-4) were docked and analyzed. The immunological and physicochemical properties of the designed vaccine were evaluated. The immune responses to the designed vaccine were simulated. Furthermore, molecular dynamic simulations were performed to study the stability and interaction of the MEV-TLRs complexes during simulation time by NAMD (Nanoscale molecular dynamic) software. Finally, the codon of the designed vaccine was optimized according to Saccharomyces boulardii. RESULTS: The conserved regions of spike glycoprotein and nucleocapsid protein were gathered. Then, safe and antigenic epitopes were selected. The population coverage of the designed vaccine was 74.83%. The instability index indicated that the designed multi-epitope was stable (38.61). The binding affinity of the designed vaccine to TLR2 and TLR4 was -11.4 and -11.1, respectively. The designed vaccine could induce humoral and cellular immunity. CONCLUSION: In silico analysis showed that the designed vaccine is a protective multi-epitope vaccine against SARS-CoV-2 variants.

Epitope-based vaccine design against the membrane and nucleocapsid proteins of SARS-CoV-2.

BACKGROUND: The high prevalence and mortality rate of coronavirus disease 2019 (COVID-19) is a major global concern. Bioinformatics approaches have helped to develop new strategies to combat infectious agents, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Indeed, the structural proteins of microorganisms provide suitable epitopes for the development of vaccines to prevent infectious diseases. OBJECTIVES: The present study aimed to use bioinformatics tools to find peptides from the membrane (M) and nucleocapsid (N) proteins with effective cellular and humoral immunogenicity. MATERIAL AND METHODS: Sequences of the M and N proteins were sourced from the National Center for Biotechnology Information (NCBI). The conserved regions of the proteins with the highest immunogenicity were identified and assessed using different servers, and the physicochemical and biochemical properties of the epitopes were evaluated. Finally, allergenicity, antigenicity and docking to human leukocyte antigen (HLA) were investigated. RESULTS: The data indicated that the best epitopes were LVIGFLFLT and LFLTWICLL (as membrane epitopes), and KLDDKDPNFKDQ (as a nucleocapsid epitope), with significant immunogenicity and no evidence of allergenicity. The 3 epitopes are stable peptides that can interact with HLA to induce strong immune responses. CONCLUSIONS: The findings indicate that 3 common epitopes could effectively elicit an immune response against the disease. Hence, in vitro and in vivo studies are recommended to confirm the theoretical information.

Designing multi-epitope mRNA construct as a universal influenza vaccine candidate for future epidemic/pandemic preparedness.

Despite the availability of prevention and treatment strategies and advancing immunization approaches, the influenza virus remains a global threat that continues to plague humanity with unpredictable pandemics. Due to the unusual genetic variability and segmented genome, the reassortment between different strains of influenza is facilitated and the viruses continuously evolve and adapt to the host cell's immunity. This underlies the seasonal vaccine mismatches that decrease the vaccine efficacy and increase the risk of outbreaks. Thus, the development of a universal vaccine covering all the influenza A and B strains would reduce the pervasiveness of the influenza virus. In the current study, a potentially universal influenza multi-epitope vaccine was designed based on the experimentally tested conserved T cell and B cell epitopes of hemagglutinin (HA), neuraminidase (NA), nucleoprotein (NP), and matrix-2 proton channel (M2) of the virus. The immune simulation and molecular docking of the vaccine construct with TLR2, TLR3, and TLR4 elicited the favorable immunogenicity of the vaccine and the formation of stable complexes, respectively. Ultimately, based on the immunoinformatics analysis, the universal mRNA multi-epitope vaccine designed in this study might have a protection potential against the various subtypes of influenza A and B.

An Immunoinformatics Approach to Design Novel and Potent Multi-Epitope-Based Vaccine to Target Lumpy Skin Disease

The lumpy skin disease (LSD) virus of the Poxviridae family is a serious threat that mostly affects cattle and causes significant economic loss. LSD has the potential to spread widely and its rapidly across borders. Despite the availability of information, there is still no competitive vaccine available for LSD. Therefore, the current study was conducted to develop an epitope-based LSD vaccine that is efficient, secure, and biocompatible and stimulates both innate and adaptive immune responses using immunoinformatics techniques. Initially, putative virion core proteins were manipulated;B-cell and T-cell epitopes have been predicted and connected with the help of adjuvants and linkers. Numerous bioinformatics methods, including antigenicity testing, transmembrane topology screening, allergenicity assessment, conservancy analysis, and toxicity evaluation, were employed to find superior epitopes. Based on promising vaccine candidates and immunogenic potential, the vaccine design was selected. Strong interactions between TLR4 and TLR9 and the anticipated vaccine design were revealed by molecular docking. Finally, based on the high docking score, computer simulations were performed in order to assess the stability, efficacy, and compactness of the constructed vaccine. The simulation outcomes showed that the polypeptide vaccine design was remarkably stable, with high expression, stability, immunogenic qualities, and considerable solubility. Additionally, computer-based research shows that the constructed vaccine provides adequate population coverage, making it a promising candidate for use in the design of vaccines against other viruses within the Poxviridae family and potentially other virus families as well. These outcomes suggest that the epitope-based vaccine developed in this study will be a significant candidate against LSD to control and prevent LSDV-related disorders if further investigated experimentally.

MERS virus spike protein HTL-epitopes selection and multi-epitope vaccine design using computational biology.

MERS-CoV, a zoonotic virus, poses a serious threat to public health globally. Thus, it is imperative to develop an effective vaccination strategy for protection against MERS-CoV. Immunoinformatics and computational biology tools provide a faster and more cost-effective strategy to design potential vaccine candidates. In this work, the spike proteins from different strains of MERS-CoV were selected to predict HTL-epitopes that show affinity for T-helper MHC-class II HTL allelic determinant (HLA-DRB1:0101). The antigenicity and conservation of these epitopes among the selected spike protein variants in different MERS-CoV strains were analyzed. The analysis identified five epitopes with high antigenicity: QSIFYRLNGVGITQQ, DTIKYYSIIPHSIRS, PEPITSLNTKYVAPQ, INGRLTTLNAFVAQQ and GDMYVYSAGHATGTT. Then, a multi-epitope vaccine candidate was designed using linkers and adjuvant molecules. Finally, the vaccine construct was subjected to molecular docking with TLR5 (Toll-like receptor-5). The proposed vaccine construct had strong binding energy of -32.3 kcal/mol when interacting with TLR5.Molecular dynamics simulation analysis showed that the complex of the vaccine construct and TLR5 is stable. Analysis using in silico immune simulation also showed that the prospective multi-epitope vaccine design had the potential to elicit a response within 70 days, with the immune system producing cytokines and immunoglobulins. Finally, codon adaptation and in silico cloning analysis showed that the candidate vaccine could be expressed in the Escherichia coli K12 strain. Here we also designed support vaccine construct MEV-2 by using B-cell and CD8+ CTL epitopes to generate the complete immunogenic effect. This study opens new avenues for the extension of research on MERS vaccine development.Communicated by Ramaswamy H. Sarma.

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.

Recombinant Protein Vaccines against Human Betacoronaviruses: Strategies, Approaches and Progress.

Betacoronaviruses have already troubled humanity more than once. In 2002-2003 and 2012, the SARS-CoV and MERS-CoV, respectively, caused outbreaks of respiratory syndromes with a fatal outcome. The spread of the SARS-CoV-2 coronavirus has become a pandemic. These three coronaviruses belong to the genus Betacoronavirus and have a zoonotic origin. The emergence of new coronavirus infections in the future cannot be ruled out, and vaccination is the main way to prevent the spread of the infection. Previous experience in the development of vaccines against SARS and MERS has helped to develop a number of vaccines against SARS-CoV-2 in a fairly short time. Among them, there are quite a few recombinant protein vaccines, which seem to be very promising in terms of safety, minimization of side effects, storage and transportation conditions. The problem of developing a universal betacoronavirus vaccine is also still relevant. Here, we summarize the information on the designing of vaccines based on recombinant proteins against highly pathogenic human betacoronaviruses SARS-CoV, MERS-CoV and SARS-CoV-2.

In-silico designing of a multi-epitope vaccine against SARS-CoV2 and studying the interaction of the vaccine with Alpha, Beta, Delta, and Omicron variants of concern.

BACKGROUND: The sudden appearance of the SARS-CoV2 virus has almost changed the future of vaccine development. There have been many different approaches to vaccination; among them, computational vaccinology in the form of multi-epitope vaccines with excellent immunological properties and minimal contamination or other adverse reactions has emerged as a promising strategy with a lot of room for further study in this area. OBJECTIVE: Designing a multi-epitope vaccine from the spike protein of SARS-CoV2 based on immunoinformatics and in-silico techniques. Evaluating the binding affinity of the constructed vaccine against the major variants of concern (alpha, beta, delta, and omicron) using docking studies. METHOD: The potential antigenic, immunogenic, and non-allergic T-cell epitopes were thoroughly explored using IEDB, NetCTL1.2, and NetMHCII pan 3.2 servers. The best suitable linker was identified using the ExPASy Protparam tool and VERIFY 3D. The 3D model of the vaccine was developed by RaptorX and the model was validated using ERRAT, Z-score, and Ramachandran Plot. Docking studies of the vaccine with TLR-2, 3, 4, and 7 and alpha, beta, delta, and omicron variants were performed using HADDOCK 2.4. RESULTS: The vaccine construct showed good antigenic, and immunogenic scores and was non-allergic as well. The model was capable of binding to all four selected Toll-like receptors. Docking scores with variants were also promising. CONCLUSION: All the variants showed good binding ability with the vaccine construct. Interaction with the alpha variant was found to be the most intense followed by delta, beta, and omicron.

Computational design of candidate multi-epitope vaccine against SARS-CoV-2 targeting structural (S and N) and non-structural (NSP3 and NSP12) proteins.

The COVID-19 pandemic caused by SARS-CoV-2 virus has created a global damage and has exposed the vulnerable side of scientific research towards novel diseases. The intensity of the pandemic is huge, with mortality rates of more than 6 million people worldwide in a span of 2 years. Considering the gravity of the situation, scientists all across the world are continuously attempting to create successful therapeutic solutions to combat the virus. Various vaccination strategies are being devised to ensure effective immunization against SARS-CoV-2 infection. SARS-CoV-2 spreads very rapidly, and the infection rate is remarkably high than other respiratory tract viruses. The viral entry and recognition of the host cell is facilitated by S protein of the virus. N protein along with NSP3 is majorly responsible for viral genome assembly and NSP12 performs polymerase activity for RNA synthesis. In this study, we have designed a multi-epitope, chimeric vaccine considering the two structural (S and N protein) and two non-structural proteins (NSP3 and NSP12) of SARS-CoV-2 virus. The aim is to induce immune response by generating antibodies against these proteins to target the viral entry and viral replication in the host cell. In this study, computational tools were used, and the reliability of the vaccine was verified using molecular docking, molecular dynamics simulation and immune simulation studies in silico. These studies demonstrate that the vaccine designed shows steady interaction with Toll like receptors with good stability and will be effective in inducing a strong and specific immune response in the body.Communicated by Ramaswamy H. Sarma.

Design of a multi-epitope-based vaccine consisted of immunodominant epitopes of structural proteins of SARS-CoV-2 using immunoinformatics approach.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown rapid global spread and has resulted in a significant death toll worldwide. In this study, we aimed to design a multi-epitope vaccine against SARS-CoV-2 based on structural proteins S, M, N, and E. We identified B- and T-cell epitopes and then the antigenicity, toxicity, allergenicity, and similarity of predicted epitopes were analyzed. T-cell epitopes were docked with corresponding HLA alleles. Consequently, the selected T- and B-cell epitopes were included in the final construct. All selected epitopes were connected with different linkers and flagellin and pan-HLA DR binding epitopes (PADRE) as an adjuvant were used in the vaccine construct. Furthermore, molecular docking was used to evaluate the complex between the final vaccine construct and two alleles, HLA-A*02:01 and HLA-DRB1*01:01. Finally, codons were optimized for in silico cloning into pET28a(+) vector using SnapGene. The final vaccine construct comprised 11 CTL, HTL, and B-cell epitopes corresponding to 394 amino acid residues. In silico evaluation showed that the designed vaccine might potentially promote an immune response. Further in vivo preclinical and clinical testing is required to determine the safety and efficacy of the designed vaccine.

Cross-variant proof predictive vaccine design based on SARS-CoV-2 spike protein using immunoinformatics approach.

Background: Coronavirus Disease (COVID-19) is caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The SARS-CoV-2 virus is evolving continuously. The omicron variant of SARS-CoV-2 has the highest mutation in its spike protein, thus making the presently available vaccine ineffective or reducing its efficiency. Furthermore, the majority of the vaccines are constructed using a spike protein sequence from wild-type SARS-CoV-2. This raises the possibility of the virus evolving to the point where the vaccine's effectiveness is completely lost, even after booster doses. The study aims to develop a predictive vaccine as well as the epitopes for the updating of the vaccine sequences of currently available vaccines. In this study, following the immunoinformatics approach, predictive vaccine construction was done with the help of epitopes present on spike proteins of wild-type, delta, and omicron variants that encompass the majority of variants and possible new variants that arise from the combination of circulating variants. Results: The vaccine that was constructed was stable and immunogenic. The vaccine was constructed with the help of 18 B-cell epitopes, 5 MHC class I epitopes, and 6 MHC class II epitopes. The epitope conservancy analysis suggests that the vaccine will work for the previously known variant of concern. The vaccine bound to TLR4, TLR2, B-cell receptor chains A and B, and ACE2 receptors with a z score of - 1.4, - 1.7, - 1.4, - 1.7, and - 1.4, respectively, with a cluster size of 121 highest for the ACE2 receptor and 46 lowest for B-cell receptor chain A. The C-ImmSim simulation results indicate that the vaccine is generating both humoral and cell-mediated responses at a sufficient level throughout the month upon injection of the vaccine as an antigen. Conclusion: The study's findings indicate that the vaccine was both stable and immunogenic, providing a sufficient level of immunity. Following experimental validation, the vaccine can be used, and the epitopes can be employed for therapeutic purposes such as antibody synthesis. Supplementary Information: The online version contains supplementary material available at 10.1186/s43088-023-00341-4.

Immunoinformatic-Based Multi-Epitope Vaccine Design for Co-Infection of Mycobacterium tuberculosis and SARS-CoV-2.

(1) Background: Many co-infections of Mycobacterium tuberculosis (MTB) and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have emerged since the occurrence of the SARS-CoV-2 pandemic. This study aims to design an effective preventive multi-epitope vaccine against the co-infection of MTB and SARS-CoV-2. (2) Methods: The three selected proteins (spike protein, diacylglycerol acyltransferase, and low molecular weight T-cell antigen TB8.4) were predicted using bioinformatics, and 16 epitopes with the highest ranks (10 helper T lymphocyte epitopes, 2 CD8+ T lymphocytes epitopes, and 4 B-cell epitopes) were selected and assembled into the candidate vaccine referred to as S7D5L4. The toxicity, sensitization, stability, solubility, antigenicity, and immunogenicity of the S7D5L4 vaccine were evaluated using bioinformatics tools. Subsequently, toll-like receptor 4 docking simulation and discontinuous B-cell epitope prediction were performed. Immune simulation and codon optimization were carried out using immunoinformatics and molecular biology tools. (3) Results: The S7D5L4 vaccine showed good physical properties, such as solubility, stability, non-sensitization, and non-toxicity. This vaccine had excellent antigenicity and immunogenicity and could successfully simulate immune responses in silico. Furthermore, the normal mode analysis of the S7D5L4 vaccine and toll-like receptor 4 docking simulation demonstrated that the vaccine had docking potential and a stable reaction. (4) Conclusions: The S7D5L4 vaccine designed to fight against the co-infection of MTB and SARS-CoV-2 may be safe and effective. The protective efficacy of this promising vaccine should be further verified using in vitro and in vivo experiments.

Implementation of immuno-chemoinformatics approaches to construct multi-epitope for vaccine development against Omicron and Delta SARS-CoV-2 variants

Background: The new coronavirus is still a life-threatening menace, because of its changing nature and capacity to produce many mutations to bypass the immune system. The vaccination is the first effective weapon against COVID-19. Aim: The study's goal was to design a multi-epitope peptide vaccine (MEPV) for a mix of Omicron and Delta Coronavirus strains using immuno-chemoinformatics tools. Methods: To create the vaccine epitopes, seven proteins from the Omicron and Delta coronavirus strains were selected (ORF1a, ORF3a, surface protein, membrane protein, ORF7a, ORF8, and nucleocapsid protein). Antigenicity, toxicity, and allergenicity of the epitopes were evaluated. Results: The designed vaccine is made up of 534 amino acids that are homogeneous, antigenic, and non-toxic. Sticky restriction enzymes (XhoI and XbaI) were used to incorporate the MEPV into the pmirGLO luciferase vector. SnapGene server was used to create primers for PCR testing. Developing the MEPV is a terrific cost-effective strategy. The created MEPV's physiochemical properties have been determined to be basic, hydrophobic, and stableImmunogenicity and immune response profiles of the developed vaccine candidate were better assessed using in silico immunological simulations. Conclusions: We advocate moving the built vaccine to the biological validation step, where it may test our findings using appropriate model organisms.

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 analysis of the conserved surface-exposed epitopes to design novel multiepitope peptide vaccine for all variants of the SARS-CoV-2.

Recently the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pervasive threat to generic health. The SARS-CoV-2 spike (S) glycoprotein plays a fundamental role in binds and fusion to the angiotensin-converting enzyme 2 (ACE2). The multi-epitope peptide vaccines would be able to elicit both long-lasting humoral and cellular immune responses, resulting the eliminating SARS-CoV-2 infections as asymptomatic patients are in large numbers. Recently, the omicron variant of the SARS-CoV-2 became a variant of concern that contained just 15-point mutations in the receptor-binding domain of the spike protein. In order to eliminate new evidence on coronavirus variants of concern detected through epidemic intelligence, the conserved epitopes of the receptor-binding domain (RBD) and spike cleavage site is the most probable target for vaccine development to inducing binds and fusion inhibitors neutralizing antibodies respectively. In this study, we utilized bioinformatics tools for identifying and analyzing the spike (S) glycoprotein sequence, e.g. the prediction of the potential linear B-cell epitopes, B-cell multi­epitope design, secondary and tertiary structures, physicochemical properties, solubility, antigenicity, allergenicity, the molecular docking and molecular dynamics simulation for the promising vaccine candidate against all variant of concern of SARS-CoV-2. Among the epitopes of the RBD region are surface-exposed epitopes SVYAWNRKRISNCV and ATRFASVYAWNRKR as the conserved sequences in all variants of concern can be a good candidate to induce an immune response. Communicated by Ramaswamy H. Sarma.

Multi Epitope-Based Vaccine Design for Protection Against Mycobacterium tuberculosis and SARS-CoV-2 Coinfection.

Background: A prophylactic and immunotherapeutic vaccine for Mycobacterium tuberculosis (MTB) and SARS-CoV-2 coinfection needs to be developed for a proactive and effective therapeutic approach. Therefore, this study aims to use immunoinformatics to design a multi-epitope vaccine for protection against MTB and SARS-CoV-2 coinfection. Methods: The bioinformatic techniques were used to screen and construct potential epitopes from outer membrane protein A Rv0899 of MTB and spike glycoprotein of SARS-CoV-2 for B and T cells. The antigenicity, allergenicity, and several physiochemical properties of the developed multi-epitope vaccination were then evaluated. Additionally, molecular docking and normal mode analysis (NMA) were utilized in evaluating the vaccine's immunogenicity and complex stability. Results: Selected proteins and predicted epitopes suggest that the vaccine prediction can be helpful in the protection against both SARS-CoV-2 and MTB coinfection. Through docking molecular and NMA, the vaccine-TLR4 protein interaction was predicted to be efficient with a high level of IgG, T-helper cells, T-cytotoxic cells, andIFN-γ. Conclusion: This epitope-based vaccine is a potentially attractive tool for SARS-CoV-2 and MTB coinfection vaccine development.

Development of a Multi-Epitope Vaccine for Mycoplasma hyopneumoniae and Evaluation of Its Immune Responses in Mice and Piglets.

Mycoplasma hyopneumoniae (Mhp), the primary pathogen causing Mycoplasma pneumonia of swine (MPS), brings massive economic losses worldwide. Genomic variability and post-translational protein modification can enhance the immune evasion of Mhp, which makes MPS prone to recurrent outbreaks on farms, even with vaccination or other treatments. The reverse vaccinology pipeline has been developed as an attractive potential method for vaccine development due to its high efficiency and applicability. In this study, a multi-epitope vaccine for Mhp was developed, and its immune responses were evaluated in mice and piglets. Genomic core proteins of Mhp were retrieved through pan-genome analysis, and four immunodominant antigens were screened by host homologous protein removal, membrane protein screening, and virulence factor identification. One immunodominant antigen, AAV27984.1 (membrane nuclease), was expressed by E. coli and named rMhp597. For epitope prioritization, 35 B-cell-derived epitopes were identified from the four immunodominant antigens, and 10 MHC-I and 6 MHC-II binding epitopes were further identified. The MHC-I/II binding epitopes were merged and combined to produce recombinant proteins MhpMEV and MhpMEVC6His, which were used for animal immunization and structural analysis, respectively. Immunization of mice and piglets demonstrated that MhpMEV could induce humoral and cellular immune responses. The mouse serum antibodies could detect all 11 synthetic epitopes, and the piglet antiserum suppressed the nuclease activity of rMhp597. Moreover, piglet serum antibodies could also detect cultured Mhp strain 168. In summary, this study provides immunoassay results for a multi-epitope vaccine derived from the reverse vaccinology pipeline, and offers an alternative vaccine for MPS.

A biepitope, adjuvant-free, self-assembled influenza nanovaccine provides cross-protection against H3N2 and H1N1 viruses in mice.

Currently, the incorporation of multiple epitopes into vaccines is more desirable than the incorporation of a single antigen for universal influenza vaccine development. However, epitopes induce poor immune responses. Although the use of adjuvants can overcome this obstacle, it may raise new problems. Effective antigen delivery vehicles that can function as both antigen carriers and intrinsic adjuvants are highly desired for vaccine development. Here, we report a biepitope nanovaccine that provides complete protection in mice against H3N2 virus as well as partial protection against H1N1 virus. This vaccine (3MCD-f) consists of two conserved epitopes (matrix protein 2 ectodomain (M2e) and CDhelix), and these epitopes were presented on the surface of ferritin in a sequential tandem format. Subcutaneous immunization with 3MCD-f in the absence of adjuvant induces robust humoral and cellular immune responses. These results provide a proof of concept for the 3MCD-f nanovaccine that might be an ideal candidate for future influenza pandemics.

Engineering of a Multi-Epitope Subunit Vaccine Against SASRS-CoV-2 Through the Viroinformatic Approach

The COVID-19 outbreak has infected millions of people worldwide, but no vaccine has been discovered to combat it efficiently. This research aims to design a multi-epitope vaccine using highly efficient B- and T-cell epitopes from the SARS-CoV-2 Surabaya isolate through a viroinformatic approach. First, the putative epitopes were linked together to develop tertiary structures and then docked with toll-like receptor 4 (TLR-4) that demonstrated a robust interaction with a low eigenvalue of 4.816138 e¡06. Furthermore, the structure's high immunogenic response was observed and successfully cloned into the expression vector pET28a (þ). This implies that the designed vaccine can prove effective in combating SARS-CoV-2. © 2022 University of Kerbala.

Implementation of immuno-chemoinformatics approaches to construct multi-epitope for vaccine development against Omicron and Delta SARS-CoV-2 variants.

Background: The new coronavirus is still a life-threatening menace, because of its changing nature and capacity to produce many mutations to bypass the immune system. The vaccination is the first effective weapon against COVID-19. Aim: The study's goal was to design a multi-epitope peptide vaccine (MEPV) for a mix of Omicron and Delta Coronavirus strains using immuno-chemoinformatics tools. Methods: To create the vaccine epitopes, seven proteins from the Omicron and Delta coronavirus strains were selected (ORF1a, ORF3a, surface protein, membrane protein, ORF7a, ORF8, and nucleocapsid protein). Antigenicity, toxicity, and allergenicity of the epitopes were evaluated. Results: The designed vaccine is made up of 534 amino acids that are homogeneous, antigenic, and non-toxic. Sticky restriction enzymes (XhoI and XbaI) were used to incorporate the MEPV into the pmirGLO luciferase vector. SnapGene server was used to create primers for PCR testing. Developing the MEPV is a terrific cost-effective strategy. The created MEPV's physiochemical properties have been determined to be basic, hydrophobic, and stableImmunogenicity and immune response profiles of the developed vaccine candidate were better assessed using in silico immunological simulations. Conclusions: We advocate moving the built vaccine to the biological validation step, where it may test our findings using appropriate model organisms.

Antecedentes: el nuevo coronavirus sigue siendo una amenaza mortal debido a su naturaleza cambiante y su capacidad de producir muchas mutaciones para eludir el sistema inmunitario. La vacunación es la primera arma eficaz contra el COVID-19. Objetivo: el objetivo del estudio era diseñar una vacuna peptídica multiepítopo (MEPV) para una mezcla de cepas de Omicron y Delta Coronavirus utilizando herramientas inmunoquimioinformáticas. Métodos: Para crear los epítopos de la vacuna, se seleccionaron siete proteínas de las cepas de coronavirus Omicron y Delta (ORF1a, ORF3a, proteína de superficie, proteína de membrana, ORF7a, ORF8 y proteína de nucleocápside). Se evaluaron la antigenicidad, toxicidad y alergenicidad de los epítopos. Resultados: La vacuna diseñada está compuesta por 534 aminoácidos que son homogéneos, antigénicos y no tóxicos. Se usaron enzimas de restricción pegajosas (XhoI y XbaI) para incorporar el MEPV en el vector de luciferasa pmirGLO. El servidor SnapGene se utilizó para crear cebadores para las pruebas de PCR. Desarrollar el MEPV es una excelente estrategia rentable. Se ha determinado que las propiedades fisicoquímicas del MEPV creado son básicas, hidrofóbicas y estables. Se utilizaron simulaciones inmunológicas in silico para evaluar mejor la inmunogenicidad y el perfil de respuesta inmunitaria de la vacuna candidata generada. Conclusiones: Abogamos por pasar la vacuna construida al paso de validación biológica, donde puede probar nuestros hallazgos utilizando organismos modelo apropiados.