Identification of vaccine candidate against Omicron variant of SARS-CoV-2 using immunoinformatic approaches

Whole proteome-integrated and vaccinomics-based next generation mRNA vaccine design against Pseudomonas aeruginosa-A hierarchical subtractive proteomics approach

Pseudomonas aeruginosa (P. aeruginosa) is a multidrug-resistant opportunistic pathogen responsible for chronic obstructive pulmonary disease (COPD), cystic fibrosis, and ventilator-associated pneumonia (VAP), leading to cancer. Developing an efficacious vaccine remains the most promising strategy for combating P. aeruginosa infections. In this study, we employed an advanced in silico strategy to design a highly efficient and stable mRNA vaccine using immunoinformatics tools. Whole proteome data were utilized to identify highly immunogenic vaccine candidates using subtractive proteomics. Three extracellular proteins were prioritized for T- and linear B-cell epitope prediction. Beta-definsin protein sequence was incorporated as an adjuvant at the N-terminus of the construct. A total of 3 CTL, 3 HTL, and 3 linear B cell highly immunogenic epitopes were combined using specific linkers to design this multi-peptide construct. The 5' and 3' UTR sequences, Kozak sequence with a stop codon, and signal peptides followed by a poly-A tail were incorporated into the above vaccine construct to create our final mRNA vaccine. The vaccines exhibited antigenicity scores >0.88, ensuring high antigenicity with no allergenic or toxic. Physiochemical properties analysis revealed high solubility and thermostability. Three-dimensional structural analysis determined high-quality structures. Vaccine-receptor docking and molecular dynamic simulations demonstrated strong molecular interactions, stable binding affinities, dynamic nature, and structural stability of this vaccine, with significant immunogenic responses of the immune system against the vaccine. The immunological simulation indicates successful cellular and humoral immune responses to defend against P. aeruginosa infection. Validation of the study outcomes necessitates both experimental and clinical testing.

Cross-variant immune shield: computational multiepitope vaccine design against B.617.2 to Omicron sub-lineages in SARS-CoV-2

The COVID-19 pandemic had a profound impact on global health. This study focuses on an in-depth analysis of the structural proteins (Spike (S), Nucleocapsid (N), Membrane (M), and Envelope (E) protein) of SARS-CoV-2 and its variants, aiming to develop a multiepitope vaccine construct that targets the virus independently of its variants. The analysis began by examining genetic variations in viral proteins relative to the reference strain Wuhan-Hu2, particularly in the S, M, N, and E proteins. T-cell epitope predictions for MHC Class-I and Class-II binding were conducted, shedding light on potential cytotoxic and helper T lymphocyte recognition. Identification of linear B-cell epitopes laid the groundwork for antibody-based humoral immune responses. The safety and efficacy of these epitopes were assessed for antigenicity, allergenicity, toxicity, immunogenicity, and conservancy. Population coverage analysis indicated promising global effectiveness of the designed vaccine construct. By incorporating 28 epitopes, we validated that was designed vaccine construct for stability through structural analysis. Molecular dynamics simulations and docking studies revealed its robust interaction with Toll-like receptor 4 (TLR4). Immune simulation studies suggested that the vaccine construct could induce a potent immune response by enhancing antibody titers, B-cell proliferation, memory cell development, and activation of T cells and natural killer cells upon administration. This comprehensive approach offers a promising multiepitope vaccine against SARS-CoV-2, with the potential for broad global coverage and strong immunogenicity. Further experimental validation holds the prospect of introducing a novel candidate vaccine to aid in the ongoing battle against the COVID-19 pandemic.

Repeated Omicron Infections Overcome T Cell Immune Imprinting to Original SARS-CoV-2

Multiple studies demonstrate the existence of attenuated neutralizing activity to the Omicron variants in the original SARS-CoV-2 strain vaccinated population undergoing breakthrough infection, which reflects a phenomenon of immune imprinting in humoral immunity. Herein, through designing spike protein peptide pools from four Omicron subvariants and the wild type (WT) counterpart, we intended to determine antiviral T cell immunoreactivity in Omicron-infected COVID-19 patients with or without previous vaccination. We have demonstrated that IFN-γ producing cells against the Omicron subvariants-derived peptide pools were significantly less than those against WT counterpart peptide pools in the Omicron BA.5/BA.7 infected patients receiving original inactivated SARS-CoV-2 vaccination whereas comparable in the unvaccinated group. Notably, reinfection with the Omicron subvariants restored viral-specific T cell immunity to the infected Omicron strains in vaccinated individuals. Therefore, similar to humoral immunity vaccination with the original SARS-CoV-2 strain-derived vaccines induces T cell immune imprinting when undergoing Omicron subvariants breakthrough infection. Since reinfection of Omicron subvariants can restore T cell immunoreactivity to the infected strains, it is necessary to design multivalent immunogens for vaccine development to overcome both B cell and T cell immune imprinting against SARS-CoV-2 and other highly mutant pathogens.

In silico analysis of the effect of HCV genotype-specific polymorphisms in Core, NS3, NS5A, and NS5B proteins on T-cell epitope processing and presentation

Background

HCV genotypes are 30-35% polymorphic at the nucleotide level, while subtypes within the same genotype differ by nearly 20%. Although previous studies have shown the immune escape potential of several mutations within the HCV proteins, little is known about the effect of genotype/subtype-specific gene polymorphism on T-cell immunity. Therefore, this study employed several in silico methods to examine the impact of genotype/subtype-specific polymorphisms in Core, NS3, NS5A, and NS5B sequences on T cell epitope processing and HLA-epitope interactions.

Methods

For this study, 8,942, 17,700, 14,645, and 3,277 HCV Core, NS3, NS5A, and NS5B sequences, respectively, from eight genotypes and 21 subtypes were retrieved from the Los Alamos HCV Database. Next, the NetCTL tool was employed to predict Cytotoxic T Lymphocyte (CTL) epitopes based on combined proteasomal cleavage, TAP efficacy, and HLA class I receptor binding scores. PEP-FOLD was used to model selected epitopes, followed by peptide-HLA docking using HPEPDOCK. Finally, molecular dynamics simulations were conducted for 200 ns using Desmond software to analyze differences in HLA-epitope (from different HCV genotypes) interaction kinetics and dynamics.

Results

A total of 3,410, 8,054, 6,532, and 14,015 CTL epitopes were observed in the HCV Core, NS3, NS5A, and NS5B sequences, respectively. Significant genotype/subtype-specific variations in CTL values and docking scores were observed among NS3, NS5A, and NS5B proteins. In silico results reveal that epitopes from genotype 6b (NS3), 6d/r (NS5B), 6o and 6 k (NS5A) exhibit higher immunogenicity than other genotypes, forming more energetically stable complexes with host receptors. These epitopes, compared to those from the same positions but different genotypes, showed binding energies of -144.24 kcal/mol, -85.30 kcal/mol, and - 43 kcal/mol, respectively. Over a 200 ns MD simulation, GT 6b and 6d/r epitopes displayed up to a 40% stronger binding energy with the HLA receptor. These findings suggest that patients infected with GT 6 may experience enhanced T cell responsiveness and broader immunogenicity.

Conclusion

Our study suggests that genotype/subtype-specific polymorphism in HCV may result in altered immune responses by modulating T-cell epitope processing and interaction with HLA receptors. Further experimental studies can be performed to confirm the effect of genotype/subtype-specific polymorphisms on T cell-mediated immune response.

mRNA vaccine design for Epstein-Barr virus: an immunoinformatic approach

Epstein-Barr Virus (EBV), structurally similar to other herpes viruses, possess significant global health challenges as it causes infectious mononucleosis and is also associated with various cancers. Due to this widespread impact, an effective messenger RNA (mRNA) vaccine is paramount to help curb its spread, further underscoring the need for its development. This study, following an immunoinformatic approach, aimed to design a comprehensive mRNA vaccine against the EBV by selecting antigenic proteins, predicting Linear B-cell epitopes, cytotoxic T-cell lymphocyte (CTL) and helper T-cell lymphocyte (HTL) epitopes, and assessing vaccine characteristics. Seventy-nine EBV isolates from diverse geographical regions were examined. Additionally, the vaccine construct's physicochemical properties, transmembrane domains, solubility, and secondary structures were analysed. Molecular docking was conducted with Toll-Like Receptor 5 (TLR-5). Population coverage was assessed for selected major histocompatibility complex (MHC) alleles, and immune response was simulated. The result of this study highlighted a vaccine construct with high antigenicity, non-toxicity, and non-allergenicity and possessed favourable physicochemical properties. The vaccine's 3D structure is native-like and strongly binds with TLR-5, indicating a solid affinity with TLR-5. The selected MHC alleles provided broad universal population coverage of 89.1%, and the immune simulations suggested a robust and wide-ranging immunogenic response, activating critical immune cells, antibodies, and cytokines. These findings provide a solid foundation for further development and testing of the EBV candidate vaccine, offering potential solutions for combating EBV infections.

Design of multi-epitope chimeric vaccine against Monkeypox virus and SARS-CoV-2: A vaccinomics perspective

The current era we experience is full with pandemic infectious agents that no longer threatens the major local source but the whole globe. Almost the most emerging infectious agents are severe acute respiratory syndrome coronavirus-2 (SARS CoV-2), followed by monkeypox virus (MPXV). Since no approved antiviral drugs nor licensed active vaccines are yet available, we aimed to utilize immunoinformatics approach to design chimeric vaccine against the two mentioned viruses. This is the first study to deal with design divalent vaccine against SARS-CoV-2 and MPXV. ORF8, E and M proteins from Omicron SARS-CoV-2 and gp182 from MPXV were used as the protein precursor from which multi-epitopes (inducing B-cell, helper T cells, cytotoxic T cells and interferon-ɣ) chimeric vaccine was contrived. The structure of the vaccine construct was predicted, validated, and docked to toll-like receptor-2 (TLR-2). Moreover, its sequence was also used to examine the immune simulation profile and was then inserted into the pET-28a plasmid for in silico cloning. The vaccine construct was probable antigen (0.543) and safe (non-allergen) with strong binding energy to TLR-2 (-1169.8 kcal/mol) and found to have significant immune simulation profile. In conclusion, the designed chimeric vaccine was potent and safe against SARS-CoV-2 and MPXV, which deserves further consideration.

Immunoinformatics-driven approach for development of potential multi-epitope vaccine against the secreted protein FlaC of Campylobacter jejuni

Campylobacter jejuni causes a leading human gastrointestinal infection which is associated with foodborne diarrhea, stomach cramping, and fever. In the recent years, numerous multidrug-resistant strains of C. jejuni has evolved and is considered in the priority pathogens category. Therefore, an increasing demand exists to develop an effective vaccine against Campylobacteriosis. The T cell and B cell epitopes from the FlaC protein were predicted using comprehensive immunoinformatics tools. The predicted epitopes were chosen based on their antigenicity, allergenicity, and toxicity profiles. Using the bioinformatics approach various physicochemical properties of the constructed vaccine were determined. The molecular docking analysis of the vaccine with the TLRs demonstrated that TLR5 has a higher binding affinity of -1159.0 kcal/mol. Molecular dynamics simulation has confirmed the stable association of the vaccine with TLR5. The immune response of the constructed vaccine was validated using immunostimulation. Based on this study, we recommend the formulation of a multi-epitope vaccine as a promising agent to effectively combat the dreadful campylobacteriosis infection.

Harnessing immunoinformatics for developing a multiple-epitope peptide-based vaccination approach against SARS-CoV-2 spike protein

COVID-19 has spread to over 200 countries with variable severity and mortality rates. Computational analysis is a valuable tool for developing B-cell and T-cell epitope-based vaccines. In this study, by harnessing immunoinformatics tools, we designed a multiple-epitope vaccine to protect against COVID-19. The candidate epitopes were designed from highly conserved regions of the SARS-CoV-2 spike (S) glycoprotein. The consensus amino acids sequence of ten SARS-CoV-2 variants including Gamma, Beta, Epsilon, Delta, Alpha, Kappa, Iota, Lambda, Mu, and Omicron was involved. Applying the multiple sequence alignment plugin and the antigenic prediction tools of Geneious prime 2021, ten predicted variants were identified and consensus S-protein sequences were used to predict the antigenic part. According to ElliPro analysis of S-protein B-cell prediction, we explored 22 continuous linear epitopes with high scores ranging from 0.879 to 0.522. First, we reported five promising epitopes: BE1 _1115-1192, BE2 _481-563, BE3 _287-313, BE4 _62-75, and BE5 _112-131 with antigenicity scores of 0.879, 0.86, 0.813, 0.779, and 0.765, respectively, while only nine discontinuous epitopes scored between 0.971 and 0.511. Next, we identified 194 Major Histocompatibility Complex (MHC) - I and 156 MHC - II epitopes with antigenic characteristics. These spike-specific peptide-epitopes with characteristically high immunogenic and antigenic scores have the potential as a SARS-CoV-2 multiple-epitope peptide-based vaccination strategy. Nevertheless, further experimental investigations are needed to test for the vaccine efficacy and efficiency.

A novel mutation-proof, next-generation vaccine to fight against upcoming SARS-CoV-2 variants and subvariants, designed through AI enabled approaches and tools, along with the machine learning based immune simulation: A vaccine breakthrough

Emerging SARS-CoV-2 variants and subvariants are great concerns for their significant mutations, which are also responsible for vaccine escape. Therefore, the study was undertaken to develop a mutation-proof, next-generation vaccine to protect against all upcoming SARS-CoV-2 variants. We used advanced computational and bioinformatics approaches to develop a multi-epitopic vaccine, especially the AI model for mutation selection and machine learning (ML) strategies for immune simulation. AI-enabled and the top-ranked antigenic selection approaches were used to select nine mutations from 835 RBD mutations. We selected twelve common antigenic B cell and T cell epitopes (CTL and HTL) containing the nine RBD mutations and joined them with the adjuvants, PADRE sequence, and suitable linkers. The constructs' binding affinity was confirmed through docking with TLR4/MD2 complex and showed significant binding free energy (-96.67 kcal mol^-1) with positive binding affinity. Similarly, the calculated eigenvalue (2.428517e-05) from the NMA of the complex reveals proper molecular motion and superior residues' flexibility. Immune simulation shows that the candidate can induce a robust immune response. The designed mutation-proof, multi-epitopic vaccine could be a remarkable candidate for upcoming SARS-CoV-2 variants and subvariants. The study method might guide researchers in developing AI-ML and immunoinformatics-based vaccines for infectious disease.

In silico design of a novel peptide-based vaccine against the ubiquitous apicomplexan Toxoplasma gondii using surface antigens

Human toxoplasmosis is a global public health concern and a commercial vaccine is still lacking. The present in silico study was done to design a novel vaccine candidate using tachyzoite-specific SAG1-realted sequence (SRS) proteins. Overlapping B-cell and strictly-chosen human MHC-I binding epitopes were predicted and connected together using appropriate spacers. Moreover, a TLR4 agonist, human high mobility group box protein 1 (HMGB1), and His-tag were added to the N- and C-terminus of the vaccine sequence. The final vaccine had 442 residues and a molecular weight of 47.71 kDa. Physico-chemical evaluation showed a soluble, highly antigenic and non-allergen protein, with coils and helices as secondary structures. The vaccine 3D model was predicted by ITASSER server, subsequently refined and was shown to possess significant interactions with human TLR4. As well, potent stimulation of cellular and humoral immunity was demonstrated upon chimeric vaccine injection. Finally, the outputs showed that this vaccine model possesses top antigenicity, which could provoke significant cell-mediated immune profile including IFN-γ, and can be utilized towards prophylactic purposes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00140-w.

In silico design of a multi-epitope vaccine against the spike and the nucleocapsid proteins of the Omicron variant of SARS-CoV-2

Computational studies can comprise an effective approach to treating and preventing viral infections. Since 2019, the world has been dealing with the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The most important achievement in this short period of time in the effort to reduce morbidity and mortality was the production of vaccines and effective antiviral drugs. Although the virus has been significantly suppressed, it continues to evolve, spread, and evade the host's immune system. Recently, researchers have turned to immunoinformatics tools to reduce side effects and save the time and cost of traditional vaccine production methods. In the present study, an attempt has been made to design a multi-epitope vaccine with humoral and cellular immune response stimulation against the Omicron variant of SARS-CoV-2 by investigating new mutations in spike (S) and nucleocapsid (N) proteins. The population coverage of the vaccine was evaluated as appropriate compared to other studies. The results of molecular dynamics simulation and molecular mechanics/generalized Born surface area (MM/GBSA) calculations predict the stability and proper interaction of the vaccine with Toll-like receptor 4 (TLR-4) as an innate immune receptor. The results of the immune simulation show a significant increase in the coordinated response of IgM and IgG after the third injection of the vaccine. Also, in the continuation of the research, spike proteins from BA.4 and BA.5 lineages were screened by immunoinformatics filters and effective epitopes were suggested for vaccine design. Despite the high precision of computational studies, in-vivo and in-vitro research is needed for final confirmation.Communicated by Ramaswamy H. Sarma.

Designing multi-epitope based peptide vaccine targeting spike protein SARS-CoV-2 B1.1.529 (Omicron) variant using computational approaches

Millions of lives have been infected since the SARS-CoV-2 outbreak in 2019. The high human-to-human transmission rate has warranted a need for a vaccine to protect people. Although some vaccines are in use, due to the high mutation rate in the SARS-CoV-2 multiple variants, the current vaccines may not be sufficient to immunize people against new variant threats. One of the emerging concern variants is B1.1.529 (Omicron), which carries ~ 30 mutations in the Spike protein (S) of SARS-CoV-2 and is predicted to evade antibody recognition even from vaccinated people. We used a structure-based approach and an epitope prediction server to develop a Multi-Epitope based Subunit Vaccine (MESV) involving SARS-CoV-2 B1.1.529 variant spike glycoprotein. The predicted epitope with better antigenicity and non-toxicity was used for designing and predicting vaccine construct features and structure models. In addition, the MESV construct In silico cloning in the pET28a expression vector predicted the construct to be highly translational. The proposed MESV vaccine construct was also subjected to immune simulation prediction and was found to be highly antigenic and elicit a cell-mediated immune response. Therefore, the proposed MESV in the present study has the potential to be evaluated further for vaccine production against the newly identified B1.1.529 (Omicron) variant of concern.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11224-022-02027-6.