Peptides for immunological purposes: design, strategies and applications

Development of membrane protein-based vaccine against lumpy skin disease virus (LSDV) using immunoinformatic tools

INTRODUCTION

Lumpy skin disease, an economically significant bovine illness, is now found in previously unheard-of geographic regions. Vaccination is one of the most important ways to stop its further spread.

AIM

Therefore, in this study, we applied advanced immunoinformatics approaches to design and develop an effective lumpy skin disease virus (LSDV) vaccine.

METHODS

The membrane glycoprotein was selected for prediction of the different B- and T-cell epitopes by using the immune epitope database. The selected B- and T-cell epitopes were combined with the appropriate linkers and adjuvant resulted in a vaccine chimera construct. Bioinformatics tools were used to predict, refine and validate the 2D, 3D structures and for molecular docking with toll-like receptor 4 using different servers. The constructed vaccine candidate was further processed on the basis of antigenicity, allergenicity, solubility, different physiochemical properties and molecular docking scores.

RESULTS

The in silico immune simulation induced significant response for immune cells. In silico cloning and codon optimization were performed to express the vaccine candidate in Escherichia coli. This study highlights a good signal for the design of a peptide-based LSDV vaccine.

CONCLUSION

Thus, the present findings may indicate that the engineered multi-epitope vaccine is structurally stable and can induce a strong immune response, which should help in developing an effective vaccine towards controlling LSDV infection.

Development of a novel multi‑epitope vaccine against the pathogenic human polyomavirus V6/7 using reverse vaccinology

BACKGROUND

Human polyomaviruses contribute to human oncogenesis through persistent infections, but currently there is no effective preventive measure against the malignancies caused by this virus. Therefore, the development of a safe and effective vaccine against HPyV is of high priority.

METHODS

First, the proteomes of 2 polyomavirus species (HPyV6 and HPyV7) were downloaded from the NCBI database for the selection of the target proteins. The epitope identification process focused on selecting proteins that were crucial, associated with virulence, present on the surface, antigenic, non-toxic, and non-homologous with the human proteome. Then, the immunoinformatic methods were used to identify cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes from the target antigens, which could be used to create epitope-based vaccine. The physicochemical features of the designed vaccine were predicted through various online servers. The binding pattern and stability between the vaccine candidate and Toll-like receptors were analyzed through molecular docking and molecular dynamics (MD) simulation, while the immunogenicity of the designed vaccines was assessed using immune simulation.

RESULTS

Online tools were utilized to forecast the most optimal epitope from the immunogenic targets, including LTAg, VP1, and VP1 antigens of HPyV6 and HPyV7. A multi-epitope vaccine was developed by combining 10 CTL, 7 HTL, and 6 LBL epitopes with suitable linkers and adjuvant. The vaccine displayed 98.35% of the world's population coverage. The 3D model of the vaccine structure revealed that the majority of residues (87.7%) were located in favored regions of the Ramachandran plot. The evaluation of molecular docking and MD simulation revealed that the constructed vaccine exhibits a strong binding (-1414.0 kcal/mol) towards the host's TLR4. Moreover, the vaccine-TLR complexes remained stable throughout the dynamic conditions present in the natural environment. The immune simulation results demonstrated that the vaccine design had the capacity to elicit robust immune responses in the host.

CONCLUSION

The multi-parametric analysis revealed that the designed vaccine is capable of inducing sustained immunity against the selected polyomaviruses, although further in-vivo investigations are needed to verify its effectiveness.

Integrating core subtractive proteomics and reverse vaccinology for multi-epitope vaccine design against Rickettsia prowazekii endemic typhus

Rickettsia prowazekii is an intracellular, obligate, gram-negative coccobacillus responsible for epidemic typhus. Usually, the infected body louse or its excrement when rubbed into the skin abrasions transmits the disease. The infection with R. prowazekii causes the highest death rate (> 20% without antibiotic treatment and now 1-7%), followed by epidemic typhus, which often manifests in unsanitary conditions (up to 15-30%). Conventionally, vaccine design has required pathogen growth and both assays (in vivo and in vitro), which are costly and time-consuming. However, advancements in bioinformatics and computational biology have accelerated the development of effective vaccine designs, reducing the need for traditional, time-consuming laboratory experiments. Subtractive genomics and reverse vaccinology have become prominent computational methods for vaccine model construction. Therefore, the RefSeq sequence of Rickettsia prowazekii (strain Madrid E) (Proteome ID: UP000002480) was subjected to subtractive genomic analysis, including factors such as non-similarity to host proteome, essentiality, subcellular localization, antigenicity, non-allergenicity, and stability. Based on these parameters, the vaccine design process selected specific proteins such as outer membrane protein R (O05971_RICPR PETR; OmpR). Eventually, the OmpR was subjected to a reverse vaccinology approach that included molecular docking, immunological simulation, and the discovery of B-cell epitopes and MHC-I and MHC-II epitopes. Consequently, a chimeric or multi-epitope-based vaccine was proposed by selecting the V11 vaccine and its 3D structure modeling along with molecular docking against TLR and HLA protein, in silico simulation, and vector designing. The obtained results from this investigation resulted in a new perception of inhibitory ways against Rickettsia prowazekii by instigating novel immunogenic targets. To further assess the efficacy and protective ability of the newly designed V11 vaccine against Rickettsia prowazekii infections, additional evaluation such as in vitro or in vivo immunoassays is recommended.

Immunoinformatics-aided rational design of multiepitope-based peptide vaccine (MEBV) targeting human parainfluenza virus 3 (HPIV-3) stable proteins

BACKGROUND

Human parainfluenza viruses (HPIVs) are common RNA viruses responsible for respiratory tract infections. Human parainfluenza virus 3 (HPIV-3) is particularly pathogenic, causing severe illnesses with no effective vaccine or therapy available.

RESULTS

The current study employed a systematic immunoinformatic/reverse vaccinology approach to design a multiple epitope-based peptide vaccine against HPIV-3 by analyzing the virus proteome. On the basis of a number of therapeutic features, all three stable and antigenic proteins with greater immunological relevance, namely matrix protein, hemagglutinin neuraminidase, and RNA-directed RNA polymerase L, were chosen for predicting and screening suitable T-cell and B-cell epitopes. All of our desired epitopes exhibited no homology with human proteins, greater population coverage (99.26%), and high conservancy among reported HPIV-3 isolates worldwide. All of the T- and B-cell epitopes are then joined by putative ligands, yielding a 478-amino acid-long final construct. Upon computational refinement, validation, and thorough screening, several programs rated our peptide vaccine as biophysically stable, antigenic, allergenic, and non-toxic in humans. The vaccine protein demonstrated sufficiently stable interaction as well as binding affinity with innate immune receptors TLR3, TLR4, and TLR8. Furthermore, codon optimization and virtual cloning of the vaccine sequence in a pET32a ( +) vector showed that it can be readily expressed in the bacterial system.

CONCLUSION

The in silico designed HPIV-3 vaccine demonstrated potential in evoking an effective immune response. This study paves the way for further preclinical and clinical evaluation of the vaccine, offering hope for a future solution to combat HPIV-3 infections.

Vaccinomics-aided next-generation novel multi-epitope-based vaccine engineering against multidrug resistant Shigella Sonnei: Immunoinformatics and chemoinformatics approaches

Shigella sonnei is a gram-negative bacterium and is the primary cause of shigellosis in advanced countries. An exceptional rise in the prevalence of the disease has been reported in Asia, the Middle East, and Latin America. To date, no preventive vaccine is available against S. sonnei infections. This pathogen has shown resistances towards both first- and second-line antibiotics. Therefore, an effective broad spectrum vaccine development against shigellosis is indispensable. In the present study, vaccinomics-aided immunoinformatics strategies were pursued to identify potential vaccine candidates from the S. sonnei whole proteome data. Pathogen essential proteins that are non-homologous to human and human gut microbiome proteome set, are feasible candidates for this purpose. Three antigenic outer membrane proteins were prioritized to predict lead epitopes based on reverse vaccinology approach. Multi-epitope-based chimeric vaccines was designed using lead B- and T-cell epitopes combined with suitable linker and adjuvant peptide sequences to enhance immune responses against the designed vaccine. The SS-MEVC construct was prioritized based on multiple physicochemical, immunological properties, and immune-receptors docking scores. Immune simulation analysis predicted strong immunogenic response capability of the designed vaccine construct. The Molecular dynamic simulations analysis ensured stable molecular interactions of lead vaccine construct with the host receptors. In silico restriction and cloning analysis predicted feasible cloning capability of the SS-MEVC construct within the E. coli expression system. The proposed vaccine construct is predicted to be more safe, effective and capable of inducing robust immune responses against S. sonnei infections and may be worthy of examination via in vitro/in vivo assays.

Prediction, Synthesis and Evaluation of a Synthetic Peptide as an Enzyme-Linked Immunosorbent Assay (ELISA) Candidate for Screening of Bovine Antibodies against Theileria annulata

Tick-borne diseases (TBDs) of livestock are endemic across various parts of tropical countries. Theileriosis is one such economically important TBD, caused by the Theileriidae family of organisms, which is transmitted by ticks. Theileria annulata, the causative agent of tropical theileriosis, contributes a significant loss to the dairy sector by causing anorexia, high fever, anemia, inflammatory changes in vital organs and icterus, thus, a loss in milk yield. Though vaccines are available, their protective efficacy is not absolute, and treatment is limited to early diagnosis of the causative agent. Routinely, microscopic identification of piroplasms in the erythrocytes (Giemsa-stained) of infected animals or schizonts in lymph node biopsies are practiced for diagnosis. PCR-based techniques (multiplex, uniplex, nested and real-time) have been reported to perform well in diagnosing active infection. Several attempts have been made using serological assays like Dot blot, ELISA and ICT, but the results were of variable sensitivity and specificity. Recombinant proteins like the Theileria annulata merozoite surface antigen (Tams1) and Theileria annulata surface protein (TaSP) have been explored as antigenic candidates for these assays. In the present study, we predicted an immunogenic peptide, i.e., TaSP-34, from the TaSP using various computational tools. The predicted peptide was custom synthesized. The diagnostic potential of the peptide was assessed by indirect plate ELISA to detect the bovine-IgM against Theileria annulata. Alongside, a recombinant truncated TaSP (rTaSP(tr)) was expressed and purified, which was used to compare the performance of the peptide as a diagnostic candidate. The IgM-based peptide ELISA was 100% sensitive and 92.77% specific as compared to PCR (Tams1 targeting), while 98.04% sensitivity and 97.44% specificity were observed in comparison with rTaSP(tr) ELISA. Almost perfect agreement between peptide ELISA and Tams1 PCR was observed with a Cohen's kappa coefficient (κ-value) of 0.901 and agreement of 95.31%. Further, the κ-value between the peptide ELISA and rTaSP(tr) ELISA was found to be 0.95, and the agreement was 97.65%, which shows a good correlation between the two tests. The findings suggest that the TaSP-34 peptide can be an efficient and new-generation diagnostic candidate for the diagnosis of T. annulata. Furthermore, the peptide can be synthesized commercially at a larger scale and can be a cost-effective alternative for the protein-based diagnostic candidates for T. annulata.

Identification and In Silico Characterization of a Conserved Peptide on Influenza Hemagglutinin Protein: A New Potential Antigen for Universal Influenza Vaccine Development

Antigenic changes in surface proteins of the influenza virus may cause the emergence of new variants that necessitate the reformulation of influenza vaccines every year. Universal influenza vaccine that relies on conserved regions can potentially be effective against all strains regardless of any antigenic changes and as a result, it can bring enormous public health impact and economic benefit worldwide. Here, a conserved peptide (HA288-107) on the stalk domain of hemagglutinin glycoprotein is identified among highly pathogenic influenza viruses. Five top-ranked B-cell and twelve T-cell epitopes were recognized by epitope mapping approaches and the corresponding Human Leukocyte Antigen alleles to T-cell epitopes showed high population coverage (>99%) worldwide. Moreover, molecular docking analysis indicated that VLMENERTL and WTYNAELLV epitopes have high binding affinity to the antigen-binding groove of the HLA-A*02:01 and HLA-A*68:02 molecules, respectively. Theoretical physicochemical properties of the peptide were assessed to ensure its thermostability and hydrophilicity. The results suggest that the HA288-107 peptide can be a promising antigen for universal influenza vaccine design. However, in vitro and in vivo analyses are needed to support and evaluate the effectiveness of the peptide as an immunogen for vaccine development.

A comprehensive immunoinformatic analysis of chitin deacetylase's and MP88 for designing multi-epitope vaccines against Cryptococcus neoformans

Cryptococcus neoformans causes life-threatening pneumonia and meningitis and is regarded as one of the leading killers of immunocompromised individuals. There is currently no vaccine against this pathogen. Recently, WHO placed it at the top among the critical priority groups in the fungal priority pathogens to accelerate the development of effective treatments. Numerous studies suggested the potential of subunit vaccines to overcome the challenges associated with live and inactivated whole-cell vaccines. Therefore, this study exploited integrated reverse vaccinology and immunoinformatic approach to construct and characterize multi-epitope vaccines targeting chitin deacetylases (Cda1, Cda2, Cda3) and MP88 of C. neoformans. 4 CTL, 8 HTL and 6 B cell epitopes were fused with different adjuvants and appropriate linkers to design two multi-epitope vaccines (VC1 and VC2). Both chimeric constructs were predicted to be highly antigenic, non-allergenic, non-toxic, soluble and had satisfactory physicochemical properties. Molecular docking and binding free energy calculation revealed strong binding interactions between vaccine constructs and human TLRs (TLR-2 and TLR-4). Classical MD Simulation and Normal mode analysis verified the stability of the vaccine-TLR complex in the biological environment. Codon adaptation, cloning and in silico expression suggested the efficient expression of recombinant vaccine proteins in E. coli. Both candidates also generated robust immune profiles comprising innate, adaptive and humoral immune responses. Taken together, experimental validations of our findings through extensive in vitro and in vivo testing might provide an effective vaccine for prophylactic control of C. neoformans.Communicated by Ramaswamy H. Sarma.

A multi-epitope based vaccine against the surface proteins expressed in cyst and trophozoite stages of parasite Entamoeba histolytica

Entamoeba histolytica, an anaerobic parasite, infects humans and other primates and causes fatal diseases, such as amebiasis, amebic liver abscesses, and many others. Thousands of people are infected and dying due to the need for a proper protective cure, especially in poor sanitizing regions, such as Latin America, Asia, and Africa. Around 10% of the world population is infected by E. histolytica every year. Consequently, novel preventive approaches are required to eliminate the threats of the parasite. A designed vaccine targeting the exposed proteins that are common between cyst and trophozoite stages of the parasite's life cycle would be an effective way to repress the impact of the parasite. Therefore, an in silico bioinformatics approach was performed to design an effective vaccine targeting surface proteins common between both stages of the parasite's life cycle using B-cell and T-cell epitopes. The epitopes derived from the conserved portions of the proteins and their corresponding isomers specific to the parasite suggested that the vaccine could benefit cross-protection. Furthermore, the three-dimensional structure of the designed vaccine was modelled, refined, and validated using multiple bioinformatics tools. The physiological properties and solubility were also predicted using different algorithmic tools and found to be highly soluble in nature. The vaccine was found interactcted with TLR immune receptors, and the stability was observed via dynamics simulation. Codon optimization and cloning were performed for expression analysis. Immune simulation prediction anticipated significant immune responses with a high IgG and IgM antibodies expression, Th and Tc cells population, B-cell population, memory cells, INF-γ, and IL-2 cytokines. Therefore, the constructed multi-epitope putative vaccine can effectively neutralize the parasite's harmful effects.

Multi-Epitope Vaccine Design against Monkeypox Virus via Reverse Vaccinology Method Exploiting Immunoinformatic and Bioinformatic Approaches

(1) Background: The monkeypox virus is a zoonotic orthopox DNA virus that is closely linked to the virus. In light of the growing concern about this virus, the current research set out to use bioinformatics and immunoinformatics to develop a potential vaccine against the virus. (2) Methods: A multiepitope vaccine was constructed from the B-cell and T-cell epitopes of the MPXVgp181 strain using adjuvant and different linkers. The constructed vaccine was predicted for antigenicity, allergenicity, toxicity, and population coverage. In silico immune simulation studies were also carried out. Expression analysis and cloning of the constructed vaccine was carried out in the pET-28a(+) vector using snapgene. (3) Results: The constructed vaccine was predicted to be antigenic, non-allergenic, and non-toxic. It was predicted to have excellent global population coverage and produced satisfactory immune response. The in silico expression and cloning studies were successful in E. coli, which makes the vaccine construct suitable for mass production in the pharmaceutical industry. (4) Conclusion: The constructed vaccine is based on the B-cell and T-cell epitopes obtained from the MPXVgp181 strain. This research can be useful in developing a vaccine to combat the monkeypox virus globally after performing in-depth in vitro and in vivo studies.

Immuno-informatics profiling of monkeypox virus cell surface binding protein for designing a next generation multi-valent peptide-based vaccine

Monkeypox is a viral etiological agent with hallmarks analogous to those observed in smallpox cases in the past. The ongoing outbreak of Monkeypox viral infection is becoming a global health problem. Multi-valent peptide based next generation vaccines provides us a promising solution to combat these emerging infectious diseases by eliciting cell-mediated and humoral immune response. Considering the success rate of subtractive proteomics pipeline and reverse vaccinology approach, in this study, we have developed a novel, next-generation, multi-valent, in silico peptide based vaccine construct by employing cell surface binding protein. After analyzing physiochemical and biological properties of the selected target, the protein was subjected to B cell derived T cell epitope mapping. Iterative scrutinization lead to the identification of two highly antigenic, virulent, non-allergic, non-toxic, water soluble, and Interferon-gamma inducer epitopes i.e. HYITENYRN and TTSPVRENY. We estimated that the shortlisted epitopes for vaccine construction, roughly correspond to 99.74% of the world’s population. UK, Finland and Sweden had the highest overall population coverage at 100% which is followed by Austria (99.99%), Germany (99.99%), France (99.98%), Poland (99.96), Croatia (99.93), Czech Republic (99.87%), Belgium (99.87), Italy (99.86%), China (97.83%), India (97.35%) and Pakistan (97.13%). The designed vaccine construct comprises of 150 amino acids with a molecular weight of 16.97242 kDa. Molecular docking studies of the modelled MEMPV (Multi-epitope Monkeypox Vaccine) with MHC I (PDB ID: 1I1Y), MHC II (PDB ID: 1KG0), and other immune mediators i.e. toll like receptors TLR3 (PDB ID: 2A0Z), and TLR4 (PDB ID: 4G8A) revealed strong binding affinity with immune receptors. Host immune simulation results predicted that the designed vaccine has strong potency to induce immune responses against target pathogen in the form of cellular and antibody-dependent immunity. Our findings suggest that the hypothesized vaccine candidate can be utilized as a potential therapeutic against Monkeypox however experimental study is required to validate the results and safe immunogenicity.

Vaccinomics to Design a Multiepitope Vaccine against Legionella pneumophila

Legionella pneumophila is found in the natural aquatic environment and can resist a wide range of environmental conditions. There are around fifty species of Legionella, at least twenty-four of which are directly linked to infections in humans. L. pneumophila is the cause of Legionnaires' disease, a potentially lethal form of pneumonia. By blocking phagosome-lysosome fusion, L. pneumophila lives and proliferates inside macrophages. For this disease, there is presently no authorized multiepitope vaccine available. For the multi-epitope-based vaccine (MEBV), the best antigenic candidates were identified using immunoinformatics and subtractive proteomic techniques. Several immunoinformatics methods were utilized to predict B and T cell epitopes from vaccine candidate proteins. To construct an in silico vaccine, epitopes (07 CTL, 03 HTL, and 07 LBL) were carefully selected and docked with MHC molecules (MHC-I and MHC-II) and human TLR4 molecules. To increase the immunological response, the vaccine was combined with a 50S ribosomal adjuvant. To maximize vaccine protein expression, MEBV was cloned and reverse-translated in Escherichia coli. To prove the MEBV's efficacy, more experimental validation is required. After its development, the resulting vaccine is greatly hoped to aid in the prevention of L. pneumophila infections.

Designing multi-epitope-based vaccine targeting surface immunogenic protein of Streptococcus agalactiae using immunoinformatics to control mastitis in dairy cattle

Background

Milk provides energy as well as the basic nutrients required by the body. In particular, milk is beneficial for bone growth and development in children. Based on scientific evidence, cattle milk is an excellent and highly nutritious dietary component that is abundant in vitamins, calcium, potassium, and protein, among other minerals. However, the commercial productivity of cattle milk is markedly affected by mastitis. Mastitis is an economically important disease that is characterized by inflammation of the mammary gland. This disease is frequently caused by microorganisms and is detected as abnormalities in the udder and milk. Streptococcus agalactiae is a prominent cause of mastitis. Antibiotics are rarely used to treat this infection, and other available treatments take a long time to exhibit a therapeutic effect. Vaccination is recommended to protect cattle from mastitis. Accordingly, the present study sought to design a multi-epitope vaccine using immunoinformatics.

Results

The vaccine was designed to be antigenic, immunogenic, non-toxic, and non-allergic, and had a binding affinity with Toll-like receptor 2 (TLR2) and TLR4 based on structural modeling, docking, and molecular dynamics simulation studies. Besides, the designed vaccine was successfully expressed in E. coli. expression vector (pET28a) depicts its easy purification for production on a larger scale, which was determined through in silico cloning. Further, immune simulation analysis revealed the effectiveness of the vaccine with an increase in the population of B and T cells in response to vaccination.

Conclusion

This multi-epitope vaccine is expected to be effective at generating an immune response, thereby paving the way for further experimental studies to combat mastitis.

A rational design of a multi-epitope vaccine against SARS-CoV-2 which accounts for the glycan shield of the spike glycoprotein

The ongoing global health crisis caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus which leads to Coronavirus Disease 2019 (COVID-19) has impacted not only the health of people everywhere, but the economy in nations across the world. While vaccine candidates and therapeutics are currently undergoing clinical trials, there is a lack of proven effective treatments or cures for COVID-19. In this study, we have presented a synergistic computational platform, including molecular dynamics simulations and immunoinformatics techniques, to rationally design a multi-epitope vaccine candidate for COVID-19. This platform combines epitopes across Linear B Lymphocytes (LBL), Cytotoxic T Lymphocytes (CTL) and Helper T Lymphocytes (HTL) derived from both mutant and wild-type spike glycoproteins from SARS-CoV-2 with diverse protein conformations. In addition, this vaccine construct also takes the considerable glycan shield of the spike glycoprotein into account, which protects it from immune response. We have identified a vaccine candidate (a 35.9 kDa protein), named COVCCF, which is composed of 5 LBL, 6 HTL, and 6 CTL epitopes from the spike glycoprotein of SARS-CoV-2. Using multi-dose immune simulations, COVCCF induces elevated levels of immunoglobulin activity (IgM, IgG1, IgG2), and induces strong responses from B lymphocytes, CD4 T-helper lymphocytes, and CD8 T-cytotoxic lymphocytes. COVCCF induces cytokines important to innate immunity, including IFN-γ, IL4, and IL10. Additionally, COVCCF has ideal pharmacokinetic properties and low immune-related toxicities. In summary, this study provides a powerful, computational vaccine design platform for rapid development of vaccine candidates (including COVCCF) for effective prevention of COVID-19.Communicated by Ramaswamy H. Sarma.

Analysis of Foot and Mouth Disease Virus Polyprotein for Multi Peptides Vaccine Design: An In silico Strategy

Foot-and-mouth disease virus (FMDV) is small RNA virus from Picornaviridae family; genus Aphthovirus. FMDV causes maximum levels of infectivity in cattle and harmful socioeconomic effects. The present report attempted to design vaccine candidate from the polyprotein of FMDV to stimulate protective immune response. The IEDB server was used to predict B and T cells epitopes that were linked via GPGPG and YAA linkers, respectively. Mycobacterium tuberculosis 50S ribosomal protein was exploited as an adjuvant and a six histidine-tag sequence was linked to the carboxyl end of the vaccine for purification and identification. The predicted vaccine comprised 313aa and was antigenic and not allergic. Moreover, the vaccine was acidic and showed stability and hydrophilicity. Vaccine secondary and tertiary structures were predicted. The tertiary structure was refined to ameliorate the quality of the global and local structures of the vaccine. Vaccine model validation was performed and the final quality score of the structural model was computed. The validated model was used for molecular docking with bovine (N*01801-BoLA-A11) allele. Docking process in terms of binding free energy score was significant. Vaccine solubility was investigated based on the protein of E. coli and the stability was based on the disulfide bonding to lessen the entropic and mobile points in vaccine. Lastly, the in silico cloning ensured the proper cloning and best translation of the DNA of vaccine in molecular vectors.

Computational design of a broad-spectrum multi-epitope vaccine candidate against seven strains of human coronaviruses

Spike (S) proteins are an attractive target as it mediates the binding of the SARS-CoV-2 to the host through ACE-2 receptors. We hypothesize that the screening of the S protein sequences of all the seven known HCoVs would result in the identification of potential multi-epitope vaccine candidates capable of conferring immunity against various HCoVs. In the present study, several machine learning-based in-silico tools were employed to design a broad-spectrum multi-epitope vaccine candidate targeting the S protein of seven known strains of human coronaviruses. Herein, multiple B-cell epitopes and T-cell epitopes (CTL and HTL) were predicted from the S protein sequences of all seven known HCoVs. Post-prediction they were linked together with an adjuvant to construct a potential broad-spectrum vaccine candidate. Secondary and tertiary structures were predicted and validated, and the refined 3D-model was docked with an immune receptor. The vaccine candidate was evaluated for antigenicity, allergenicity, solubility, and its ability to achieve high-level expression in bacterial hosts. Finally, the immune simulation was carried out to evaluate the immune response after three vaccine doses. The designed vaccine is antigenic (with or without the adjuvant), non-allergenic, binds well with TLR-3 receptor and might elicit a diverse and strong immune response.

Multi-epitope chimeric vaccine design against emerging Monkeypox virus via reverse vaccinology techniques- a bioinformatics and immunoinformatics approach

The emerging monkeypox virus (MPXV) is a zoonotic orthopoxvirus that causes infections in humans similar to smallpox. Since May 2022, cases of monkeypox (MPX) have been increasingly reported by the World Health Organization (WHO) worldwide. Currently, there are no clinically validated treatments for MPX infections. In this study, an immunoinformatics approach was used to identify potential vaccine targets against MPXV. A total of 190 MPXV-2022 proteins were retrieved from the ViPR database and subjected to various analyses including antigenicity, allergenicity, toxicity, solubility, IFN-γ, and virulence. Three outer membrane and extracellular proteins were selected based on their respective parameters to predict B-cell and T-cell epitopes. The epitopes are conserved among different strains of MPXV and the population coverage is 100% worldwide, which will provide broader protection against various strains of the virus globally. Nine overlapping MHC-I, MHC-II, and B-cell epitopes were selected to design multi-epitope vaccine constructs linked with suitable linkers in combination with different adjuvants to enhance the immune responses of the vaccine constructs. Molecular modeling and structural validation ensured high-quality 3D structures of vaccine constructs. Based on various immunological and physiochemical properties and docking scores, MPXV-V2 was selected for further investigation. In silico cloning revealed a high level of gene expression for the MPXV-V2 vaccine within the bacterial expression system. Immune and MD simulations confirmed the molecular stability of the MPXV-V2 construct, with high immune responses within the host cell. These results may aid in the development of experimental vaccines against MPXV with increased potency and improved safety.

Insight Into Novel Anti-tuberculosis Vaccines by Using Immunoinformatics Approaches

Tuberculosis (TB), an infectious disease, has been a leading cause of morbidity and mortality for decades. The causative agent of TB is the Mycobacterium tuberculosis (Mtb) which can infects various parts of the body, mainly the lungs in pulmonary TB cases. Mycobacterium bovis Bacillus Calmette–Guerin (BCG) is the only approved vaccine for TB, but its efficiency to combat pulmonary TB is limited. Multidrug-resistant (MDR) TB and extensive drug-resistant (XDR) TB requires the evolution of more potent vaccines. Therefore, this research aims to generate a universal TB subunit vaccine using advanced immunoinformatics techniques. In generating a novel multiepitope subunit vaccine, we selected the conserved and experimentally confirmed antigens Rv0058, Rv0101, and Rv3343. After a rigorous evaluation, the top candidates from predicted Helper T-lymphocytes (HTL), Cytotoxic T-lymphocytes (CTL), and B-cell epitopes were considered potential vaccine candidates. Immunogenicity was enhanced by the addition of an adjuvant to the ultimate construct of the vaccine. B-cell epitopes predictions guaranteed the eventual induction of a humoral response. Thereafter, dynamics simulations and molecular docking validated the vaccine-receptor complex’s stability and high affinity for the immune receptor TLR-3. Also, immune simulations revealed the significantly elevated levels of immunoglobulins such as IgM, cytokines such as interleukin-2, helper T (Th) cells, and cytotoxic T-cell populations. These results agreed with the actual inflammatory response and showed rapid antigen clearance after manifold exposure. Finally, the E. coli K12 strain was confirmed via in-silico cloning for quality expression. Nevertheless, in vivo experiments should be performed to validate the safety of the proposed vaccine and its inherent ability to prevent TB infection.

Proteome based mapping and reverse vaccinology techniques to contrive multi-epitope based subunit vaccine (MEBSV) against Streptococcus pyogenes

Streptococcus pyogenes is a root cause of human infection like pharyngitis, tonsillitis, scarlet fever, impetigo, and respiratory tract infections. About 11 million individuals in the US suffer from pharyngitis every year. Unfortunately, no vaccine against S. pyogenes is available yet. The purpose of this study is to create a multiepitope-based subunit vaccine (MEBSV) targeting S. pyogenes top four highly antigenic proteins by using a combination of immunological techniques and molecular docking to tackle term group A streptococcal (GAS) infections. T-cell (HTL & CTL), B-cell, and IFN-γ of target proteins were forecasted and epitopes having high antigenic properties being selected for subsequent research. For designing of final vaccine, 5LBL, 9CTL, and 4HTL epitopes were joined by the KK, AAY, and GPGPG linkers. To enhance the immune response, the N-end of the vaccine was linked by adjuvant (Cholera enterotoxin subunit B) with a linker named EAAAK. With the addition of adjuvants and linkers, the construct size was 421 amino acids. IFN-γ and B-cell epitopes illustrate that the modeled construct is optimized for cell-mediated immune or humoral responses. The developed MEBSV structure was assessed to be highly antigenic, non-toxic, and non-allergenic. Moreover, disulphide engineering further enhanced the stability of the final vaccine protein. Molecular docking of the MEBSV with toll-like receptor 4 (TLR4) was conducted to check the vaccine's compatibility with the receptor. Besides, in-silico cloning has been carried out for credibility validation and proper expression of vaccine construct. These findings suggested that the multi-epitope vaccine produced might be a potential immunogenic against Group A streptococcus infections but further experimental testing is required to validate this study.

In silico design and analyses of a multi-epitope vaccine against Crimean-Congo hemorrhagic fever virus through reverse vaccinology and immunoinformatics approaches

Crimean Congo Hemorrhagic Fever virus (CCHFV) is a deadly human pathogen that causes an emerging zoonotic disease with a broad geographic spread, especially in Africa, Asia, and Europe, and the second most common viral hemorrhagic fever and widely transmitted tick-borne viral disease. Following infection, the patients are presented with a variety of clinical manifestations and a fatality rate of 40%. Despite the high fatality rate, there are unmet clinical interventions, as no antiviral drugs or vaccines for CCHF have been approved. Immunoinformatics pipeline and reverse vaccinology were used in this study to design a multi-epitope vaccine that may elicit a protective humoral and cellular immune response against Crimean-Congo hemorrhagic fever virus infection. Three essential virulent and antigenic proteins (S, M, and L) were used to predict seven CTL and 18 HTL epitopes that were non-allergenic, antigenic, IFN-γ inducing, and non-toxic. The epitopes were connected using linkers and 50S ribosomal protein L7/L12 was used as an adjuvant and raised a multi-epitope vaccine (MEV) that is 567 amino acids long. Molecular docking and simulation of the predicted 3D structure of the MEV with the toll-like (TLR2, TLR3, and TLR4) receptors and major histocompatibility complex (MCH-I and MCH-II) indicate high interactions and stability of the complexes, MM-GBSA free binding energy calculation revealed a favourable protein-protein complex. Maximum MEV expression was achieved with a CAI value of 0.98 through in silico cloning in the Drosophila melanogaster host. According to the immune simulation, IgG1, T-helper cells, T-cytotoxic cells, INF-γ, and IL-2 were predicted to be significantly elevated. These robust computational analyses demonstrated that the proposed MEV is effective in preventing CCHFV infections. However, it is still necessary to conduct both in vitro and in vivo experiments to validate the potential of the vaccine.

Rational design of chimeric Multiepitope Based Vaccine (MEBV) against human T-cell lymphotropic virus type 1: An integrated vaccine informatics and molecular docking based approach

Human T-cell lymphotropic virus type 1 (HTLV-1) is an infectious virus that has been linked to adult T cell leukemia /lymphoma, aggressive CD4-T cell malignancy and many other immune-related medical illnesses. So far, no effective vaccine is known to combat HTLV-1, hence, the current research work was performed to design a potential multi-epitope-based subunit vaccine (MEBV) by adopting the latest methodology of reverse vaccinology. Briefly, three highly antigenic proteins (Glycoprotein, Accessory protein, and Tax protein) with no or minimal (<37%) similarity with human proteome were sorted out and potential B- and T-cell epitopes were forecasted from them. Highly antigenic, immunogenic, non-toxic, non-allergenic and overlapping epitopes were short-listed for vaccine development. The chosen T-cell epitopes displayed a strong binding affinity with their corresponding Human Leukocyte Antigen alleles and demonstrated 95.8% coverage of the world's population. Finally, nine Cytotoxic T Lymphocytes, six Helper T Lymphocytes and five Linear B Lymphocytes epitopes, joint through linkers and adjuvant, were exploited to design the final MEBV construct, comprising of 382 amino acids. The developed MEBV structure showed highly antigenic properties while being non-toxic, soluble, non-allergenic, and stable in nature. Moreover, disulphide engineering further enhanced the stability of the final vaccine protein. Additionally, Molecular docking analysis and Molecular Dynamics (MD) simulations confirmed the strong association between MEBV construct and human pathogenic immune receptor TLR-3. Repeated-exposure simulations and Immune simulations ensured the rapid antigen clearance and higher levels of cell-mediated immunity, respectively. Furthermore, MEBV codon optimization and in-silico cloning was carried out to confirm its augmented expression. Results of our experiments suggested that the proposed MEBV could be a potential immunogenic against HTLV-1; nevertheless, additional wet lab experiments are needed to elucidate our conclusion.

Implementation of Vaccinomics and In-Silico Approaches to Construct Multimeric Based Vaccine Against Ovarian Cancer

One of the most common gynecologic cancers is ovarian cancer and ranked third after the other two most common cancers: cervical and uterine. The highest mortality rate has been observed in the case of ovarian cancer. To treat ovarian cancer, an immune-informatics approach was used to design a multi-epitope vaccine (MEV) structure. Epitopes prediction of the cancer testis antigens (NY-ESO-1), A-Kinase anchor protein (AKAP4), Acrosin binding protein (ACRBP), Piwi-like protein (PIWIL3), and cancer testis antigen 2 (LAGE-1) was done. Non-toxic, highly antigenic, non-allergenic, and overlapping epitopes were shortlisted for vaccine construction. Chosen T-cell epitopes displayed a robust binding attraction with their corresponding Human Leukocyte Antigen (HLA) alleles demonstrated 97.59% of population coverage. The vaccine peptide was established by uniting three key constituents, comprising the 14 epitopes of CD8 + cytotoxic T lymphocytes (CTLs), 5 helper epitopes, and the adjuvant. For the generation of the effective response of CD4 + cells towards the T-helper cells, granulocyte–macrophage-colony-stimulating factor (GM-CSF) was applied. With the addition of adjuvants and linkers, the construct size was 547 amino acids. The developed MEV structure was predicted to be antigenic, non-toxic, non-allergenic, and firm in nature. I-tasser anticipated the 3D construction of MEV. Moreover, disulfide engineering further enhanced the stability of the final vaccine protein. In-silico cloning and vaccine codon optimization were done to analyze the up-regulation of its expression. The outcomes established the vaccine’s immunogenicity and safety profile, besides its aptitude to encourage both humoral and cellular immune responses. The offered vaccine, grounded on our in-silico investigation, may be considered for ovarian cancer immunotherapy.

Proteome-Wide Mapping and Reverse Vaccinology Approaches to Design a Multi-Epitope Vaccine against Clostridium perfringens

C. perfringens is a highly versatile bacteria of livestock and humans, causing enteritis (a common food-borne illness in humans), enterotoxaemia (in which toxins are formed in the intestine which damage and destroy organs, i.e., the brain), and gangrene (wound infection). There is no particular cure for the toxins of C. perfringens. Supportive care (medical control of pain, intravenous fluids) is the standard treatment. Therefore, a multiple-epitope vaccine (MEV) should be designed to battle against C. perfringens infection. Furthermore, the main objective of this in silico investigation is to design an MEV that targets C. perfringens. For this purpose, we selected the top three proteins that were highly antigenic using immuno-informatics approaches, including molecular docking. B-cells, IFN-gamma, and T cells for target proteins were predicted and the most conserved epitopes were selected for further investigation. For the development of the final MEV, epitopes of LBL5, CTL17, and HTL13 were linked to GPGPG, AAY, and KK linkers. The vaccine N-end was joined to an adjuvant through an EAAK linker to improve immunogenicity. After the attachment of linkers and adjuvants, the final construct was 415 amino acids. B-cell and IFN-gamma epitopes demonstrate that the model structure is enhanced for humoral and cellular immune responses. To validate the immunogenicity and safety of the final construct, various physicochemical properties, and other properties such as antigenicity and non-allergens, were evaluated. Furthermore, molecular docking was carried out for verification of vaccine compatibility with the receptor, evaluated in silico. Also, in silico cloning was employed for the verification of the proper expression and credibility of the construct.

Design of a novel multiple epitope-based vaccine: An immunoinformatics approach to combat SARS-CoV-2 strains

BACKGROUND

Since the SARS-CoV-2 outbreak in December 2019 in Wuhan, China, the virus has infected more than 153 million individuals across the world due to its human-to-human transmission. The USA is the most affected country having more than 32-million cases till date. Sudden high fever, pneumonia and organ failure have been observed in infected individuals.

OBJECTIVES

In the current situation of emerging viral disease, there is no specific vaccine, or any therapeutics available for SARS-CoV-2, thus there is a dire need to design a potential vaccine to combat the virus by developing immunity in the population. The purpose of present study was to develop a potential vaccine by targeting B and T-cell epitopes using bioinformatics approaches.

METHODS

B- and T-cell epitopes are predicted from novel M protein-SARS-CoV-2 for the development of a unique multiple epitope vaccine by applying bioinformatics approaches. These epitopes were analyzed and selected for their immunogenicity, antigenicity scores, and toxicity in correspondence to their ability to trigger immune response. In combination to epitopes, best multi-epitope of potential immunogenic property was constructed. The epitopes were joined using EAAAK, AAY and GPGPG linkers.

RESULTS

The constructed vaccine showed good results of worldwide population coverage and promising immune response. This constructed vaccine was subjected to in-silico immune simulations by C-ImmSim. Chimeric protein construct was cloned into PET28a (+) vector for expression study in Escherichia coli using snapgene.

CONCLUSION

This vaccine design proved effective in various computer-based immune response analysis as well as showed good population coverage. This study is solely dependent on developing M protein-based vaccine, and these in silico findings would be a breakthrough in the development of an effective vaccine to eradicate SARS-CoV-2 globally.

Integrated Core Proteomics, Subtractive Proteomics, and Immunoinformatics Investigation to Unveil a Potential Multi-Epitope Vaccine against Schistosomiasis

Schistosomiasis is a parasitic infection that causes considerable morbidity and mortality in the world. Infections of parasitic blood flukes, known as schistosomes, cause the disease. No vaccine is available yet and thus there is a need to design an effective vaccine against schistosomiasis. Schistosoma japonicum, Schistosoma mansoni, and Schistosoma haematobium are the main pathogenic species that infect humans. In this research, core proteomics was combined with a subtractive proteomics pipeline to identify suitable antigenic proteins for the construction of a multi-epitope vaccine (MEV) against human-infecting Schistosoma species. The pipeline revealed two antigenic proteins-calcium binding and mycosubtilin synthase subunit C-as promising vaccine targets. T and B cell epitopes from the targeted proteins were predicted using multiple bioinformatics and immunoinformatics databases. Seven cytotoxic T cell lymphocytes (CTL), three helper T cell lymphocytes (HTL), and four linear B cell lymphocytes (LBL) epitopes were fused with a suitable adjuvant and linkers to design a 217 amino-acid-long MEV. The vaccine was coupled with a TLR-4 agonist (RS-09; Sequence: APPHALS) adjuvant to enhance the immune responses. The designed MEV was stable, highly antigenic, and non-allergenic to human use. Molecular docking, molecular dynamics (MD) simulations, and molecular mechanics/generalized Born surface area (MMGBSA) analysis were performed to study the binding affinity and molecular interactions of the MEV with human immune receptors (TLR2 and TLR4) and MHC molecules (MHC I and MHC II). The MEV expression capability was tested in an Escherichia coli (strain-K12) plasmid vector pET-28a(+). Findings of these computer assays proved the MEV as highly promising in establishing protective immunity against the pathogens; nevertheless, additional validation by in vivo and in vitro experiments is required to discuss its real immune-protective efficacy.

Multi-epitope-Based Vaccine Designed by Targeting Cytoadherence Proteins of Mycoplasma gallisepticum

Mycoplasma gallisepticum causes chronic respiratory disease in chickens leading to large economic losses in the poultry industry, and the impacts remain to be a great challenge for a longer period. Among the other approaches, a vaccine targeting the adhesion proteins of M. gallisepticum would be a promising candidate in controlling the infection. Thus, the present study is aimed to design a multi-epitope vaccine candidate using cytoadhesion proteins of M. gallisepticum through an advanced immunoinformatics approach. As a result, the multi-epitope vaccine was constructed, which comprised potential T-cell and B-cell binding epitopes with appropriate adjuvants. The designed multi-epitope vaccine represented high antigenicity with viable physiochemical properties. The prospective three-dimensional structure of the epitope was predicted, refined, and validated. The molecular docking analysis of multi-epitope vaccine candidates with the chicken Toll-like receptor-5 predicted effective binding. Furthermore, codon optimization and in silico cloning ensured high expression. Thus, the present finding indicates that the engineered multi-epitope vaccine is structurally stable and can induce a strong immune response. Furthermore, the multi-epitope vaccine is suggested to be a suitable vaccine candidate for the M. gallisepticum infection due to its effective binding capacity and precise specificity.

Carboxymethyl-β-glucan/chitosan nanoparticles: new thermostable and efficient carriers for antigen delivery

In the last few decades, nanotechnology has emerged as an important tool aimed at enhancing the immune response against modern antigens. Nanocarriers designed specifically for this purpose have been shown to provide protection, stability, and controlled release properties to proteins, peptides, and polynucleotide-based antigens. Polysaccharides are particularly interesting biomaterials for the construction of these nanocarriers given their wide distribution among pathogens, which facilitates their recognition by antigen-presenting cells (APCs). In this work, we focused on an immunostimulant beta-glucan derivative, carboxymethyl-β-glucan, to prepare a novel nanocarrier in combination with chitosan. The resulting carboxymethyl-β-glucan/chitosan nanoparticles exhibited adequate physicochemical properties and an important protein association efficiency, with ovalbumin as a model compound. Moreover, thermostability was achieved through the optimization of a lyophilized form of the antigen-loaded nanoparticles, which remained stable for up to 1 month at 40 ºC. Biodistribution studies in mice showed an efficient drainage of the nanoparticles to the nearest lymph node following subcutaneous injection, and a significant co-localization with dendritic cells. Additionally, subcutaneous immunization of mice with a single dose of the ovalbumin-loaded nanoparticles led to induced T cell proliferation and antibody responses, comparable to those achieved with alum-adsorbed ovalbumin. These results illustrate the potential of these novel nanocarriers in vaccination.

Structural Analysis of the Polymerase Protein for Multiepitopes Vaccine Prediction against Hepatitis B Virus

Hepatitis B virus (HBV) is the most common cause of hepatocellular carcinoma and liver cirrhosis with significant morbidity and mortality worldwide. DNA polymerase protein of HBV is the immunogenic protein inducing immune response against B and T cells. The aim of this study wasto develop multi-epitope vaccine fromthe polymerase protein elicitingimmune responses.The predicted vaccine comprises epitopes against B and T lymphocytesobtained by IEDB server. The predicted epitopes were linked via suitable spacers (linkers). The 50S ribosomal protein L7/L12 was used as an adjuvant at amino terminal and His-tag at the carboxyl terminal of the vaccine construct. The candidate vaccine contains 457aa and was potentially antigenic and nonallergic. Vaccine molecular weightwas 50.03 KDa with pI of 10.04. The instability index was 25.78 and GRAVY was -0.354 indicating stability andhydrophilicity of the chimeric vaccine,respectively.Vaccine structure (Secondary and tertiary structures) were predicted, refined and used for molecular docking with TLR4.The docking with TLR4 provided energy scores of -1458.7 and -1410.3 for chain A and B, respectively, demonstrated strong binding between the chimeric vaccine and TLR4 chains.The vaccine provided favorable solubility compared to E. coli proteins. Stability via disulfide bonds engineering was predicted to reduce the entropy and mobility regions invaccine construct. Molecular dynamics simulation wasperformed to strengthen the prediction. In silicomolecular cloning was usedto guarantee the efficient clonabilityof the vaccine and translation within suitable vector.

Computational design of a new multi-epitope vaccine using immunoinformatics approach against mastitis disease

Mastitis disease causes significant economic losses in dairy farms by reducing milk production, increasing production costs, and reducing milk quality. Streptococcus agalactiae continues to be a major cause of mastitis in dairy cattle. To date, there has been no approved multi-epitope vaccine against this pathogen in the market. In the present study, an efficient multi-epitope vaccine against S. agalactiae, the causative agent of mastitis, was designed using various immonoinformtics approaches. Potential epitopes were selected from Sip protein to improve vaccine immunogenicity. The designed vaccine is more antigenic in nature. Then, linkers and profilin adjuvant were added to enhance the immunity of vaccines. The designed vaccine was evaluated in terms of molecular weight, PI, immunogenicity, Toxicity, and allergenicity. Prediction of three-dimensional (3 D) structure of multi-epitope vaccine, followed by refinement and validation, was conducted to obtain a high-quality 3 D structure of the designed multi-epitope vaccine. The designed vaccine was then subjected to molecular docking with Toll-like receptor 11 (TLR11) receptor to evaluate its binding efficiency followed by dynamic simulation for stable interaction. In silico cloning approach was carried out to improve the expression of the vaccine construct. These analyses indicate that the designed multi-epitope vaccine may produce particular immune responses against S. agalactiae and may be further helpful to control mastitis after in vitro and in vivo immunological assays.

Immuno-Informatics Analysis of Pakistan-Based HCV Subtype-3a for Chimeric Polypeptide Vaccine Design

Hepatitis C virus (HCV) causes chronic and acute hepatitis infections. As there is extreme variability in the HCV genome, no approved HCV vaccine has been available so far. An effective polypeptide vaccine based on the functionally conserved epitopes will be greatly helpful in curing disease. For this purpose, an immuno-informatics study is performed based on the published HCV subtype-3a from Pakistan. First, the virus genome was translated to a polyprotein followed by a subsequent prediction of T-cell epitopes. Non-allergenic, IFN-γ producer, and antigenic epitopes were shortlisted, including 5 HTL epitopes and 4 CTL, which were linked to the final vaccine by GPGPG and AAY linkers, respectively. Beta defensin was included as an adjuvant through the EAAAK linker to improve the immunogenicity of the polypeptide. To ensure its safety and immunogenicity profile, antigenicity, allergenicity, and various physiochemical attributes of the polypeptide were evaluated. Molecular docking was conducted between TLR4 and vaccine to evaluate the binding affinity and molecular interactions. For stability assessment and binding of the vaccine-TLR4 docked complex, molecular dynamics (MD) simulation and MMGBSA binding free-energy analyses were conducted. Finally, the candidate vaccine was cloned in silico to ensure its effectiveness. The current vaccine requires future experimental confirmation to validate its effectiveness. The vaccine construct produced might be useful in providing immune protection against HCV-related infections.

Immunoinformatics analysis to design novel epitope based vaccine candidate targeting the glycoprotein and nucleoprotein of Lassa mammarenavirus (LASMV) using strains from Nigeria

Lassa mammarenavirus (LASMV) is responsible for a specific type of acute viral hemorrhagic fever known as Lassa fever. Lack of effective treatments and counter-measures against the virus has resulted in a high mortality rate in its endemic regions. Therefore, in this study, a novel epitope-based vaccine has been designed using the methods of immunoinformatics targeting the glycoprotein and nucleoprotein of the virus. After numerous robust analyses, two CTL epitopes, eight HTL epitopes and seven B-cell epitopes were finally selected for constructing the vaccine. All these most promising epitopes were found to be antigenic, non-allergenic, nontoxic and non-human homolog, which made them suitable for designing the subunit vaccine. Furthermore, the selected T-cell epitopes which were found to be fully conserved across different isolates of the virus, were also considered for final vaccine construction. After that, numerous validation experiments, i.e. molecular docking, molecular dynamics simulation and immune simulation were conducted, which predicted that our designed vaccine should be stable within the biological environment and effective in combating the LASMV infection. In the end, codon adaptation and in silico cloning studies were performed to design a recombinant plasmid for producing the vaccine industrially. However, further in vitro and in vivo assessments should be done on the constructed vaccine to finally confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

Rational design of multimeric based subunit vaccine against Mycoplasma pneumonia: Subtractive proteomics with immunoinformatics framework

Mycoplasma pneumoniae is the prevalent cause of acquired respiratory infections around the globe. A multi-epitope vaccine (MEV) must be developed to combat infections of M. pneumoniae because there is no specific disease-modifying treatment or vaccination is present. The objective of this research is to design a vaccine that targets M. pneumoniae top five highly antigenic proteins using a combination of immunological techniques and molecular docking. T-cell (HTL & CTL), B-cell, and IFN-γ of target proteins were forecasted and highly conservative epitopes were chosen for further study. For designing of final vaccine, 4LBL, 7CTL, and 5HTL epitopes were joined by linkers of KK, AAY, and GPGPG. The N-end of the vaccine was linked to an adjuvant (Cholera enterotoxin subunit B) with a linker named EAAAK to enhance immunogenicity. After the addition of adjuvants and linkers, the size of the construct was 395 amino acids. The epitopes of IFN-γ and B-cells illustrate that the model construct is optimized for cell-mediated immune or humoral responses. To ensure that the final design is safer and immunogenic, properties like non-allergens, antigenicity, and various physicochemical properties were evaluated. Molecular docking of the vaccine with the toll-like receptor 4 (TLR4) was conducted to check the compatibility of the vaccine with the receptor. Besides, in-silico cloning was utilized for validation of the credibility and proper expression of the vaccine. Furthermore, to confirm that the multi-epitope vaccine created is protective and immunogenic, this research requires experimental validation.

Computational Design and Preliminary Serological Analysis of a Novel Multi-Epitope Vaccine Candidate against Onchocerciasis and Related Filarial Diseases

: Onchocerciasis is a skin and eye disease that exerts a heavy socio-economic burden, particularly in sub-Saharan Africa, a region which harbours greater than 96% of either infected or at-risk populations. The elimination plan for the disease is currently challenged by many factors including amongst others; the potential emergence of resistance to the main chemotherapeutic agent, ivermectin (IVM). Novel tools, including preventative and therapeutic vaccines, could provide additional impetus to the disease elimination tool portfolio. Several observations in both humans and animals have provided evidence for the development of both natural and artificial acquired immunity. In this study, immuno-informatics tools were applied to design a filarial-conserved multi-epitope subunit vaccine candidate, (designated Ov-DKR-2) consisting of B-and T-lymphocyte epitopes of eight immunogenic antigens previously assessed in pre-clinical studies. The high-percentage conservation of the selected proteins and epitopes predicted in related nematode parasitic species hints that the generated chimera may be instrumental for cross-protection. Bioinformatics analyses were employed for the prediction, refinement, and validation of the 3D structure of the Ov-DKR-2 chimera. In-silico immune simulation projected significantly high levels of IgG1, T-helper, T-cytotoxic cells, INF-γ, and IL-2 responses. Preliminary immunological analyses revealed that the multi-epitope vaccine candidate reacted with antibodies in sera from both onchocerciasis-infected individuals, endemic normals as well as loiasis-infected persons but not with the control sera from European individuals. These results support the premise for further characterisation of the engineered protein as a vaccine candidate for onchocerciasis.

In silico analysis of epitope-based vaccine candidate against tuberculosis using reverse vaccinology

Tuberculosis (TB) kills more individuals in the world than any other disease, and a threat made direr by the coverage of drug-resistant strains of Mycobacterium tuberculosis (Mtb). Bacillus Calmette-Guérin (BCG) is the single TB vaccine licensed for use in human beings and effectively protects infants and children against severe military and meningeal TB. We applied advanced computational techniques to develop a universal TB vaccine. In the current study, we select the very conserved, experimentally confirmed Mtb antigens, including Rv2608, Rv2684, Rv3804c (Ag85A), and Rv0125 (Mtb32A) to design a novel multi-epitope subunit vaccine. By using the Immune Epitopes Database (IEDB), we predicted different B-cell and T-cell epitopes. An adjuvant (Griselimycin) was also added to vaccine construct to improve its immunogenicity. Bioinformatics tools were used to predict, refined, and validate the 3D structure and then docked with toll-like-receptor (TLR-3) using different servers. The constructed vaccine was used for further processing based on allergenicity, antigenicity, solubility, different physiochemical properties, and molecular docking scores. The in silico immune simulation results showed significant response for immune cells. For successful expression of the vaccine in E. coli, in-silico cloning and codon optimization were performed. This research also sets out a good signal for the design of a peptide-based tuberculosis vaccine. In conclusion, our findings show that the known multi-epitope vaccine may activate humoral and cellular immune responses and maybe a possible tuberculosis vaccine candidate. Therefore, more experimental validations should be exposed to it.

Discovery of potential immune epitopes and peptide vaccine design - a prophylactic strategy against Rift Valley fever virus

Background: Rift Valley fever virus (RVFV) is an emerging arbovirus infecting both animals and humans. Any form of direct contact with body fluids, blood or tissue of infected animals is the mode of transmission of this pathogen. Despite being an emerging virus, no proper vaccinations are yet available for the public. Our objective is to compose a multiepitope vaccine utilizing immuno-bioinformatics as a strategy against RVFV. Methods: To identify immunodominant epitopes and design a potent vaccine candidate, we applied a series of immunoinformatic approaches with molecular dynamics and immune response simulation frameworks. Results: A glycoprotein with the highest antigenicity was selected and employed for determining promising epitopes. We selected T cell epitopes based on their immunological potencies and cytokine inducing properties, while B cell epitopes were selected based on their antigenic features. Finally, we selected four cytotoxic T-lymphocyte, two helper T-lymphocyte, and three linear B-lymphocyte epitopes that were arranged into a vaccine construct with appropriate adjuvants and linkers. The chimera protein was modeled, refined, and validated prior to docking against toll-like receptor 4. Docking studies suggest strong binding interactions while dynamics simulation revealed the stable nature of the docked complex. Furthermore, the immune simulation showed robust and prolonged immune responses with rapid antigen clearance. Finally, codon optimization and cloning conducted with Escherichia coli K12 suggests high translation efficiency within the host system. Conclusion: We believe that our designed multiepitope vaccine is a promising prophylactic candidate against RVFV pathogenesis.

A Rational Design of a Multi-Epitope Vaccine Against SARS-CoV-2 Which Accounts for the Glycan Shield of the Spike Glycoprotein

The ongoing global health crisis caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus which leads to Coronavirus Disease 2019 (COVID-19) has impacted not only the health of people everywhere, but the economy in nations across the world. While vaccine candidates and therapeutics are currently undergoing clinical trials, there is yet to be a proven effective treatment or cure for COVID-19. In this study, we have presented a synergistic computational platform, including molecular dynamics simulations and immunoinformatics techniques, to rationally design a multi-epitope vaccine candidate for COVID-19. This platform combines epitopes across Linear B Lymphocytes (LBL), Cytotoxic T Lymphocytes (CTL) and Helper T Lymphocytes (HTL) derived from both mutant and wild-type spike glycoproteins from SARS-CoV-2 with diverse protein conformations. In addition, this vaccine construct also takes the considerable glycan shield of the spike glycoprotein into account, which protects it from immune response. We have identified a vaccine candidate (a 35.9 kDa protein), named COVCCF, which is composed of 5 LBL, 6 HTL, and 6 CTL epitopes from the spike glycoprotein of SARS-CoV-2. Using multi-dose immune simulations, COVCCF induces elevated levels of immunoglobulin activity (IgM, IgG1, IgG2), and induces strong responses from B lymphocytes, CD4 T-helper lymphocytes, and CD8 T-cytotoxic lymphocytes. COVCCF induces cytokines important to innate immunity, including IFN-γ, IL4, and IL10. Additionally, COVCCF has ideal pharmacokinetic properties and low immune-related toxicities. In summary, this study provides a powerful, computational vaccine design platform for rapid development of vaccine candidates (including COVCCF) for effective prevention of COVID-19.

Bioinformatics design and experimental validation of influenza A virus multi-epitopes that induce neutralizing antibodies

Pandemics caused by influenza A virus (IAV) are responsible for the deaths of millions of humans around the world. One of these pandemics occurred in Mexico in 2009. Despite the impact of IAV on human health, there is no effective vaccine. Gene mutations and translocation of genome segments of different IAV subtypes infecting a single host cell make the development of a universal vaccine difficult. The design of immunogenic peptides using bioinformatics tools could be an interesting strategy to increase the success of vaccines. In this work, we used the predicted amino acid sequences of the neuraminidase (NA) and hemagglutinin (HA) proteins of different IAV subtypes to perform multiple alignments, epitope predictions, molecular dynamics simulations, and experimental validation. Peptide selection was based on the following criteria: promiscuity, protein surface exposure, and the degree of conservation among different medically relevant IAV strains. These peptides were tested using immunological assays to test their ability to induce production of antibodies against IAV. We immunized rabbits and mice and measured the levels of IgG and IgA antibodies in serum samples and nasal washes. Rabbit antibodies against the peptides P11 and P14 (both of which are hybrids of NA and HA) recognized HA from both group 1 (H1, H2, and H5) and group 2 (H3 and H7) IAV and also recognized the purified NA protein from the viral stock (influenza A Puerto Rico/916/34). IgG antibodies from rabbits immunized with P11 and P14 were capable of recognizing viral particles and inhibited virus hemagglutination. Additionally, intranasal immunization of mice with P11 and P14 induced specific IgG and IgA antibodies in serum and nasal mucosa, respectively. Interestingly, the IgG antibodies were found to have neutralizing capability. In conclusion, the peptides designed through in silico studies were validated in experimental assays.

Exploring Lassa Virus Proteome to Design a Multi-epitope Vaccine Through Immunoinformatics and Immune Simulation Analyses

Lassa virus (LASV) is responsible for a type of acute viral haemorrhagic fever referred to as Lassa fever. Lack of adequate treatment and preventive measures against LASV resulted in a high mortality rate in its endemic regions. In this study, a multi-epitope vaccine was designed using immunoinformatics as a prophylactic agent against the virus. Following a rigorous assessment, the vaccine was built using T-cell (N_CTL = 8 and N_HTL = 6) and B-cell (N_LBL = 4) epitopes from each LASV-derived protein in addition with suitable linkers and adjuvant. The physicochemistry, immunogenic potency and safeness of the designed vaccine (~ 68 kDa) were assessed. In addition, chosen CTL and HTL epitopes of our vaccine showed 97.37% worldwide population coverage. Besides, disulphide engineering also improved the stability of the chimeric vaccine. Molecular docking of our vaccine protein with toll-like receptor 2 (TLR2) showed binding efficiency followed by dynamics simulation for stable interaction. Furthermore, higher levels of cell-mediated immunity and rapid antigen clearance were suggested by immune simulation and repeated-exposure simulation, respectively. Finally, the optimized codons were used in in silico cloning to ensure higher expression within E. coli K12 bacterium. With further assessment both in vitro and in vivo, we believe that our proposed peptide-vaccine would be potential immunogen against Lassa fever.

Designing a multi-epitopic vaccine against the enterotoxigenic Bacteroides fragilis based on immunoinformatics approach

Enterotoxigenic Bacteroides fragilis is an enteric pathogen which is described as a causative agent of various intestinal infections and inflammatory diseases. Moreover, various research studies have reported it to be a leading factor in the development of colorectal cancer. As a part of the normal human microbiome, its treatment has become quite a challenge due to the alarming resistance against the available antibiotics. Although, this particular strain of B. fragilis shows susceptibility to few antibiotics, it is pertinent to devise an effective vaccine strategy for its elimination. There is no vaccine available against this pathogen up to date; therefore, we systematically ventured the outer membrane toxin producing proteins found exclusively in the toxigenic B. fragilis through the in-silico approaches to predict a multi-epitopic chimeric vaccine construct. The designed protein constitutes of epitopes which are predicted for linear B cells, Helper and T cells of outer membrane proteins expected to be putative vaccine candidates. The finalized proteins are only expressed in the enterotoxigenic B. fragilis, thus proving them to be exclusive. The 3D structure of the protein was first predicted followed by its refinement and validation via utilizing the bioinformatic approaches. Docking of the designed protein with the TLR2 receptor forecasted apt binding. Upon immune simulation, notable levels were observed in the expression of the immune cells.

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

Onchocerciasis is a parasitic disease with high socio-economic burden particularly in sub-Saharan Africa. The elimination plan for this disease has faced numerous challenges. A multi-epitope prophylactic/therapeutic vaccine targeting the infective L3 and microfilaria stages of the parasite's life cycle would be invaluable to achieve the current elimination goal. There are several observations that make the possibility of developing a vaccine against this disease likely. For example, despite being exposed to high transmission rates of infection, 1 to 5% of people have no clinical manifestations of the disease and are thus considered as putatively immune individuals. An immuno-informatics approach was applied to design a filarial multi-epitope subunit vaccine peptide consisting of linear B-cell and T-cell epitopes of proteins reported to be potential novel vaccine candidates. Conservation of the selected proteins and predicted epitopes in other parasitic nematode species suggests that the generated chimera could be helpful for cross-protection. The 3D structure was predicted, refined, and validated using bioinformatics tools. Protein-protein docking of the chimeric vaccine peptide with the TLR4 protein predicted efficient binding. Immune simulation predicted significantly high levels of IgG₁, T-helper, T-cytotoxic cells, INF-γ, and IL-2. Overall, the constructed recombinant putative peptide demonstrated antigenicity superior to current vaccine candidates.

Potent HIV-1-Specific CD8 T Cell Responses Induced in Mice after Priming with a Multiepitopic DNA-TMEP and Boosting with the HIV Vaccine MVA-B

An effective vaccine against Human Immunodeficiency Virus (HIV) still remains the best solution to provide a sustainable control and/or eradication of the virus. We have previously generated the HIV-1 vaccine modified vaccinia virus Ankara (MVA)-B, which exhibited good immunogenicity profile in phase I prophylactic and therapeutic clinical trials, but was unable to prevent viral rebound after antiretroviral (ART) removal. To potentiate the immunogenicity of MVA-B, here we described the design and immune responses elicited in mice by a new T cell multi-epitopic B (TMEP-B) immunogen, vectored by DNA, when administered in homologous or heterologous prime/boost regimens in combination with MVA-B. The TMEP-B protein contained conserved regions from Gag, Pol, and Nef proteins including multiple CD4 and CD8 T cell epitopes functionally associated with HIV control. Heterologous DNA-TMEP/MVA-B regimen induced higher HIV-1-specific CD8 T cell responses with broader epitope recognition and higher polyfunctional profile than the homologous DNA-TMEP/DNA-TMEP or the heterologous DNA-GPN/MVA-B combinations. Moreover, higher HIV-1-specific CD4 and Tfh immune responses were also detected using this regimen. After MVA-B boost, the magnitude of the anti-VACV CD8 T cell response was significantly compromised in DNA-TMEP-primed animals. Our results revealed the immunological potential of DNA-TMEP prime/MVA-B boost regimen and supported the application of these combined vectors in HIV-1 prevention and/or therapy.

Self-assembling anticaries mucosal vaccine containing ferritin cage nanostructure and glucan-binding region of S. mutans glucosyltransferase effectively prevents caries formation in rodents

Anticaries protein vaccines that induce a mucosal immune response are not effective. Therefore, development of effective and convenient anticaries vaccines is a priority of dental research. Here we generated self-assembling nanoparticles by linking the glucan-binding region of Streptococcus mutans glucosyltransferase (GLU) to the N-terminal domain of ferritin to determine whether these novel nanoparticles enhanced the immunogenicity of an anticaries protein vaccine against GLU in rodents. We constructed the expression plasmid pET28a-GLU-FTH and purified the proteins from bacteria using size-exclusion chromatography. BALB/c mice were used to evaluate the ability of GLU-ferritin (GLU-FTH) nanoparticles to induce GLU-specific mucosal and systemic responses. The protective efficiency of GLU-FTH nanoparticles was compared with that of GLU alone or a mixture of GLU and poly(I:C) after administering an intranasal infusion to Wistar rats. The phagocytosis and maturation of dendritic cells (DCs) exposed in vitro to the nanoparticles were assessed using flow cytometry. The GLU-FTH nanoparticle vaccine elicited significantly higher levels of GLU-specific antibodies compared with GLU or a mixture of GLU and poly(I:C). Immunization with GLU-FTH achieved lower caries scores compared with those of the other vaccines. Administration of GLU-FTH nanoparticles enhanced phagocytosis by DCs and their maturation. Thus, self-assembling GLU-FTH is a highly effective anticaries mucosal vaccine that enhanced antibody production and inhibited S. mutans infection in rodents.

Enhancing Antibody Serodiagnosis Using a Controlled Peptide Coimmobilization Strategy

Antigen immunoreactivity is often determined by surface regions defined by the 3D juxtapositions of amino acids stretches that are not continuous in the linear sequence. As such, mimicking an antigen immunoreactivity by means of putative linear peptide epitopes for diagnostic purposes is not trivial. Here we present a straightforward and robust method to extend the reach of immune-diagnostic probes design by copresenting peptides belonging to the same antigenic surface. In this case study focused on a computationally predicted Zika virus NS1 protein putative antigenic region, we reached a diagnostic confidence by the oriented and spatially controlled coimmobilization of peptide sequences found adjacent within the protein fold, that cooperatively interacted to provide enhanced immunoreactivity with respect to single linear epitopes. Through our method, we were able to differentiate Zika infected individuals from healthy controls. Remarkably, our strategy fits well with the requirements to build high-throughput screening platforms of linear and mixed peptide libraries, and it could possibly facilitate the rapid identification of conformational immunoreactive regions.

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

Introduction: In this study, we targeted the worm stage of Echinococcus granulosus to design a novel multi-epitope B- and helper T-cell based vaccine construct for immunization of dogs against this multi-host parasite.

Methods: The vaccine was designed based on the local Eg14-3-3 antigen (Ag). DNA samples were extracted from the protoscoleces of the infected sheep’s liver, and then subjected to the polymerase chain reaction (PCR) with 14-3-3 specific forward and reverse primers. For the vaccine designing, several in silico steps were undertaken. Three-dimensional (3D) structure of the local Eg14-3-3 Ag was modeled by EasyModeller software. The protein modeling accuracy was then analyzed via various validation assays. Potential transmembrane helix, signal peptide, post-translational modifications and allergenicity of Eg14-3-3 were evaluated as the preliminary measures of B-cell epitopes (BEs ) prediction. Having used many web-servers, a well-designed process was carried out for improved prediction of BEs. High ranked linear and conformational BEs were utilized for engineering the final vaccine construct. Possible T-helper epitopes (TEs) were identified by the molecular docking between 13-mer fragments of the Eg14-3-3 Ag and two high frequent dog class II MHC alleles (i.e., DLA-DRB1*01101 and DRB1*01501). The epitopes coverage was evaluated by Shannon’s variability plot.

Results: The final designed construct was analyzed based on different physicochemical properties, which was then codon optimized for high-level expression in Escherichia coli k12. This minigene construct is the first dog-specific epitopic vaccine construct that is established based on TEs with high-binding affinity to canine MHC alleles.

Conclusion: This in silico study is the first part of a multi-antigenic vaccine designing work that represents as a novel dog-specific vaccine against E. granulosus. Here, we present key data on the step-by-step methodologies used for designing this de novo vaccine, which is under comprehensive in vivo investigations.

HLA based selection of epitopes offers a potential window of opportunity for vaccine design against HIV

The pace of progression to AIDS after HIV infection varies from individual to individual. While some individuals develop AIDS quickly, others are protected from the onset of disease for more than a decade (elite controllers and long term non-progressors). The mechanisms of protection are not yet clearly understood, though various factors including host genetics, immune components and virus attenuation have been elucidated partly. The influence of HLA alleles on HIV-1 infection and disease outcome has been studied extensively. Several HLA alleles are known to be associated with resistance to infection or delayed progression to AIDS after infection. Similarly, certain HLA alleles are reported to be associated with rapid progression to disease. Since HLA alleles influence the outcome of HIV infection differentially, selection of epitopes specifically recognized by protective alleles could serve asa rational means for HIV vaccine design. In this review article, we discuss existing knowledge on HLA alleles and their association with resistance/susceptibility to HIV and its relevance to vaccine design.

Flexible vs Rigid Epitope Conformations for Diagnostic- and Vaccine-Oriented Applications: Novel Insights from the Burkholderia pseudomallei BPSL2765 Pal3 Epitope

Peptides seldom retain stable conformations if separated from their native protein structure. In an immunological context, this potentially affects the development of selective peptide-based bioprobes and, from a vaccine perspective, poses inherent limits in the elicitation of cross-reactive antibodies by candidate epitopes. Here, a 1,4-disubstituted-1,2,3-triazole-mediated stapling strategy was used to stabilize the native α-helical fold of the Pal3 peptidic epitope from the protein antigen PalBp (BPSL2765) from Burkholderia pseudomallei, the etiological agent of melioidosis. Whereas Pal3 shows no propensity to fold outside its native protein context, the engineered peptide (Pal3H) forms a stable α-helix, as assessed by MD, NMR, and CD structural analyses. Importantly, Pal3H shows an enhanced ability to discriminate between melioidosis patient subclasses in immune sera reactivity tests, demonstrating the potential of the stapled peptide for diagnostic purposes. With regard to antibody elicitation and related bactericidal activities, the linear peptide is shown to elicit a higher response. On these bases, we critically discuss the implications of epitope structure engineering for diagnostic- and vaccine-oriented applications.