Designing a multi-epitopes subunit vaccine against human herpes virus 6A based on molecular dynamics and immune stimulation

Immunoinformatic approach for designing a multi-epitope vaccine against non-typhoidal salmonellosis using starvation-stress response proteins from Salmonella Oranienburg

Non-typhoidal Salmonella is responsible for gastrointestinal illnesses worldwide. Therefore, it is important to implement effective therapeutic interventions for preventing these diseases. Vaccines have proven highly efficacious in the treatment and prevention of several illnesses. Nevertheless, there is currently no authorized vaccine available for non-typhoidal salmonellosis. This study aimed to employ in silico techniques to develop a multi-epitope vaccine targeting non-typhoidal salmonellosis. Specifically, we focused on proteins associated with the starvation stress response (SSR) in Salmonella Oranienburg. The presence of these proteins is essential for the survival and disease of the host organism. The vaccine sequence was constructed utilizing B-cell and T-cell epitopes. Linkers, adjuvants and PADRE sequences were used to establish connections between epitopes. The vaccine exhibited no allergenicity, toxigenicity and a significantly high antigenicity score. Docking analysis conducted between the designed vaccine and the TLR-1, TLR-2 and TLR-4 receptors demonstrated favorable interactions and the potential to activate these receptors. In addition, it was found through immunological simulation testing that the vaccine elicits a robust immune response. The use of these proteins in the construction of a multi-epitope vaccine shows potential in terms of both safety and immunogenicity.

Immune mechanisms in multiple sclerosis: CD3 levels on CD28+ CD4+ T cells link antibody responses to human herpesvirus 6

Compelling evidence suggests a significant association between antibody-mediated immune responses and multiple sclerosis (MS). However, the exact causal relationships between these immune responses and MS remain unclear. In this study, we conducted a comprehensive examination of the link between antibody-mediated immune responses and MS via Mendelian randomization (MR) analysis to identify specific infectious pathogens potentially involved in the onset and progression of MS. We compared immune cell infiltration between MS patients and control subjects. Furthermore, single-cell sequencing was employed to conduct a comparative analysis of the marker genes associated with each cell subtype between individuals diagnosed with MS and the control cohort. We revealed connections between antibody-mediated immune responses and immune cells, as well as the associations between these immune cells and MS. We discovered that CD3 levels on CD28+ CD4+ T cells significantly influence MS progression by altering the ratio of human herpesvirus 6 (HHV-6). These findings provide novel insights into the biological mechanisms underlying HHV-6-mediated MS.

Exploratory algorithms to devise multi-epitope subunit vaccine by examining HIV-1 envelope glycoprotein: An immunoinformatics and viroinformatics approach

Acquired immune deficiency syndrome (AIDS), a widespread pandemic and severe health issue, is triggered by the human immunodeficiency virus (HIV); there is no specific vaccine to cure this infection, and the situation is worsening. Therefore, this research sought to develop a vaccine with multiple epitopes against this infection targeting envelope glycoprotein (vital in host-cell interaction) through the immunoinformatics and viroinformatics approach. We identified one B-cell, eight MHC-I, and four MHC-II epitopes on its immunogen-assisted screening. In addition, these putative epitopes were conjoined concurrently using a specific linker (EAAAK, KK, GPGPG), including an adjuvant and a His-Tag at the N and C terminal, respectively, to augment its immune reaction. The final constructed entity consists of 284 amino acids; immunological evaluation demonstrated that the developed vaccine possesses antigenic features with a value of 0.6222, is non-allergenic, and has prospective physiochemical characteristics. The secondary and tertiary structures were anticipated, and their quality has been evaluated. Further, docking analysis between vaccines with TLR3 shows a strong molecular interaction with a -20.0 kcal/mol binding energy, and the stability was analysed through the MD simulation (100ns). Moreover, the designed vaccine expression and immune response were analysed, and a high vaccine expression level was found (pET28a (+)) and robust immune response followed by codon adaptation index value 0.94, 58.36% GC content, and the generation of IgM +  IgG, cytokines and interleukin. Based on overall investigation, the developed vaccine stimulates a robust immune response. Nevertheless, laboratory analysis is needed to confirm the protective potency of the vaccine.

An immunoinformatics and extensive molecular dynamics study to develop a polyvalent multi-epitope vaccine against cryptococcosis

Cryptococcosis is a lethal mycosis instigated by the pathogenic species Cryptococcus neoformans and Cryptococcus gattii, primarily affects the lungs, manifesting as pneumonia, and the brain, where it presents as meningitis. Mortality rate could reach 100% if infections remain untreated in cryptococcal meningitis. Treatment options for cryptococcosis are limited and and there are no licensed vaccines clinically available to treat or prevent cryptococcosis. Our study utilizes an integrated bioinformatics approaches to develop a polyvalent multiepitope subunit vaccine focusing on the key virulent proteins Heat shock transcription factor and Chaperone DnaK of both C. neoformans and C. gatti. Then in silico analysis was done to predict highly antigenic epitopes by assessing antigenicity, transmembrane topology screening, allergenecity, toxicity, and molecular docking approaches. Following this analysis, we designed two vaccine constructs integrating a compatible adjuvant and suitable linkers. These constructs exhibited notable characteristics including high antigenicity, non-toxicity, solubility, stability, and compatibility with Toll-like receptors (TLRs). The interaction between both vaccine constructs and TLR2, TLR3, and TLR9 was assessed through molecular docking analysis. Molecular dynamics simulations and MM-PBSA calculations suggest the substantial stabilizing property and binding affinity of Vaccine Construct V1 against TLR9. Both the vaccines revealed to have a higher number of interchain hydrogen bond with TLR9. These findings serve as a crucial stepping stone towards a comprehensive solution for combating cryptococcus infections induced by both C. neoformans and C. gattii. Further validation through in vivo studies is crucial to confirm the effectiveness and potential of the vaccine to curb the spread of cryptococcosis. Subsequent validation through in vivo studies is paramount to confirm the effectiveness and potential of the vaccine in reducing the spread of cryptococcosis.

Immunoinformatic based designing of highly immunogenic multi-epitope subunit vaccines to stimulate an adaptive immune response against Junin virus

The Junin virus causes Argentine hemorrhagic fever, leading to severe complications such as high fever, malaise, muscle pain, and bleeding disorders, including hemorrhages in the skin and mucous membranes. Neurological issues like confusion, seizures, and coma can also occur. Without prompt and effective treatment, the disease can be fatal, with mortality rates reaching up to 30%. Taking serious measures is essential to mitigate the spread of the disease. Vaccination is the most effective choice to neutralize the Junin virus in the current situation. Consequently, to design the highly immunogenic and non-allergenic multi-epitope subunit vaccine against the Junin virus, we employed the immunoinformatic approach to screen the glycoprotein, nucleoprotein, and RDRP protein for potential immunogenic CTL (Cytotoxic T Lymphocyte), HTL (Helper T Lymphocyte) and B (B Lymphocyte) cell epitopes. Afterward, the predicted epitopes were subjected to 3D modeling and validation. The strong binding affinity of the constructed vaccines with the human TLR3 was confirmed through molecular docking, with scores of - 333 kcal/mol for glycoprotein, - 297 kcal/mol for nucleoprotein, - 308 kcal/mol for RDRP, and - 305 kcal/mol for combined vaccines. Additionally, the binding free energies recorded were - 63.54 kcal/mol, - 64.16 kcal/mol, - 56.81 kcal/mol, and - 51.52 kcal/mol, respectively. Furthermore, the dynamic stability, residual fluctuation, and compactness of vaccine-TLR-3 complexes were confirmed by the molecular dynamic simulation. The codon adaptation index (CAI) values and high GC content confirmed the stable expression of constructed vaccines in the pET-28a ( +) expression vector. The immune simulation analysis demonstrated that administering booster doses of the developed vaccines resulted in a notable increase in IgG, IgM, interleukins, and cytokines levels, indicating effective antigen clearance over time. In conclusion, our study provides preclinical evidence for designing a highly effective Junin virus vaccine, necessitating further in-vitro and in-vivo experiments.

Designing a multi-epitope subunit vaccine against Orf virus using molecular docking and molecular dynamics

Orf virus (ORFV) is an acute contact, epitheliotropic, zoonotic, and double-stranded DNA virus that causes significant economic losses in the livestock industry. The objective of this study is to design an immunoinformatics-based multi-epitope subunit vaccine against ORFV. Various immunodominant cytotoxic T lymphocytes (CTL), helper T lymphocytes (HTL), and B-cell epitopes from the B2L, F1L, and 080 protein of ORFV were selected and linked by short connectors to construct a multi-epitope subunit vaccine. Immunogenicity was enhanced by adding an adjuvant β-defensin to the N-terminal of the vaccine using the EAAAK linker. The vaccine exhibited a significant degree of antigenicity and solubility, without allergenicity or toxicity. The 3D formation of the vaccine was subsequently anticipated, improved, and verified. The optimized model exhibited a lower Z-score of -4.33, indicating higher quality. Molecular docking results demonstrated that the vaccine strongly binds to TLR2 and TLR4. Molecular dynamics results indicated that the docked vaccine-TLR complexes were stable. Immune simulation analyses further confirmed that the vaccine can induce a marked increase in IgG and IgM antibody titers, and elevated levels of IFN-γ and IL-2. Finally, the optimized DNA sequence of the vaccine was cloned into the vector pET28a (+) for high expression in the E.coli expression system. Overall, the designed multi-epitope subunit vaccine is highly stable and can induce robust humoral and cellular immunity, making it a promising vaccine candidate against ORFV.

Rational design of novel peptide-based vaccine against the emerging OZ virus

Oz virus (OZV) belongs to the Orthomyxoviridae family which includes viruses with a negative-sense, single-stranded, and segmented RNA genome. OZV is a zoonotic pathogen, particularly since the virus can cause deadly illness when injected intracerebrally into nursing mice. OZV is an emerging pathogen with the potential to spark a pandemic as there is no preventive and licensed treatment against this virus. The goal of this study was to develop a novel multi-epitope vaccination against OZV proteins utilizing immunoinformatics and immunological simulation analysis. This work evaluated immunological epitopes (B cells, MHC-I, and MHC-II) to identify highly antigenic OZV target proteins. Shortlisted epitopes were joined together by using appropriate linkers and adjuvants to design multi-epitope vaccine constructs (MEVC). The vaccine models were designed, improved, validated, and the globular regions and post-translational modifications (PTMs) were also evaluated in the vaccine's structure. Molecular docking analysis with the Toll-like receptor (TLR4) showed strong interactions and appropriate binding energies. Molecular dynamics (MD) simulation confirmed stable interactions between the vaccines and TLR4. Bioinformatics tools helped optimize codons, resulting in successful cloning into appropriate host vectors. This study showed that the developed vaccines are stable and non-allergenic in the human body and successfully stimulated immunological responses against OZV. Finally, a mechanism of action for the designed vaccine construct was also proposed. Further experimental validations of the designed vaccine construct will pave the way to create a potentially effective vaccine against this emerging pathogen.

Leveraging artificial intelligence in vaccine development: A narrative review

Vaccine development stands as a cornerstone of public health efforts, pivotal in curbing infectious diseases and reducing global morbidity and mortality. However, traditional vaccine development methods are often time-consuming, costly, and inefficient. The advent of artificial intelligence (AI) has ushered in a new era in vaccine design, offering unprecedented opportunities to expedite the process. This narrative review explores the role of AI in vaccine development, focusing on antigen selection, epitope prediction, adjuvant identification, and optimization strategies. AI algorithms, including machine learning and deep learning, leverage genomic data, protein structures, and immune system interactions to predict antigenic epitopes, assess immunogenicity, and prioritize antigens for experimentation. Furthermore, AI-driven approaches facilitate the rational design of immunogens and the identification of novel adjuvant candidates with optimal safety and efficacy profiles. Challenges such as data heterogeneity, model interpretability, and regulatory considerations must be addressed to realize the full potential of AI in vaccine development. Integrating emerging technologies, such as single-cell omics and synthetic biology, promises to enhance vaccine design precision and scalability. This review underscores the transformative impact of AI on vaccine development and highlights the need for interdisciplinary collaborations and regulatory harmonization to accelerate the delivery of safe and effective vaccines against infectious diseases.

Genome-level therapeutic targets identification and chimeric Vaccine designing against the Blastomyces dermatitidis

Blastomyces dermatitidis is a thermally dimorphic fungus that can cause serious and sometimes fatal infections, including blastomycosis. After spore inhalation, a pulmonary infection develops, which can be asymptomatic and have lethal effects, such as acute respiratory distress syndrome. Its most common extra-pulmonary sites are the central nervous system, bones, skin, and genito-urinary systems. Currently, no vaccine has been approved by the FDA to prevent this infection. In the study, a peptide-based vaccine was developed against blastomycosis by using subtractive proteomics and reverse vaccinology approaches. It focuses on mining the whole genome of B. dermatitidis, identifying potential therapeutic targets, and pinpointing potential epitopes for both B- and T-cells that are immunogenic, non-allergenic, non-toxic, and highly antigenic. Multi-epitope constructs were generated by incorporating appropriate linker sequences. A linker (EAAAK) was also added to incorporate an adjuvant sequence to increase immunological potential. The addition of adjuvants and linkers ultimately resulted in the formation of a vaccine construct in which the number of amino acids was 243 and the molecular weight was 26.18 kDa. The designed antigenic and non-allergenic vaccine constructs showed suitable physicochemical properties. The vaccine's structures were predicted, and further analysis verified their interactions with the human TLR-4 receptor through protein-protein docking. Additionally, MD simulation showed a potent interaction between prioritized vaccine-receptor complexes. Immune simulation predicted that the final vaccine injections resulted in significant immune responses for the T- and B-cell immune responses. Moreover, in silico cloning ensured a high expression possibility of the lead vaccine in the E. coli (K12) vector. This study offers an initiative for the development of effective vaccines against B. dermatitidis; however, it is necessary to validate the designed vaccine's immunogenicity experimentally.

Designing a Candidate Multi-Epitope Vaccine against Transmissible Gastroenteritis Virus Based on Immunoinformatic and Molecular Dynamics

Transmissible gastroenteritis virus (TGEV) is an etiological agent of enteric disease that results in high mortality rates in piglets. The economic impact of the virus is considerable, causing significant losses to the pig industry. The development of an efficacious subunit vaccine to provide promising protection against TGEV is of the utmost importance. The viral antigen, spike glycoprotein (S), is widely regarded as one of the most effective antigenic components for vaccine research. In this study, we employed immunoinformatics and molecular dynamics approaches to develop an 'ideal' multi-epitope vaccine. Firstly, the dominant, non-toxic, highly antigenic T (Th, CTL) and B cell epitopes predicted from the TGEV S protein were artificially engineered in tandem to design candidate subunit vaccines. Molecular docking and dynamic simulation results demonstrate that it exhibits robust interactions with toll-like receptor 4 (TLR4). Of particular significance was the finding that the vaccine was capable of triggering an immune response in mammals, as evidenced by the immune simulation results. The humoral aspect is typified by elevated levels of IgG and IgM, whereas the cellular immune aspect is capable of eliciting the robust production of interleukins and cytokines (IFN-γ and IL-2). Furthermore, the adoption of E. coli expression systems for the preparation of vaccines will also result in cost savings. This study offers logical guidelines for the development of a secure and efficacious subunit vaccine against TGEV, in addition to providing a novel theoretical foundation and strategy to prevent associated CoV infections.

Design of a multi-epitope vaccine against goatpox virus using an immunoinformatics approach

Introduction

Goatpox, a severe infectious disease caused by goatpox virus (GTPV), leads to enormous economic losses in the livestock industry. Traditional live attenuated vaccines cause serious side effects and exist a risk of dispersal. Therefore, it is urgent to develop efficient and safer vaccines to prevent and control of GTPV.

Methods

In the present study, we are aimed to design a multi-epitope subunit vaccine against GTPV using an immunoinformatics approach. Various immunodominant cytotoxic T lymphocytes (CTL) epitopes, helper T lymphocytes (HTL) epitopes, and B-cell epitopes from P32, L1R, and 095 proteins of GTPV were screened and liked by the AAY, GPGPG, and KK connectors, respectively. Furthermore, an adjuvant β-defensin was attached to the vaccine's N-terminal using the EAAAK linker to enhance immunogenicity.

Results

The constructed vaccine was soluble, non-allergenic and non-toxic and exhibited high levels of antigenicity and immunogenicity. The vaccine's 3D structure was subsequently predicted, refined and validated, resulting in an optimized model with a Z-value of -3.4. Molecular docking results demonstrated that the vaccine had strong binding affinity with TLR2(-27.25 kcal/mol), TLR3(-39.84 kcal/mol), and TLR4(-59.42 kcal/mol). Molecular dynamics simulation results indicated that docked vaccine-TLR complexes were stable. Immune simulation analysis suggested that the vaccine can induce remarkable increase in antibody titers of IgG and IgM, higher levels of IFN-γ and IL-2.

Conclusion

The designed GTPV multi-epitope vaccine is structurally stable and can induce robust humoral and cellular immune responses, which may be a promising vaccine candidate against GTPV.