In Silico design and evaluation of a multi-epitope vaccine candidate against Toxoplasma gondii for humans

Bioinformatics-driven design and protective efficacy assessment of a multi-epitope vaccine for Toxoplasma gondii

Introduction Toxoplasma gondii can cause toxoplasmosis. It is an important type of pathogen within the broad category of emerging and re-emerging zoonoses. As an infectious disease featuring a complex multi-host transmission cycle, it poses an increasingly severe threat to global public health. No licensed vaccines are currently available for pets and humans, and thus a novel high-efficiency vaccine is urgently required. Methods Six antigens (GRA1, MIC17A, OWP2, LEA880, LEA870, and a hypothetical protein LEA530) representing different stages of the parasite lifecycle were selected from ToxoDB. T-cell and B-cell epitopes were predicted using immunoinformatics tools and screened based on antigenicity, allergenicity, and toxicity. The multi-epitope peptide (MEP1) was evaluated using molecular docking with Toll-like receptor 4 (TLR4) and immune simulation. The optimized sequence was expressed in HEK293T cells as a recombinant plasmid (MEP1-pcDNA3.1) and further evaluated in BALB/c mice. Results MEP1 contained 13 cytotoxic T lymphocyte epitopes, 16 helper T lymphocyte epitopes, and 12 B-cell epitopes, with a length of 732 amino acids and a predicted molecular weight of 75.73 kDa. The antigenicity score was 0.7343, and structural modeling indicated stable secondary and tertiary conformations. Molecular docking suggested strong binding affinity to TLR4. Immune simulation predicted increased B-cell and T-cell responses following vaccination. In vivo, MEP1-pcDNA3.1 immunization significantly increased serum IFN-γ levels (526.81 pg/mL) compared with PBS and pcDNA3.1 controls. Splenocyte proliferation was significantly enhanced in the MEP1-pcDNA3.1 group (SI = 1.58 ± 0.21) compared with PBS (1.10 ± 0.09) and pcDNA3.1 (1.12 ± 0.04) groups (P < 0.01). Following challenge with 5 × 10³ tachyzoites of the PLK strain, survival was markedly prolonged in vaccinated mice, whereas all control mice died within 2–4 days. Conclusion This study demonstrates an immunoinformatics-guided multi-epitope vaccine strategy against T. gondii, supported by in vivo immunogenicity and partial protective efficacy in a mouse model.

An integrated subtractive genomics and immunoinformatics approach for designing a universal multi-epitope vaccine against Brucella spp.

Introduction Brucella spp. are Gram-negative bacteria accountable for brucellosis in immunocompromised individuals and livestock. Due to the slow-growing latent phenotype, current antibiotics are insufficient to treat the infection. The lack of an approved vaccine for human use against this pathogen represents a significant public health concern and indicates the urgent need for novel prophylactic interventions. Methodology In this study, the reverse vaccinology method was combined with pan-genome analysis to identify potential vaccine targets. Proteins have been screened for antigenicity, solubility, immunogenicity, and subcellular localization. B cell and T cell epitopes exhibiting high immunogenicity and solubility have been identified. Multi-epitope vaccine constructs have been evaluated and further analyzed depending on their physicochemical properties. Molecular docking, conformational dynamics, in silico cloning, and immune simulations were conducted to identify the optimal vaccine candidate. Results Four proteins, trigger factor, outer membrane protein assembly factor BamA, urease subunit beta (UreB), and urease subunit alpha (UreC1) were considered for potential vaccine targets. A total of 26 B cell and 97 T cell epitopes with notable immunogenicity and solubility have been shortlisted. Twelve multi-epitope vaccine constructs were generated, among which Vc7 has been chosen based on structural and physicochemical properties. Molecular docking analysis revealed a good correlation with 2FSE and 2Z65, which were further analyzed to reveal that Vc7 exhibited stronger binding affinity (−135.24 kcal/mol) towards 2FSE, mediated by hydrophobic contacts, salt bridges, and intermolecular hydrogen bonds, making it the ideal vaccine complex and validated through a 150 ns molecular dynamics simulation. In silico cloning established construct compatibility, and immune simulation confirmed Vc7’s potential to elicit T cell, B cell, antibody, and cytokine-mediated responses. Conclusion Vc7 has been identified as a structurally stable and highly immunogenic construct, suggesting its potential as a universal multi-epitope vaccine candidate for the prevention of brucellosis.

High-throughput in silico multi-epitope reverse vaccine design against hydatidosis

The Middle East is a significant hotspot for human hydatidosis caused by Echinococcus granulosus, a complex multi-stage pathogen exhibiting antigenic variation with diverse epitopes. Multi-epitope vaccines, designed using immunoinformatics, represent a promising approach to effectively control this challenging parasite. A total of 1150 secreted, non-toxic, antigenic proteins were obtained from database and analyzed for their immunogenic potential, leading to the identification of 1024 CTL, 80 HTL, and 172 LBL prioritized epitopes, which were then ranked and clustered to prefer the most immunogenicity epitopes to include in novel vaccine construct. The chosen Construct (Con2) was modified for dual-plasmid insertion, facilitating the expression of three different vaccine constructs which were predicted by C-ImmSim to stimulate robust IFN-γ/IL-2 production and enhance IgM/IgG antibody secretion. Utilizing in silico, next-generation vaccine design, we propose several vaccine candidates that warrant further validation through in vitro laboratory testing and in vivo studies to assess their immunological efficacy.

Integrative immunoinformatics and structural modeling for the rational design of a multi-epitope vaccine candidate against human cytomegalovirus

Human cytomegalovirus (CMV) is a globally widespread pathogen associated with significant morbidity in immunocompromised individuals. Despite its clinical importance, no licensed vaccine is currently available. This study aimed to design a rational multi-epitope vaccine candidate targeting CMV using an integrative approach combining immunoinformatics and structural biology. Viral proteins were screened to identify epitopes with high affinity for B cells, cytotoxic T cells (CTLs), and helper T cells (HTLs) using the Immune Epitope Database (IEDB). Selected epitopes were filtered according to their antigenicity and toxicity and then assembled into a chimeric construct incorporating an immunostimulatory adjuvant. The designed vaccine was evaluated for its physicochemical properties, validated by Ramchandran and ERRAT analyses. Molecular modeling demonstrated strong and stable interactions with key innate immunity receptors, including TLR7 and TLR9, interactions confirmed by molecular dynamics simulations. In silico immune simulation predicted a robust and durable immune response, characterized by high levels of IgM and IgG, as well as significant activation of CD4 + and CD8 + lymphocytes and innate immunity components. These results highlight the potential of the proposed multi-epitope construct as a promising vaccine candidate against HCMV. However, experimental validation is essential to confirm its immunogenicity, safety, and translational applicability.

Integrative reverse vaccinology and computational modeling for the rational design of a broadly immunogenic multi-epitope vaccine against Marburg virus infection.

Immuno-informatics strategy for designing and development of a multi-epitope chimeric vaccine for livestock against Taenia infections

The computationally designed vaccine meets all essential criteria and has shown immense potential to be an effective vaccine through in silico analysis, however, additional In-vitro and In-vivo validations are imperative.