Vaccinomics approach for developing multi-epitope peptide pneumococcal vaccine

Development of a broad-spectrum epitope-based vaccine against Streptococcus pneumoniae

Streptococcus pneumoniae (SPN) is a significant pathogen causing pneumonia and meningitis, particularly in vulnerable populations like children and the elderly. Available pneumonia vaccines have limitations since they only cover particular serotypes and have high production costs. The emergence of antibiotic-resistant SPN strains further underscores the need for a new, cost-effective, broad-spectrum vaccine. Two potential vaccine candidates, CbpA and PspA, were identified, and their B-cell, CTL, and HTL epitopes were predicted and connected with suitable linkers, adjivant and PADRE sequence. The vaccine construct was found to be antigenic, non-toxic, non-allergenic, and soluble. The three-dimensional structure of the vaccine candidate was built and validated. Docking analysis of the vaccine candidate by ClusPro demonstrated robust and stable binding interactions between the MEV and toll-like receptor 4 in both humans and animals. The iMOD server and Amber v.22 tool has verified the stability of the docking complexes. GenScript server confirmed the high efficiency of cloning for the construct and in-silico cloning into the pET28a (+) vector using SnapGene, demonstrating successful translation of the epitope region. Immunological responses were shown to be enhanced by the C-IMMSIM server. This study introduced a strong peptide vaccine candidate that has the potential to contribute to the development of a rapid and cost-effective solution for combating SPN. However, experimental verification is necessary to evaluate the vaccine's effectiveness.

Design and in silico analysis of a novel peptide-based multiepitope vaccine against glioblastoma multiforme by targeting tumor-associated macrophage

CD204 is a distinct indicator for tumor-associated macrophages (TAMs) in glioma. Evidence indicates that CD204-positive TAMs are involved in the aggressive behavior of various types of cancers. This study was conducted to develop a new and effective peptide-based vaccine for GBM, specifically targeting CD204. Epitopes of the target protein were identified using NetMHCpan 4.1a, NetMHCIIpan-4.0, and ABCpred tools. Subsequently, the predicted epitopes were evaluated using bioinformatics tools to assess their antigenicity, non-allergenicity, immunogenicity, non-toxicity, and potential to stimulate the production of IL-4 and IFN-γ in HTL epitopes. Selected T-cell epitopes demonstrated a robust binding affinity with the particular HLA alleles. Finally, four HTL epitopes, three CTL epitopes, and two B-cell epitopes, jointed via linkers and adjuvant, were used for the final vaccine construct design. Analysis disclosed that the developed vaccine demonstrated robust antigenic properties while proving soluble, stable, non-toxic, and non-allergenic. Additionally, molecular docking studies and molecular dynamics simulations confirmed a robust correlation between the designed vaccine and TLR-2 and TLR-4 immune receptors. The molecular docking results demonstrated a strong interaction between the newly developed vaccine and TLR2 (-895.1 kcal/mol) and TLR4 (-881.0 kcal/mol) receptors. During the simulation, the vaccine-TLR2 and vaccine-TLR4 complexes exhibited binding energies of -113.41 and -106.61 kcal/mol, respectively. Analysis by different bioinformatic tools indicated the potential of the designed vaccine in immune stimulation and a significant elevation in IgG and IgM antibodies, T-helper cells, T-cytotoxic cells, INF-γ, IL-2, and IL-4. Research findings show that the newly designed multi-epitope vaccine is promising in providing long-term immunity against GBM and offers a promising therapeutic alternative.

In silico design and assessment of a multi-epitope peptide vaccine against multidrug-resistant Acinetobacter baumannii

Acinetobacter baumannii, an opportunistic and notorious nosocomial pathogen, is responsible for many infections affecting soft tissues, skin, lungs, bloodstream, and urinary tract, accounting for more than 722,000 cases annually. Despite the numerous advancements in therapeutic options, no approved vaccine is currently available for this particular bacterium. Consequently, this study focused on creating a rational vaccine design using bioinformatics tools. Three outer membrane proteins with immunogenic potential and properties of good vaccine candidates were used to select epitopes based on good antigenic properties, non-allergenicity, high binding scores, and a low IC50 value. A multi-epitope peptide (MEP) construct was created by sequentially linking the epitopes using suitable linkers. ClusPro 2.0 and C-ImmSim web servers were used for docking analysis with TLR2/TLR4 and immune response respectively. The Ramachandran plot showed an accurate model of the MEP with 100% residue in the most favored and allowed regions. The construct was highly antigenic, stable, non-allergenic, non-toxic, and soluble, and showed maximum population coverage. Additionally, molecular docking demonstrated strong binding between the designed MEP vaccine and TLR2/TLR4. In silico immunological simulations showed significant increases in T-cell and B-cell populations. Finally, codon optimization and in silico cloning were conducted using the pET-28a (+) plasmid vector to evaluate the efficiency of the expression of vaccine peptide in the host organism (Escherichia coli). This designed MEP vaccine would support and accelerate the laboratory work to develop a potent vaccine targeting MDR Acinetobacter baumannii.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00292-3.

In Silico Design of CT26 Polytope and its Surface Display by ClearColi™-Derived Outer Membrane Vesicles as a Cancer Vaccine Candidate Against Colon Carcinoma

Simultaneous targeting of several mutations can be useful in colorectal cancer (CRC) due to its heterogeneity and presence of somatic mutations. As CT26 mutations and expression profiles resemble those of human CRC, we focused on designing a polyepitope vaccine based on CT26 neoepitopes. Due to its low immunogenicity, outer membrane vesicles (rOMV) as an antigen delivery system and adjuvant was applied. Herein, based on previous experimental and our in silico studies four CT26 neoepitopes with the ability to bind MHC-I and MHC-II, TCR, and induce IFN-α production were selected. To increase their immunogenicity, the gp70 and PADRE epitopes were added. The order of the neoepitopes was determined through 3D structure analysis using ProSA, Verify 3D, ERRAT, and Ramachandran servers. The stable peptide-protein docking between the selected epitopes and MHC alleles strengthen our prediction. The CT26 polytope vaccine sequence was fused to the C-terminal of cytolysin A (ClyA) anchor protein and rOMVs were isolated from endotoxin-free ClearColi™ strain. The results of the C-ImmSim server showed that the ClyA-CT26 polytope vaccine could induce T and B cells immunity.The ClyA-CT26 polytope was characterized as a soluble, stable, immunogen, and non-allergen vaccine and optimized for expression in ClearColi™ 24 h after induction with 1 mM IPTG at 25 °C. Western blot analysis confirmed the expression of ClyA-CT26 polytope by ClearColi™ and also on ClearColi™-derived rOMVs. In conclusion, we found that ClearColi™-derived rOMVs with CT26 polytope can deliver CRC neoantigens and induce antitumor immunity, but in vivo immunological studies are needed to confirm vaccine efficacy.

A review on the development of bacterial multi-epitope recombinant protein vaccines via reverse vaccinology

Bacterial vaccines play a crucial role in combating bacterial infectious diseases. Apart from the prevention of disease, bacterial vaccines also help to reduce the mortality rates in infected populations. Advancements in vaccine development technologies have addressed the constraints of traditional vaccine design, providing novel approaches for the development of next-generation vaccines. Advancements in reverse vaccinology, bioinformatics, and comparative proteomics have opened horizons in vaccine development. Specifically, the use of protein structural data in crafting multi-epitope vaccines (MEVs) to target pathogens has become an important research focus in vaccinology. In this review, we focused on describing the methodologies and tools for epitope vaccine development, along with recent progress in this field. Moreover, this article also discusses the challenges in epitope vaccine development, providing insights for the future development of bacterial multi-epitope genetically engineered vaccines.

Design of a Helicobacter pylori multi-epitope vaccine based on immunoinformatics

Helicobacter pylori (H. pylori) is an infectious bacterium that colonizes the stomach of approximately half of the global population. It has been classified as a Group I carcinogen by the World Health Organization due to its strong association with an increased incidence of gastric cancer and exacerbation of stomach diseases. The primary treatment for H. pylori infection currently involves triple or quadruple therapy, primarily consisting of antibiotics and proton pump inhibitors. However, the increasing prevalence of antibiotic resistance poses significant challenges to this approach, underscoring the urgent need for an effective vaccine. In this study, a novel multi-epitope H. pylori vaccine was designed using immunoinformatics. The vaccine contains epitopes derived from nine essential proteins. Software tools and online servers were utilized to predict, evaluate, and analyze the physiochemical properties, secondary and tertiary structures, and immunogenicity of the candidate vaccine. These comprehensive assessments ultimately led to the formulation of an optimal design scheme for the vaccine. Through constructing a novel multi-epitope vaccine based on immunoinformatics, this study offers promising prospects and great potential for the prevention of H. pylori infection. This study also provides a reference strategy to develop multi-epitope vaccines for other pathogens.

In silico designing of novel epitope-based peptide vaccines against HIV-1

The HIV-1 virus has been regarded as a catastrophe for human well-being. The global incidence of HIV-1-infected individuals is increasing. Hence, development of effective immunostimulatory molecules has recently attracted an increasing attention in the field of vaccine design against HIV-1 infection. In this study, we explored the impacts of CD40L and IFN-γ as immunostimulatory adjuvants for our candidate HIV-1 Nef vaccine in human and mouse using immunoinformatics analyses. Overall, 18 IFN-γ-based vaccine constructs (9 constructs in human and 9 constructs in mouse), and 18 CD40L-based vaccine constructs (9 constructs in human and 9 constructs in mouse) were designed. To find immunogenic epitopes, important characteristics of each component (e.g., MHC-I and MHC-II binding, and peptide-MHC-I/MHC-II molecular docking) were determined. Then, the selected epitopes were applied to create multiepitope constructs. Finally, the physicochemical properties, linear and discontinuous B cell epitopes, and molecular interaction between the 3D structure of each construct and CD40, IFN-γ receptor or toll-like receptors (TLRs) were predicted. Our data showed that the full-length CD40L and IFN-γ linked to the N-terminal region of Nef were capable of inducing more effective immune response than multiepitope vaccine constructs. Moreover, molecular docking of the non-allergenic full-length- and epitope-based CD40L and IFN-γ constructs to their cognate receptors, CD40 and IFN-γ receptors, and TLRs 4 and 5 in mouse were more potent than in human. Generally, these findings suggest that the full forms of these adjuvants could be more efficient for improvement of HIV-1 Nef vaccine candidate compared to the designed multiepitope-based constructs.

Advancing molecular modeling and reverse vaccinology in broad-spectrum yellow fever virus vaccine development

Yellow fever outbreaks are prevalent, particularly in endemic regions. Given the lack of an established treatment for this disease, significant attention has been directed toward managing this arbovirus. In response, we developed a multiepitope vaccine designed to elicit an immune response, utilizing advanced immunoinformatic and molecular modeling techniques. To achieve this, we predicted B- and T-cell epitopes using the sequences from all structural (E, prM, and C) and nonstructural proteins of 196 YFV strains. Through comprehensive analysis, we identified 10 cytotoxic T-lymphocyte (CTL) and 5T-helper (Th) epitopes that exhibited overlap with B-lymphocyte epitopes. These epitopes were further evaluated for their affinity to a wide range of human leukocyte antigen system alleles and were rigorously tested for antigenicity, immunogenicity, allergenicity, toxicity, and conservation. These epitopes were linked to an adjuvant ( β -defensin) and to each other using ligands, resulting in a vaccine sequence with appropriate physicochemical properties. The 3D structure of this sequence was created, improved, and quality checked; then it was anchored to the Toll-like receptor. Molecular Dynamics and Quantum Mechanics/Molecular Mechanics simulations were employed to enhance the accuracy of docking calculations, with the QM portion of the simulations carried out utilizing the density functional theory formalism. Moreover, the inoculation model was able to provide an optimal codon sequence that was inserted into the pET-28a( +) vector for in silico cloning and could even stimulate highly relevant humoral and cellular immunological responses. Overall, these results suggest that the designed multi-epitope vaccine can serve as prophylaxis against the yellow fever virus.

Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer

The ideal vaccines for combating diseases that may emerge in the future require more than simply inactivating a few pathogenic strains. This study aims to provide a peptide-based multi-epitope vaccine effective against various severe acute respiratory syndrome coronavirus 2 strains. To design the vaccine, a library of peptides from the spike, nucleocapsid, membrane, and envelope structural proteins of various strains was prepared. Then, the final vaccine structure was optimized using the fully protected epitopes and the fynomer scaffold. Using bioinformatics tools, the antigenicity, allergenicity, toxicity, physicochemical properties, population coverage, and secondary and three-dimensional structures of the vaccine candidate were evaluated. The bioinformatic analyses confirmed the high quality of the vaccine. According to further investigations, this structure is similar to native protein and there is a stable and strong interaction between vaccine and receptors. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli. In conclusion, the fynomer-based vaccine can be considered as a new style in designing and updating vaccines to protect against coronavirus disease.

Peptide nanovaccine in melanoma immunotherapy

Melanoma is an especially fatal neoplasm resistant to traditional treatment. The advancement of novel therapeutical approaches has gained attention in recent years by shedding light on the molecular mechanisms of melanoma tumorigenesis and their powerful interplay with the immune system. The presence of many mutations in melanoma cells results in the production of a varied array of antigens. These antigens can be recognized by the immune system, thereby enabling it to distinguish between tumors and healthy cells. In the context of peptide cancer vaccines, generally, they are designed based on tumor antigens that stimulate immunity through antigen-presenting cells (APCs). As naked peptides often have low potential in eliciting a desirable immune reaction, immunization with such compounds usually necessitates adjuvants and nanocarriers. Actually, nanoparticles (NPs) can provide a robust immune response to peptide-based melanoma vaccines. They improve the directing of peptide vaccines to APCs and induce the secretion of cytokines to get maximum immune response. This review provides an overview of the current knowledge of the utilization of nanotechnology in peptide vaccines emphasizing melanoma, as well as highlights the significance of physicochemical properties in determining the fate of these nanovaccines in vivo, including their drainage to lymph nodes, cellular uptake, and influence on immune responses.

Immunoinformatics-driven In silico vaccine design for Nipah virus (NPV): Integrating machine learning and computational epitope prediction

The Nipah virus (NPV) is a highly lethal virus, known for its significant fatality rate. The virus initially originated in Malaysia in 1998 and later led to outbreaks in nearby countries such as Bangladesh, Singapore, and India. Currently, there are no specific vaccines available for this virus. The current work employed the reverse vaccinology method to conduct a comprehensive analysis of the entire proteome of the NPV virus. The aim was to identify and choose the most promising antigenic proteins that could serve as potential candidates for vaccine development. We have also designed B and T cell epitopes-based vaccine candidate using immunoinformatics approach. We have identified a total of 5 novel Cytotoxic T Lymphocytes (CTL), 5 Helper T Lymphocytes (HTL), and 6 linear B-cell potential antigenic epitopes which are novel and can be used for further vaccine development against Nipah virus. Then we performed the physicochemical properties, antigenic, immunogenic and allergenicity prediction of the designed vaccine candidate against NPV. Further, Computational analysis indicated that these epitopes possessed highly antigenic properties and were capable of interacting with immune receptors. The designed vaccine were then docked with the human immune receptors, namely TLR-2 and TLR-4 showed robust interaction with the immune receptor. Molecular dynamics simulations demonstrated robust binding and good dynamics. After numerous dosages at varied intervals, computational immune response modeling showed that the immunogenic construct might elicit a significant immune response. In conclusion, the immunogenic construct shows promise in providing protection against NPV, However, further experimental validation is required before moving to clinical trials.

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.

Design, development, and assessment of a novel multi-peptide vaccine targeting PspC, PsaA, and PhtD proteins of Streptococcus pneumoniae

Pneumococcus is the top cause of diseases such as pneumonia/meningitis, and of secondary infections after viral respiratory diseases like COVID-19/flu. Pneumococcal protein-based vaccines consisting of proteins with various functions in virulence might provide a qualified alternative for present vaccines. In this project, PspC, PsaA, and PhtD proteins were considered to anticipate B/T-cell epitopes using immunoinformatics to develop 4 multi-peptide constructs (C, A, and D individual constructs, and a fusion construct CAD). We tested whether vaccination with CAD is able to elicit more efficient protective responses against infection than vaccination with the individual constructs or combination of C + A + D. Based on the in silico results, the constructs were predicted to be antigenic, soluble, non-toxic, and stable, and also be able to provoke humoral/cellular immune reactions. When mice were immunized with the fusion protein, significantly higher levels of IgG and cytokines were induced in serum. The IgG in the fusion group had an effective bioactivity for pneumococcus clearance utilizing the complement pathway. The mice immunized with fusion protein were the most protected from challenge. This report for the first time presents a novel multi-peptide vaccine composed of immunodominant peptides of PspC, PsaA, and PhtD. In general, the experimental results supported the immunoinformatics predictions.

Immunoinformatics-based potential multi-peptide vaccine designing against Jamestown Canyon Virus (JCV) capable of eliciting cellular and humoral immune responses

Jamestown Canyon virus (JCV) is a deadly viral infection transmitted by various mosquito species. This mosquito-borne virus belongs to Bunyaviridae family, posing a high public health threat in the in tropical regions of the United States causing encephalitis in humans. Common symptoms of JCV include fever, headache, stiff neck, photophobia, nausea, vomiting, and seizures. Despite the availability of resources, there is currently no vaccine or drug available to combat JCV. The purpose of this study was to develop an epitope-based vaccine using immunoinformatics approaches. The vaccine aimed to be secure, efficient, bio-compatible, and capable of stimulating both innate and adaptive immune responses. In this study, the protein sequence of JCV was obtained from the NCBI database. Various bioinformatics methods, including toxicity evaluation, antigenicity testing, conservancy analysis, and allergenicity assessment were utilized to identify the most promising epitopes. Suitable linkers and adjuvant sequences were used in the design of vaccine construct. 50s ribosomal protein sequence was used as an adjuvant at the N-terminus of the construct. A total of 5 CTL, 5 HTL, and 5 linear B cell epitopes were selected based on non-allergenicity, immunological potential, and antigenicity scores to design a highly immunogenic multi-peptide vaccine construct. Strong interactions between the proposed vaccine and human immune receptors, i.e., TLR-2 and TLR-4, were revealed in a docking study using ClusPro software, suggesting their possible relevance in the immunological response to the vaccine. Immunological and physicochemical properties assessment ensured that the proposed vaccine demonstrated high immunogenicity, solubility and thermostability. Molecular dynamics simulations confirmed the strong binding affinities, as well as dynamic and structural stability of the proposed vaccine. Immune simulation suggest that the vaccine has the potential to effectively stimulate cellular and humoral immune responses to combat JCV infection. Experimental and clinical assays are required to validate the results of this study.

Immunoinformatics Prediction and Protective Efficacy of Vaccine Candidate PiuA-PlyD4 Against Streptococcus Pneumoniae

Purpose

This study was designed to evaluate the immune protective efficacy of the novel Streptococcus pneumoniae (S. pneumoniae) protein vaccine PiuA-PlyD4 through immunoinformatics prediction and in vitro and in vivo experiments.

Methods

In this study, we conducted immunoinformatics prediction and protection analysis on the fusion protein PiuA-PlyD4. The epitope composition of the vaccine was analyzed based on the prediction of B-cell and helper T-cell epitopes. Meanwhile, the molecular docking of PiuA and TLR2/4 was simulated. After immunizing C57BL/6 mice with the prepared vaccine, the biological safety, immunogenicity and conservation were evaluated. By constructing different infection models and from the aspects of adhesion inhibition and cytokines, the protective effect of the fusion protein vaccine PiuA-PlyD4 on S. pneumoniae infection was explored.

Results

PiuA-PlyD4 has abundant B-cell and helper T-cell epitopes and shows a high antigenicity score and structural stability. Molecular docking analysis suggested the potential interaction between PiuA and TLR2/4. The specific antibody titer of fusion protein antiserum was as high as (7.81±2.32) ×105. The protective effect of the immunized mice on nasal and lung colonization was significantly better than that of the control group, and the survival rate against S. pneumoniae infection of serotype 3 reached 50%. Cytokine detection showed that the humoral immune response, Th1, Th2 and Th17 cellular immune pathways were all involved in the process.

Conclusion

The study indicates that PiuA-PlyD4, whether the results are predicted by immunoinformatics or experimentally validated in vivo and in vitro, has good immunogenicity and immunoreactivity and can provide effective protection against S. pneumoniae infection. Therefore, it can be considered a promising prophylactic vaccine candidate for S. pneumoniae.

Use of immunoinformatics and the simulation approach to identify Helicobacter pylori epitopes to design a multi-epitope subunit vaccine for B- and T-cells

BACKGROUND

Helicobacter pylori cause a variety of gastric malignancies, gastric ulcers, and cause erosive diseases. The extreme nature of the bacterium and the implantation of this bacterium protects it against designing a potent drug against it. Therefore, employing a precise and effective design for a more safe and stable antigenic vaccine against this pathogen can effectively control its associated infections. This study, aimed at improving the design of multiple subunit vaccines against H. pylori, adopts multiple immunoinformatics approaches in combination with other computational approaches.

RESULTS

In this regard, 10 HTL, and 11 CTL epitopes were employed based on appropriate adopted MHC binding scores and c-terminal cut-off scores of 4 main selected proteins (APO, LeoA, IceA1, and IceA2). An adjuvant was added to the N end of the vaccine to achieve higher stability. For validation, immunogenicity and sensitization of physicochemical analyses were performed. The vaccine could be antigenic with significantly strong interactions with TOLK-2, 4, 5, and 9 receptors. The designed vaccine was subjected to Gromacs simulation and immune response prediction modelling that confirmed expression and immune-stimulating response efficiency. Besides, the designed vaccine showed better interactions with TLK-9.

CONCLUSIONS

Based on our analyses, although the suggested vaccine could induce a clear response against H. pylori, precise laboratory validation is required to confirm its immunogenicity and safety status.

Recent progress in pneumococcal protein vaccines

Pneumococcal infections continue to pose a significant global health concern, necessitating the development of effective vaccines. Despite the progress shown by pneumococcal polysaccharide and conjugate vaccines, their limited coverage and the emergence of non-vaccine serotypes have highlighted the need for alternative approaches. Protein-based pneumococcal vaccines, targeting conserved surface proteins of Streptococcus pneumoniae, have emerged as a promising strategy. In this review, we provide an overview of the advancements made in the development of pneumococcal protein vaccines. We discuss the key protein vaccine candidates, highlight their vaccination results in animal studies, and explore the challenges and future directions in protein-based pneumococcal vaccine.

The Promising Potential of Reverse Vaccinology-Based Next-Generation Vaccine Development over Conventional Vaccines against Antibiotic-Resistant Bacteria

The clinical use of antibiotics has led to the emergence of multidrug-resistant (MDR) bacteria, leading to the current antibiotic resistance crisis. To address this issue, next-generation vaccines are being developed to prevent antimicrobial resistance caused by MDR bacteria. Traditional vaccine platforms, such as inactivated vaccines (IVs) and live attenuated vaccines (LAVs), were effective in preventing bacterial infections. However, they have shown reduced efficacy against emerging antibiotic-resistant bacteria, including MDR M. tuberculosis. Additionally, the large-scale production of LAVs and IVs requires the growth of live pathogenic microorganisms. A more promising approach for the accelerated development of vaccines against antibiotic-resistant bacteria involves the use of in silico immunoinformatics techniques and reverse vaccinology. The bioinformatics approach can identify highly conserved antigenic targets capable of providing broader protection against emerging drug-resistant bacteria. Multi-epitope vaccines, such as recombinant protein-, DNA-, or mRNA-based vaccines, which incorporate several antigenic targets, offer the potential for accelerated development timelines. This review evaluates the potential of next-generation vaccine development based on the reverse vaccinology approach and highlights the development of safe and immunogenic vaccines through relevant examples from successful preclinical and clinical studies.

The use of RNA-based treatments in the field of cancer immunotherapy

Over the past several decades, mRNA vaccines have evolved from a theoretical concept to a clinical reality. These vaccines offer several advantages over traditional vaccine techniques, including their high potency, rapid development, low-cost manufacturing, and safe administration. However, until recently, concerns over the instability and inefficient distribution of mRNA in vivo have limited their utility. Fortunately, recent technological advancements have mostly resolved these concerns, resulting in the development of numerous mRNA vaccination platforms for infectious diseases and various types of cancer. These platforms have shown promising outcomes in both animal models and humans. This study highlights the potential of mRNA vaccines as a promising alternative approach to conventional vaccine techniques and cancer treatment. This review article aims to provide a thorough and detailed examination of mRNA vaccines, including their mechanisms of action and potential applications in cancer immunotherapy. Additionally, the article will analyze the current state of mRNA vaccine technology and highlight future directions for the development and implementation of this promising vaccine platform as a mainstream therapeutic option. The review will also discuss potential challenges and limitations of mRNA vaccines, such as their stability and in vivo distribution, and suggest ways to overcome these issues. By providing a comprehensive overview and critical analysis of mRNA vaccines, this review aims to contribute to the advancement of this innovative approach to cancer treatment.

Development of a Novel Vaccine Candidates against Cardiobacterium valvarum through Reverse Vaccinology and Computational Approaches

Antibiotic resistance is a major public health concern that has resulted in high healthcare costs, increased mortality, and the emergence of novel bacterial diseases. Cardiobacterium valvarum, an antibiotic-resistant bacterium, is one of the leading causes of heart disease. Currently, there is no licensed vaccination against C. valvarum. In this research, an in silico-based vaccine was designed against C. valvarum using reverse vaccinology, bioinformatics, and immunoinformatics techniques. 4206 core proteins, 2027 nonredundant proteins, and 2179 redundant proteins were predicted. Among nonredundant proteins, 23 proteins were predicted in an extracellular membrane, 30 in the outer membrane, and 62 in the periplasmic membrane region. After applying several subtractive proteomics filters, two proteins, TonB-dependent siderophore receptor and hypothetical protein, were chosen for epitope prediction. In the epitope selection phase, B and T-cellepitopes were analyzed and shortlisted for vaccine design. The vaccine model was designed by linking selected epitopes with GPGPG linkers to avoid flexibility. Furthermore, the vaccine model was linked to cholera toxin B adjuvant to induce a proper immune response. The docking approach was utilized to analyze binding affinity to immune cell receptors. Molecular docking results predicted 12.75 kcal/mol for a Vaccine with MHC-I, 6.89 for a vaccine with MHC-II, and 19.51 vaccine with TLR-4. The MMGBSA estimated -94, -78, and -76 kcal/mol for TLR-4 and vaccine, MHC-I and vaccine, and MHC-II and vaccine, while the MMPBSA analysis estimated -97, -61, and -72 kcal/mol for TLR-4 with the vaccine, MHC-I with vaccine, and MHC-II with a vaccine. Molecular dynamic simulation analysis revealed that the designed vaccine construct has proper stability with immune cell receptors as it is essential for inducing an immune response. In conclusion, we observed that the model vaccine candidate has the potency to induce an immune response in the host. However, the study is designed purely on a computational basis; hence, experimental validation is strongly recommended.

Advances in Computational and Bioinformatics Tools and Databases for Designing and Developing a Multi-Epitope-Based Peptide Vaccine

A vaccine is defined as a biologic preparation that trains the immune system, boosts immunity, and protects against a deadly microbial infection. They have been used for centuries to combat a variety of contagious illnesses by means of subsiding the disease burden as well as eradicating the disease. Since infectious disease pandemics are a recurring global threat, vaccination has emerged as one of the most promising tools to save millions of lives and reduce infection rates. The World Health Organization reports that immunization protects three million individuals annually. Currently, multi-epitope-based peptide vaccines are a unique concept in vaccine formulation. Epitope-based peptide vaccines utilize small fragments of proteins or peptides (parts of the pathogen), called epitopes, that trigger an adequate immune response against a particular pathogen. However, conventional vaccine designing and development techniques are too cumbersome, expensive, and time-consuming. With the recent advancement in bioinformatics, immunoinformatics, and vaccinomics discipline, vaccine science has entered a new era accompanying a modern, impressive, and more realistic paradigm in designing and developing next-generation strong immunogens. In silico designing and developing a safe and novel vaccine construct involves knowledge of reverse vaccinology, various vaccine databases, and high throughput techniques. The computational tools and techniques directly associated with vaccine research are extremely effective, economical, precise, robust, and safe for human use. Many vaccine candidates have entered clinical trials instantly and are available prior to schedule. In light of this, the present article provides researchers with up-to-date information on various approaches, protocols, and databases regarding the computational designing and development of potent multi-epitope-based peptide vaccines that can assist researchers in tailoring vaccines more rapidly and cost-effectively.

An immunoinformatics approach to epitope-based vaccine design against PspA in Streptococcus pneumoniae

BACKGROUND

Streptococcus pneumoniae (SPN) is the agent responsible for causing respiratory diseases, including pneumonia, which causes severe health hazards and child deaths globally. Antibiotics are used to treat SPN as a first-line treatment, but nowadays, SPN is showing resistance to several antibiotics. A vaccine can overcome this global problem by preventing this deadly pathogen. The conventional methods of wet-laboratory vaccine design and development are an intense, lengthy, and costly procedure. In contrast, epitope-based in silico vaccine designing can save time, money, and energy. In this study, pneumococcal surface protein A (PspA), one of the major virulence factors of SPN, is used to design a multi-epitope vaccine.

METHODS

For designing the vaccine, the sequence of PspA was retrieved, and then, phylogenetic analysis was performed. Several CTL epitopes, HTL epitopes, and LBL epitopes of PspA were all predicted by using several bioinformatics tools. After checking the antigenicity, allergenicity, and toxicity scores, the best epitopes were selected for the vaccine construction, and then, physicochemical and immunological properties were analyzed. Subsequently, vaccine 3D structure prediction, refinement, and validation were performed. Molecular docking, molecular dynamic simulation, and immune simulation were performed to ensure the binding between HLA and TLR4. Finally, codon adaptation and in silico cloning were performed to transfer into a suitable vector.

RESULTS

The constructed multi-epitope vaccine showed a strong binding affinity with the receptor molecule TLR4. Analysis of molecular dynamic simulation, C-immune simulation, codon adaptation, and in silico cloning validated that our designed vaccine is a suitable candidate against SPN.

CONCLUSION

The in silico analysis has proven the vaccine as an alternative medication to combat against S. pneumoniae. The designated vaccine can be further tested in the wet lab, and a novel vaccine can be developed.

Structural vaccinology-based design of multi-epitopes vaccine against Streptococcus gordonii and validation using molecular modeling and immune simulation approaches

Streptococcus gordonii is an oral bacterium colonizing the dental cavity and leading to plaque formation. This pervasive colonizer is also the etiologic agent of bacterial endocarditis and has a major role in infective endocarditis. The bacteria reach the heart through oral bleeding, leading to inflammation of cardiovascular valves. Over the past 50 years, it has shown a significant pathogenic role in immunocompromised and neutropenic patients. Since antibiotic resistance has created prophylaxis failure towards infective endocarditis, a potent therapeutic candidate is needed. Therefore, multi-epitopes vaccine offers advantages over the other approaches. Thus, herein, numerous molecular-omics tools were exploited to mine immunogenic peptides, i.e., T-cell and B-cell epitopes, and construct a vaccine sequence. Our findings revealed a total of 24 epitopes, including CTL, HTL, and B-cell are responsible for imparting immune responses, which were combined with the help of different linkers, and MEVC was constructed. Multifactorial validation of the candidate vaccine was performed to minimize the risk factors. The final sequence was docked with TLR2 to validate its conformation compatibility with receptor and long-term interactions stability. Our analysis revealed that the vaccine construct is immunogenic and non-allergenic. The construct also established various contacts with the immune receptor. Finally, the vaccine sequence was reverse-translated, optimized for codon usage, and analyzed for expression in the Escherichia coli K12 strain. Maximum expression was noted with a CAI score of 0.95. In silico immune simulation revealed that the antigen was neutralized on the 3rd day after injection. In conclusion, the current study warrants validation of the vaccine construct both in in vitro and in vivo models for accurate therapeutic intervention.

Pneumococcal Vaccination in Children: A Systematic Review and Meta-Analysis of Cost-Effectiveness Studies

OBJECTIVES

Pneumococcal conjugate vaccines (PCVs) have significantly reduced disease burden caused by Streptococcus pneumoniae, a leading cause of childhood morbidity and mortality globally. This systematic review and meta-analysis aimed to assess the incremental net benefit (INB) of the 13-valent PCV (PCV13) and 10-valent PCV (PCV10) in children.

METHODS

We performed a comprehensive search in several databases published before May 2022. Studies were included if they were cost-effectiveness or cost-utility analyses of PCV13 or PCV10 compared with no vaccination or with each other in children. Various monetary units were converted to purchasing power parity, adjusted to 2021 US dollars. The INBs were calculated and then pooled across studies stratified by country income level, perspective, and consideration of herd effects, using a random-effect model.

RESULTS

Seventy studies were included. When herd effects were considered, PCV13 was cost-effective compared with PCV10 from the payer perspective in both high-income countries (HICs) (INB, $103.94; 95% confidence interval, $75.28-$132.60) and low- and middle-income countries (LMICs) (INB, $53.49; 95% confidence interval, $30.42-$76.55) with statistical significance. These findings were robust across a series of sensitivity analyses. PCV13 was cost-effective compared with no vaccination across perspectives and consideration of herd effects in both HICs and LMICs, whereas findings were less consistent for PCV10.

CONCLUSION

PCVs were generally cost-effective compared with no vaccination in HICs and LMICs. Our study found that PCV13 was cost-effective compared with PCV10 when herd effects were considered from the payer perspective in both HICs and LMICs. The results are sensitive to the consideration of herd effects.

Vaccine development for bacterial pathogens: Advances, challenges and prospects

The advent and use of antimicrobials have played a key role in treating potentially life-threatening infectious diseases, improving health, and saving the lives of millions of people worldwide. However, the emergence of multidrug resistant (MDR) pathogens has been a significant health challenge that has compromised the ability to prevent and treat a wide range of infectious diseases that were once treatable. Vaccines offer potential as a promising alternative to fight against antimicrobial resistance (AMR) infectious diseases. Vaccine technologies include reverse vaccinology, structural biology methods, nucleic acid (DNA and mRNA) vaccines, generalised modules for membrane antigens, bioconjugates/glycoconjugates, nanomaterials and several other emerging technological advances that are offering a potential breakthrough in the development of efficient vaccines against pathogens. This review covers the opportunities and advancements in vaccine discovery and development targeting bacterial pathogens. We reflect on the impact of the already-developed vaccines targeting bacterial pathogens and the potential of those currently under different stages of preclinical and clinical trials. More importantly, we critically and comprehensively analyse the challenges while highlighting the key indices for future vaccine prospects. Finally, the issues and concerns of AMR for low-income countries (sub-Saharan Africa) and the challenges with vaccine integration, discovery and development in this region are critically evaluated.

Immunoinformatics-aided design of a new multi-epitope vaccine adjuvanted with domain 4 of pneumolysin against Streptococcus pneumoniae strains

BACKGROUND

Streptococcus pneumoniae (Pneumococcus) has remained a leading cause of fatal infections such as pneumonia, meningitis, and sepsis. Moreover, this pathogen plays a major role in bacterial co-infection in patients with life-threatening respiratory virus diseases such as influenza and COVID-19. High morbidity and mortality in over one million cases, especially in very young children and the elderly, are the main motivations for pneumococcal vaccine development. Due to the limitations of the currently marketed polysaccharide-based vaccines, non-serotype-specific protein-based vaccines have received wide research interest in recent years. One step further is to identify high antigenic regions within multiple highly-conserved proteins in order to develop peptide vaccines that can affect various stages of pneumococcal infection, providing broader serotype coverage and more effective protection. In this study, immunoinformatics tools were used to design an effective multi-epitope vaccine in order to elicit neutralizing antibodies against multiple strains of pneumococcus.

RESULTS

The B- and T-cell epitopes from highly protective antigens PspA (clades 1-5) and PhtD were predicted and immunodominant peptides were linked to each other with proper linkers. The domain 4 of Ply, as a potential TLR4 agonist adjuvant candidate, was attached to the end of the construct to enhance the immunogenicity of the epitope vaccine. The evaluation of the physicochemical and immunological properties showed that the final construct was stable, soluble, antigenic, and non-allergenic. Furthermore, the protein was found to be acidic and hydrophilic in nature. The protein 3D-structure was built and refined, and the Ramachandran plot, ProSA-web, ERRAT, and Verify3D validated the quality of the final model. Molecular docking analysis showed that the designed construct via Ply domain 4 had a strong interaction with TLR4. The structural stability of the docked complex was confirmed by molecular dynamics. Finally, codon optimization was performed for gene expression in E. coli, followed by in silico cloning in the pET28a(+) vector.

CONCLUSION

The computational analysis of the construct showed acceptable results, however, the suggested vaccine needs to be experimentally verified in laboratory to ensure its safety and immunogenicity.

In-silico design and evaluation of an epitope-based serotype-independent promising vaccine candidate for highly cross-reactive regions of pneumococcal surface protein A

BACKGROUND

The pathogenicity of pneumococcus with high morbidity, mortality, and multi-drug resistance patterns has been increasing. The limited coverage of the licensed polysaccharide-based vaccines and the replacement of the non-vaccine serotypes are the main reasons for producing a successful serotype-independent vaccine. Pneumococcal surface protein A (PspA) is an extremely important virulence factor and an interesting candidate for conserved protein-based pneumococcal vaccine classified into two prominent families containing five clades. PspA family-elicited immunity is clade-dependent, and the level of the PspA cross-reactivity is restricted to the same family.

METHODS

To cover and overcome the clade-dependent immunity of the PspAs in this study, we designed and tested a PspA_1-5c+p vaccine candidate composed of the highest immunodominant coverage of B- and T-cell epitope truncated domain of each clade focusing on two cross-reactive B and C regions of the PspAs. The antigenicity, toxicity, physicochemical properties, 3D structure prediction, stability and flexibility of the designed protein using molecular dynamic (MD) simulation, molecular docking of the construct withHLADRB1*(01:01) and human lactoferrin N-lop, and immune simulation were assessed using immunoinformatics tools. In the experimental section, after intraperitoneal immunization of the mice with Alum adjuvanted recombinant PspA_1-5c+p, we evaluated the immune response, cross-reactivity, and functionality of the Anti-PspA_1-5c+p antibody using ELISA, Opsonophagocytic killing activity, and serum bactericidal assay.

RESULTS

For the first time, this work suggested a novel PspA-based vaccine candidate using immunoinformatics tools. The designed PspA_1-5c+p protein is predicted to be highly antigenic, non-toxic, soluble, stable with low flexibility in MD simulation, and able to stimulate both humoral and cellular immune responses. The designed protein also could interact strongly with HLADRB1*(01:01) and human lactoferrin N-lop in the docking study. Our immunoinformatics predictions were validated using experimental data. Results showed that the anti-PspA_1-5c+p IgG not only had a high titer with strong and same cross-reactivity coverage against all pneumococcal serotypes used but also had high and effective bioactivity for pneumococcal clearance using complement system and phagocytic cells.

CONCLUSION

Our findings elucidated the potential application of the PspA_1-5c+p vaccine candidate as a serotype-independent pneumococcal vaccine with a strong cross-reactivity feature. Further in-vitro and in-vivo investigations against other PspA clades should be performed to confirm the full protection of the PspA_1-5c+p vaccine candidate.

A subunit vaccine against pneumonia: targeting Streptococcus pneumoniae and Klebsiella pneumoniae

Community-acquired pneumonia is primarily caused by Streptococcus pneumoniae and Klebsiella pneumoniae, two pathogens that have high morbidity and mortality rates. This is largely due to bacterial resistance development against current antibiotics and the lack of effective vaccines. The objective of this work was to develop an immunogenic multi-epitope subunit vaccine capable of eliciting a robust immune response against S. pneumoniae and K. pneumoniae. The targeted proteins were the pneumococcal surface proteins (PspA and PspC) and choline-binding protein (CbpA) of S. pneumoniae and the outer membrane proteins (OmpA and OmpW) of K. pneumoniae. Different computational approaches and various immune filters were employed for designing a vaccine. The immunogenicity and safety of the vaccine were evaluated by utilizing many physicochemical and antigenic profiles. To improve structural stability, disulfide engineering was applied to a portion of the vaccine structure with high mobility. Molecular docking was performed to examine the binding affinities and biological interactions at the atomic level between the vaccine and Toll-like receptors (TLR2 and 4). Further, the dynamic stabilities of the vaccine and TLRs complexes were investigated by molecular dynamics simulations. While the immune response induction capability of the vaccine was assessed by the immune simulation study. Vaccine translation and expression efficiency was determined through an in silico cloning experiment utilizing the pET28a(+) plasmid vector. The obtained results revealed that the designed vaccine is structurally stable and able to generate an effective immune response to combat pneumococcal infection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13721-023-00416-3.

Core Proteomics and Immunoinformatic Approaches to Design a Multiepitope Reverse Vaccine Candidate against Chagas Disease

Chagas disease is a tropical ailment indigenous to South America and caused by the protozoan parasite Trypanosoma cruzi, which has serious health consequences globally. Insect vectors transmit the parasite and, due to the lack of vaccine availability and limited treatment options, we implemented an integrated core proteomics analysis to design a reverse vaccine candidate based on immune epitopes for disease control. Firstly, T. cruzi core proteomics was used to identify immunodominant epitopes. Therefore, we designed the vaccine sequence to be non-allergic, antigenic, immunogenic, and to have better solubility. After predicting the tertiary structure, docking and molecular dynamics simulation (MDS) were performed with TLR4, MHC-I, and MHC-II receptors to discover the binding affinities. The final vaccine design demonstrated significant hydrogen bond interactions upon docking with TLR4, MHC-I, and MHC-II receptors. This indicated the efficacy of the vaccine candidate. A server-based immune simulation approach was generated to predict the efficacy. Significant structural compactness and binding stability were found based on MDS. Finally, by optimizing codons on Escherichia coli K12, a high GC content and CAI value were obtained, which were then incorporated into the cloning vector pET2+ (a). Thus, the developed vaccine sequence may be a viable therapy option for Chagas disease.

Computational Based Designing of a Multi-Epitopes Vaccine against Burkholderia mallei

The emergence of antibiotic resistance in bacterial species is a major threat to public health and has resulted in high mortality as well as high health care costs. Burkholderia mallei is one of the etiological agents of health care-associated infections. As no licensed vaccine is available against the pathogen herein, using reverse vaccinology, bioinformatics, and immunoinformatics approaches, a multi-epitope-based vaccine against B. mallei was designed. In completely sequenced proteomes of B. mallei, 18,405 core, 3671 non-redundant, and 14,734 redundant proteins were predicted. Among the 3671 non-redundant proteins, 3 proteins were predicted in the extracellular matrix, 11 were predicted as outer membrane proteins, and 11 proteins were predicted in the periplasmic membrane. Only two proteins, type VI secretion system tube protein (Hcp) and type IV pilus secretin proteins, were selected for epitope prediction. Six epitopes, EAMPERMPAA, RSSPPAAGA, DNRPISINL, RQRFDAHAR, AERERQRFDA, and HARAAQLEPL, were shortlisted for multi-epitopes vaccine design. The predicted epitopes were linked to each other via a specific GPGPG linker and the epitopes peptide was then linked to an adjuvant molecule through an EAAAK linker to make the designed vaccine more immunologically potent. The designed vaccine was also found to have favorable physicochemical properties with a low molecular weight and fewer transmembrane helices. Molecular docking studies revealed vaccine construct stable binding with MHC-I, MHC-II, and TLR-4 with energy scores of −944.1 kcal/mol, −975.5 kcal/mol, and −1067.3 kcal/mol, respectively. Molecular dynamic simulation assay noticed stable dynamics of the docked vaccine-receptors complexes and no drastic changes were observed. Binding free energies estimation revealed a net value of −283.74 kcal/mol for the vaccine-MHC-I complex, −296.88 kcal/mol for the vaccine-MHC-II complex, and −586.38 kcal/mol for the vaccine-TLR-4 complex. These findings validate that the designed vaccine construct showed promising ability in terms of binding to immune receptors and may be capable of eliciting strong immune responses once administered to the host. Further evidence from experimentations in mice models is required to validate real immune protection of the designed vaccine construct against B. mallei.

In silico designing of a novel epitope-based candidate vaccine against Streptococcus pneumoniae with introduction of a new domain of PepO as adjuvant

BACKGROUND

Streptococcus pneumoniae is the leading reason for invasive diseases including pneumonia and meningitis, and also secondary infections following viral respiratory diseases such as flu and COVID-19. Currently, serotype-dependent vaccines, which have several insufficiency and limitations, are the only way to prevent pneumococcal infections. Hence, it is plain to need an alternative effective strategy for prevention of this organism. Protein-based vaccine involving conserved pneumococcal protein antigens with different roles in virulence could provide an eligible alternative to existing vaccines.

METHODS

In this study, PspC, PhtD and PsaA antigens from pneumococcus were taken to account to predict B-cell and helper T-cell epitopes, and epitope-rich regions were chosen to build the construct. To enhance the immunogenicity of the epitope-based vaccine, a truncated N-terminal fragment of pneumococcal endopeptidase O (PepO) was used as a potential TLR2/4 agonist which was identified by molecular docking studies. The ultimate construct was consisted of the chosen epitope-rich regions, along with the adjuvant role (truncated N-PepO) and suitable linkers.

RESULTS

The epitope-based vaccine was assessed as regards physicochemical properties, allergenicity, antigenicity, and toxicity. The 3D structure of the engineered construct was modeled, refined, and validated. Molecular docking and simulation of molecular dynamics (MD) indicated the proper and stable interactions between the vaccine and TLR2/4 throughout the simulation periods.

CONCLUSIONS

For the first time this work presents a novel vaccine consisting of epitopes of PspC, PhtD, and PsaA antigens which is adjuvanted with a new truncated domain of PepO. The computational outcomes revealed that the suggested vaccine could be deemed an efficient therapeutic vaccine for S. pneumoniae; nevertheless, in vitro and in vivo examinations should be performed to prove the potency of the candidate vaccine.

Novel Chimeric Vaccine Candidate Development against Leptotrichia buccalis

The misuse of antibiotics in our daily lives has led to the emergence of antimicrobial resistance. As a result, many antibiotics are becoming ineffective. This phenomenon is linked with high rates of mortality and morbidity. Therefore, new approaches are required to address this major health issue. Leptotrichia buccalis is a Gram-negative, rod-shaped bacterium which normally resides in the oral and vaginal cavities. It is an emerging bacterial pathogen which is developing new antibiotic-resistance mechanisms. No approved vaccine is available against this pathogen, which is a cause for growing concern. In this study, an in silico-based, multi-epitopes vaccine against this pathogen was designed by applying reverse vaccinology and immunoinformatic approaches. Of a total of 2193 predicted proteins, 294 were found to be redundant while 1899 were non-redundant. Among the non-redundant proteins, 6 were predicted to be present in the extracellular region, 12 in the periplasmic region and 23 in the outer-membrane region. Three proteins (trypsin-like peptidase domain-containing protein, sel1 repeat family protein and TrbI/VirB10 family protein) were predicted to be virulent and potential subunit vaccine targets. In the epitopes prediction phase, the three proteins were subjected to B- and T-cell epitope mapping; 19 epitopes were used for vaccine design. The vaccine construct was docked with MHC-I, MHC-II and TLR-4 immune receptors and only the top-ranked complex (based on global energy value) was selected in each case. The selected docked complexes were examined in a molecular dynamic simulation and binding free energies analysis in order to assess their intermolecular stability. It was observed that the vaccine binding mode with receptors was stable and that the system presented stable dynamics. The net binding free energy of complexes was in the range of -300 to -500 kcal/mol, indicating the formation of stable complexes. In conclusion, the data reported herein might help vaccinologists to formulate a chimeric vaccine against the aforementioned target pathogen.

Application of reverse vaccinology to design a multi-epitope subunit vaccine against a new strain of Aeromonas veronii

BACKGROUND

Aeromonas veronii is one of the most common pathogens of freshwater fishes that cause sepsis and ulcers. There are increasing numbers of cases showing that it is a significant zoonotic and aquatic agent. Epidemiological studies have shown that A. veronii virulence and drug tolerance have both increased over the last few years as a result of epidemiological investigations. Cadaverine reverse transporter (CadB) and maltoporin (LamB protein) contribute to the virulence of A. veronii TH0426. TH0426 strain is currently showing severe cases on fish species, and its resistance against therapeutic has been increasing. Despite these devastating complications, there is still no effective cure or vaccine for this strain of A.veronii.

RESULTS

In this regard, an immunoinformatic method was used to generate an epitope-based vaccine against this pathogen. The immunodominant epitopes were identified using the CadB and LamB protein of A. veronii. The final constructed vaccine sequence was developed to be immunogenic, non-allergenic as well as have better solubility. Molecular dynamic simulation revealed significant binding stability and structural compactness. Finally, using Escherichia coli K12 as a model, codon optimization yielded ideal GC content and a higher CAI value, which was then included in the cloning vector pET2+ (a).

CONCLUSION

Altogether, our outcomes imply that the proposed peptide vaccine might be a good option for A. veronii TH0426 prophylaxis.

A multi-epitope vaccine designed against blood-stage of malaria: an immunoinformatic and structural approach

Malaria is a complex disease caused by parasites of the genus Plasmodium and is the leading cause of morbidity and mortality worldwide. The most severe form of malaria disease is caused by Plasmodium falciparum. Thus, a combination of different approaches is needed to control malaria. Resistance to first-line drugs and insecticides, on the other hand, makes the need for an effective vaccination more urgent than ever. Because erythrocyte parasites cause the most clinical symptoms, developing a vaccination for this stage of infection might be highly beneficial. In this research, we employed various bioinformatics methods to create an efficient multi-epitope vaccine that induces antibodies against the blood stage of malaria infection. For this purpose, we selected the malaria PfGARP protein as the target here. The B, HTL epitopes, and epitope conservation were predicted. The predicted epitopes (including 5 B and 5 HTL epitopes) were connected using suitable linkers, and the flagellin molecule was used as an adjuvant to improve its immunogenicity. The final construct vaccine with 414 amino acids long was designed. The vaccine's allergenicity, antigenicity, solubility, physicochemical characteristics, 2D and 3D structure modeling, molecular docking, molecular dynamics simulation, in silico cloning, and immunological simulation were tested. In silico immune simulation results showed significantly elevated IgG1 and IgM and T helper cells, INF γ, IL 2, and B-cell populations after the injection of the designed vaccine. These significant computational analyses indicated that our proposed vaccine candidate might activate suitable immune responses against malaria. However, in vitro and in vivo studies are essential for further validation.

Computer-Aided Multi-Epitope Vaccine Design against Enterobacter xiangfangensis

Antibiotic resistance is a global public health threat and is associated with high mortality due to antibiotics’ inability to treat bacterial infections. Enterobacter xiangfangensis is an emerging antibiotic-resistant bacterial pathogen from the Enterobacter genus and has the ability to acquire resistance to multiple antibiotic classes. Currently, there is no effective vaccine against Enterobacter species. In this study, a chimeric vaccine is designed comprising different epitopes screened from E. xiangfangensis proteomes using immunoinformatic and bioinformatic approaches. In the first phase, six fully sequenced proteomes were investigated by bacterial pan-genome analysis, which revealed that the pathogen consists of 21,996 core proteins, 3785 non-redundant proteins and 18,211 redundant proteins. The non-redundant proteins were considered for the vaccine target prioritization phase where different vaccine filters were applied. By doing so, two proteins; ferrichrome porin (FhuA) and peptidoglycan-associated lipoprotein (Pal) were shortlisted for epitope prediction. Based on properties of antigenicity, allergenicity, water solubility and DRB*0101 binding ability, three epitopes (GPAPTIAAKR, ATKTDTPIEK and RNNGTTAEI) were used in multi-epitope vaccine designing. The designed vaccine construct was analyzed in a docking study with immune cell receptors, which predicted the vaccine’s proper binding with said receptors. Molecular dynamics analysis revealed that the vaccine demonstrated stable binding dynamics, and binding free energy calculations further validated the docking results. In conclusion, these in silico results may help experimentalists in developing a vaccine against E. xiangfangensis in specific and Enterobacter in general.

Use of Integrated Core Proteomics, Immuno-Informatics, and In Silico Approaches to Design a Multiepitope Vaccine against Zoonotic Pathogen Edwardsiella tarda

Multidrug-resistant Edwardsiella tarda has been reported as the main causative agent for massive fish mortality. The pathogen is well-known for causing hemorrhagic septicemia in fish and has been linked to gastrointestinal infections in humans. Formalin-inactivated Edwardsiella vaccination has previously been found to be ineffective in aquaculture species. Therefore, based on E. tarda’s integrated core complete sequenced genomes, the study aimed to design a subunit vaccine based on T and B cell epitopes employing immunoinformatics approach. Initially, the top immunodominant and antigenic epitopes were predicted from the core complete sequenced genomes of the E. tarda genome and designed the vaccine by using linkers and adjuvant. In addition, vaccine 3D structure was predicted followed by refinement, and molecular docking was performed for the analysis of interacting residues between vaccines with TLR5, MHC-I, and MHC-II, respectively. The final vaccine constructs demonstrated strong hydrogen bond interactions. Molecular dynamic simulation of vaccine-TLR5 receptor complex showed a stable structural binding and compactness. Furthermore, E. coli used as a model organism for codon optimization proved optimal GC content and CAI value, which were subsequently cloned in vector pET2+ (a). Overall, the findings of the study imply that the designed epitope vaccine might be a good option for prophylaxis for E. tarda.

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.

Execution and Design of an Anti HPIV-1 Vaccine with Multiple Epitopes Triggering Innate and Adaptive Immune Responses: An Immunoinformatic Approach

Human Parainfluenza Virus (HPIV) Type-1, which is an anti-sense ribonucleic acid (RNA) virus belonging to the paramyxoviridae family, induces upper and lower respiratory tract infections. The infections caused by the HPIV Type-1 virus are usually confined to northwestern regions of America. HPIV-1 causes infections through the virulence of the hemagglutinin-neuraminidase (HN) protein, which plays a key role in the attachment of the viral particle with the host’s receptor cells. To the best of our knowledge, there is no effective antiviral drugs or vaccines being developed to combat the infection caused by HPIV-1. In the current study, a multiple epitope-based vaccine was designed against HPIV-1 by taking the viral HN protein as a probable vaccine candidate. The multiple epitopes were selected in accordance with their allergenicity, antigenicity and toxicity scoring. The determined epitopes of the HN protein were connected simultaneously using specific conjugates along with an adjuvant to construct the subunit vaccine, with an antigenicity score of 0.6406. The constructed vaccine model was docked with various Toll-like Receptors (TLRs) and was computationally cloned in a pET28a (+) vector to analyze the expression of vaccine sequence in the biological system. Immune stimulations carried out by the C-ImmSim Server showed an excellent result of the body’s defense system against the constructed vaccine model. The AllerTop tool predicted that the construct was non-allergen with and without the adjuvant sequence, and the VaxiJen 2.0 with 0.4 threshold predicted that the construct was antigenic, while the Toxinpred predicted that the construct was non-toxic. Protparam results showed that the selected protein was stable with 36.48 instability index (II) scores. The Grand average of Hydropathicity or GRAVY score indicated that the constructed protein was hydrophilic in nature. Aliphatic index values (93.53) confirmed that the construct was thermostable. This integrated computational approach shows that the constructed vaccine model has a potential to combat laryngotracheobronchitis infections caused by HPIV-I.

Vaccinomics to Design a Multi-Epitopes Vaccine for Acinetobacter baumannii

Antibiotic resistance (AR) is the result of microbes’ natural evolution to withstand the action of antibiotics used against them. AR is rising to a high level across the globe, and novel resistant strains are emerging and spreading very fast. Acinetobacter baumannii is a multidrug resistant Gram-negative bacteria, responsible for causing severe nosocomial infections that are treated with several broad spectrum antibiotics: carbapenems, β-lactam, aminoglycosides, tetracycline, gentamicin, impanel, piperacillin, and amikacin. The A. baumannii genome is superplastic to acquire new resistant mechanisms and, as there is no vaccine in the development process for this pathogen, the situation is more worrisome. This study was conducted to identify protective antigens from the core genome of the pathogen. Genomic data of fully sequenced strains of A. baumannii were retrieved from the national center for biotechnological information (NCBI) database and subjected to various genomics, immunoinformatics, proteomics, and biophysical analyses to identify potential vaccine antigens against A. baumannii. By doing so, four outer membrane proteins were prioritized: TonB-dependent siderphore receptor, OmpA family protein, type IV pilus biogenesis stability protein, and OprD family outer membrane porin. Immuoinformatics predicted B-cell and T-cell epitopes from all four proteins. The antigenic epitopes were linked to design a multi-epitopes vaccine construct using GPGPG linkers and adjuvant cholera toxin B subunit to boost the immune responses. A 3D model of the vaccine construct was built, loop refined, and considered for extensive error examination. Disulfide engineering was performed for the stability of the vaccine construct. Blind docking of the vaccine was conducted with host MHC-I, MHC-II, and toll-like receptors 4 (TLR-4) molecules. Molecular dynamic simulation was carried out to understand the vaccine-receptors dynamics and binding stability, as well as to evaluate the presentation of epitopes to the host immune system. Binding energies estimation was achieved to understand intermolecular interaction energies and validate docking and simulation studies. The results suggested that the designed vaccine construct has high potential to induce protective host immune responses and can be a good vaccine candidate for experimental in vivo and in vitro studies.

Designing of a Novel Multi-Antigenic Epitope-Based Vaccine against E. hormaechei: An Intergraded Reverse Vaccinology and Immunoinformatics Approach

Enterobacter hormaechei is involved in multiple hospital-associated infections and is resistant to beta-lactam and tetracycline antibiotics. Due to emerging antibiotics resistance in E. hormaechei and lack of licensed vaccine availability, efforts are required to overcome the antibiotics crisis. In the current research study, a multi-epitope-based vaccine against E. hormaechei was designed using reverse vaccinology and immunoinformatic approaches. A total number of 50 strains were analyzed from which the core proteome was extracted. One extracellular (curlin minor subunit CsgB) and two periplasmic membrane proteins (flagellar basal-body rod protein (FlgF) and flagellar basal body P-ring protein (FlgI) were prioritized for B and T-cell epitope prediction. Only three filtered TPGKMDYTS, GADMTPGKM and RLSAESQAT epitopes were used when designing the vaccine construct. The epitopes were linked via GPGPG linkers and EAAAK linker-linked cholera toxin B-subunit adjuvant was used to enhance the immune stimulation efficacy of the vaccine. Docking studies of the vaccine construct with immune cell receptors revealed better interactions, vital for generating proper immune reactions. Docked complexes of vaccine with MHC-I, MHC-II and Tool-like receptor 4 (TLR-4) reported the lowest binding energy of −594.1 kcal/mol, −706.7 kcal/mol, −787.2 kcal/mol, respectively, and were further subjected to molecular dynamic simulations. Net binding free energy calculations also confirmed that the designed vaccine has a strong binding affinity for immune receptors and thus could be a good vaccine candidate for future experimental investigations.

Designing a novel mRNA vaccine against Vibrio harveyi infection in fish: an immunoinformatics approach

Vibrio harveyi belongs to the family Vibrionaceae of class Gammaproteobacteria. Around 12 Vibrio species can cause gastroenteritis (gastrointestinal illness) in humans. A large number of bacterial particles can be found in the infected cells, which may cause death. Despite these devastating complications, there is still no cure or vaccine for the bacteria. As a result, we used an immunoinformatics approach to develop a multi-epitope vaccine against the most pathogenic hemolysin gene of V. harveyi. The immunodominant T- and B-cell epitopes were identified using the hemolysin protein. We developed a vaccine employing three possible epitopes: cytotoxic T-lymphocytes, helper T-lymphocytes, and linear B-lymphocyte epitopes, after thorough testing. The vaccine was developed to be antigenic, immunogenic, and non-allergenic, as well as have a better solubility. Molecular dynamics simulation revealed significant structural stiffness and binding stability. In addition, the immunological simulation generated by computers revealed that the vaccination might elicit immune reactions Escherichia coli K12 as a model, codon optimization yielded ideal GC content and a higher codon adaptation index value, which was then included in the cloning vector pET2+ (a). Altogether, our experiment implies that the proposed peptide vaccine might be a good option for vibriosis prophylaxis.

Designing of a Recombinant Multi-Epitopes Based Vaccine against Enterococcus mundtii Using Bioinformatics and Immunoinformatics Approaches

Enterococcus species are an emerging group of bacterial pathogens that have a significant role in hospital-associated infections and are associated with higher mortality and morbidity rates. Among these pathogens, Enterococcus mundtii is one of the causative agents of multiple hospital associated infections. Currently, no commercially available licensed vaccine is present, and multi-drug resistant strains of the pathogen are prominent. Due to several limitations of experimental vaccinology, computational vaccine designing proved to be helpful in vaccine designing against several bacterial pathogens. Herein, we designed a multi-epitope-based vaccine against E. mundtii using in silico approaches. After an in-depth analysis of the core genome, three probable antigenic proteins (lytic polysaccharide monooxygenase, siderophore ABC transporter substrate-binding protein, and lytic polysaccharide monooxygenase) were shortlisted for epitope prediction. Among predicted epitopes, ten epitopes-GPADGRIAS, TTINHGGAQA, SERTALSVTT, GDGGNGGGEV, GIKEPDLEK, KQADDRIEA, QAIGGDTSN, EPLDEQTASR, AQWEPQSIEA, QPLKFSDFEL-were selected for multi-epitope vaccine construct designing. The screened B- and T-cell epitopes were joined with each other via specific linkers and linked to the cholera toxin B subunit as an adjuvant to enhance vaccine immune protection efficacy. The designed vaccine construct induced cellular and humoral immune responses. Blind docking with immune cell receptors, followed by molecular dynamic simulation results confirms the good binding potency and stability of the vaccine in providing protection against the pathogen.

Development of peptide vaccine candidate using highly antigenic PE-PGRS family proteins to stimulate the host immune response against Mycobacterium tuberculosis H37Rv: an immuno-informatics approach

Tuberculosis (TB) is a fast spreading; transmissible disease caused by the Mycobacterium tuberculosis (M. tuberculosis). M. tuberculosis has a high death rate in its endemic regions due to a lack of appropriate treatment and preventative measures. We have used a vaccinomics strategy to create an effective multi-epitope vaccine against M. tuberculosis. The antigenic proteins with the highest antigenicity were utilised to predict cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes. CTL and HTL epitopes were covered in 99.97% of the population. Seven epitopes each of CTL, HTL, and LBL were ultimately selected and utilised to develop a multi-epitope vaccine. A vaccine design was developed by combining these epitopes with suitable linkers and LprG adjuvant. The vaccine chimera was revealed to be highly immunogenic, non-allergenic, and non-toxic. To ensure a better expression within the Escherichia coli K12 (E. coli K12) host system, codon adaptation and in silico cloning were accomplished. Following that, various validation studies were conducted, including molecular docking, molecular dynamics simulation, and immunological simulation, all of which indicated that the designed vaccine would be stable in the biological environment and effective against M. tuberculosis infection. The immune simulation revealed higher levels of T-cell and B-cell activity, which corresponded to the actual immune response. Exposure simulations were repeated several times, resulting in increased clonal selection and faster antigen clearance. These results suggest that, if proposed vaccine chimera would test both in-vitro and in-vivo, it could be a viable treatment and preventive strategy for TB.Communicated by Ramaswamy H. Sarma.

Computational Design of a Multi-Epitope Vaccine Against Porphyromonas gingivalis

Porphyromonas gingivalis is a Gram-negative pathogenic bacterium associated with chronic periodontitis. The development of a chimeric peptide-based vaccine targeting this pathogen could be highly beneficial in preventing oral bone loss as well as other severe gum diseases. We applied a computational framework to design a multi-epitope-based vaccine candidate against P. gingivalis. The vaccine comprises epitopes from subunit proteins prioritized from the P. gingivalis reference strain (P. gingivalis ATCC 33277) using several reported vaccine properties. Protein-based subunit vaccines were prioritized through genomics techniques. Epitope prediction was performed using immunoinformatic servers and tools. Molecular modeling approaches were used to build a putative three-dimensional structure of the vaccine to understand its interactions with host immune cells through biophysical techniques such as molecular docking simulation studies and binding free energy methods. Genome subtraction identified 18 vaccine targets: six outer-membrane, nine cytoplasmic membrane-, one periplasmic, and two extracellular proteins. These proteins passed different vaccine checks required for the successful development of a vaccine candidate. The shortlisted proteins were subjected to immunoinformatic analysis to map B-cell derived T-cell epitopes, and antigenic, water-soluble, non-toxic, and good binders of DRB1*0101 were selected. The epitopes were then modeled into a multi-epitope peptide vaccine construct (linked epitopes plus adjuvant) to enhance immunogenicity and effectively engage both innate and adaptive immunity. Further, the molecular docking approach was used to determine the binding conformation of the vaccine to TLR2 innate immune receptor. Molecular dynamics simulations and binding free energy calculations of the vaccine–TLR2 complex were performed to highlight key intermolecular binding energies. Findings of this study will be useful for vaccine developers to design an effective vaccine for chronic periodontitis pathogens, specifically P. gingivalis.

Deciphering the immunogenic T-cell epitopes from spike protein of SARS-CoV-2 concerning the diverse population of India

Scientists are rigorously looking for an efficient vaccine against the current pandemic due to the SARS-CoV-2 virus. The reverse vaccinology approach may provide us with significant therapeutic leads in this direction and further determination of T-cell/B-cell response to antigen. In the present study, we conducted a population coverage analysis referring to the diverse Indian population. From the Immune epitope database (IEDB), HLA- distribution analysis was performed to find the most promiscuous T-cell epitope out of In silico determined epitope of Spike protein from SARS-CoV-2. Epitopes were selected based on their binding affinity with the maximum number of HLA alleles belonging to the highest population coverage rate values for the chosen geographical area in India. 404 cleavage sites within the 1288 amino acids sequence of spike glycoprotein were determined by NetChop proteasomal cleavage prediction suggesting the presence of adequate sites in the protein sequence for cleaving into appropriate epitopes. For population coverage analysis, 179 selected epitopes present the projected population coverage up to 97.45% with 56.16 average hit and 15.07 pc90. 54 epitopes are found with the highest coverage among the Indian population and highly conserved within the given spike RBD domain sequence. Among all the predicted epitopes, 9-mer TRFASVYAW and RFDNPVLPF along with 12-mer LLAGTITSGWTF and VSQPFLMDLEGK epitopes are observed as the best due to their decent docking score and best binding affinity to corresponding HLA alleles during MD simulations. Outcomes from this study could be critical to design a vaccine against SARS-CoV-2 for a different set of populations within the country.Communicated by Ramaswamy H. Sarma.

Peptide-Based Vaccines for Tuberculosis

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. As a result of the coronavirus disease 2019 (COVID-19) pandemic, the global TB mortality rate in 2020 is rising, making TB prevention and control more challenging. Vaccination has been considered the best approach to reduce the TB burden. Unfortunately, BCG, the only TB vaccine currently approved for use, offers some protection against childhood TB but is less effective in adults. Therefore, it is urgent to develop new TB vaccines that are more effective than BCG. Accumulating data indicated that peptides or epitopes play essential roles in bridging innate and adaptive immunity and triggering adaptive immunity. Furthermore, innovations in bioinformatics, immunoinformatics, synthetic technologies, new materials, and transgenic animal models have put wings on the research of peptide-based vaccines for TB. Hence, this review seeks to give an overview of current tools that can be used to design a peptide-based vaccine, the research status of peptide-based vaccines for TB, protein-based bacterial vaccine delivery systems, and animal models for the peptide-based vaccines. These explorations will provide approaches and strategies for developing safer and more effective peptide-based vaccines and contribute to achieving the WHO's End TB Strategy.

Exploring Klebsiella pneumoniae capsule polysaccharide proteins to design multiepitope subunit vaccine to fight against pneumonia

BACKGROUND

Klebsiella pneumoniae is an emerging human pathogen causing neonatal lung disease, catheter-associated infections, and nosocomial outbreaks with high fatality rates. Capsular polysaccharide (CPS) protein plays a major determinant in virulence and is considered as a promising target for vaccine development.

RESEARCH DESIGN AND METHODS

In this study, we used immunoinformatic approaches to design a multi-peptide vaccine against K. pneumonia. The epitopes were selected through several immune filters, such as antigenicity, conservancy, nontoxicity, non-allergenicity, binding affinity to HLA alleles, overlapping epitopes, and peptides having common epitopes.

RESULTS

Finally, a construct comprising 2 B-Cell, 8 CTL, 2 HTL epitopes, along with adjuvant, linkers was designed. Peptide-HLA interaction analysis showed strong binding of these epitopes with several common HLA molecules. The in silico immune simulation and population coverage analysis of the vaccine showed its potential to evoke strong immune responses.. Further, the interaction between vaccine and immune was evaluated by docking and simulation, revealing high affinity and complex stability. Codon adaptation and in silico cloning revealed higher expression of vaccine in E. coli K12 expression system.

CONCLUSIONS

Conclusively, the findings of the present study suggest that the designed novel multi-epitopic vaccine holds potential for further experimental validation against the pathogen.

Designing of a Multi-epitope Vaccine against the Structural Proteins of Marburg Virus Exploiting the Immunoinformatics Approach

Marburg virus disease (MVD) caused by the Marburg virus (MARV) generally appears with flu-like symptoms and leads to severe hemorrhagic fever. It spreads via direct contact with infected individuals or animals. Despite being considered to be less threatening in terms of appearances and the number of infected patients, the high fatality rate of this pathogenic virus is a major concern. Until now, no vaccine has been developed to combat this deadly virus. Therefore, vaccination for this virus is necessary to reduce its mortality. Our current investigation focuses on the design and formulation of a multi-epitope vaccine based on the structural proteins of MARV employing immunoinformatics approaches. The screening of potential T-cell and B-cell epitopes from the seven structural proteins of MARV was carried out through specific selection parameters. Afterward, we compiled the shortlisted epitopes by attaching them to an appropriate adjuvant and linkers. Population coverage analysis, conservancy analysis, and MHC cluster analysis of the shortlisted epitopes were satisfactory. Importantly, physicochemical characteristics, human homology assessment, and structure validation of the vaccine construct delineated convenient outcomes. We implemented disulfide bond engineering to stabilize the tertiary or quaternary interactions. Furthermore, stability and physical movements of the vaccine protein were explored using normal-mode analysis. The immune simulation study of the vaccine complexes also exhibited significant results. Additionally, the protein-protein docking and molecular dynamics simulation of the final construct exhibited a higher affinity toward toll-like receptor-4 (TLR4). From simulation trajectories, multiple descriptors, namely, root mean square deviations (rmsd), radius of gyration (Rg), root mean square fluctuations (RMSF), solvent-accessible surface area (SASA), and hydrogen bonds, have been taken into account to demonstrate the inflexible and rigid nature of receptor molecules and the constructed vaccine. Inclusively, our findings suggested the vaccine constructs' ability to regulate promising immune responses against MARV pathogenesis.