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

Epitopes screening and vaccine molecular design of PEDV S protein based on immunoinformatics

Porcine epidemic diarrhea virus (PEDV) is a serious disease that poses a significant threat to the pig industry. This study focused on analyzing the Spike protein of PEDV, which harbors crucial antigenic determinants, in identifying dominant epitopes. Immunoinformatics tools were used to screen for B-cell, CD4+ and CD8+ predominance epitopes. These epitopes were then connected to the N-terminal of ferritin to form a self-assembled nanoparticle vaccine. Various physical and chemical properties of the candidate vaccine were analyzed, including secondary structure prediction, tertiary structure modeling, molecular docking, immune response simulation and computer cloning. The results demonstrated that the candidate vaccine was antigenic, soluble, stable, non-allergic, and formed a stable complex with the target receptor TLR-3. Immune simulation analysis showed that the candidate vaccine effectively stimulated both cellular and humoral reactions, leading to increased related cytokines production. Furthermore, efficient and stable expression of the candidate vaccine was achieved through reverse translation in the Escherichia coli K12 expression system following codon optimization and in silico cloning. The developed nanoparticle candidate vaccine in this study holds promise as an effective PEDV vaccine candidate, offering a new approach for the research, development and improvement of vaccines targeting porcine enteric diarrhea coronavirus.

A novel multi-epitope peptide vaccine targeting immunogenic antigens of Ebola and monkeypox viruses with potential of immune responses provocation in silico

The emergence or reemergence of monkeypox (Mpox) and Ebola virus (EBOV) agents causing zoonotic diseases remains a huge threat to human health. Our study aimed at designing a multi-epitope vaccine (MEV) candidate to target both the Mpox and EBOV agents using immunoinformatics tools. Viral protein sequences were retrieved, and potential nonallergenic, nontoxic, and antigenic epitopes were obtained. Next, cytotoxic and helper T-cell (CTL and HTL, respectively) and B-cell (BCL) epitopes were predicted, and those potential epitopes were fused utilizing proper linkers. The in silico cloning and expression processes were implemented using Escherichia coli K12. The immune responses were prognosticated using the C-ImmSim server. The MEV construct (29.53 kDa) included four BCL, two CTL, and four HTL epitopes and adjuvant. The MEV traits were pertinent in terms of antigenicity, non-allergenicity, nontoxicity, physicochemical characters, and stability. The MEV candidate was also highly expressed in E. coli K12. The strong affinity of MEV-TLR3 was confirmed using molecular docking and molecular dynamics simulation analyses. Immune simulation analyses unraveled durable activation and responses of cellular and humoral arms alongside innate immune responses. The designed MEV candidate demonstrated appropriate traits and was promising in the prediction of immune responses against both Mpox and EBOV agents. Further experimental assessments of the MEV are required to verify its efficacy.

Development of a novel multi-epitope vaccine for brucellosis prevention

Brucellosis, a zoonotic disease caused by Brucella, presents a significant threat to both animal and human health. In animals, the disease can lead to infertility, miscarriage, and high fever, while in humans, symptoms may include recurrent fever, fatigue, sweating, hepatosplenomegaly, and joint and muscle pain following infection. Treatment often involves long-term antibiotic therapy, placing a substantial psychological and financial burden on patients. While vaccination is crucial for prevention, current animal vaccines have drawbacks such as residual virulence, and a safe and effective human vaccine is lacking. Hence, the development of a vaccine for brucellosis is imperative. In this study, we utilized bioinformatics methods to design a multi-epitope vaccine targeting Brucella. Targeting Heme transporter BhuA and polysaccharide export protein, we identified antigenic epitopes, including six cytotoxic T lymphocyte (CTL) dominant epitopes, six helper T lymphocyte (HTL) dominant epitopes, one conformation B cell dominant epitope, and three linear B cell dominant epitopes. By linking these epitopes with appropriate linkers and incorporating a Toll-like receptor (TLR) agonist (human beta-defensin-2) and an auxiliary peptide (Pan HLA-DR epitopes), we constructed the multi-epitope vaccine (MEV). The MEV demonstrated high antigenicity, non-toxicity, non-allergenicity, non-human homology, stability, and solubility. Molecular docking analysis and molecular dynamics simulations confirmed the interaction and stability of the MEV with receptors (MHCI, MHCII, TLR4). Codon optimization and in silico cloning validated the translation efficiency and successful expression of MEV in Escherichia coli. Immunological simulations further demonstrated the efficacy of MEV in inducing robust immune responses. In conclusion, our findings suggest that the engineered MEVs have the potential to stimulate both humoral and cellular immune responses, offering valuable insights for the future development of safe and efficient Brucella vaccines.

Designing multi-epitope vaccine against human cytomegalovirus integrating pan-genome and reverse vaccinology pipelines

Human cytomegalovirus (HCMV) is accountable for high morbidity in neonates and immunosuppressed individuals. Due to the high genetic variability of HCMV, current prophylactic measures are insufficient. In this study, we employed a pan-genome and reverse vaccinology approach to screen the target for efficient vaccine candidates. Four proteins, envelope glycoprotein M, UL41A, US23, and US28, were shortlisted based on cellular localization, high solubility, antigenicity, and immunogenicity. A total of 29 B-cell and 44 T-cell highly immunogenic and antigenic epitopes with high global population coverage were finalized using immunoinformatics tools and algorithms. Further, the epitopes that were overlapping among the finalized B-cell and T-cell epitopes were linked with suitable linkers to form various combinations of multi-epitopic vaccine constructs. Among 16 vaccine constructs, Vc12 was selected based on physicochemical and structural properties. The docking and molecular simulations of VC12 were performed, which showed its high binding affinity (-23.35 kcal/mol) towards TLR4 due to intermolecular hydrogen bonds, salt bridges, and hydrophobic interactions, and there were only minimal fluctuations. Furthermore, Vc12 eliciting a good response was checked for its expression in Escherichia coli through in silico cloning and codon optimization, suggesting it to be a potent vaccine candidate.

Integrating pan-genome and reverse vaccinology to design multi-epitope vaccine against Herpes simplex virus type-1

Herpes simplex virus type-1 (HSV-1), the etiological agent of sporadic encephalitis and recurring oral (sometimes genital) infections in humans, affects millions each year. The evolving viral genome reduces susceptibility to existing antivirals and, thus, necessitates new therapeutic strategies. Immunoinformatics strategies have shown promise in designing novel vaccine candidates in the absence of a clinically licensed vaccine to prevent HSV-1. However, to encourage clinical translation, the HSV-1 pan-genome was integrated with the reverse-vaccinology pipeline for rigorous screening of universal vaccine candidates. Viral targets were screened from 104 available complete genomes. Among 364 proteins, envelope glycoprotein D being an outer membrane protein with a high antigenicity score (> 0.4) and solubility (> 0.6) was selected for epitope screening. A total of 17 T-cell and 4 B-cell epitopes with highly antigenic, immunogenic, non-toxic properties and high global population coverage were identified. Furthermore, 8 vaccine constructs were designed using different combinations of epitopes and suitable linkers. VC-8 was identified as the most potential vaccine candidate regarding chemical and structural stability. Molecular docking revealed high interactive affinity (low binding energy: - 56.25 kcal/mol) of VC-8 with the target elicited by firm intermolecular H-bonds, salt-bridges, and hydrophobic interactions, which was validated with simulations. Compatibility of the vaccine candidate to be expressed in pET-29(a) + plasmid was established by in silico cloning studies. Immune simulations confirmed the potential of VC-8 to trigger robust B-cell, T-cell, cytokine, and antibody-mediated responses, thereby suggesting a promising candidate for the future of HSV-1 prevention.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04022-6.

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

INTRODUCTION

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSION

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

A Multi-epitope Vaccine Candidate Against Bolivian Hemorrhagic fever Caused by Machupo Virus

Bolivian hemorrhagic fever (BHF) caused by Machupo virus (MACV) is a New World arenavirus having a reported mortality rate of 25-35%. The BHF starts with fever, followed by headache, and nausea which rapidly progresses to severe hemorrhagic phase within 7 days of disease onset. One of the key promoters for MACV viral entry into the cell followed by viral propagation is performed by the viral glycoprotein (GPC). GPC is post-transcriptionally cleaved into GP1, GP2 and a signal peptide. These proteins all take part in the viral infection in host body. Therefore, GPC protein is an ideal target for developing therapeutics against MACV infection. In this study, GPC protein was considered to design a multi-epitope, multivalent vaccine containing antigenic and immunogenic CTL and HTL epitopes. Different structural validations and physicochemical properties were analysed to validate the vaccine. Docking and molecular dynamics simulations were conducted to understand the interactions of the vaccine with various immune receptors. Finally, the vaccine was codon optimised in silico and along with which immune simulation studies was performed in order to evaluate the vaccine's effectiveness in triggering an efficacious immune response against MACV.

Immunoinformatics, molecular docking and dynamics simulation approaches unveil a multi epitope-based potent peptide vaccine candidate against avian leukosis virus

Lymphoid leukosis is a poultry neoplastic disease caused by avian leukosis virus (ALV) and is characterized by high morbidity and variable mortality rates in chicks. Currently, no effective treatment and vaccination is the only means to control it. This study exploited the immunoinformatics approaches to construct multi-epitope vaccine against ALV. ABCpred and IEDB servers were used to predict B and T lymphocytes epitopes from the viral proteins, respectively. Antigenicity, allergenicity and toxicity of the epitopes were assessed and used to construct the vaccine with suitable adjuvant and linkers. Secondary and tertiary structures of the vaccine were predicted, refined and validated. Structural errors, solubility, stability, immune simulation, dynamic simulation, docking and in silico cloning were also evaluated.The constructed vaccine was hydrophilic, antigenic and non-allergenic. Ramchandran plot showed most of the residues in the favored and additional allowed regions. ProsA server showed no errors in the vaccine structure. Immune simulation showed significant immunoglobulins and cytokines levels. Stability was enhanced by disulfide engineering and molecular dynamic simulation. Docking of the vaccine with chicken's TLR7 revealed competent binding energies.The vaccine was cloned in pET-30a(+) vector and efficiently expressed in Escherichia coli. This study provided a potent peptide vaccine that could assist in tailoring a rapid and cost-effective vaccine that helps to combat ALV. However, experimental validation is required to assess the vaccine efficiency.

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.

Computational exploration and design of a multi-epitopes vaccine construct against Chlamydia psittaci

Chlamydia psittaci is an intracellular pathogen and causes variety of deadly infections in humans. Antibiotics are effective against C. psittaci however high percentage of resistant strains have been reported in recent times. As there is no licensed vaccine, we used in-silico techniques to design a multi-epitopes vaccine against C. psittaci. Following a step-wise protocol, the proteome of available 26 strains was retrieved and filtered for subcellular localized proteins. Five proteins were selected (2 extracellular and 3 outer membrane) and were further analyzed for B-cell and T-cell epitopes prediction. Epitopes were further checked for antigenicity, solubility, stability, toxigenicity, allergenicity, and adhesive properties. Filtered epitopes were linked via linkers and the 3D structure of the designed vaccine construct was predicted. Binding of the designed vaccine with immune receptors: MHC-I, MHC-II, and TLR-4 was analyzed, which resulted in docking energy scores of -4.37 kcal/mol, -0.20 kcal/mol and -22.38 kcal/mol, respectively. Further, the docked complexes showed stable dynamics with a maximum value of vaccine-MHC-I complex (7.8 Å), vaccine-MHC-II complex (6.2 Å) and vaccine-TLR4 complex (5.2 Å). As per the results, the designed vaccine construct reported robust immune responses to protect the host against C. psittaci infections. In the study, the C. psittaci proteomes were considered in pan-genome analysis to extract core proteins. The pan-genome analysis was conducted using bacterial pan-genome analysis (BPGA) software. The core proteins were checked further for non-redundant proteins using a CD-Hit server. Surface localized proteins were investigated using PSORTb v 3.0. The surface proteins were BLASTp against Virulence Factor Data Base (VFDB) to predict virulent factors. Antigenicity prediction of the shortlisted proteins was further done using VAXIGEN v 2.0. The epitope mapping was done using the immune epitope database (IEDB). A multi-epitopes vaccine was built and a 3D structure was generated using 3Dprot online server. The docking analysis of the designed vaccine with immune receptors was carried out using PATCHDOCK. Molecular dynamics and post-simulation analyses were carried out using AMBER v20 to decipher the dynamics stability and intermolecular binding energies of the docked complexes.Communicated by Ramaswamy H. Sarma.

Computational design of a multi-epitope vaccine candidate against Langya henipavirus using surface proteins

In July 2022, Langya henipavirus (LayV) was identified in febrile patients in China. There is currently no approved vaccine against this virus. Therefore, this research aimed to design a multi-epitope vaccine against LayV using reverse vaccinology. The best epitopes were selected from LayV's fusion protein (F) and glycoprotein (G), and a multi-epitope vaccine was designed using these epitopes, adjuvant, and appropriate linkers. The physicochemical properties, antigenicity, allergenicity, toxicity, and solubility of the vaccine were evaluated. The vaccine's secondary and 3D structures were predicted, and molecular docking and molecular dynamics (MD) simulations were used to assess the vaccine's interaction and stability with toll-like receptor 4 (TLR4). Immune simulation, codon optimization, and in silico cloning of the vaccine were also performed. The vaccine candidate showed good physicochemical properties, as well as being antigenic, non-allergenic, and non-toxic, with acceptable solubility. Molecular docking and MD simulation revealed that the vaccine and TLR4 have stable interactions. Furthermore, immunological simulation of the vaccine indicated its ability to elicit immune responses against LayV. The vaccine's increased expression was also ensured using codon optimization. This study's findings were encouraging, but in vitro and in vivo tests are needed to confirm the vaccine's protective effect.Communicated by Ramaswamy H. Sarma.

CCHFV vaccine development, current challenges, limitations, and future directions

Crimean-Congo hemorrhagic fever (CCHF) is the most prevalent tick-borne viral disease affecting humans. The disease is life-threatening in many regions of the developing world, including Africa, Asia, the Middle East, and Southern Europe. In line with the rapidly increasing disease prevalence, various vaccine strategies are under development. Despite a large number of potential vaccine candidates, there are no approved vaccines as of yet. This paper presents a detailed comparative analysis of current efforts to develop vaccines against CCHFV, limitations associated with current efforts, and future research directions.

In silico formulation of a next-generation multiepitope vaccine for use as a prophylactic candidate against Crimean-Congo hemorrhagic fever

BACKGROUND

Crimean-Congo hemorrhagic fever (CCHF) is a widespread disease transmitted to humans and livestock animals through the bite of infected ticks or close contact with infected persons' blood, organs, or other bodily fluids. The virus is responsible for severe viral hemorrhagic fever outbreaks, with a case fatality rate of up to 40%. Despite having the highest fatality rate of the virus, a suitable treatment option or vaccination has not been developed yet. Therefore, this study aimed to formulate a multiepitope vaccine against CCHF through computational vaccine design approaches.

METHODS

The glycoprotein, nucleoprotein, and RNA-dependent RNA polymerase of CCHF were utilized to determine immunodominant T- and B-cell epitopes. Subsequently, an integrative computational vaccinology approach was used to formulate a multi-epitopes vaccine candidate against the virus.

RESULTS

After rigorous assessment, a multiepitope vaccine was constructed, which was antigenic, immunogenic, and non-allergenic with desired physicochemical properties. Molecular dynamics (MD) simulations of the vaccine-receptor complex show strong stability of the vaccine candidates to the targeted immune receptor. Additionally, the immune simulation of the vaccine candidates found that the vaccine could trigger real-life-like immune responses upon administration to humans.

CONCLUSIONS

Finally, we concluded that the formulated multiepitope vaccine candidates would provide excellent prophylactic properties against CCHF.

Identification of B-Cell Epitopes on Capsid Protein Reveals Two Potential Neutralization Mechanisms in Red-Spotted Grouper Nervous Necrosis Virus

Nervous necrosis virus (NNV), a formidable pathogen in marine and freshwater fish, has inflicted enormous financial tolls on the aquaculture industry worldwide. Although capsid protein (CP) is the sole structural protein with pathogenicity and antigenicity, public information on immunodominant regions remains extremely scarce. Here, we employed neutralizing monoclonal antibodies (MAbs) specific for red-spotted grouper NNV (RGNNV) CNPgg2018 in combination with partially overlapping truncated proteins and peptides to identify two minimal B-cell epitope clusters on CP, ¹²²GYVAGFL¹²⁸ and ²²⁷SLYNDSL²³³. Site-directed mutational analysis confirmed residues Y123, G126, and L128 and residues L228, Y229, N230, D231, and L233 as the critical residues responsible for the direct interaction with ligand, respectively. According to homologous modeling and bioinformatic evaluation, ¹²²GYVAGFL¹²⁸ is harbored at the groove of the CP junction with strict conservation among all NNV isolates, while ²²⁷SLYNDSL²³³ is localized in proximity to the tip of a viral protrusion having relatively high evolutionary dynamics in different genotypes. Additionally, ²²⁷SLYNDSL²³³ was shown to be a receptor-binding site, since the corresponding polypeptide could moderately suppress RGNNV multiplication by impeding virion entry. In contrast, ¹²²GYVAGFL¹²⁸ seemed dedicated only to stabilizing viral native conformation and not to assisting initial virus attachment. Altogether, these findings contribute to a novel understanding of the antigenic distribution pattern of NNV and the molecular basis for neutralization, thus advancing the development of biomedical products, especially epitope-based vaccines, against NNV. IMPORTANCE NNV is a common etiological agent associated with neurological virosis in multiple aquatic organisms, causing significant hazards to the host. However, licensed drugs or vaccines to combat NNV infection are very limited to date. Toward the advancement of broad-spectrum prophylaxis and therapeutics against NNV, elucidating the diversity of immunodominant regions within it is undoubtedly essential. Here, we identified two independent B-cell epitopes on NNV CP, followed by the confirmation of critical amino acid residues participating in direct interaction. These two sites were distributed on the shell and protrusion domains of the virion, respectively, and mediated the neutralization exerted by MAbs via drastically distinct mechanisms. Our work promotes new insights into NNV antigenicity as well as neutralization and, more importantly, offers promising targets for the development of antiviral countermeasures.

Design of a multi-epitope protein as a subunit vaccine against lumpy skin disease using an immunoinformatics approach

Lumpy skin disease (LSD) is a transboundary viral disease of cattle that causes substantial economic loss globally. There is no specific treatment and subunit vaccine for this disease to date. Reports of the global spread of this disease are worrisome. We designed a multi-epitope protein using an immunoinformatics approach in this study. We analyzed the proteome of LSDV and found 32 structural/surface proteins. Four of these 32 proteins were predicted as antigenic and non-homologous to bovine and highly conserved in 26 LSDV isolates. The predicted B-cell epitopes and CTL epitopes were stitched together with the help of an AAY linker leading to the formation of a multi-epitope protein. The in silico study revealed that the modeled subunit vaccine candidate and TLR4 receptor interact with high affinity. This interaction was also found to be stable using a molecular dynamics simulation study. Our study demonstrates a leap towards developing a subunit vaccine against LSD.

Computational Design of a Chimeric Vaccine against Plesiomonas shigelloides Using Pan-Genome and Reverse Vaccinology

The swift emergence of antibiotic resistance (AR) in bacterial pathogens to make themselves adaptable to changing environments has become an alarming health issue. To prevent AR infection, many ways can be accomplished such as by decreasing the misuse of antibiotics in human and animal medicine. Among these AR bacterial species, Plesiomonas shigelloides is one of the etiological agents of intestinal infection in humans. It is a gram-negative rod-shaped bacterium that is highly resistant to several classes of antibiotics, and no licensed vaccine against the aforementioned pathogen is available. Hence, substantial efforts are required to screen protective antigens from the pathogen whole genome that can be subjected easily to experimental evaluations. Here, we employed a reverse vaccinology (RV) approach to design a multi-antigenic epitopes based vaccine against P. shigelloides. The complete genomes of P. shigelloides were retrieved from the National Center for Biotechnological Information (NCBI) that on average consist of 5226 proteins. The complete proteomes were subjected to different subtractive proteomics filters, and in the results of that analysis, out of total proteins, 2399 were revealed as non-redundant and 2827 as redundant proteins. The non-redundant proteins were further checked for subcellular localization analysis, in which three were localized in the extracellular matrix, eight were outer membrane, and 13 were found in the periplasmic membrane. All surface localized proteins were found to be virulent. Out of a total of 24 virulent proteins, three proteins (flagellar hook protein (FlgE), hypothetical protein, and TonB-dependent hemoglobin/transferrin/lactoferrin family receptor protein) were considered as potential vaccine targets and subjected to epitopes prediction. The predicted epitopes were further examined for antigenicity, toxicity, and solubility. A total of 10 epitopes were selected (GFKESRAEF, VQVPTEAGQ, KINENGVVV, ENKALSQET, QGYASANDE, RLNPTDSRW, TLDYRLNPT, RVTKKQSDK, GEREGKNRP, RDKKTNQPL). The selected epitopes were linked with each other via specific GPGPG linkers in order to design a multi-epitopes vaccine construct, and linked with cholera toxin B subunit adjuvant to make the designed vaccine construct more efficient in terms of antigenicity. The 3D structure of the vaccine construct was modeled ab initio as no appropriate template was available. Furthermore, molecular docking was carried out to check the interaction affinity of the designed vaccine with major histocompatibility complex (MHC-)I (PDB ID: 1L1Y), MHC-II (1KG0), and toll-like receptor 4 ((TLR-4) (PDB: 4G8A). Molecular dynamic simulation was applied to evaluate the dynamic behavior of vaccine-receptor complexes. Lastly, the binding free energies of the vaccine with receptors were estimated by using MMPB/GBSA methods. All of the aforementioned analyses concluded that the designed vaccine molecule as a good candidate to be used in experimental studies to disclose its immune protective efficacy in animal models.

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.

Designing a Novel Peptide-Based Multi-Epitope Vaccine to Evoke a Robust Immune Response against Pathogenic Multidrug-Resistant Providencia heimbachae

Providencia heimbachae, a Gram -ve, rod-shaped, and opportunistic bacteria isolated from the urine, feces, and skin of humans engage in a wide range of infectious diseases such as urinary tract infection (UTI), gastroenteritis, and bacteremia. This bacterium belongs to the Enterobacteriaceae family and can resist antibiotics known as multidrug-resistant (MDR), and as such can be life-threatening to humans. After retrieving the whole proteomic sequence of P. heimbachae ATCC 35613, a total of 6 non-homologous and pathogenic proteins were separated. These shortlisted proteins were further analyzed for epitope prediction and found to be highly non-toxic, non-allergenic, and antigenic. From these sequences, T-cell and B-cell (major histocompatibility complex class 1 and 2) epitopes were extracted that provided vaccine constructs, which were then analyzed for population coverage to find its reliability worldwide. The population coverage for MHC-1 and MHC-2 was 98.29% and 81.81%, respectively. Structural prediction was confirmed by validation through physiochemical molecular and immunological characteristics to design a stable and effective vaccine that could give positive results when injected into the body of the organism. Due to this approach, computational vaccines could be an effective alternative against pathogenic microbe since they cover a large population with positive results. In the end, the given findings may help the experimental vaccinologists to develop a very potent and effective peptide-based vaccine.

Immunoinformatics-Based Proteome Mining to Develop a Next-Generation Vaccine Design against Borrelia burgdorferi: The Cause of Lyme Borreliosis

The tick-borne bacterium, Borrelia burgdorferi has been implicated in Lyme disease-a deadly infection, formerly confined to North America, but currently widespread across Europe and Asia. Despite the severity of this disease, there is still no human Lyme disease vaccine available. A reliable immunoinformatic approach is urgently needed for designing a therapeutic vaccine against this Gram-negative pathogen. Through this research, we explored the immunodominant proteins of B. burgdorferi and developed a novel and reliable vaccine design with great immunological predictability as well as low contamination and autoimmunity risks. Our initial analysis involved proteome-wide analysis to filter out proteins on the basis of their redundancy, homology to humans, virulence, immunogenicity, and size. Following the selection of proteins, immunoinformatic tools were employed to identify MHC class I & II epitopes and B-cell epitopes, which were subsequently subjected to a rigorous screening procedure. In the final formulation, ten common MHC-I and II epitopes were used together with a suitable adjuvant. We predicted that the final chimeric multi-epitope vaccine could invoke B-cell responses and IFN-gamma-mediated immunity as well as being stable and non-allergenic. The dynamics simulations predicted the stable folding of the designed molecule, after which the molecular docking predicted the stability of the interaction between the potential antigenic epitopes and human immune receptors. Our studies have shown that the designed next-generation vaccine stimulates desirable immune responses, thus potentially providing a viable way to prevent Lyme disease. Nevertheless, further experimental studies in a wet lab are needed in order to validate the results.