Immunoinformatics and molecular docking studies reveal a novel Multi-Epitope peptide vaccine against pneumonia infection

Computational strategies in Klebsiella pneumoniae vaccine design: navigating the landscape of in silico insights

The emergence of multidrug-resistant Klebsiella pneumoniae poses a grave threat to global public health, necessitating urgent strategies for vaccine development. In this context, computational tools have emerged as indispensable assets, offering unprecedented insights into klebsiellal biology and facilitating the design of effective vaccines. Here, a review of the application of computational methods in the development of K. pneumoniae vaccines is presented, elucidating the transformative impact of in silico approaches. Through a systematic exploration of bioinformatics, structural biology, and immunoinformatics techniques, the complex landscape of K. pneumoniae pathogenesis and antigenicity was unravelled. Key insights into virulence factors, antigen discovery, and immune response mechanisms are discussed, highlighting the pivotal role of computational tools in accelerating vaccine development efforts. Advancements in epitope prediction, antigen selection, and vaccine design optimisation are examined, highlighting the potential of in silico approaches to update vaccine development pipelines. Furthermore, challenges and future directions in leveraging computational tools to combat K. pneumoniae are discussed, emphasizing the importance of multidisciplinary collaboration and data integration. This review provides a comprehensive overview of the current state of computational contributions to K. pneumoniae vaccine development, offering insights into innovative strategies for addressing this urgent global health challenge.

Immunoinformatic approach for multi-epitope vaccine design against Staphylococcus aureus based on hemolysin proteins

Staphylococcus aureus is a common bacterium that causes a variety of infections in humans. This microorganism produces several virulence factors, including hemolysins, which contribute to its disease-causing ability. The treatment of S. aureus infections typically involves the use of antibiotics. However, the emergence of antibiotic-resistant strains has become a major concern. Therefore, vaccination against S. aureus has gained attention as an alternative approach. Vaccination has the advantage of stimulating the immune system to produce specific antibodies that can neutralize bacteria and prevent infection. However, developing an effective vaccine against S. aureus has proven to be challenging. This study aimed to use in silico methods to design a multi-epitope vaccine against S. aureus infection based on hemolysin proteins. The designed vaccine contained four B-cell epitopes, four CTL epitopes, and four HTL epitopes, as well as the ribosomal protein L7/L12 and pan-HLA DR-binding epitope, included as adjuvants. Furthermore, the vaccine was non-allergenic and non-toxic with the potential to stimulate the TLR2-, TLR-4, and TLR-6 receptors. The predicted vaccine exhibited a high degree of antigenicity and stability, suggesting potential for further development as a viable vaccine candidate. The population coverage of the vaccine was 94.4 %, indicating potential widespread protection against S. aureus. Overall, these findings provide valuable insights into the design of an effective multi-epitope vaccine against S. aureus infection and pave the way for future experimental validations.

New Insights into the Structure-Activity Relationship of a Novel Immunomodulatory Peptide (HPHPHLSF) from Casein Hydrolyzed by Kluyveromyces marxianus JY-1: Molecular Docking, Interaction Evaluation, and HOMO Analysis

Casein is rich in immunomodulatory peptides. In this study, the release of casein-derived immunomodulatory peptides by Kluyveromyces marxianus JY-1 was investigated for the first time, and an immunosuppressive mouse model was used to evaluate the immunomodulatory activity in the casein hydrolysate. The results showed that the cellular and humoral immunity of immunosuppressed mice could be significantly enhanced by casein hydrolysate. Peptide HPHPHLSF with high immunomodulatory activity from casein hydrolysate was screened using the virtual screening technique. HPHPHLSF possessed strong immunomodulatory activity and significantly upregulated the expression of IL-6, IL-1β, and TNF-α. Next, the interaction of HPHPHLSF with TLR2/4 on the cell surface of RAW264.7 cells was further elucidated by molecular docking and combined analysis of double-stranded small interfering RNA and receptor inhibitors. Further, the results of the highest occupied molecular orbital energy distribution elucidated that the histidine active site C48═O49 played an important role in the immunomodulatory activity of HPHPHLSF. This study confirmed that casein hydrolyzed by K. marxianus JY-1 was a natural immunomodulator, while the structure-activity relationship analysis provided new theoretical and technical support for the targeted preparation and screening of casein-derived immunomodulatory peptides.

Design and characterization of a multi-epitope vaccine targeting Chlamydia abortus using immunoinformatics approach

Chlamydiosis is a widespread ailment affecting humans, livestock, and wildlife, caused by C. abortus, a member of the Chlamydia genus. This disease leads to reproductive disorders in bovines and poses a zoonotic risk, resulting in adverse outcomes such as abortion, stillbirths, weak offspring, endometritis, repeat breeding, and perinatal mortality. However, current chlamydiosis vaccines have limitations in terms of safety, efficacy, and stability, necessitating the development of effective and safe alternatives. In this study, our objective was to design a multi-epitope vaccine (MEV) targeting all strains of C. abortus using bioinformatics and immunoinformatics approaches. We identified highly antigenic and non-allergic proteins (yidC, yajC, secY, CAB503, and CAB746) using VaxiJen and AlgPred tools. Physicochemical analyses and secondary structure predictions confirmed protein stability through ProtParam and SOPMA methods. Furthermore, we employed IEDB-AR, NETMHCpan, and ToxinPred2 tools to predict cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B-cell epitopes, resulting in the identification of conserved epitopes for further analysis. The MEV construct, consisting of 545 amino acids, incorporated the adjuvant Beta defensin-3, along with 9 CTL epitopes and 21 HTL epitopes linked by EAAAK, KK, and AAY linkers. We assessed the safety and immunogenicity of the vaccine through comprehensive evaluations of antigenicity, toxicity, allergenicity, and physicochemical properties. Structural stability and quality were examined using 3D modeling via the ab initio approach with the Robetta platform. Molecular docking analysis explored the compatibility of the MEV with Toll-like receptor 9 (TLR9) using ClusPro, while molecular dynamics simulation with the DESMOND Maestro software predicted the stability and flexibility of the docked complex. Despite promising in silico findings, further wet lab investigations are crucial to validate the safety and efficacy of the MEV. Successful development and validation of this MEV hold significant potential in combatting chlamydiosis in both animal and human populations.Communicated by Ramaswamy H. Sarma.

A broad-spectrum multiepitope vaccine against seasonal influenza A and B viruses in mice

BACKGROUND

Influenza viruses pose a persistent threat to global public health, necessitating the development of innovative and broadly effective vaccines.

METHODS

This study focuses on a multiepitope vaccine (MEV) designed to provide broad-spectrum protection against different influenza viruses. The MEV, containing 19 B-cell linear epitopes, 7 CD4+ T cells, and 11 CD8+ T cells epitopes identified through enzyme-linked immunospot assay (ELISPOT) in influenza viruses infected mice, was administered through a regimen of two doses of DNA vaccine followed by one dose of a protein vaccine in C57BL/6 female mice.

FINDINGS

Upon lethal challenge with both seasonal circulating strains (H1N1, H3N2, BV, and BY) and historical strains (H1N1-PR8 and H3N2-X31), MEV demonstrated substantial protection against different influenza seasonal strains, with partial efficacy against historical strains. Notably, the increased germinal centre B cells and antibody-secreting cells, along with robust T cell immune responses, highlighted the comprehensive immune defence elicited by MEV. Elevated hemagglutinin inhibition antibody was also observed against seasonal circulating and historical strains. Additionally, mice vaccinated with MEV exhibited significantly lower counts of inflammatory cells in the lungs compared to negative control groups.

INTERPRETATION

Our results demonstrated the efficacy of a broad-spectrum MEV against influenza viruses in mice. Conducting long-term studies to evaluate the durability of MEV-induced immune responses and explore its potential application in diverse populations will offer valuable insights for the continued advancement of this promising vaccine.

FUNDING

Funding bodies are described in the Acknowledgments section.

Putative new combination vaccine candidates identified by reverse vaccinology and genomic approaches to control enteric pathogens

OBJECTIVES

The pathogenic microorganisms that cause intestinal diseases can significantly jeopardize people's health. Currently, there are no authorized treatments or vaccinations available to combat the germs responsible for intestinal disease.

METHODS

Using immunoinformatics, we developed a potent multi-epitope Combination (combo) vaccine versus Salmonella and enterohemorrhagic E. coli. The B and T cell epitopes were identified by performing a conservancy assessment, population coverage analysis, physicochemical attributes assessment, and secondary and tertiary structure assessment of the chosen antigenic polypeptide. The selection process for vaccine development included using several bioinformatics tools and approaches to finally choose two linear B-cell epitopes, five CTL epitopes, and two HTL epitopes.

RESULTS

The vaccine had strong immunogenicity, cytokine production, immunological properties, non-toxicity, non-allergenicity, stability, and potential efficacy against infections. Disulfide bonding, codon modification, and computational cloning were also used to enhance the stability and efficacy of expression in the host E. coli. The vaccine's structure has a strong affinity for the TLR4 ligand and is very durable, as shown by molecular docking and molecular modeling. The results of the immunological simulation demonstrated that both B and T cells had a heightened response to the vaccination component.

CONCLUSIONS

The comprehensive in silico analysis reveals that the proposed vaccine will likely elicit a robust immune response against pathogenic bacteria that cause intestinal diseases. Therefore, it is a promising option for further experimental testing.

Novel casein-derived immunomodulatory peptide PFPEVFG: Activity assessment, molecular docking, activity site and mechanism of action

Nowadays, there is still a gap in the knowledge of the structure-activity relationship of immunomodulatory peptides. In this study, PFPEVFG was selected as a peptide with immunomodulatory activity from casein hydrolysate by virtual screening and its immunomodulatory activity was verified by the phagocytosis, proliferation, and expression of cytokines (IL-6, IL-1β, TNF-α) and chemokines (CXCL1, CXCL2) in RAW 264.7 macrophages. Next, molecular docking and double-stranded small interfering RNA (siRNA) mutually verified that the immunomodulatory activity of PFPEVFG was mediated by TLR2/4. Furthermore, the highest occupied molecular orbital (HOMO) analysis showed that the C19 = O20 site with a HOMO contribution of 32.22988% was its active site, and the phenylalanine, where the C19 = O20 site was located, was its active amino acid. Finally, the combination of pathway inhibitors and Western blot revealed that PFPEVFG activated macrophages through the nuclear factor-κB (NF-κB) signaling pathway. In summary, this study provided a new perspective on deeply understanding the structure-activity relationship of casein-derived immunomodulatory peptides, as well as a further theoretical and technological basis for the application of immunomodulatory peptides.

An integrated comparative genomics, subtractive proteomics and immunoinformatics framework for the rational design of a Pan-Salmonella multi-epitope vaccine

Salmonella infections pose a significant global public health concern due to the substantial expenses associated with monitoring, preventing, and treating the infection. In this study, we explored the core proteome of Salmonella to design a multi-epitope vaccine through Subtractive Proteomics and immunoinformatics approaches. A total of 2395 core proteins were curated from 30 different isolates of Salmonella (strain NZ CP014051 was taken as reference). Utilizing the subtractive proteomics approach on the Salmonella core proteome, Curlin major subunit A (CsgA) was selected as the vaccine candidate. csgA is a conserved gene that is related to biofilm formation. Immunodominant B and T cell epitopes from CsgA were predicted using numerous immunoinformatics tools. T lymphocyte epitopes had adequate population coverage and their corresponding MHC alleles showed significant binding scores after peptide-protein based molecular docking. Afterward, a multi-epitope vaccine was constructed with peptide linkers and Human Beta Defensin-2 (as an adjuvant). The vaccine could be highly antigenic, non-toxic, non-allergic, and have suitable physicochemical properties. Additionally, Molecular Dynamics Simulation and Immune Simulation demonstrated that the vaccine can bind with Toll Like Receptor 4 and elicit a robust immune response. Using in vitro, in vivo, and clinical trials, our findings could yield a Pan-Salmonella vaccine that might provide protection against various Salmonella species.

A computational approach to design a multiepitope vaccine against H5N1 virus

Since 1997, highly pathogenic avian influenza viruses, such as H5N1, have been recognized as a possible pandemic hazard to men and the poultry business. The rapid rate of mutation of H5N1 viruses makes the whole process of designing vaccines extremely challenging. Here, we used an in silico approach to design a multi-epitope vaccine against H5N1 influenza A virus using hemagglutinin (HA) and neuraminidase (NA) antigens. B-cell epitopes, Cytotoxic T lymphocyte (CTL) and Helper T lymphocyte (HTL) were predicted via IEDB, NetMHC-4 and NetMHCII-2.3 respectively. Two adjuvants consisting of Human β-defensin-3 (HβD-3) along with pan HLA DR-binding epitope (PADRE) have been chosen to induce more immune response. Linkers including KK, AAY, HEYGAEALERAG, GPGPGPG and double EAAAK were utilized to link epitopes and adjuvants. This construct encodes a protein having 350 amino acids and 38.46 kDa molecular weight. Antigenicity of ~ 1, the allergenicity of non-allergen, toxicity of negative and solubility of appropriate were confirmed through Vaxigen, AllerTOP, ToxDL and DeepSoluE, respectively. The 3D structure of H5N1 was refined and validated with a Z-Score of - 0.87 and an overall Ramachandran of 99.7%. Docking analysis showed H5N1 could interact with TLR7 (docking score of - 374.08 and by 4 hydrogen bonds) and TLR8 (docking score of - 414.39 and by 3 hydrogen bonds). Molecular dynamics simulations results showed RMSD and RMSF of 0.25 nm and 0.2 for H5N1-TLR7 as well as RMSD and RMSF of 0.45 nm and 0.4 for H5N1-TLR8 complexes, respectively. Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) confirmed stability and continuity of interaction between H5N1-TLR7 with the total binding energy of - 29.97 kJ/mol and H5N1-TLR8 with the total binding energy of - 23.9 kJ/mol. Investigating immune response simulation predicted evidence of the ability to stimulate T and B cells of the immunity system that shows the merits of this H5N1 vaccine proposed candidate for clinical trials.

Designing a conjugate vaccine targeting Klebsiella pneumoniae ST258 and ST11

Klebsiella pneumoniae (K. pneumoniae) is a common bacterium that can cause iatrogenic infection. Recently, the rise of antibiotic resistance among K. pneumoniae strains is one key factor associated with antibiotic treatment failure. Hencefore, there is an urgent need for effective K. pneumoniae vaccines. This study aimed to design a multi-epitope vaccine (MEV) candidate against K. pneumonia by utilizing an immunoinformatics method. In this study, we obtained 15 cytotoxic T lymphocyte epitopes, 10 helper T lymphocyte epitopes, 6 linear B-cell epitopes, and 2 conformational B-cell epitopes for further research. Then, we designed a multi-epitope vaccine composed of a total of 743 amino acids, containing the epitopes linked by GPGPG flexible links and an EAAAK linker to the Cholera Toxin Subunit B coadjuvant. The observed properties of the MEV, including non-allergenicity, high antigenicity, and hydrophilicity, are noteworthy. The improvements in the tertiary structure through structural refinement and disulfide bonding, coupled with promising molecular interactions revealed by molecular dynamics simulations with TLR4, position the MEV as a strong candidate for further investigation against K. pneumoniae.

Designing a T-cell epitope-based vaccine using in silico approaches against the Sal k 1 allergen of Salsola kali plant

Allergens originated from Salsola kali (Russian thistle) pollen grains are one of the most important sources of aeroallergens causing pollinosis in desert and semi-desert regions. T-cell epitope-based vaccines (TEV) are more effective among different therapeutic approaches developed to alleviate allergic diseases. The physicochemical properties, and B as well as T cell epitopes of Sal k 1 (a major allergen of S. kali) were predicted using immunoinformatic tools. A TEV was constructed using the linkers EAAAK, GPGPG and the most suitable CD4+ T cell epitopes. RS04 adjuvant was added as a TLR4 agonist to the amino (N) and carboxyl (C) terminus of the TEV protein. The secondary and tertiary structures, solubility, allergenicity, toxicity, stability, physicochemical properties, docking with immune receptors, BLASTp against the human and microbiota proteomes, and in silico cloning of the designed TEV were assessed using immunoinformatic analyses. Two CD4+ T cell epitopes of Sal k1 that had high affinity with different alleles of MHC-II were selected and used in the TEV. The molecular docking of the TEV with HLADRB1, and TLR4 showed TEV strong interactions and stable binding pose to these receptors. Moreover, the codon optimized TEV sequence was cloned between NcoI and XhoI restriction sites of pET-28a(+) expression plasmid. The designed TEV can be used as a promising candidate in allergen-specific immunotherapy against S. kali. Nonetheless, effectiveness of this vaccine should be validated through immunological bioassays.

In silico design of a broad-spectrum multiepitope vaccine against influenza virus

Influenza remains a global health concern due to its potential to cause pandemics as a result of rapidly mutating influenza virus strains. Existing vaccines often struggle to keep up with these rapidly mutating flu viruses. Therefore, the development of a broad-spectrum peptide vaccine that can stimulate an optimal antibody response has emerged as an innovative approach to addressing the influenza threat. In this study, an immunoinformatic approach was employed to rapidly predict immunodominant epitopes from different antigens, aiming to develop an effective multiepitope influenza vaccine (MEV). The immunodominant B-cell linear epitopes of seasonal influenza strains hemagglutinin (HA) and neuraminidase (NA) were predicted using an antibody-peptide microarray, involving a human cohort including vaccinees and infected patients. On the other hand, bioinformatics tools were used to predict immunodominant cytotoxic T-cell (CTL) and helper T-cell (HTL) epitopes. Subsequently, these epitopes were evaluated by various immunoinformatic tools. Epitopes with high antigenicity, high immunogenicity, non-allergenicity, non-toxicity, as well as exemplary conservation were then connected in series with appropriate linkers and adjuvants to construct a broad-spectrum MEV. Moreover, the structural analysis revealed that the MEV candidates exhibited good stability, and the docking results demonstrated their strong affinity to Toll-like receptors 4 (TLR4). In addition, molecular dynamics simulation confirmed the stable interaction between TLR4 and MEVs. Three injections with MEVs showed a high level of B-cell and T-cell immune responses according to the immunological simulations in silico. Furthermore, in-silico cloning was performed, and the results indicated that the MEVs could be produced in considerable quantities in Escherichia coli (E. coli). Based on these findings, it is reasonable to create a broad-spectrum MEV against different subtypes of influenza A and B viruses in silico.

Design of a novel multi-epitopes vaccine against Escherichia fergusonii: a pan-proteome based in- silico approach

Escherichia fergusonii a gram-negative rod-shaped bacterium in the Enterobacteriaceae family, infect humans, causing serious illnesses such as urinary tract infection, cystitis, biliary tract infection, pneumonia, meningitis, hemolytic uremic syndrome, and death. Initially treatable with penicillin, antibiotic misuse led to evolving resistance, including resistance to colistin, a last-resort drug. With no licensed vaccine, the study aimed to design a multi-epitope vaccine against E. fergusonii. The study started with the retrieval of the complete proteome of all known strains and proceeded to filter the surface exposed virulent proteins. Seventeen virulent proteins (4 extracellular, 4 outer membranes, 9 periplasmic) with desirable physicochemical properties were identified from the complete proteome of known strains. Further, these proteins were processed for B-cell and T-cell epitope mapping. Obtained epitopes were evaluated for antigenicity, allergenicity, solubility, MHC-binding, and toxicity and the filtered epitopes were fused by specific linkers and an adjuvant into a vaccine construct. Structure of the vaccine candidate was predicted and refined resulting in 78.1% amino acids in allowed regions and VERIFY3D score of 81%. Vaccine construct was docked with TLR-4, MHC-I, and MHC-II, showing binding energies of -1040.8 kcal/mol, -871.4 kcal/mol, and -1154.6 kcal/mol and maximum interactions. Further, molecular dynamic simulation of the docked complexes was carried out resulting in a significant stable nature of the docked complexes (high B-factor and deformability values, lower Eigen and high variance values) in terms of intermolecular binding conformation and interactions. The vaccine was also reported to stimulate a variety of immunological pathways after administration. In short, the designed vaccine revealed promising predictions about its immune protective potential against E. fergusonii infections however experimental validation is needed to validate the results.

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.

A DNA vaccine (EG95-PT1/2/3-IL2) encoding multi-epitope antigen and IL-2 provokes efficient and long-term immunity to echinococcosis

Echinococcosis is a highly prevalent global zoonosis, and vaccines are required. The commercial vaccine based on a protein-based subunit (EG95), however, is limited by its insufficient cellular immunity, a short protection period, and limited prevention against novel mutant strains. Herein, we applied bioinformatics to develop a DNA vaccine (pEG95-IL2) expressing both multi-epitope-based antigens (EG95-PT1/2/3) and an IL-2 adjuvant to regulate T cell differentiation and memory cell response. EG95-PT1/2/3 was screened with hierarchical structure prediction from the epitope conformation of B cells with high confidence across various species to guarantee immunogenicity. Importantly, cationic arginine-rich lipid nanoparticles (RNP) were utilized as a delivery vehicle to form lipoplexes that had a transfection efficiency of nearly two orders of magnitude greater than that of commercial reagents (Lipofectamine 2000 and polyethyleneimine) with both immune and nonimmune cells (DC2.4 and L929 cells, respectively). RNP/pEG95-IL2 lipoplexes displayed a robust and long-term antigen expression, as well as adjuvant effects during the immunization. Consequently, intramuscular injection of RNP/pEG95-IL2 elicited similar humoral immune responses and significantly greater cellular responses in mice when compared with those of the commercial vaccine. In addition, the inoculation protocol of RNP/pEG95-IL2 with sequential booster further strengthens cellular immunity in comparison with the homologous booster. Those findings provide a promising strategy for improving plasmid vaccine efficacy.

Designing a bioadjuvant candidate vaccine targeting infectious bursal disease virus (IBDV) using viral VP2 fusion and chicken IL-2 antigenic epitope: A bioinformatics approach

Infectious Bursal Disease (IBD) is a common and contagious viral infection that significantly affects the poultry industry. This severely suppresses the immune system in chickens, thereby threating their health and well-being. Vaccination is the most effective strategy for preventing and controlling this infectious agent. The development of VP2-based DNA vaccines combined with biological adjuvants has recently received considerable attention due to their effectiveness in eliciting both humoral and cellular immune responses. In this study, we applied bioinformatics tools to design a fused bioadjuvant candidate vaccine from the full-length sequence of the VP2 protein of IBDV isolated in Iran using the antigenic epitope of chicken IL-2 (chiIL-2). Furthermore, to improve the antigenic epitope presentation and to maintain the three-dimensional structure of the chimeric gene construct, the P2A linker (L) was used to fuse the two fragments. Our in-silico analysis for the design of a candidate vaccine indicates that a continuous sequence of amino acid residues ranging from 105 to 129 in chiIL-2 is proposed as a B cell epitope by epitope prediction servers. The final 3D structure of the VP2-L-chiIL-2105-129 was subjected to physicochemical property determination, molecular dynamic simulation, and antigenic site determination. The results of these analyses led to the development of a stable candidate vaccine that is non-allergenic and has the potential for antigenic surface display potential and adjuvant activity. Finally, it is necessary to investigate the immune response induced by our proposed vaccine in avian hosts. Notably, increasing the immunogenicity of DNA vaccines can be achieved by combining antigenic proteins with molecular adjuvants using the principle of rational vaccine design.

An integrative reverse vaccinology, immunoinformatic, docking and simulation approaches towards designing of multi-epitopes based vaccine against monkeypox virus

Monkeypox is a viral zoonotic disease that is caused by the monkeypox virus (MPXV) and is mainly transmitted to human through close contact with an infected person, animal, or fomites which is contaminated by the virus. In the present research work, reverse vaccinology and several other bioinformatics and immunoinformatics tools were utilized to design multi-epitopes-based vaccine against MPXV by exploring three probable antigenic extracellular proteins: cupin domain-containing protein, ABC transporter ATP-binding protein and DUF192 domain-containing protein. Both cellular and humoral immunity induction were the main concerning qualities of the vaccine construct, hence from selected proteins both B and T-cells epitopes were predicted. Antigenicity, allergenicity, toxicity, and water solubility of the predicted epitopes were assessed and only probable antigenic, non-allergic, non-toxic and good water-soluble epitopes were used in the multi-epitopes vaccine construct. The developed vaccine was found to be potentially effective against MPXV and to be highly immunogenic, cytokine-producing, antigenic, non-toxic, non-allergenic, and stable. Additionally, to increase stability and expression efficiency in the host E. coli, disulfide engineering, codon adaptation, and in silico cloning were employed. Molecular docking and other biophysical approaches were utilized to evaluate the binding mode and dynamic behavior of the vaccine construct with TLR-2, TLR-4, and TLR-8. The outcomes of the immune simulation demonstrated that both B and T cells responded more strongly to the vaccination component. The detailed in silico analysis concludes that the proposed vaccine will induce a strong immune response against MPXV infection, making it a promising target for additional experimental trials.Communicated by Ramaswamy H. Sarma.

Designing of multi-epitope peptide vaccine against Acinetobacter baumannii through combined immunoinformatics and protein interaction-based approaches

Acinetobacter baumannii is one of the major pathogenic ESKAPE bacterium, which is responsible for about more than 722,000 cases in a year, globally. Despite the alarming increase in multidrug resistance, a safe and effective vaccine for Acinetobacter infections is still not available. Hence in the current study, a multiepitope vaccine construct was developed using linear B cell, cytotoxic T cell, and helper T cell epitopes from the antigenic and well-conserved lipopolysaccharide assembly proteins employing systematic immunoinformatics and structural vaccinology strategies. The multi-peptide vaccine was predicted to be highly antigenic, non-allergenic, non-toxic, and cover maximum population coverage worldwide. Further, the vaccine construct was modeled along with adjuvant and peptide linkers and validated to achieve a high-quality three-dimensional structure which was subsequently utilized for cytokine prediction, disulfide engineering, and docking analyses with Toll-like receptor (TLR4). Ramachandran plot showed 98.3% of the residues were located in the most favorable and permitted regions, thereby corroborating the feasibility of the modeled vaccine construct. Molecular dynamics simulation for a 100 ns timeframe further confirmed the stability of the binding vaccine-receptor complex. Finally, in silico cloning and codon adaptation were also performed with the pET28a (+) plasmid vector to determine the efficiency of expression and translation of the vaccine. Immune simulation studies demonstrated that the vaccine could trigger both B and T cell responses and can elicit strong primary, secondary, and tertiary immune responses. The designed multi-peptide subunit vaccine would certainly expedite the experimental approach for the development of a vaccine against A. baumannii infection.

Integrated immunoinformatics and subtractive proteomics approach for multi-epitope vaccine designing to combat S. pneumoniae TIGR4

Streptococcus pneumoniae is one of the major precarious pathogens accountable for over 1.2 million fatalities annually. The key drivers for pneumococcal vaccine development involve high morbidity and mortality in over one million cases, especially in very young children and the elderly. In this study, immunoinformatics was integrated with subtractive proteomics to find antigenic proteins for designing a multi-epitope vaccine against S. pneumoniae. As prospective vaccine targets, the developed pipeline identified two antigenic proteins, i.e., penicillin-binding protein and ATP synthase subunit. Several immunoinformatics and bioinformatics resources were used to forecast T- and B-cell epitopes from specific proteins. By employing a mixture of five cytotoxic T-cell lymphocytes, six helper T-cell lymphocytes, and seven linear B-cell lymphocyte epitopes, a 392 amino acid-long vaccine was designed. To enhance immune responses, the designed vaccine was coupled with a cholera enterotoxin subunit B adjuvant. The designed vaccine was highly antigenic, non-allergenic, and stable for human usage. The stability of the vaccine with toll-like receptor-4 was evaluated by molecular docking and molecular dynamic simulation. In addition, immunological simulation was performed to test its real-world potency. The vaccine codon was then cloned in silico. Overall, this study paves the way for the development of a multi-epitope S. pneumoniae vaccine under laboratory conditions. Furthermore, the current findings warrant for the experimental validation of the final multi-epitope vaccine construct to demonstrate its immunological reinforcing capability and clinical applicability.

An immunoinformatics and structural vaccinology study to design a multi-epitope vaccine against Staphylococcus aureus infection

Staphylococcus aureus has been widely reported to be majorly responsible for causing nosocomial infections worldwide. Due to an increase in antibiotic-resistant strains, the development of an effective vaccine against the bacteria is the most viable alternative. Therefore, in the current work, an effort has been undertaken to develop a novel peptide-based vaccine construct against S aureus that can potentially evoke the B and T cell immune responses. The fibronectin-binding proteins are an attractive target as they play a prominent role in bacterial adherence and host cell invasion and are also well conserved among rapidly mutating pathogens. Therefore, highly immunogenic linear B lymphocytes (LBL), cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL) epitopes were identified from the antigenic fibronectin-binding proteins A and B (FnBPA and FnBPB) of S aureus using immunoinformatics approaches. The selected peptides were confirmed to be non-allergenic, non-toxic, and with a high binding affinity to the majority of human leukocyte antigens (HLA) alleles. Consequently, the multi-peptide vaccine construct was developed by fusing the screened epitopes (three LBL, five CTL, and two HTL) together with the suitable adjuvant and linkers. In addition, the tertiary conformation of the peptide construct was modeled and later docked to the Toll-like receptor 2. Subsequently, a molecular dynamics simulation of 100 ns was employed to corroborate the stability of the designed vaccine-receptor complex. Besides exhibiting high immunogenicity and conformational stability, the developed vaccine was observed to possess wide population coverage of 99.51% worldwide. Additional in vivo and in vitro validation studies would certainly corroborate the designed vaccine construct to have improved prophylactic efficacy against S aureus.

Immunoinformatics aided approach for predicting potent cytotoxic T cell epitopes of respiratory syncytial virus

Respiratory syncytial virus (RSV) is an infectious viral pathogen that causing serious respiratory infection in adults and neonates. The only approved therapies for RSV are the monoclonal antibodies palivizumab and its derivative motavizumab. Both treatments are expensive and require a hospital setting for administration. A vaccine represents a safe, effective and cheaper alternative for preventing RSV infection. In silico prediction methods have proven to be valuable in speeding up the process of vaccine design. In this study, reverse vaccinology methods were used to predict the cytotoxic T lymphocytes (CTL) epitopes from the entire proteome of RSV strain A. From amongst 3402 predicted binders to 12 high frequency alleles from the Immune Epitope Database (IEDB), 567 had positive processing scores while 327 epitopes were predicted to be immunogenic. A thorough examination of the 327 epitopes for possible antigenicity, allergenicity and toxicity resulted in 95 epitopes with desirable properties. A BLASTp analysis revealed 94 unique and non-homologous epitopes that were subjected to molecular docking across the 12 high frequency alleles. The final dataset of 70 epitopes contained 13 experimentally proven and 57 unique epitopes from a total of 11 RSV proteins. From our findings on selected T-cell-specific RSV antigen epitopes, notably the four epitopes confirmed to exhibit stable binding by molecular dynamics. The prediction pipeline used in this study represents an effective way to screen the immunogenic epitopes from other pathogens.Communicated by Ramaswamy H. Sarma.

Immunogenic multi-epitope-based vaccine development to combat cyclosporiasis of immunocompromised patients applying computational biology method

Cyclospora cayetanensis infections, also known as cyclosporiasis, persist to be the prevalent emerging protozoan parasite and an opportunist that causes digestive illness in immunocompromised individuals. In contrast, this causal agent can affect people of all ages, with children and foreigners being the most susceptible populations. For most immunocompetent patients, the disease is self-limiting; in extreme circumstances, this illness can manifest as severe or persistent diarrhea as well as colonize on secondary digestive organs leading to death. According to recent reports, worldwide 3.55% of people are infected by this pathogen, with Asia and Africa being more prevalent. For the treatment, trimethoprim-sulfamethoxazole is the only licensed drug and does not appear to work as well in some patient populations. Therefore, the much more effective strategy to avoid this illness is immunization through the vaccine. This present study uses immunoinformatics for identifying a computational multi-epitope-based peptide vaccine candidate for Cyclospora cayetanensis. Following the review of the literature, a highly efficient, secure, and vaccine complex based on multi-epitopes was designed by utilizing the identified proteins. These selected proteins were then used to predict non-toxic and antigenic HTL-epitopes, B-cell-epitopes, and CTL-epitopes. Ultimately, both a few linkers and an adjuvant were combined to create a vaccine candidate with superior immunological epitopes. Then, to establish the vaccine-TLR complex binding constancy, the TLR receptor and vaccine candidates were placed into the FireDock, PatchDock, and ClusPro servers for molecular docking and iMODS server for molecular-dynamic simulation. Finally, this selected vaccine construct was cloned into Escherichia coli strain-K12; thus, the constructed vaccines against Cyclospora cayetanensiscould improve the host immune response and can be produced experimentally.

Recent trends in next generation immunoinformatics harnessed for universal coronavirus vaccine design

The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has globally devastated public health, the economies of many countries and quality of life universally. The recent emergence of immune-escaped variants and scenario of vaccinated individuals being infected has raised the global concerns about the effectiveness of the current available vaccines in transmission control and disease prevention. Given the high rate mutation of SARS-CoV-2, an efficacious vaccine targeting against multiple variants that contains virus-specific epitopes is desperately needed. An immunoinformatics approach is gaining traction in vaccine design and development due to the significant reduction in time and cost of immunogenicity studies and increasing reliability of the generated results. It can underpin the development of novel therapeutic methods and accelerate the design and production of peptide vaccines for infectious diseases. Structural proteins, particularly spike protein (S), along with other proteins have been studied intensively as promising coronavirus vaccine targets. Numbers of promising online immunological databases, tools and web servers have widely been employed for the design and development of next generation COVID-19 vaccines. This review highlights the role of immunoinformatics in identifying immunogenic peptides as potential vaccine targets, involving databases, and prediction and characterization of epitopes which can be harnessed for designing future coronavirus vaccines.

Designing a Next-Generation Multiepitope-Based Vaccine against Staphylococcus aureus Using Reverse Vaccinology Approaches

Staphylococcus aureus is a human bacterial pathogen that can cause a wide range of symptoms. As virulent and multi-drug-resistant strains of S. aureus have evolved, invasive S. aureus infections in hospitals and the community have become one of the leading causes of mortality and morbidity. The development of novel techniques is therefore necessary to overcome this bacterial infection. Vaccines are an appropriate alternative in this context to control infections. In this study, the collagen-binding protein (CnBP) from S. aureus was chosen as the target antigen, and a series of computational methods were used to find epitopes that may be used in vaccine development in a systematic way. The epitopes were passed through a filtering pipeline that included antigenicity, toxicity, allergenicity, and cytokine inducibility testing, with the objective of identifying epitopes capable of eliciting both T and B cell-mediated immune responses. To improve vaccine immunogenicity, the final epitopes and phenol-soluble modulin α4 adjuvant were fused together using appropriate linkers; as a consequence, a multiepitope vaccine was developed. The chosen T cell epitope ensemble is expected to cover 99.14% of the global human population. Furthermore, docking and dynamics simulations were used to examine the vaccine's interaction with the Toll-like receptor 2 (TLR2), revealing great affinity, consistency, and stability between the two. Overall, the data indicate that the vaccine candidate may be extremely successful, and it will need to be evaluated in experimental systems to confirm its efficiency.

HPV and molecular mimicry in systemic lupus erythematosus and an impact of compiling B-cell epitopes and MHC-class II binding profiles with in silico evidence

Epidemiological link between HPV and SLE is evolving. The possibility of HPV infection-induced molecular mimicry and systemic lupus erythematosus (SLE) was elucidated through detailed in silico analyses. Conserved regions in the structural protein sequences of high-risk HPV types were inferred, and sequence homologies between viral and human peptides were identified to delineate proteins implicated in SLE. B-cell epitopes and MHC-class II binding were compiled using Immune Epitope Database and ProPred II analysis tool. Molecular modeling and molecular dynamics/simulation (MDS) were performed using AutoDock Vina and GROMACS, respectively. Sequence alignment revealed 32 conserved regions, and 27/32 viral peptides showed varying similarities to human peptides, rich in B-cell epitopes with superior accessibility, high hydrophilicity, antigenicity and disposition to bind many class-II HLA alleles. Molecular docking of 13 viral peptides homologous (100%) to human peptides implicated in SLE showed that VIR-PEP1 (QLFNKPYWL) and VIR-PEP2 (DTYRFVTS) exhibited higher binding affinities than corresponding human peptides to SLE predisposing HLA-DRB1 allele. MDS of these peptides showed that the viral peptides had superior folding, compactness, and a higher number of hydrogen bonds than human peptides throughout the simulation period. SASA analysis revealed that the VIR-PEP1&2 fluctuated less frequently than corresponding human peptides. MM-PBSA revealed that the VIR-PEP2 complex exhibited higher binding energy than the human peptide complex. This suggests that highly conserved structural peptides of high-risk HPV types homologous to human peptides could compete and bind avidly to the HLA allele associated with SLE and predispose HPV-infected individuals to SLE through molecular mimicry.Communicated by Ramaswamy H. Sarma.

Integration of immunoinformatics and cheminformatics to design and evaluate a multitope vaccine against Klebsiella pneumoniae and Pseudomonas aeruginosa coinfection

Introduction: Klebsiella pneumoniae (K. pneumoniae) and Pseudomonas aeruginosa (P. aeruginosa) are the most common Gram-negative bacteria associated with pneumonia and coinfecting the same patient. Despite their high virulence, there is no effective vaccine against them. Methods: In the current study, the screening of several proteins from both pathogens highlighted FepA and OmpK35 for K. pneumonia in addition to HasR and OprF from P. aeruginosa as promising candidates for epitope mapping. Those four proteins were linked to form a multitope vaccine, that was formulated with a suitable adjuvant, and PADRE peptides to finalize the multitope vaccine construct. The final vaccine's physicochemical features, antigenicity, toxicity, allergenicity, and solubility were evaluated for use in humans. Results: The output of the computational analysis revealed that the designed multitope construct has passed these assessments with satisfactory scores where, as the last stage, we performed a molecular docking study between the potential vaccine construct and K. pneumonia associated immune receptors, TLR4 and TLR2, showing affinitive to both targets with preferentiality for the TLR4 receptor protein. Validation of the docking studies has proceeded through molecular dynamics simulation, which estimated a strong binding and supported the nomination of the designed vaccine as a putative solution for K. pneumoniae and P. aeruginosa coinfection. Here, we describe the approach for the design and assessment of our potential vaccine.

Molecular Bases of Protein Antigenicity and Determinants of Immunogenicity, Anergy, and Mitogenicity

BACKGROUND

The immune system is able to recognize substances that originate from inside or outside the body and are potentially harmful. Foreign substances that bind to immune system components exhibit antigenicity and are defined as antigens. The antigens exhibiting immunogenicity can induce innate or adaptive immune responses and give rise to humoral or cell-mediated immunity. The antigens exhibiting mitogenicity can cross-link cell membrane receptors on B and T lymphocytes leading to cell proliferation. All antigens vary greatly in physicochemical features such as biochemical nature, structural complexity, molecular size, foreignness, solubility, and so on.

OBJECTIVE

Thus, this review aims to describe the molecular bases of protein-antigenicity and those molecular bases that lead to an immune response, lymphocyte proliferation, or unresponsiveness.

CONCLUSION

The epitopes of an antigen are located in surface areas; they are about 880-3,300 Da in size. They are protein, carbohydrate, or lipid in nature. Soluble antigens are smaller than 1 nm and are endocytosed less efficiently than particulate antigens. The more the structural complexity of an antigen increases, the more the antigenicity increases due to the number and variety of epitopes. The smallest immunogens are about 4,000-10,000 Da in size. The more phylogenetically distant immunogens are from the immunogen-recipient, the more immunogenicity increases. Antigens that are immunogens can trigger an innate or adaptive immune response. The innate response is induced by antigens that are pathogen-associated molecular patterns. Exogenous antigens, T Dependent or T Independent, induce humoral immunogenicity. TD protein-antigens require two epitopes, one sequential and one conformational to induce antibodies, whereas, TI non-protein-antigens require only one conformational epitope to induce low-affinity antibodies. Endogenous protein antigens require only one sequential epitope to induce cell-mediated immunogenicity.

Vaccines against SARS-CoV-2 variants and future pandemics

INTRODUCTION

Vaccination continues to be the most effective method for controlling COVID-19 infectious diseases. Nonetheless, SARS-CoV-2 variants continue to evolve and emerge, resulting in significant public concerns worldwide, even after more than 2 years since the COVID-19 pandemic. It is important to better understand how different COVID-19 vaccine platforms work, why SARS-CoV-2 variants continue to emerge, and what options for improving COVID-19 vaccines can be considered to fight against SARS-CoV-2 variants and future pandemics.

AREA COVERED

Here, we reviewed the innate immune sensors in the recognition of SARS-CoV-2 virus, innate and adaptive immunity including neutralizing antibodies by different COVID-19 vaccines. Efficacy comparison of the several COVID-19 vaccine platforms approved for use in humans, concerns about SARS-CoV-2 variants and breakthrough infections, and the options for developing future COIVD-19 vaccines were also covered.

EXPERT OPINION

Owing to the continuous emergence of novel pathogens and the reemergence of variants, safer and more effective new vaccines are needed. This review also aims to provide the knowledge basis for the development of next-generation COVID-19 and pan-coronavirus vaccines to provide cross-protection against new SARS-CoV-2 variants and future coronavirus pandemics.

A designed peptide-based vaccine to combat Brucella melitensis, B. suis and B. abortus: Harnessing an epitope mapping and immunoinformatics approach

Vaccines against Brucella abortus, B. melitensis and B. suis have been based on weakened or killed bacteria, however there is no recombinant vaccine for disease prevention or therapy. This study attempted to predict IFN-γ epitopes, T cell cytotoxicity, and T lymphocytes in order to produce a multiepitope vaccine based on BtpA, Omp16, Omp28, virB10, Omp25, and Omp31 antigens against B. melitensis, B. abortus, and B. suis. AAY, GPGPG, and EAAAK peptides were used as epitope linkers, while the PADRE sequence was used as a Toll-like receptor 2 (TLR2) and TLR4 agonist. The final construct included 389 amino acids, and was a soluble protein with a molecular weight of 41.3 kDa, and nonallergenic and antigenic properties. Based on molecular docking studies, molecular dynamics simulations such as Gyration, RMSF, and RMSD, as well as tertiary structure validation methods, the modeled protein had a stable structure capable of interacting with TLR2/4. As a result, this novel vaccine may stimulate immune responses in B and T cells, and could prevent infection by B. suis, B. abortus, and B. melitensis.

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

Background

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

Results

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

Conclusion

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

Nanotechnology and COVID-19 Convergence: Toward New Planetary Health Interventions Against the Pandemic

COVID-19 is a systemic disease affecting multiple organ systems and caused by infection with the SARS-CoV-2 virus. Two years into the COVID-19 pandemic and after the introduction of several vaccines, the pandemic continues to evolve in part owing to global inequities in access to preventive and therapeutic measures. We are also witnessing the introduction of antivirals against COVID-19. Against this current background, we review the progress made with nanotechnology-based approaches such as nanoformulations to combat the multiorgan effects of SARS-CoV-2 infection from a systems medicine lens. While nanotechnology has previously been widely utilized in the antiviral research domain, it has not yet received the commensurate interest in the case of COVID-19 pandemic response strategies. Notably, SARS-CoV-2 and nanomaterials are similar in size ranging from 50 to 200 nm. Nanomaterials offer the promise to reduce the side effects of antiviral drugs, codeliver multiple drugs while maintaining stability in the biological milieu, and sustain the release of entrapped drug(s) for a predetermined time period, to name but a few conceivable scenarios, wherein nanotechnology can enable and empower preventive medicine and therapeutic innovations against SARS-CoV-2. We conclude the article by underlining that nanotechnology-based interventions warrant further consideration to enable precision planetary health responses against the COVID-19 pandemic.

In-silico design of an immunoinformatics based multi-epitope vaccine against Leishmania donovani

BACKGROUND

Visceral Leishmaniasis (VL) is a fatal vector-borne parasitic disorder occurring mainly in tropical and subtropical regions. VL falls under the category of neglected tropical diseases with growing drug resistance and lacking a licensed vaccine. Conventional vaccine synthesis techniques are often very laborious and challenging. With the advancement of bioinformatics and its application in immunology, it is now more convenient to design multi-epitope vaccines comprising predicted immuno-dominant epitopes of multiple antigenic proteins. We have chosen four antigenic proteins of Leishmania donovani and identified their T-cell and B-cell epitopes, utilizing those for in-silico chimeric vaccine designing. The various physicochemical characteristics of the vaccine have been explored and the tertiary structure of the chimeric construct is predicted to perform docking studies and molecular dynamics simulations.

RESULTS

The vaccine construct is generated by joining the epitopes with specific linkers. The predicted tertiary structure of the vaccine has been found to be valid and docking studies reveal the construct shows a high affinity towards the TLR-4 receptor. Population coverage analysis shows the vaccine can be effective on the majority of the world population. In-silico immune simulation studies confirms the vaccine to raise a pro-inflammatory response with the proliferation of activated T and B cells. In-silico codon optimization and cloning of the vaccine nucleic acid sequence have also been achieved in the pET28a vector.

CONCLUSION

The above bioinformatics data support that the construct may act as a potential vaccine. Further wet lab synthesis of the vaccine and in vivo works has to be undertaken in animal model to confirm vaccine potency.

Engineering a novel immunogenic chimera protein utilizing bacterial infections associated with atherosclerosis to induce a deviation in adaptive immune responses via Immunoinformatics approaches

Recent studies have established the role of bacteria including Streptococcus pneumoniae, Helicobacter pylori, Chlamydia pneumonia, Mycobacterium tuberculosis, and Porphyromonas gingivalis in the development of atherosclerosis. These bacteria contribute to plaque formation via promoting Th1 immune responses and speeding up ox-LDL formation. Hence, we employed computational reverse vaccinology (RV) approaches to deviate immune response toward Th2 via engineering a novel immunogenic chimera protein. Prominent atherogenic antigens from related bacteria were identified. Then, machine learning-based servers were employed for predicting CTL and HTL epitopes. We selected epitopes from a wide variety of HLAs. Then, a chimeric protein sequence containing TAT peptide, adjuvant, IL-10 inducer, and linker-separated epitopes was designed. The conformational structure of the vaccine was built via multiple-template homology modelling using MODELLER. The initial structure was refined and validated by Ramachandran plot. The vaccine was also docked with TLR4. After that, molecular dynamics (MD) simulation of the docked vaccine-TLR4 was conducted. Finally, the immune simulation of the vaccine was conducted via the C-ImmSim server. A chimera protein with 629 amino acids was built and, classified as a non-allergenic probable antigen. An improved ERRAT score of 80.95 for the refined structure verified its stability. Additionally, validation via the Ramachandran plot showed 98.09% of the residues were located in the most favorable and permitted regions. MD simulations showed the vaccine-TLR4 complex reached a stable conformation. Also, RMS fluctuations analysis revealed no sign of protein denaturation or unfolding. Finally, immune response simulations indicated a promising response by innate and adaptive immunity. In summary, we built an immunogenic vaccine against atherosclerosis and demonstrated its favorable properties via advanced Immunoinformatics analyses. This study may pave the path for combat against atherosclerosis.

Immunoinformatics-guided designing of epitope-based subunit vaccine from Pilus assembly protein of Acinetobacter baumannii bacteria

Acinetobacter baumannii, a prominent pathogen responsible for chronic infections in the blood, urinary tract, and lungs, has a high mortality due to its virulence and limited preventive methods. The present study aims to characterize the pilus assembly protein of A. baumannii to offer leads for epitope-based vaccine development. FilF is the putative pilus assembly protein that reportedly plays a supreme character in the virulence of this WHO-listed ESKAPE bacterium. Implementing various bioinformatics tools, led to the recognition of many antigenic B and T cell epitopes. Most promising B and T-cell epitopes were selected based on their binding efficiency with commonly occurring MHC alleles. Finally, we stepped down to fourteen protective antigenic peptides. These epitopes were also revealed to be non-allergenic and non-toxic. As a result, a vaccine chimera was created by linking these epitopes with appropriate linkers and adjuvant such as β-defensins. Furthermore, homology modeling and validation were carried out, with the modeled structure being employed for molecular docking with the immunological receptor (TLR-4) found on lymphocyte cells. As a result of the molecular dynamics simulation, the interaction between human TLR-4 and the multi-epitope vaccine sequence was stable. Finally, in silico cloning and immune simulation were carried out to see the efficacy of the construct vaccine. This is the first study targeting the pilus assembly protein from A. baumannii to identify novel epitopes that hold potential for further experimental design of multi-peptide vaccine construct against the pathogen.

Combing Immunoinformatics with Pangenome Analysis To Design a Multiepitope Subunit Vaccine against Klebsiella pneumoniae K1, K2, K47, and K64

Klebsiella pneumoniae is an opportunistic Gram-negative bacterium that has become a leading causative agent of nosocomial infections, mainly infecting patients with immunosuppressive diseases. Capsular (K) serotypes K1, K2, K47, and K64 are commonly associated with higher virulence (hypervirulent Klebsiella pneumoniae), and more threateningly, isolates belonging to the last two K serotypes are also frequently associated with resistance to carbapenem (hypervirulent carbapenem-resistant Klebsiella pneumoniae). The prevalence of these isolates has posed significant threats to human health, and there are no appropriate therapies available against them. Therefore, in this study, a method combining immunoinformatics and pangenome analysis was applied for contriving a multiepitope subunit vaccine against these four threatening serotypes. To obtain cross-protection, 12 predicted conserved antigens were screened from the core genome of 274 complete Klebsiella pneumoniae genomes (KL1, KL2, KL47, and KL64), from which the epitopes of T and B cells were extracted for vaccine construction. In addition, the immunological properties, the interaction with Toll-like receptors, and the stability in a simulative humoral environment were evaluated by immunoinformatics methods, molecular docking, and molecular dynamics simulation. All of these evaluations indicated the potency of this constructed vaccine to be an effective therapeutic agent. Lastly, the cDNA of the designed vaccine was optimized and ligated to pET-28a(+) for expression vector construction. Overall, our research provides a newly cross-protective control strategy against these troublesome pathogens and paves the way for the development of a safe and effective vaccine.

IMPORTANCEKlebsiella pneumoniae is an opportunistic Gram-negative bacterium that has become a leading causative agent of nosocomial infections. Among the numerous capsular serotypes, K1, K2, K47, and K64 are commonly associated with higher virulence (hypervirulent K. pneumoniae). More threateningly, the last two serotypes are frequently associated with resistance to carbapenem (hypervirulent carbapenem-resistant K. pneumoniae). However, there is currently no therapeutic agent or vaccine specifically against these isolates. Therefore, development of a vaccine against these pathogens is very essential. In this study, for the first time, a method combining pangenome analysis, reverse vaccinology, and immunoinformatics was applied for contriving a multiepitope subunit vaccine against K. pneumoniae isolates of K1, K2, K47, and K64. Also, the immunological properties of the constructed vaccine were evaluated and its high potency was revealed. Overall, our research will pave the way for the vaccine development against these four threatening capsular serotypes of K. pneumoniae.

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.

Designing a novel multi-epitope vaccine to evoke a robust immune response against pathogenic multidrug-resistant Enterococcus faecium bacterium

Enterococcus faecium is an emerging ESKAPE bacterium that is capable of causing severe public health complications in humans. There are currently no licensed treatments or vaccinations to combat the deadly pathogen. We aimed to design a potent and novel prophylactic chimeric vaccine against E. faecium through an immunoinformatics approach The antigenic Penicillin-binding protein 5 (PBP 5) protein was selected to identify B and T cell epitopes, followed by conservancy analysis, population coverage, physiochemical assessment, secondary and tertiary structural analysis. Using various immunoinformatics methods and tools, two linear B-cell epitopes, five CTL epitopes, and two HTL epitopes were finally selected for vaccine development. The constructed vaccine was determined to be highly immunogenic, cytokine-producing, antigenic, non-toxic, non-allergenic, and stable, as well as potentially effective against E. faecium. In addition, disulfide engineering, codon adaptation, and in silico cloning, were used to improve stability and expression efficiency in the host E. coli. Molecular docking and molecular dynamics simulations indicated that the structure of the vaccine is stable and has a high affinity for the TLR4 receptor. The immune simulation results revealed that both B and T cells had an increased response to the vaccination component. Conclusively, the in-depth in silico analysis suggests, the proposed vaccine to elicit a robust immune response against E. faecium infection and hence a promising target for further experimental trials.

Promising Acinetobacter baumannii Vaccine Candidates and Drug Targets in Recent Years

In parallel to the uncontrolled use of antibiotics, the emergence of multidrug-resistant bacteria, like Acinetobacter baumannii, has posed a severe threat. A. baumannii predominates in the nosocomial setting due to its ability to persist in hospitals and survive antibiotic treatment, thereby eventually leading to an increasing prevalence and mortality due to its infection. With the increasing spectra of drug resistance and the incessant collapse of newly discovered antibiotics, new therapeutic countermeasures have been in high demand. Hence, recent research has shown favouritism towards the long-term solution of designing vaccines. Therefore, being a realistic alternative strategy to combat this pathogen, anti-A. Baumannii vaccines research has continued unearthing various antigens with variable results over the last decade. Again, other approaches, including pan-genomics, subtractive proteomics, and reverse vaccination strategies, have shown promise for identifying promiscuous core vaccine candidates that resulted in chimeric vaccine constructs. In addition, the integration of basic knowledge of the pathobiology of this drug-resistant bacteria has also facilitated the development of effective multiantigen vaccines. As opposed to the conventional trial-and-error approach, incorporating the in silico methods in recent studies, particularly network analysis, has manifested a great promise in unearthing novel vaccine candidates from the A. baumannii proteome. Some studies have used multiple A. baumannii data sources to build the co-functional networks and analyze them by k-shell decomposition. Additionally, Whole Genomic Protein Interactome (GPIN) analysis has utilized a rational approach for identifying essential proteins and presenting them as vaccines effective enough to combat the deadly pathogenic threats posed by A. baumannii. Others have identified multiple immune nodes using network-based centrality measurements for synergistic antigen combinations for different vaccination strategies. Protein-protein interactions have also been inferenced utilizing structural approaches, such as molecular docking and molecular dynamics simulation. Similar workflows and technologies were employed to unveil novel A. baumannii drug targets, with a similar trend in the increasing influx of in silico techniques. This review integrates the latest knowledge on the development of A. baumannii vaccines while highlighting the in silico methods as the future of such exploratory research. In parallel, we also briefly summarize recent advancements in A. baumannii drug target research.

Using Molecular Dynamics Simulations to Interrogate T Cell Receptor Non-Equilibrium Kinetics

•

Insights into the atomic-scale interaction of the T Cell Receptor with the peptide Major Histocompatibility Complex.

•

Investigation of the physiochemical features that correspond with T Cell Receptor recognition during dynamic dissociation.

•

Implications of force-dependent non-equilibrium kinetics on T Cell Receptor mechanosensing.

An atomic-scale mechanism of T Cell Receptor (TCR) mechanosensing of peptides in the binding groove of the peptide-major histocompatibility complex (pMHC) may inform the design of novel TCRs for immunotherapies. Using steered molecular dynamics simulations, our study demonstrates that mutations to peptides in the binding groove of the pMHC – which are known to discretely alter the T cell response to an antigen – alter the MHC conformation at equilibrium. This subsequently impacts the overall strength (duration and length) of the TCR-pMHC bond under constant load. Moreover, physiochemical features of the TCR-pMHC dynamic bond strength, such as hydrogen bonds and Lennard-Jones contacts, correlate with the immunogenic response elicited by the specific peptide in the MHC groove. Thus, formation of transient TCR-pMHC bonds is characteristic of immunogenic peptides, and steered molecular dynamics simulations can be used in the overall design strategy of TCRs for immunotherapies.

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.

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.

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.

Computational design and characterization of a multiepitope vaccine against carbapenemase-producing Klebsiella pneumoniae strains, derived from antigens identified through reverse vaccinology

Klebsiella pneumoniae is a Gram-negative pathogen of clinical relevance, which can provoke serious urinary and blood infections and pneumonia. This bacterium is a major public health threat due to its resistance to several antibiotic classes. Using a reverse vaccinology approach, 7 potential antigens were identified, of which 4 were present in most of the sequences of Italian carbapenem-resistant K. pneumoniae clinical isolates. Bioinformatics tools demonstrated the antigenic potential of these bacterial proteins and allowed for the identification of T and B cell epitopes. This led to a rational design and in silico characterization of a multiepitope vaccine against carbapenem-resistant K. pneumoniae strains. As adjuvant, the mycobacterial heparin-binding hemagglutinin adhesin (HBHA), which is a Toll-like receptor 4 (TLR-4) agonist, was included, to increase the immunogenicity of the construct. The multiepitope vaccine candidate was analyzed by bioinformatics tools to assess its antigenicity, solubility, allergenicity, toxicity, physical and chemical parameters, and secondary and tertiary structures. Molecular docking binding energies to TLR-2 and TLR-4, two important innate immunity receptors involved in the immune response against K. pneumoniae infections, and molecular dynamics simulations of such complexes supported active interactions. A codon optimized multiepitope sequence cloning strategy is proposed, for production of recombinant vaccine in classical bacterial vectors. Finally, a 3 dose-immunization simulation with the multiepitope construct induced both cellular and humoral immune responses. These results suggest that this multiepitope construct has potential as a vaccination strategy against carbapenem-resistant K. pneumoniae and deserves further validation.

Molecular Characterization and Designing of a Novel Multiepitope Vaccine Construct Against Pseudomonas aeruginosa

ABSTRACT

Pseudomonas aeruginosa, an ESKAPE pathogen causes many fatal clinical diseases in humans across the globe. Despite an increase in clinical instances of Pseudomonas infection, there is currently no effective vaccine or treatment available. The major membrane protein candidate of the P. aeruginosa bacterial cell is known to be a critical component for cellular bacterial susceptibility to antimicrobial peptides and survival inside the host organisms. Therefore, the current computational study aims to examine P. aeruginosa's major membrane protein, OprF, and OprI, in order to design linear B-cell, cytotoxic T-cell, and helper T-cell peptide-based vaccine constructs. Utilizing various immune-informatics tools and databases, a total of two B-cells and twelve T-cells peptides were predicted. The final vaccine design was simulated to generate a high-quality three-dimensional structure, which included epitopes, adjuvant, and linkers. The vaccine was shown to be nonallergenic, antigenic, soluble, and had the best biophysical properties. The vaccine and Toll-like receptor 4 have a strong and stable interaction, according to protein-protein docking and molecular dynamics simulations. Additionally, in silico cloning was employed to see how the developed vaccine expressed in the pET28a (+) vector. Ultimately, an immune simulation was performed to see the vaccine efficacy. In conclusion, the newly developed vaccine appears to be a promising option for a vaccine against P. aeruginosa infection.

GRAPHICAL ABSTRACT

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10989-021-10356-z.

Genome-based identification and comparative analysis of enzymes for carotenoid biosynthesis in microalgae

Microalgae are potential feedstocks for the commercial production of carotenoids, however, the metabolic pathways for carotenoid biosynthesis across algal lineage are largely unexplored. This work is the first to provide a comprehensive survey of genes and enzymes associated with the less studied methylerythritol 4-phosphate/1-deoxy-D-xylulose 5-phosphate pathway as well as the carotenoid biosynthetic pathway in microalgae through bioinformatics and comparative genomics approach. Candidate genes/enzymes were subsequently analyzed across 22 microalgae species of lineages Chlorophyta, Rhodophyta, Heterokonta, Haptophyta, Cryptophyta, and known Arabidopsis homologs in order to study the evolutional divergence in terms of sequence-structure properties. A total of 403 enzymes playing a vital role in carotene, lutein, zeaxanthin, violaxanthin, canthaxanthin, and astaxanthin were unraveled. Of these, 85 were hypothetical proteins whose biological roles are not yet experimentally characterized. Putative functions to these hypothetical proteins were successfully assigned through a comprehensive investigation of the protein family, motifs, intrinsic physicochemical features, subcellular localization, pathway analysis, etc. Furthermore, these enzymes were categorized into major classes as per the conserved domain and gene ontology. Functional signature sequences were also identified which were observed conserved across microalgal genomes. Additionally, the structural modeling and active site architecture of three vital enzymes, DXR, PSY, and ZDS catalyzing the vital rate-limiting steps in Dunaliella salina were achieved. The enzymes were confirmed to be stereochemically reliable and stable as revealed during molecular dynamics simulation of 100 ns. The detailed functional information about individual vital enzymes will certainly help to design genetically modified algal strains with enhanced carotenoid contents.