Pan-Genome Analysis of Oral Bacterial Pathogens to Predict a Potential Novel Multi-Epitopes Vaccine Candidate

Immunoinformatics assisted profiling of West Nile virus proteome to determine immunodominant epitopes for the development of next-generation multi-peptide vaccine

Emerging infectious diseases represent a significant threat to global health, with West Nile virus (WNV) being a prominent example due to its potential to cause severe neurological disorders alongside mild feverish conditions. Particularly prevalent in the continental United States, WNV has emerged as a global concern, with outbreaks indicating the urgent need for effective prophylactic measures. The current problem is that the absence of a commercial vaccine against WNV highlights a critical gap in preventive strategies against WNV. This study aims to address this gap by proposing a novel, multivalent vaccine designed using immunoinformatics approaches to elicit comprehensive humoral and cellular immune responses against WNV. The objective of the study is to provide a theoretical framework for experimental scientists to formulate of vaccine against WNV and tackle the current problem by generating an immune response inside the host. The research employs reverse vaccinology and subtractive proteomics methodologies to identify NP_041724.2 polyprotein and YP_009164950.1 truncated flavivirus polyprotein NS1 as the prime antigens. The selection process for epitopes focused on B and T-cell reactivity, antigenicity, water solubility, and non-allergenic properties, prioritizing candidates with the potential for broad immunogenicity and safety. The designed vaccine construct integrates these epitopes, connected via GPGPG linkers, and supplemented with an adjuvant with the help of another linker EAAAK, to enhance immunogenicity. Preliminary computational analyses suggest that the proposed vaccine could achieve near-universal coverage, effectively targeting approximately 99.74% of the global population, with perfect coverage in specific regions such as Sweden and Finland. Molecular docking and immune simulation studies further validate the potential efficacy of the vaccine, indicating strong binding affinity with toll-like receptor 3 (TLR-3) and promising immune response profiles, including significant antibody-mediated and cellular responses. These findings present the vaccine construct as a viable candidate for further development and testing. While the theoretical and computational results are promising, advancing from in-silico predictions to a tangible vaccine requires comprehensive laboratory validation. This next step is essential to confirm the vaccine's efficacy and safety in eliciting an immune response against WNV. Through this study, we propose a novel approach to vaccine development against WNV and contribute to the broader field of immunoinformatics, showcasing the potential to accelerate the design of effective vaccines against emerging viral threats. The journey from hypothesis to practical solution embodies the interdisciplinary collaboration essential for modern infectious disease management and prevention strategies.

Design and validation of a novel multi-epitopes vaccine against hantavirus

Hantavirus is a member of the order Bunyavirales and an emerging global pathogen. Hantavirus infections have affected millions of people globally based on available epidemiological data and research studies. Hemorrhagic fever with renal syndrome (HFRS) and hantavirus pulmonary syndrome (HPS) are the two main human diseases associated with hantavirus infections. Hence, efforts are required to develop a potent vaccine against the pathogen. The only vaccine that is in use for hantavirus is an inactivated virus vaccine, "Hantavax", but it failed to produce neutralizing antibodies. Vaccine development is of much importance in dealing with the surge of hantavirus globally. In this study, hantavirus five proteins (N protein, G1 and G2, L protein, and non-structural proteins) were used in NetCTL 1.2 program to predict T-cell epitopes. To predict major histocompatibility complex (MHC) binding alleles, an immune epitope database (IEDB) was used. All predicted epitopes were then investigated for different immunoinformatics analyses such as antigenicity and toxicity analyses. The good water-soluble, non-toxic, probable antigenic, and DRB*0101 binder was selected. A multi-epitopes-based vaccine designing was then done where linkers were used to connect the shortlisted epitopes. In addition, an adjuvant molecule was supplementary to the multi-epitopes peptide to improve the vaccine's immunogenic potential. The final vaccine construct's three-dimensional structure was modeled by ab initio method. The vaccine molecule was then evaluated for its binding potential with TLR-3 immune receptor, which is key for its recognition and processing by the host immune system. Docking studies were performed using HADDOCK software. The best-docked complex was selected and visualized for intermolecular binding and interactions using UCSF Chimera 1.16 software. The findings revealed that the designed vaccine might be a potential vaccine against hantavirus and can be used in experimental animal model testings.Communicated by Ramaswamy H. Sarma.

A computational quest for identifying potential vaccine candidates against Moraxella lacunata: a multi-pronged approach

Moraxella lacunata is an emerging gram-negative bacterium that is responsible for multiple nosocomial infections. The bacterium is evolving resistance to several antibiotics, and currently, no effective licensed vaccines are available, which warrants the search for new therapeutics. A multi-epitope-based vaccine has been designed for M. lacunata. The complete proteome of M. lacunata contains 10,110 core proteins. Subcellular localization analysis revealed the presence of five proteins in the extracellular matrix, while 19 proteins were predicted to be located in the outer membrane, and 21 proteins were predicted to be located in the periplasmic region. Only two proteins, the type VI secretion system tube protein (Hcp) and the transporter substrate-binding domain-containing protein, were selected for epitope prediction as they fulfilled all the criteria for being potential vaccine candidates. Shortlisted epitopes from the selected proteins were fused together using "GPGPG" linkers to overcome the limitations of single-epitope vaccines. Next, the cholera toxin-B adjuvant was attached to the peptide epitope using an EAAAK linker. Docking analysis was performed to examine the interaction between the vaccine and immune cell receptors, revealing robust intermolecular interactions and a stable binding conformation. Molecular dynamics simulation findings revealed no drastic changes in the binding conformation of complexes during the simulation period. The net binding free energy of vaccine-receptor complexes was estimated using the molecular mechanics energies combined with the Poisson-Boltzmann and surface area continuum solvation (MM-PBSA) method. The reported values were -586.38 kcal/mol, -283.74 kcal/mol, and -296.88 kcal/mol for the TLR-4-vaccine complex, MHC-I-vaccine complex, and MHC-II-vaccine complex, respectively. Furthermore, the molecular mechanics energies combined with the generalized Born and surface area continuum solvation (MM-GBSA) analysis predicted binding free energies of -596.69 kcal/mol, -287.39 kcal/mol, and -298.28 kcal/mol for the TLR-4-vaccine complex, MHC-I-vaccine complex, and MHC-II-vaccine complex, respectively. The theoretical vaccine design proposed in the study could potentially serve as a powerful therapeutic against targeted pathogens, subject to validation through experimental studies.Communicated by Ramaswamy H. Sarma.

Bioinformatics and immunoinformatics assisted multiepitope vaccine construct against Burkholderia anthina

Burkholderia anthina is a pathogenic bacterial species belonging to the Burkholderiaceae family and it is mainly considered the etiological agent of chronic obstructive pulmonary diseases associated with cystic fibrosis, due to being intrinsic antibiotic resistant making it difficult to treat pulmonary infections. Hence increased rate of antibiotic-resistant bacterial species vaccine development is the priority to tackle this problem. In research work, we designed a multi-epitope-based vaccine construct against B. anthina using reverse vaccinology immunoinformatics and biophysical approaches. Based on the subtractive proteomic screening of core proteins we identified 3 probable antigenic proteins and good vaccine targets namely, type VI secretion system tube protein hcp Burkholderia, fimbria/pilus periplasmic chaperone and fimbrial biogenesis outer membrane usher protein. The selected 3 proteins were used for B and B cells B-derived T-cell epitopes prediction. In epitopes prediction, different epitopes were predicted with various lengths and percentile scores and subjected to further immunoinformatics analysis. In immunoinformatics screening a total number of 06, IDDGNANAL, KTVKPDPRY, SEVESGSAP, YGGDLTVEV, SVSHDTNGR, and GSKADGYQR epitopes were considered good vaccine target candidates and shortlisted for vaccine construct designing. The vaccine construct was designed by joining selected epitopes with the help of a GPGPG linker and additionally linked with cholera toxin b subunit adjuvant to increase the efficacy of the vaccine construct the sequence of the said adjuvant were retrieved from protein data bank through its (PDB ID: 5ELD). The designed vaccine construct was evaluated for its physiochemical properties analysis in which we reported that the vaccine construct comprises 216 amino acids with a molecular weight of 22.37499 kilo Dalton, 15.55 instability index (II) is computed, and this classifies that the vaccine construct is properly stable. VaxiJen v2.0 web server predicted that the vaccine construct is probable antigenic in nature with 0.6320 predicted value. Furthermore AllerTOP v. 2.0 tool predicted that the designed vaccine construct is non allergic in nature. Molecular docking analysis was done for analysis of the binding affinity of the vaccine construct with TLR-2 (PDB ID: 6NIG), the docking results predicted 799.2 kcal/mol binding energy score that represents the vaccine construct has a good binding ability with TLR-2. Moreover, molecular dynamic simulation analysis results revealed that the vaccine construct and immune cell receptor has proper binding stability over various environmental condition, i.e. change in pressure range, temperature, and motion. After each analysis, we observed that the vaccine construct is safe stable, and probably antigenic and could generate an immune response against the target pathogen but in the future, experimental analysis is still needed to verify in silico base results.

A novel therapeutic approach to prevent Helicobacter pylori induced gastric cancer using networking biology, molecular docking, and simulation approaches

Helicobacter pylori infects 50% of the world population and in 80% of cases, the infection progresses to the point where an ulcer develops leading to gastric cancer (GC). This study aimed to prevent GC by predicting Hub genes that are inducing GC. Furthermore, the study objective was to screen inhibitory molecules that block the function of predicted genes through several biophysical approaches. These proteins, such as Mucin 4 (MUC4) and Baculoviral IAP repeat containing 3 (BIRC3), had LogFC values of 2.28 and 3.39, respectively, and were found to be substantially expressed in those who had H. pylori infection. The MUC4 and BIRC3 inhibit apoptosis of infected cells and promote cancerous cell survival. The proteins were examined for their Physico-chemical characteristics, 3D structure and secondary structure analysis, solvent assessable surface area (SASA), active site identification, and network analysis. The MUC4 and BIRC3 expression was inhibited by docking eighty different compounds collected from the ZINC database. Fifty-seven compounds were successfully docked into the active site resulting in the lowest binding energy scores. The ZINC585267910 and ZINC585268691 compounds showed the lowest binding energy of -8.5 kcal/mol for MUC4 and -7.1 kcal/mol for BIRC3, respectively, and were considered best-docked solutions for molecular dynamics simulations. The mean root mean square deviation (RMSD) value for the ZINC585267910-MUC4 complex was 0.86 Å and the ZINC585268691-BIRC3 complex was 1.01 Å. The net MM/GBSA energy value of the ZINC585267910-MUC4 complex estimated was -46.84 kcal/mol and that of the ZINC585268691-BIRC3 complex was -44.84 kcal/mol. In a nutshell, the compounds might be investigated further as an inhibitor of the said proteins to stop the progress of GC induced by H. pylori.Communicated by Ramaswamy H. Sarma.

An In Silico Multi-epitopes Vaccine Ensemble and Characterization Against Nosocomial Proteus penneri

Proteus penneri (P. penneri) is a bacillus-shaped, gram-negative, facultative anaerobe bacterium that is primarily an invasive pathogen and the etiological agent of several hospital-associated infections. P. penneri strains are naturally resistant to macrolides, amoxicillin, oxacillin, penicillin G, and cephalosporins; in addition, no vaccines are available against these strains. This warrants efforts to propose a theoretical based multi-epitope vaccine construct to prevent pathogen infections. In this research, reverse vaccinology bioinformatics and immunoinformatics approaches were adopted for vaccine target identification and construction of a multi-epitope vaccine. In the first phase, a core proteome dataset of the targeted pathogen was obtained using the NCBI database and subjected to bacterial pan-genome analysis using bacterial pan-genome analysis (BPGA) to predict core protein sequences which were then used to find good vaccine target candidates. This identified two proteins, Hcp family type VI secretion system effector and superoxide dismutase family protein, as promising vaccine targets. Afterward using the IEDB database, different B-cell and T-cell epitopes were predicted. A set of four epitopes "KGSVNVQDRE, NTGKLTGTR, IIHSDSWNER, and KDGKPVPALK" were chosen for the development of a multi-epitope vaccine construct. A 183 amino acid long vaccine design was built along with "EAAAK" and "GPGPG" linkers and a cholera toxin B-subunit adjuvant. The designed vaccine model comprised immunodominant, non-toxic, non-allergenic, and physicochemical stable epitopes. The model vaccine was docked with MHC-I, MHC-II, and TLR-4 immune cell receptors using the Cluspro2.0 web server. The binding energy score of the vaccine was - 654.7 kcal/mol for MHC-I, - 738.4 kcal/mol for MHC-II, and - 695.0 kcal/mol for TLR-4. A molecular dynamic simulation was done using AMBER v20 package for dynamic behavior in nanoseconds. Additionally, MM-PBSA binding free energy analysis was done to test intermolecular binding interactions between docked molecules. The MM-GBSA net binding energy score was - 148.00 kcal/mol, - 118.00 kcal/mol, and - 127.00 kcal/mol for vaccine with TLR-4, MHC-I, and MHC-II, respectively. Overall, these in silico-based predictions indicated that the vaccine is highly promising in terms of developing protective immunity against P. penneri. However, additional experimental validation is required to unveil the real immune response to the designed vaccine.

Computational study to investigate Proteus mirabilis proteomes for multi-epitope vaccine construct design

Proteus mirabilis is a gram-negative bacterium particularly known for its unique swarming ability. The swarming gives the bacteria ability to enhance adherence to the catheter surface and epithelium cells of the urethra to cause catheter associated urinary tract infections. P. mirabilis has evolved resistant to antibiotics. Additionally, there is an approved vaccine against P. mirabilis, thus demanding for identification of new vaccine targets. This gram-negative bacterium consists of 19,502 core proteins, out of which 19,063 are redundant proteins and remaining 439 are non-redundant proteins. The non-redundant proteins have 21 proteins present on the cell surface out of which 11 proteins are virulent. Antigenicity analysis predicted only 2 proteins as antigenic (fimbrial biogenesis outer membrane usher protein and ligand-gated channel protein). Four and seven B-cells epitopes were predicted from the former and later proteins, respectively. The predicted B-cells epitopes were used for T- cells epitopes prediction. The predicted epitopes were linked to each other through GPGPG linkers and joined with cholera toxin beta subunit adjuvant. A multi-epitopes vaccine construct consisting of 226 residues was docked with MHC-I, MHC-II and TLR-4. The best docked complex in each case has binding energy of -714.6, -744.6 and -829.5 kcal/mol, respectively. Moreover, the docking results were validated through molecular dynamics simulation and binding free energies estimation. The net energy of -137.2 kcal/mol was calculated for vaccine-MHC-I complex, -133.39 kcal/mol for vaccine-MHC-II and -158.68 kcal/mol for vaccine-TLR-4 complex. The designed vaccine construct could provoke immune responses against targeted pathogen and may be used in experimental testing.Communicated by Ramaswamy H. Sarma.

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.

Designing a novel chimeric multi-epitope vaccine subunit against Staphylococcus argenteus through artificial intelligence approach integrating pan-genome analysis, in vitro identification, and immunogenicity profiling

Staphylococcus argenteus is a newly identified pathogen that causes respiratory tract infections, skin infections, such as cellulitis, abscesses, and impetigo, and currently, there is no licensed vaccine available against it. To develop a vaccine against S. argenteus, a bacterial pan-genome analysis was applied to identify potential vaccine candidates. A total of 4908 core proteins were retrieved and utilized for identifying four proteins, including SG38 Panton-Valentine leukocidin LukS-PV protein, SG62 staphylococcal enterotoxin type A protein, SG39 enterotoxin B protein, and SG43 enterotoxin type C3 protein as potential vaccine candidates. Epitopes were predicted for these proteins using different types of B and T-cell epitope prediction tools, and only those with a non-toxic profile, antigenic, non-allergenic, and immunogenic were selected. The selected epitopes were linked to each other to form a multi-epitope vaccine construct, which was further linked to the PADRE sequence (AKFVAAWTLKAAA) and 50s ribosomal L7/L12 protein to enhance the vaccine's antigenicity. The three-dimensional structure of the vaccine construct was assessed to determine its binding affinity with key Toll-like receptor 9 (TLR-9) and Toll-like receptor 5 (TLR-5) immune cell receptors. Our findings demonstrate that the vaccine exhibits favorable binding interactions with these immune cell receptors, indicating its potential efficacy. Molecular dynamic simulations further confirmed the accessibility of vaccine epitopes to the host immune system, substantiating its ability to elicit protective immune responses. Taken together, this study highlights the promising candidacy of the modeled vaccine construct for future in vivo and in vitro experimental investigations.Communicated by Ramaswamy H. Sarma.

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

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

Pan-genome analysis and molecular docking unveil the biocontrol potential of Bacillus velezensis VB7 against Phytophthora infestans

Management of late blight of potato incited by Phytophthora infestans remains a major challenge. Coevolution of pathogen with resistant strains and the rise of fungicide resistance have made it more challenging to prevent the spread of P. infestans. Here, the anti-oomycete potential of Bacillus velezensis VB7 against P. infestans through pan-genome analysis and molecular docking were explored. The Biocontrol potential of VB7 against P. infestans was assessed using a confrontational assay. The biomolecules from the inhibition zone were identified and subjected to in silico analysis against P. infestans target proteins. Nucleotide sequences for 54 B. velezensis strains from different geographical locations were used for pan-genome analysis. The confrontational assay revealed the anti-oomycetes potential of VB7 against P. infestans. Molecular docking confirmed that the penicillamine disulfide had the maximum binding energy with eight effector proteins of P. infestans. Besides, scanning electron microscopic observations of P. infestans interaction with VB7 revealed structural changes in hypha and sporangia. Pan-genome analysis between 54 strains of B. velezensis confirmed that the core genome had 2226 genes, and it has an open pan-genome. The present study confirmed the anti-oomycete potential of B. velezensis VB7 against P. infestans and paved the way to explore the genetic potential of VB7.

Proteome-Wide Screening of Potential Vaccine Targets against Brucella melitensis

The ongoing antibiotic-resistance crisis is becoming a global problem affecting public health. Urgent efforts are required to design novel therapeutics against pathogenic bacterial species. Brucella melitensis is an etiological agent of brucellosis, which mostly affects sheep and goats but several cases have also been reported in cattle, water buffalo, yaks and dogs. Infected animals also represent the major source of infection for humans. Development of safer and effective vaccines for brucellosis remains a priority to support disease control and eradication in animals and to prevent infection to humans. In this research study, we designed an in-silico multi-epitopes vaccine for B. melitensis using computational approaches. The pathogen core proteome was screened for good vaccine candidates using subtractive proteomics, reverse vaccinology and immunoinformatic tools. In total, 10 proteins: catalase; siderophore ABC transporter substrate-binding protein; pyridoxamine 5'-phosphate oxidase; superoxide dismutase; peptidylprolyl isomerase; superoxide dismutase family protein; septation protein A; hypothetical protein; binding-protein-dependent transport systems inner membrane component; and 4-hydroxy-2-oxoheptanedioate aldolase were selected for epitopes prediction. To induce cellular and antibody base immune responses, the vaccine must comprise both B and T-cells epitopes. The epitopes were next screened for antigenicity, allergic nature and water solubility and the probable antigenic, non-allergic, water-soluble and non-toxic nine epitopes were shortlisted for multi-epitopes vaccine construction. The designed vaccine construct comprises 274 amino acid long sequences having a molecular weight of 28.14 kDa and instability index of 27.62. The vaccine construct was further assessed for binding efficacy with immune cell receptors. Docking results revealed that the designed vaccine had good binding potency with selected immune cell receptors. Furthermore, vaccine-MHC-I, vaccine-MHC-II and vaccine-TLR-4 complexes were opted based on a least-binding energy score of -5.48 kcal/mol, 0.64 kcal/mol and -2.69 kcal/mol. Those selected were then energy refined and subjected to simulation studies to understand dynamic movements of the docked complexes. The docking results were further validated through MMPBSA and MMGBSA analyses. The MMPBSA calculated -235.18 kcal/mol, -206.79 kcal/mol, and -215.73 kcal/mol net binding free energy, while MMGBSA estimated -259.48 kcal/mol, -206.79 kcal/mol and -215.73 kcal/mol for TLR-4, MHC-I and MHC-II complexes, respectively. These findings were validated by water-swap and entropy calculations. Overall, the designed vaccine construct can evoke proper immune responses and the construct could be helpful for experimental researchers in formulation of a protective vaccine against the targeted pathogen for both animal and human use.

Targeted Protein-Specific Multi-Epitope-Based Vaccine Designing against Human Cytomegalovirus by Using Immunoinformatics Approaches

Cytomegaloviruses are emerging pathogenic agents known to cause congenital disorders in humans. In this study, immune epitopes (CTL, B cell and HTL) were screened for highly antigenic target proteins of the Human Cytomegalovirus. These shortlisted epitopes were then joined together through suitable linkers to construct multi epitope-based vaccine constructs (MEVCs). The functionality of each vaccine construct was evaluated through tertiary vaccine structure modelling and validations. Furthermore, physio-chemical properties including allergenicity, antigenicity molecular weight and many others were also predicted. The vaccine designs were also docked with the human TLR-4 receptor to demonstrate the receptor specific affinity and formed interactions. The vaccine peptides sequences were also subjected to codon optimization to confirm the potential vaccines expression in E. coli hosts. Additionally, all the MEVCs were also evaluated for immune response (IgG and IgM) induction. However, further in vivo tests are needed to ensure the efficacy of these vaccine designs.

Integrativesubtractive proteomics, immunoinformatics, docking, and simulation approaches reveal candidate vaccine against Sin Nombre orthohantavirus

The emergence of Sin Nombre orthohantavirus, an etiological agent of hantavirus cardiopulmonary syndrome, exacerbates the situation and imposes a heavy financial burden on healthcare organizations. Multidrug-resistant forms of the disease are prevalent, and there is currently no licensed commercial vaccine. Due to the numerous limitations of experimental vaccines, vaccines against various bacterial and viral diseases have developed via computational vaccine design. Several subtractive proteomics, immunoinformatics, docking, and simulation approaches were used in this study to develop a multi-epitope–based vaccine against Sin Nombre orthohantavirus. One possible antigenic protein—the glycoprotein precursor of surface glycoproteins (accession number >AAC42202.1)—was selected as a candidate for B cell–derived T cell epitopes mapping the detailed analysis of the core genome. Among the predicted epitopes, four epitopes (QVDWTKKSST, GLAASPPHL, SSYSYRRKLV, and MESGWSDTA), which were probably antigenic, nonallergenic, nontoxic, and water soluble, were used in the multi-epitope vaccine’s construction. The shortlisted epitopes have the potency to cover 99.78% of the world’s population, 97.93% of the Chinese population, and 97.36% of the Indian population. The epitopes were connected through AAY linkers and joined with >50S ribosomal adjuvant to enhance their efficacy. The vaccine comprises 182 amino acids with a molecular weight of 19.03770 kDa and an instability index of 26.52, indicating that the protein is stable. A molecular docking study revealed that the vaccine has a good binding affinity with TLR-4 and TLR-8, which is vital for inducing the immune system. Top-1 docked complexes of vaccine- TLR-4 and TLR-8 with the lowest binding energy of -12.52 kc/mol and -5.42 kc/mol, respectively, were considered for molecular dynamic simulation analysis. Furthermore, we predicted that the docked complexes are properly stable throughout simulation time in both normal mode and AMBER-based simulation analysis. The MMGBSA analysis calculated -122.17 and -125.4 net binding energies for the TLR-8- and TLR4-vaccine complexes, respectively, while the MMPBSA analysis estimated -115.63 and -118.19 for the TLR-8- and TLR4-vaccine complex, respectively, confirming that the binding stability with receptors is stable, which is important for inducing a strong response. However, the current work is computation-based, so experimental validation is highly recommended.