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

Development of multi-epitope mRNA vaccine against Clostridioides difficile using reverse vaccinology and immunoinformatics approaches

Clostridioides difficile (C. difficile), as the major pathogen of diarrhea in healthcare settings, has become increasingly prevalent within community populations, resulting in significant morbidity and mortality. However, the therapeutic options for Clostridioides difficile infection (CDI) remain limited, and as of now, no authorized vaccine is available to combat this disease. Therefore, the development of a novel vaccine against C. difficile is of paramount importance. In our study, the complete proteome sequences of 118 strains of C. difficile were downloaded and analyzed. We found four antigenic proteins that were highly conserved and can be used for epitope identification. We designed two vaccines, WLcd1 and WLcd2, that contain the ideal T-cell and B-cell epitopes, adjuvants, and the pan HLA DR-binding epitope (PADRE) sequences. The biophysical and chemical assessments of these vaccine candidates indicated that they were suitable for immunogenic applications. Molecular docking analyses revealed that WLcd1 bonded with higher affinity to Toll-like receptors (TLRs) than WLcd2. Furthermore, molecular dynamics (MD) simulations, performed using Gmx_MMPBSA v1.56, confirmed the binding stability of WLcd1 with TLR2 and TLR4. The preliminary findings suggested that this multi-epitope vaccine could be a promising candidate for protection against CDI; however, experimental studies are necessary to confirm these predictions.

Inhibition of porcine origin Klebsiella pneumoniae capsular polysaccharide and immune escape by BY3 compounded traditional Chinese medicine residue fermentation broth

Klebsiella pneumoniae (K. pneumoniae) is a gram-negative conditionally pathogenic bacterium that causes disease primarily in immunocompromised individuals. Recently, highly virulent K. pneumoniae strains have caused severe disease in healthy individuals, posing significant challenges to global infection control. Capsular polysaccharide (CPS), a major virulence determinant of K. pneumoniae, protects the bacteria from being killed by the host immune system, suggesting an urgent need for the development of drugs to prevent or treat K. pneumoniae infections. In this study, BY3 compounded traditional Chinese medicine residue (TCMR) was carried out using Lactobacillus rhamnosus as a fermentation strain, and BY3 compounded TCMR fermentation broth (BY3 fermentation broth) was obtained. The transcription of K. pneumoniae CPS-related biosynthesis genes after treatment with BY3 fermentation broth was detected using quantitative real-time polymerase chain reaction. The effects of BY3 fermentation broth on K. pneumoniae serum killing, macrophage phagocytosis, complement deposition and human β-defensin transcription were investigated. The therapeutic effect of BY3 fermentation broth on K. pneumoniae-infected mice was also observed, and the major active components of BY3 fermentation broth were analysed via LC‒MS analysis, network pharmacology, and molecular docking. The results showed that BY3 fermentation broth inhibited K. pneumoniae CPS production and downregulated transcription of CPS-related biosynthesis genes, which weakened bacterial resistance to serum killing and phagocytosis, while promoting bacterial surface complement C3 deposition and human β-defensin expression. BY3 fermentation broth demonstrated safety and therapeutic effects in vivo and in vitro, restoring body weight and visceral indices, significantly reducing the organ bacterial load and serum cytokine levels, and alleviating pathological organ damage in mice. In addition, three natural compounds-oleanolic acid, quercetin, and palmitoleic acid-were identified as the major active components in the BY3 fermentation broth. Therefore, BY3 fermentation broth may be a promising strategy for the prevention or treatment of K. pneumoniae infections.

Protein profiling and immunoinformatic analysis of the secretome of a metal-resistant environmental isolate Pseudomonas aeruginosa S-8

The bacterial secretome represents a comprehensive catalog of proteins released extracellularly that have multiple important roles in virulence and intercellular communication. This study aimed to characterize the secretome of an environmental isolate Pseudomonas aeruginosa S-8 by analyzing trypsin-digested culture supernatant proteins using nano-LC-MS/MS tool. Using a combined approach of bioinformatics and mass spectrometry, 1088 proteins in the secretome were analyzed by PREDLIPO, SecretomeP 2.0, SignalP 4.1, and PSORTb tool for their subcellular localization and further categorization of secretome proteins according to signal peptides. Using the gene ontology tool, secretome proteins were categorized into different functional categories. KEGG pathway analysis identified the secreted proteins into different metabolic functional pathways. Moreover, our LC-MS/MS data revealed the secretion of various CAZymes into the extracellular milieu, which suggests its strong biotechnological applications to breakdown complex carbohydrate polymers. The identified immunodominant epitopes from the secretome of P. aeruginosa showed the characteristic of being non-allergenic, highly antigenic, nontoxic, and having a low risk of triggering autoimmune responses, which highlights their potential as successful vaccine targets. Overall, the identification of secreted proteins of P. aeruginosa could be important for both diagnostic purposes and the development of an effective candidate vaccine.

TgVax452, an epitope-based candidate vaccine targeting Toxoplasma gondii tachyzoite-specific SAG1-related sequence (SRS) proteins: immunoinformatics, structural simulations and experimental evidence-based approaches

BACKGROUND

The highly expressed surface antigen 1 (SAG1)-related sequence (SRS) proteins of T. gondii tachyzoites, as a widespread zoonotic parasite, are critical for host cell invasion and represent promising vaccine targets. In this study, we employed a computer-aided multi-method approach for in silico design and evaluation of TgVax452, an epitope-based candidate vaccine against T. gondii tachyzoite-specific SRS proteins.

METHODS

Using immunoinformatics web-based tools, structural modeling, and static/dynamic molecular simulations, we identified and screened B- and T-cell immunodominant epitopes and predicted TgVax452's antigenicity, stability, safety, adjuvanticity, and physico-chemical properties.

RESULTS

The designed protein possessed 452 residues, a MW of 44.07 kDa, an alkaline pI (6.7), good stability (33.20), solubility (0.498), and antigenicity (0.9639) with no allergenicity. Comprehensive molecular dynamic (MD) simulation analyses confirmed the stable interaction (average potential energy: 3.3799 × 106 KJ/mol) between the TLR4 agonist residues (RS09 peptide) of the TgVax452 in interaction with human TLR4, potentially activating innate immune responses. Also, a dramatic increase was observed in specific antibodies (IgM and IgG), cytokines (IFN-γ), and lymphocyte responses, based on C-ImmSim outputs. Finally, we optimized TgVax452's codon adaptation and mRNA secondary structure for efficient expression in E. coli BL21 expression machinery.

CONCLUSION

Our findings suggest that TgVax452 is a promising candidate vaccine against T. gondii tachyzoite-specific SRS proteins and requires further experimental studies for its potential use in preclinical trials.

Immunoinformatics design and synthesis of a multi-epitope vaccine against Helicobacter pylori based on lipid nanoparticles

Helicobacter pylori (H. pylori) is responsible for various chronic or acute diseases, such as stomach ulcers, dyspepsia, peptic ulcers, gastroesophageal reflux, gastritis, lymphoma, and stomach cancers. Although specific drugs are available to treat the bacterium's harmful effects, there is an urgent need to develop a preventive or therapeutic vaccine. Therefore, the current study aims to create a multi-epitope vaccine against H. pylori using lipid nanoparticles. Five epitopes from five target proteins of H. pylori, namely, Urease, CagA, HopE, SabA, and BabA, were used. Immunogenicity, MHC (Major Histocompatibility Complex) bonding, allergenicity, toxicity, physicochemical analysis, and global population coverage of the entire epitopes and final construct were carefully examined. The study involved using various bioinformatic web tools to accomplish the following tasks: modeling the three-dimensional structure of a set of epitopes and the final construct and docking them with Toll-Like Receptor 4 (TLR4). In the experimental phase, the final multi-epitope construct was synthesized using the solid phase method, and it was then enclosed in lipid nanoparticles. After synthesizing the construct, its loading, average size distribution, and nanoliposome shape were checked using Nanodrop at 280 nm, dynamic light scattering (DLS), and atomic force microscope (AFM). The designed vaccine has been confirmed to be non-toxic and anti-allergic. It can bind with different MHC alleles at a rate of 99.05%. The construct loading was determined to be about 91%, with an average size of 54 nm. Spherical shapes were also observed in the AFM images. Further laboratory tests are necessary to confirm the safety and immunogenicity of the multi-epitope vaccine.

The immune factors have complex causal regulation effects on kidney stone disease: a mendelian randomization study

PURPOSE

Previous studies have reported the potential impact of immune cells on kidney stone disease (KSD), but definitive causal relationships have yet to be established. The purpose of this paper is to elucidate the potential causal association between immune cells and KSD by Mendelian randomization (MR) analysis.

METHODS

In our study, a thorough two-sample Mendelian randomization (MR) analysis was performed by us to determine the potential causal relationship between immune cell traits and kidney stone disease. We included a total of four immune traits (median fluorescence intensity (MFI), relative cellular (RC), absolute cellular (AC), and morphological parameters (MP)), which are publicly available data. GWAS summary data related to KSD (9713 cases and 366,693 controls) were obtained from the FinnGen consortium. The primary MR analysis method was Inverse variance weighted. Cochran's Q test, MR Egger, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) were used to assess the stability of the results.

RESULTS

After FDR correction, the CD8 on HLA DR + CD8br (OR = 0.95, 95% CI = 0.93-0.98, p-value = 7.20 × 10- 4, q-value = 0.088) was determined to be distinctly associated with KSD, and we also found other 25 suggestive associations between immune cells and KSD, of which 13 associations were suggested as protective factors and 12 associations were suggested as risk factors. There was no horizontal pleiotropy or significant heterogeneity in our MR analysis, as determined by the p-value results of our Cochrane Q-test, MR Egger's intercept test, and MR-PRESSO, which were all > 0.05.

CONCLUSIONS

Our study has explored the potential causal connection between immune cells and KSD by Mendelian randomization analysis, thus providing some insights for future clinical studies.

Enhancing tuberculosis vaccine development: a deconvolution neural network approach for multi-epitope prediction

Tuberculosis (TB) a disease caused by Mycobacterium tuberculosis (Mtb) poses a significant threat to human life, and current BCG vaccinations only provide sporadic protection, therefore there is a need for developing efficient vaccines. Numerous immunoinformatic methods have been utilized previously, here for the first time a deep learning framework based on Deconvolutional Neural Networks (DCNN) and Bidirectional Long Short-Term Memory (DCNN-BiLSTM) was used to predict Mtb Multiepitope vaccine (MtbMEV) subunits against six Mtb H37Rv proteins. The trained model was used to design MEV within a few minutes against TB better than other machine learning models with 99.5% accuracy. The MEV has good antigenicity, and physiochemical properties, and is thermostable, soluble, and hydrophilic. The vaccine's BLAST search ruled out the possibility of autoimmune reactions. The secondary structure analysis revealed 87% coil, 10% beta, and 2% alpha helix, while the tertiary structure was highly upgraded after refinement. Molecular docking with TLR3 and TLR4 receptors showed good binding, indicating high immune reactions. Immune response simulation confirmed the generation of innate and adaptive responses. In-silico cloning revealed the vaccine is highly expressed in E. coli. The results can be further experimentally verified using various analyses to establish a candidate vaccine for future clinical trials.

A novel chimeric vaccine containing multiple epitopes for simulating robust immune activation against Klebsiella pneumoniae

BACKGROUND

Due to antibiotic resistance, the Klebsiella genus is linked to morbidity and death, necessitating the development of a universally protective vaccine against Klebsiella pathogens.

METHODS

Core sequence analysis prioritized non-redundant host molecules and expected lipid bilayer peptides from fully sequenced Klebsiella genomes. These proteins were refined to identify epitopes, examining their immunogenicity, toxicity, solubility, and interaction with MHC alleles. Epitopes were linked to CPG ODN C274 via EAAAK, HEYGAEALERAG, and GGGS linkers to enhance immunological responses. The vaccine's tertiary structure was modelled and docked with MHC-I and MHC-II.

RESULTS

Fifty-five proteins were recognized in the Vaxign collection as having remarkable features. Twenty-three proteins with potential pathogenicity were then identified. Eight options for vaccines emerged after the immunogenicity of proteins was examined. The best antigens were three proteins: MrkD, Iron-regulated lipid membrane polypeptides, and RmpA. These compounds were selected for their sensitivity. The structural protein sequences of K. pneumoniae were utilized to identify seven CTL epitopes, seven HTL epitopes, and seven LBL epitopes, respectively. The produced immunization displayed a stable contact with the receptors, based on molecular dynamic simulations lasting 250 nanoseconds. Intermolecular binding free energies also indicated the dominance of the van der Waals and electrostatic energies.

CONCLUSION

In summary, the results of this study might help scientists develop a novel vaccine to prevent K. pneumoniae infections.

Identification of potential vaccine targets for elicitation of host immune cells against SARS-CoV-2 by reverse vaccinology approach

The COVID-19 pandemic has emerged as a critical global health crisis, demanding urgent and effective strategies for containment. While some knowledge exists about epitope sequences recognized by human immune cells and their activation of CD8+ T cells within the HLA context, comprehensive information remains limited. This study employs reverse vaccinology to explore antigenic HLA-restricted T-cell epitopes capable of eliciting durable immunity. Screening reveals 187 consensus epitopes, with 23 offering broad population coverage worldwide, spanning over 5000 HLA alleles. Sequence alignment analysis highlights the genetic distinctiveness of these peptides from Homo sapiens and their intermediate to high TAP binding efficiency. Notably, these epitopes share 100 % sequence identity across strains from nine countries, indicating potential for a uniform protective immune response among diverse ethnic populations. Docking simulations further confirm their binding capacity with the HLA allele, validating them as promising targets for SARS-CoV-2 immune recognition. The anticipated epitopes are connected with suitable linkers and adjuvant, and then assessed for its translational efficacy within a bacterial expression vector through computational cloning. Through docking, it is observed that the chimeric vaccine construct forms lasting hydrogen bonds with Toll-like receptor (TLR4), while immune simulation illustrates an increased cytotoxic response aimed at CD8+ T cells. This comprehensive computational analysis suggests the chimeric vaccine construct's potential to provoke a robust immune response against SARS-CoV-2. By delineating these antigenic fragments, our study offers valuable insights into effective vaccine and immunotherapy development against COVID-19, contributing significantly to global efforts in combating this infectious threat.

Identification of the shared hub gene signatures and molecular mechanisms between HIV-1 and pulmonary arterial hypertension

The close link between HIV-1 infection and the occurrence of pulmonary arterial hypertension (PAH). However, the underlying molecular mechanisms of their interrelation remain unclear. The microarray data of HIV-1 and PAH were downloaded from GEO database. We utilized WGCNA to identify shared genes between HIV-1 and PAH, followed by conducting GO and pathway enrichment analyses. Subsequently, differentially genes analysis was performed using external validation datasets to further filter hub genes. Immunoinfiltration analysis was performed using CIBERSORT. Finally, hub gene expression was validated using scRNA-seq data. We identified 109 shared genes through WGCNA, primarily enriched in type I interferon (IFN) pathways. By taking the intersection of WGCNA important module genes and DEGs, ISG15 and IFI27 were identified as pivotal hub genes. Immunoinfiltration analysis and scRNA-seq results indicated the significant role of monocytes in the shared molecular mechanisms of HIV-1 and PAH. In summary, our study illustrated the possible mechanism of PAH secondary to HIV-1 and showed that the heightened IFN response in HIV-1 might be a crucial susceptibility factor for PAH, with monocytes being pivotal cells involved in the type I IFN response pathway. This provides potential new insights for further investigating the molecular mechanisms connecting HIV-1 and PAH.

Discovery of small molecule entry inhibitors targeting the linoleic acid binding pocket of SARS-CoV-2 spike protein

Spike glycoprotein has a significant role in the entry of SARS-CoV-2 to host cells, which makes it a potential drug target. Continued accumulation of non-synonymous mutations in the receptor binding domain of spike protein poses great challenges in identifying antiviral drugs targeting this protein. This study aims to identify potential entry inhibitors of SARS-CoV-2 using virtual screening and molecular dynamics (MD) simulations from three distinct chemical libraries including Pandemic Response Box, Drugbank and DrugCentral, comprising 6971 small molecules. The molecules were screened against a binding pocket identified in the receptor-binding domain (RBD) region of the spike protein which is known as the linoleic acid binding pocket, a highly conserved motif among several SARS-CoV-2 variants. Through virtual screening and binding free energy calculations, we identified four top-scoring compounds, MMV1579787 ([2-Oxo-2-[2-(3-phenoxyphenyl)ethylamino]ethyl]phosphonic acid), Tretinoin, MMV1633963 ((2E,4E)-5-[3-(3,5-dichlorophenoxy)phenyl]penta-2,4-dienoic acid) and Polydatin, which were previously reported to have antibacterial, antifungal or antiviral properties. These molecules showed stable binding on MD simulations over 100 ns and maintained stable interactions with TYR365, PHE338, PHE342, PHE377, TYR369, PHE374 and LEU368 of the spike protein RBD that are found to be conserved among SARS-CoV-2 variants. Our findings were further validated with free energy landscape, principal component analysis and dynamic cross-correlation analysis. Our in silico analysis of binding mode and MD simulation analyses suggest that the identified compounds may impede viral entrance by interacting with the linoleic acid binding site of the spike protein of SARS-CoV-2 regardless of its variants, and they thus demand for further in vitro and in vivo research.Communicated by Ramaswamy H. Sarma.

In silico approaches for the identification of potential allergens among hypothetical proteins from Alternaria alternata and its functional annotation

Direct exposure to the fungal species Alternaria alternata is a major risk factor for the development of asthma, allergic rhinitis, and inflammation. As of November 23rd 2020, the NCBI protein database showed 11,227 proteins from A. alternata genome as hypothetical proteins (HPs). Allergens are the main causative of several life-threatening diseases, especially in fungal infections. Therefore, the main aim of the study is to identify the potentially allergenic inducible proteins from the HPs in A. alternata and their associated functional assignment for the complete understanding of the complex biological systems at the molecular level. AlgPred and Structural Database of Allergenic Proteins (SDAP) were used for the prediction of potential allergens from the HPs of A. alternata. While analyzing the proteome data, 29 potential allergens were predicted by AlgPred and further screening in SDAP confirmed the allergic response of 10 proteins. Extensive bioinformatics tools including protein family classification, sequence-function relationship, protein motif discovery, pathway interactions, and intrinsic features from the amino acid sequence were used to successfully predict the probable functions of the 10 HPs. The functions of the HPs are characterized as chitin-binding, ribosomal protein P1, thaumatin, glycosyl hydrolase, and NOB1 proteins. The subcellular localization and signal peptide prediction of these 10 proteins has further provided additional information on localization and function. The allergens prediction and functional annotation of the 10 proteins may facilitate a better understanding of the allergenic mechanism of A. alternata in asthma and other diseases. The functional domain level insights and predicted structural features of the allergenic proteins help to understand the pathogenesis and host immune tolerance. The outcomes of the study would aid in the development of specific drugs to combat A. alternata infections.

Construction of an aerolysin-based multi-epitope vaccine against Aeromonas hydrophila: an in silico machine learning and artificial intelligence-supported approach

Aeromonas hydrophila, a gram-negative coccobacillus bacterium, can cause various infections in humans, including septic arthritis, diarrhea (traveler's diarrhea), gastroenteritis, skin and wound infections, meningitis, fulminating septicemia, enterocolitis, peritonitis, and endocarditis. It frequently occurs in aquatic environments and readily contacts humans, leading to high infection rates. This bacterium has exhibited resistance to numerous commercial antibiotics, and no vaccine has yet been developed. Aiming to combat the alarmingly high infection rate, this study utilizes in silico techniques to design a multi-epitope vaccine (MEV) candidate against this bacterium based on its aerolysin toxin, which is the most toxic and highly conserved virulence factor among the Aeromonas species. After retrieval, aerolysin was processed for B-cell and T-cell epitope mapping. Once filtered for toxicity, antigenicity, allergenicity, and solubility, the chosen epitopes were combined with an adjuvant and specific linkers to create a vaccine construct. These linkers and the adjuvant enhance the MEV's ability to elicit robust immune responses. Analyses of the predicted and improved vaccine structure revealed that 75.5%, 19.8%, and 1.3% of its amino acids occupy the most favored, additional allowed, and generously allowed regions, respectively, while its ERRAT score reached nearly 70%. Docking simulations showed the MEV exhibiting the highest interaction and binding energies (-1,023.4 kcal/mol, -923.2 kcal/mol, and -988.3 kcal/mol) with TLR-4, MHC-I, and MHC-II receptors. Further molecular dynamics simulations demonstrated the docked complexes' remarkable stability and maximum interactions, i.e., uniform RMSD, fluctuated RMSF, and lowest binding net energy. In silico models also predict the vaccine will stimulate a variety of immunological pathways following administration. These analyses suggest the vaccine's efficacy in inducing robust immune responses against A. hydrophila. With high solubility and no predicted allergic responses or toxicity, it appears safe for administration in both healthy and A. hydrophila-infected individuals.

In silico assessment of a natural small molecule as an inhibitor of programmed death ligand 1 for cancer immunotherapy: a computational approach

Programmed cell death ligand 1 (PD-L1) is a crucial target for cancer therapy. Here, an in silico study investigates PD-L1 to inhibit its interaction with PD1, thereby promoting an immune response to eliminate cancer cells. The study employed machine learning (ML) -based QSAR to detect PDL1 inhibitors. Morgan's fingerprint with docking score showed a 0.83 correlation with the experimental IC50, enabling the screening of 3200 natural compounds. The top three compounds, considered 2819, 2821 and 3188, were selected from the ML-based QSAR and subjected to molecular docking and simulation. The binding scores for 2819, 2821 and 3188 were -7.0, -9.0 and -8.9 kcal/mol, respectively. The stability of the ligands during a 100 ns simulation was assessed using RMSD, showing that 2819 and 2821 maintained stable patterns comparable to the control inhibitor. Notably, 2819 exhibited a consistent stable pattern throughout the simulation, while 2821 showed stability in the last 40 ns. The control compound showed the highest number of hydrogen bonds with proteins, whereas compounds 2819 and 2821 formed continuous H-bonds. 3188 was separated from the protein in later phases and is not regarded as a potential PD-L1-binding molecule. MMGBSA binding free energy for complexes was computed. Control had the lowest binding free energy, while 2819 and 2821 also had lower binding energies. In contrast, 3188 showed poor binding free energy, causing protein separation. Principal component analysis showed a loss of entropy and reduced protein conformational variation. Overall, 2819 and 2821 are potential binders for PD-L1 inhibition and immune response triggering.Communicated by Ramaswamy H. Sarma.

Structure-based evaluation of the envelope domain III-nonstructural protein 1 (EDIII-NS1) fusion as a dengue virus vaccine candidate

The lack of effective medicines or vaccines, combined with climate change and other environmental factors, annually subjects a significant proportion of the world's inhabitants to the risk of dengue virus (DENV) infection. These conditions increase the likelihood of exposure to mosquito-borne diseases such as dengue fever. Hence, many research approaches tend to develop efficient vaccine candidates against the dengue virus. Therefore, we used immunoinformatics and bioinformatics to design a construction for developing a candidate vaccine against dengue virus serotypes. In this study, the in silico structure, containing the non-structural protein 1 region (NS1) (consensus and epitope), the envelope domain III protein (EDIII) as the structural part of the virus construction, and the bc-loop of envelope domain II (EDII) as the neutralizing and protected epitope, were employed. We utilized in silico tools to enhance the immunogenicity and effectiveness of dengue virus vaccine candidates. Evaluations included refining and validating physicochemical characteristics, B and T-cell epitopes, homology modeling, and the three-dimensional structure to assess the designed vaccine's quality. In silico results for tertiary structure prediction and validation revealed high-quality modeling for all vaccine constructs. Additionally, the instructed model demonstrated stability throughout molecular dynamics simulation. The results of the immune simulation suggested that the titers of IgG and IgM could be raised to desirable values following injection into in vivo models. It can be concluded that the designed construct effectively induce humoral and cellular immunity and can be proposed as effective vaccine candidate against four dengue serotypes.Communicated by Ramaswamy H. Sarma.

Immunoinformatics-driven approach for development of potential multi-epitope vaccine against the secreted protein FlaC of Campylobacter jejuni

Campylobacter jejuni causes a leading human gastrointestinal infection which is associated with foodborne diarrhea, stomach cramping, and fever. In the recent years, numerous multidrug-resistant strains of C. jejuni has evolved and is considered in the priority pathogens category. Therefore, an increasing demand exists to develop an effective vaccine against Campylobacteriosis. The T cell and B cell epitopes from the FlaC protein were predicted using comprehensive immunoinformatics tools. The predicted epitopes were chosen based on their antigenicity, allergenicity, and toxicity profiles. Using the bioinformatics approach various physicochemical properties of the constructed vaccine were determined. The molecular docking analysis of the vaccine with the TLRs demonstrated that TLR5 has a higher binding affinity of -1159.0 kcal/mol. Molecular dynamics simulation has confirmed the stable association of the vaccine with TLR5. The immune response of the constructed vaccine was validated using immunostimulation. Based on this study, we recommend the formulation of a multi-epitope vaccine as a promising agent to effectively combat the dreadful campylobacteriosis infection.Communicated by Ramaswamy H. Sarma.

Inhibition of respiratory syncytial virus by Daclatasvir and its derivatives: synthesis of computational derivatives as a new drug development

The most common cause of respiratory tract illness in newborns and young children is the respiratory syncytial virus (RSV). There is no approved vaccination or specific antiviral medication for RSV infections. Here, an attempt has been made to explore the potential of currently marketed drugs as well as their probable derivatives to improve the possibility of developing stronger medications against RSV. From the 100 synthetic drug compounds library, the best drug molecule was identified through drug-likeness properties, toxicity, molecular docking and molecular dynamics simulations. Molecular Mechanics Generalized Born Surface Area (MM-GBSA) was also a method that was applied in this study. Daclatasvir showed the highest binding energy and appeared as the best drug to inhibit matrix protein and a fusion protein of RSV. Based on Daclatasvir, 40 computational derivatives were made. D28, D34 and D40 showed far better results than the actual drug. Changes in lipophilicity character increase the binding energy of derivatives. Molecular dynamic simulations showed their non-deviated, non-fluctuated and stable complex formation with target proteins. The high number of amino acid contacts throughout the trajectory increases the stability and effectiveness of derivatives. The key to producing a novel medicine to eradicate RSV is provided by derivatives. Daclatasvir will be employed as a potential RSV inhibitor up until that point.Communicated by Ramaswamy H. Sarma.

Epitopes mapping for identification of potential cross-reactive peptide against leptospirosis

Leptospira, the pathogenic helical spirochetes that cause leptospirosis, is an emerging zoonotic disease with effective dissemination tactics in the host and can infect humans and animals with moderate or severe illnesses. Thus, peptide-based vaccines may be the most effective strategy to manage the immune response against Leptospira to close these gaps. In the current investigation, highly immunogenic proteins from the proteome of Leptospira interorgan serogroup Icterohaemorrhagie serovar Lai strain 56601 were identified using immunoinformatic methods. It was discovered that the conserved and most immunogenic outer membrane Lepin protein was both antigenic and non-allergenic by testing 15 linear B-cells and the ten best T-cell (Helper-lymphocyte (HTL) with the most significant number of HLA-DR binding alleles and the eight cytotoxic T lymphocyte (CTL)) epitopes. Furthermore, a 3D structural model of CTL epitopes was created using the Pep-Fold3 platform. Using the Autodock 4.2 docking server, research was conducted to determine how well the top-ranked CTL peptide models attach to HLA-A*0201 (PDB ID: 4U6Y). With HLA-A*0201, the epitope SSGTGNLHV binds with a binding energy of -1.29 kcal/mol. Utilizing molecular dynamics modeling, the projected epitope-allele docked complex structure was optimized, and the stability of the complex system was assessed. Therefore, this epitope can trigger an immunological response and produce effective Leptospira vaccine candidates. Overall, this study offers a unique vaccination candidate and may encourage additional research into leptospirosis vaccines.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.

Reverse vaccinology & immunoinformatics approach to design a multiepitope vaccine (CV3Ag-antiMRSA) against methicillin resistant Staphylococcus aureus (MRSA) - a pathogen affecting both human and animal health

Infections caused by drug resistant bacteria is a silent detrimental pandemic affecting the global health care profoundly. Methicillin resistant Staphylococcus aureus (MRSA) is a pathogen that causes serious infections in different settings (community, hospital & veterinary) whose treatment remains highly challenging due to its powerful characteristics (antibiotic resistance strategies, virulence factors). In this study, we used reverse vaccinology (RV) approach and designed an immunogenic multi epitope vaccine (CV3Ag-antiMRSA) targeting three potential antigen candidates viz., mecA encoding transpeptidase (PBP2a) protein responsible for conferring methicillin resistance and two virulence determinants - hlgA encoding gamma-hemolysin component A (a pore forming toxin) and isdB encoding iron regulated surface determinant B (heme transport component that allows S. aureus to scavenge iron from host hemoglobin and myoglobin). We employed an array of immunoinformatic tools/server to identify and use immunogenic epitopes (B cell and MHC class) to develop the chimeric subunit vaccine V4 (CV3Ag-antiMRSA) with immune modulating adjuvant and linkers. Based on different parameters, the vaccine construct V4 (CV3Ag-antiMRSA) was determined to be suitable vaccine (antigenic and non-allergen). Molecular docking and simulation of CV3Ag-antiMRSA with Toll Like Receptor (TLR2) predicted its immuno-stimulating potential. Finally, in silico cloning of CV3Ag-antiMRSA construct into pet28a and pet30 vector displayed its feasibility for the heterologous expression in the E. coli expression system. This vaccine candidate (CV3Ag-antiMRSA) designed based on the MRSA genomes obtained from both animal and human hosts can be experimentally validated and thereby contribute to vaccine development to impart protection to both animal and human health.Communicated by Ramaswamy H. Sarma.

Designing a novel multi-epitopes pan-vaccine against SARS-CoV-2 and seasonal influenza: in silico and immunoinformatics approach

The merger of COVID-19 and seasonal influenza infections is considered a potentially serious threat to public health. These two viral agents can cause extensive and severe lower and upper respiratory tract infections with lung damage with host factors. Today, the development of vaccination has been shown to reduce the risk of hospitalization and mortality from the COVID-19 virus and influenza epidemics. Therefore, this study contributes to an immunoinformatics approach to producing a vaccine that can elicit strong and specific immune responses against COVID-19 and influenza A and B viruses. The NCBI, GISAID, and Uniprot databases were used to retrieve sequences. Linear B cell, Cytotoxic T lymphocyte, and Helper T lymphocyte epitopes were predicted using the online servers. Population coverage of MHC I epitopes worldwide for SARS-CoV-2, Influenza virus H3N2, H3N2, and Yamagata/Victoria were 99.93%, 68.67%, 68.38%, and 85.45%, respectively. Candidate epitopes were linked by GGGGS, GPGPG, and KK linkers. Different epitopes were permutated several times to form different peptides and then screened for antigenicity, allergenicity, and toxicity. The vaccine construct was analyzed for physicochemical properties, conformational B-cell epitopes, interaction with Toll-like receptors, and IFN-gamma-induced. Immune stimulation response of final construct was evaluated using C-IMMSIM. Eventually, the final construct sequence was codon-optimized for Escherichia coli K12 and Homo sapiens to design a multi-epitope vaccine and mRNA vaccine. In conclusion, due to the variable nature of SARS-CoV-2 and influenza proteins, the design of a multi-epitope vaccine can protect against all their standard variants, but laboratory validation is required.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.