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A computational approach to developing a multi-epitope vaccine for combating Pseudomonas aeruginosa-induced pneumonia and sepsis.

ABSTRACT: Pseudomonas aeruginosa is a complex nosocomial infectious agent responsible for numerous illnesses, with its growing resistance variations complicating treatment development. Studies have emphasized the importance of virulence factors OprE and OprF in pathogenesis, highlighting their potential as vaccine candidates. In this study, B-cell, MHC-I, and MHC-II epitopes were identified, and molecular linkers were active to join these epitopes with an appropriate adjuvant to construct a vaccine. Computational tools were employed to forecast the tertiary framework, characteristics, and also to confirm the vaccine's composition. The potency was weighed through population coverage analysis and immune simulation. This project aims to create a multi-epitope vaccine to reduce P. aeruginosa-related illness and mortality using immunoinformatics resources. The ultimate complex has been determined to be stable, soluble, antigenic, and non-allergenic upon inspection of its physicochemical and immunological properties. Additionally, the protein exhibited acidic and hydrophilic characteristics. The Ramachandran plot, ProSA-web, ERRAT, and Verify3D were employed to ensure the final model's authenticity once the protein's three-dimensional structure had been established and refined. The vaccine model showed a significant binding score and stability when interacting with MHC receptors. Population coverage analysis indicated a global coverage rate of 83.40%, with the USA having the highest coverage rate, exceeding 90%. Moreover, the vaccine sequence underwent codon optimization before being cloned into the Escherichia coli plasmid vector pET-28a (+) at the EcoRI and EcoRV restriction sites. Our research has developed a vaccine against P. aeruginosa that has strong binding affinity and worldwide coverage, offering an acceptable way to mitigate nosocomial infections.

SUBMITTER: Roy SK

PROVIDER: S-EPMC11318047 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

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A computational approach to developing a multi-epitope vaccine for combating Pseudomonas aeruginosa-induced pneumonia and sepsis.

Roy Suronjit Kumar SK Biswas Mohammad Shahangir MS Foyzur Raman Md M Hasan Rubait R Rahmann Zahidur Z Uddin P K Md Moyen MM

Briefings in bioinformatics 20240701 5

Pseudomonas aeruginosa is a complex nosocomial infectious agent responsible for numerous illnesses, with its growing resistance variations complicating treatment development. Studies have emphasized the importance of virulence factors OprE and OprF in pathogenesis, highlighting their potential as vaccine candidates. In this study, B-cell, MHC-I, and MHC-II epitopes were identified, and molecular linkers were active to join these epitopes with an appropriate adjuvant to construct a vaccine. Compu ...[more]

PMID: 39133098

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Project description:Multidrug-resistant Pseudomonas aeruginosa is one of the worldwide health problems involved in elevated mortality and morbidity. Therefore, it is important to find a therapeutic for this pathogen. In the present study, we have designed a chimeric vaccine against P. aeruginosa with the help of comparative proteomics and reverse vaccinology approaches. Using comparative subtractive proteomic analysis of 1,191 proteomes of P. aeruginosa, a total of twenty unique non-redundant proteomes were selected. In these proteomes, fifteen outer membrane proteins (OMPs) of P. aeruginosa were selected based on the basis of hydrophilicity, non-secretory nature, low transmembrane helix (<1), essentiality, virulence, pathway association, antigenic, and protein-protein network analysis. Reverse vaccinology approach was used to identify antigenic and immunogenic MHC class I, MHC class II and B cell epitopes present in the selected OMPs that can enhance T cell and B cell mediated immunogenicity. The selected epitopes were shortlisted based on their allergenicity, toxicity potentials, solubility, and hydrophilicity analysis. Immunogenic peptides were used to design a multi-epitope vaccine construct. Immune-modulating adjuvants and PADRE (Pan HLA-DR epitopes) sequence were added with epitopes sequence to enhance the immunogenicity. All the epitopes, adjuvants and PADRE sequence were joined by linkers. The designed vaccine constructs (VT1, VT2, VT3, and VT4) were analyzed by their physiochemical properties using different tools. Selected chimeric vaccine constructs (VT1, VT3, and VT4) were further shortlisted by their docking score with different HLA alleles. The final selected VT4 construct was docked with TLR4/MD2 complex and confirmed by molecular dynamics simulation studies. The final vaccine VT-4 construct was in-silico cloned in pET28a. Therefore, the designed construct VT4 may be studied to control the interaction of P. aeruginosa with host and infection caused by P. aeruginosa.

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

Project description:Helicobacter pylori is a gram-negative bacterium that persistently infects the human stomach, leading to peptic ulcers, gastritis, and an increased risk of gastric cancer. The extremophilic characteristics of this bacterium make it resistant to current drug treatments, and there are no licensed vaccines available against H. pylori. Computational approaches offer a viable alternative for designing antigenic, stable, and safe vaccines to control infections caused by this pathogen. In this study, we employed an immunoinformatic strategy to design a set of candidate multi-epitope subunit vaccines by combining the most potent B and T cell epitopes from three targeted antigenic proteins (BabA, CagA, and VacA). Out of the 12 hypothetical vaccines generated, two (HP_VaX_V1 and HP_VaX_V2) were found to be strongly immunogenic, non-allergenic, and structurally stable. The proposed vaccine candidates were evaluated based on population coverage, molecular docking, immune simulations, codon adaptation, secondary mRNA structure, and in silico cloning. The vaccine candidates exhibited antigenic scores of 1.19 and 1.01, with 93.5% and 90.4% of the most rama-favored regions, respectively. HP_VaX_V1 and HP_VaX_V2 exhibited the strongest binding affinity towards TLR-7 and TLR-8, as determined by molecular docking simulations (ΔG = -20.3 and -20.9, respectively). Afterward, multi-scale normal mode analysis simulation revealed the structural flexibility and stability of vaccine candidates. Additionally, immune simulations showed elevated levels of cell-mediated immunity, while repeated exposure simulations indicated rapid antigen clearance. Finally, in silico cloning was performed using the expression vector pET28a (+) with optimized restriction sites to develop a viable strategy for large-scale production of the chosen vaccine constructs. These analyses suggest that the proposed vaccines may elicit potent immune responses against H. pylori, but laboratory validation is needed to verify their safety and immunogenicity.

Project description:BackgroundThe World Health Organization has categorized Acinetobacter baumannii (A. baumannii) as a critical priority pathogen due to its high antibiotic resistance. This resistance complicates treatment and underscores the urgent need for new antibiotics and strategies. This study developed a multi-epitope vaccine (MEV) to address this significant public health threat.MethodsThis study employed a computational approach to design MEV targeting A. baumannii strain VB7036. Surface-exposed proteins were identified using PSORTb and TMHMM, followed by antigenicity and allergenicity predictions using VaxiJen and AlgPred. Linear B-cell epitopes and MHC-II binding sites were predicted using BepiPred and TepiTool, while physicochemical properties were analyzed with ExPASy ProtParam and Protein-Sol. The MEV construct was validated through molecular docking with TLR2 and TLR4 using HDOCK, revealing strong binding interactions. Molecular dynamic simulations confirmed the stability of the vaccine-receptor complexes, while PCA analysis indicated minimal conformational transitions. Immune simulations were conducted using C-ImmSim online software.ResultsThis study identified eight OMPs from A. baumannii strain VB7036 as potential immunogenic targets. MEV was designed using five critical B-cell epitopes from four proteins based on their antigenicity, non-allergenicity, and physicochemical properties. This MEV demonstrated strong binding to TLR2 and TLR4, indicating effective immune activation. Molecular dynamics simulations confirmed the structural stability of the MEV-TLR complexes. In silico immune simulations revealed that the MEV induced robust humoral and cell-mediated immune responses, including increased antibody production, T-cell activation, and cytokine release, suggesting the MEV's potential as an effective vaccine candidate for A. baumannii.ConclusionThis study developed an optimized MEV and identified novel drug targets against A. baumannii, providing broad protection against multidrug-resistant A. baumannii strains. MEV demonstrated significant potential due to its favorable physicochemical properties, as confirmed by molecular docking and dynamic simulations. However, more in vitro and in vivo studies are required to verify the drug's effectiveness.

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

Dataset Information

A computational approach to developing a multi-epitope vaccine for combating Pseudomonas aeruginosa-induced pneumonia and sepsis.

Publications

A computational approach to developing a multi-epitope vaccine for combating Pseudomonas aeruginosa-induced pneumonia and sepsis.

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