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A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
Published on: March 25, 2014
In silico design and assessment of a multi-epitope peptide vaccine against multidrug-resistant Acinetobacter
Shiv Nandan Sah1,2, Sumit Gupta3, Neha Bhardwaj1
1Department of Microbiology, Panjab University, Chandigarh, 160014 India.
Abstract:
Acinetobacter baumannii, an opportunistic and notorious nosocomial pathogen, is responsible for many infections affecting soft tissues, skin, lungs, bloodstream, and urinary tract, accounting for more than 722,000 cases annually. Despite the numerous advancements in therapeutic options, no approved vaccine is currently available for this particular bacterium. Consequently, this study focused on creating a rational vaccine design using bioinformatics tools. Three outer membrane proteins with immunogenic potential and properties of good vaccine candidates were used to select epitopes based on good antigenic properties, non-allergenicity, high binding scores, and a low IC50 value. A multi-epitope peptide (MEP) construct was created by sequentially linking the epitopes using suitable linkers. ClusPro 2.0 and C-ImmSim web servers were used for docking analysis with TLR2/TLR4 and immune response respectively. The Ramachandran plot showed an accurate model of the MEP with 100% residue in the most favored and allowed regions. The construct was highly antigenic, stable, non-allergenic, non-toxic, and soluble, and showed maximum population coverage. Additionally, molecular docking demonstrated strong binding between the designed MEP vaccine and TLR2/TLR4. In silico immunological simulations showed significant increases in T-cell and B-cell populations. Finally, codon optimization and in silico cloning were conducted using the pET-28a (+) plasmid vector to evaluate the efficiency of the expression of vaccine peptide in the host organism (Escherichia coli). This designed MEP vaccine would support and accelerate the laboratory work to develop a potent vaccine targeting MDR Acinetobacter baumannii.
Supplementary Information:
The online version contains supplementary material available at 10.1007/s40203-024-00292-3.
Insights
A novel multi-epitope peptide vaccine was designed using bioinformatics to combat Acinetobacter baumannii infections. This approach shows promise for developing a potent vaccine against this challenging nosocomial pathogen.
Area of Science:
- * Bioinformatics
- * Vaccinology
- * Computational Biology
Background:
- * Acinetobacter baumannii is a significant nosocomial pathogen causing numerous infections annually.
- * Current therapeutic options are limited, and no approved vaccine exists for A. baumannii.
- * There is a critical need for effective vaccine strategies against multidrug-resistant (MDR) strains.
Purpose of the Study:
- * To design a rational, multi-epitope peptide (MEP) vaccine against Acinetobacter baumannii using bioinformatics tools.
- * To identify and select immunogenic epitopes from outer membrane proteins with favorable vaccine properties.
- * To evaluate the potential efficacy and immunogenicity of the designed MEP construct in silico.
Main Methods:
- * Selection of immunogenic epitopes based on antigenicity, non-allergenicity, binding affinity, and low IC50 values.
- * Construction of a multi-epitope peptide (MEP) by linking selected epitopes.
- * In silico analysis including molecular docking with TLR2/TLR4, immune response simulation (C-ImmSim), and structural validation (Ramachandran plot).
- * Codon optimization and in silico cloning into pET-28a (+) for expression in Escherichia coli.
Main Results:
- * A stable, non-allergenic, non-toxic, and highly antigenic MEP construct was successfully designed.
- * Molecular docking confirmed strong binding affinity between the MEP vaccine and TLR2/TLR4.
- * In silico simulations predicted significant increases in T-cell and B-cell populations, indicating robust immune response.
- * In silico cloning and codon optimization suggested efficient expression in Escherichia coli.
Conclusions:
- * The designed MEP vaccine holds significant potential for combating Acinetobacter baumannii infections.
- * This bioinformatics-driven approach accelerates the development of a novel vaccine candidate.
- * Further laboratory validation is warranted to confirm the efficacy of this MEP vaccine against MDR A. baumannii.
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