Computational design of a fimbriae-derived multi-epitope vaccine candidate against <i>Klebsiella pneumoniae</i>

<i>Klebsiella pneumoniae</i> is a pathogen that causes infections in various parts of the body, with high mortality rates reported in antibiotic-resistant cases. Treating at-risk individuals requires crucial vaccination efforts due to the challenges that exist. This research involved designing a multi-epitope vaccine from <i>K. pneumoniae</i>'s fimbriae antigens. Optimal T-cell and B-cell epitopes were chosen through <i>in silico</i> studies including epitope-HLAs molecular docking. The multi-epitope was created, featuring antigenic T- and B-cell epitopes, β-defensin as an adjuvant, the PADRE sequence to boost immunogenicity and well-suited linkers. The tertiary structure of the multi-epitope was achieved through modeling and molecular dynamics-based refinements. The construct underwent scrutiny for structural traits, physicochemical properties, conformational B epitope prediction, immune responses simulation, <i>in silico</i> cloning, molecular docking for assay binding to toll-like receptors (TLRs), and deformability studies. The outcomes indicated the vaccine candidate's positive attributes, encompassing immunogenicity, structure, physicochemical properties, solubility, TLR binding, toxicity, stability, allergenicity, and cross-reactivity. The multi-epitope vaccine candidate exhibits the potential for provoking diverse immune responses against <i>K. pneumoniae</i>. Nevertheless, additional <i>in vitro</i> and <i>in vivo</i> experimental tests are necessary to substantiate its efficacy.

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Publication Details

Journal
Journal of Biomolecular Structure and Dynamics
Published
2025-03-08
DOI
https://doi.org/10.1080/07391102.2025.2472407
Citations
1
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
0.81
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article

Computational design of a fimbriae-derived multi-epitope vaccine candidate against Klebsiella pneumoniae

Hana Heidarinia, Salar Khaledian, Tarek A. Ahmad, Farjam Goudarzi et al.
1 citations
Journal of Biomolecular Structure and Dynamics
vaccines and immunoinformatics approaches
0.81
article

Computational design of a fimbriae-derived multi-epitope vaccine candidate against Klebsiella pneumoniae

Hana Heidarinia, Salar Khaledian, Tarek A. Ahmad, Farjam Goudarzi, Mosayeb Rostamian, Keyghobad Ghadiri, Roya Chegene Lorestani
article en
1 citations

Abstract

<i>Klebsiella pneumoniae</i> is a pathogen that causes infections in various parts of the body, with high mortality rates reported in antibiotic-resistant cases. Treating at-risk individuals requires crucial vaccination efforts due to the challenges that exist. This research involved designing a multi-epitope vaccine from <i>K. pneumoniae</i>'s fimbriae antigens. Optimal T-cell and B-cell epitopes were chosen through <i>in silico</i> studies including epitope-HLAs molecular docking. The multi-epitope was created, featuring antigenic T- and B-cell epitopes, β-defensin as an adjuvant, the PADRE sequence to boost immunogenicity and well-suited linkers. The tertiary structure of the multi-epitope was achieved through modeling and molecular dynamics-based refinements. The construct underwent scrutiny for structural traits, physicochemical properties, conformational B epitope prediction, immune responses simulation, <i>in silico</i> cloning, molecular docking for assay binding to toll-like receptors (TLRs), and deformability studies. The outcomes indicated the vaccine candidate's positive attributes, encompassing immunogenicity, structure, physicochemical properties, solubility, TLR binding, toxicity, stability, allergenicity, and cross-reactivity. The multi-epitope vaccine candidate exhibits the potential for provoking diverse immune responses against <i>K. pneumoniae</i>. Nevertheless, additional <i>in vitro</i> and <i>in vivo</i> experimental tests are necessary to substantiate its efficacy.

Journal of Biomolecular Structure and DynamicsVol. 43(18)
Bibliotheca Alexandrina (EG), Kermanshah University of Medical Sciences (IR), Islamic Azad University of Shahrekord (IR)
Zero hunger
Openalex Percentile: Top 30%
vaccines and immunoinformatics approaches
0.81
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