Bioinformatics analysis of the in silico engineered protein vaccine with and without Escherichia coli heat labile enterotoxin adjuvant on the model of Klebsiella pneumoniae

Klebsiella pneumoniae (K. pneumoniae) has been identified as a major cause of nosocomial infections with multidrug-resistant phenotypes. Vaccination is one of the most effective methods to prevent infectious diseases. We aim to design a vaccine candidate based on the epitope-rich domains of the OmpA, OMPK17, and fimb proteins of K. pneumoniae that could protect against this infection. A vaccine structure was constructed by selecting five epitope-rich domains from three proteins. We decided to add the heat-labile toxin (LT) of Escherichia coli as an adjuvant to the designed protein structure. The evaluation of the vaccine candidates' interaction with the immune system's receptors showed an appropriate interaction of the specially adjuvated protein with TLR2 and TLR4. The stability of the interactions was also studied by molecular dynamics (MD) for to 100 ns. All parameters showed that the structure of the candidate proteins alone and in complex with TLR2 and TLR4 are stable, especially the adjuvanted protein. Immune response simulations showed that both candidates induce acceptable protective immune responses. Overall, the LT-adjuvanted design protein may have the potential to induce more favorable protective immune responses. However, further in vitro and in vivo studies are required to obtain more definitive results.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-03-01
DOI
https://doi.org/10.1038/s41598-025-91602-y
Citations
2
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
1.61
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bioinformatics analysis of the in silico engineered protein vaccine with and without Escherichia coli heat labile enterotoxin adjuvant on the model of Klebsiella pneumoniae

Behzad Shahbazi, Parisa Sarkoohi, Khadijeh Ahmadi, Maryam Babaei et al.
2 citations
Scientific Reports
vaccines and immunoinformatics approaches
1.61
article

Bioinformatics analysis of the in silico engineered protein vaccine with and without Escherichia coli heat labile enterotoxin adjuvant on the model of Klebsiella pneumoniae

Behzad Shahbazi, Parisa Sarkoohi, Khadijeh Ahmadi, Maryam Babaei, Kimia Jafari Ranjbar
article en
2 citations

Abstract

Klebsiella pneumoniae (K. pneumoniae) has been identified as a major cause of nosocomial infections with multidrug-resistant phenotypes. Vaccination is one of the most effective methods to prevent infectious diseases. We aim to design a vaccine candidate based on the epitope-rich domains of the OmpA, OMPK17, and fimb proteins of K. pneumoniae that could protect against this infection. A vaccine structure was constructed by selecting five epitope-rich domains from three proteins. We decided to add the heat-labile toxin (LT) of Escherichia coli as an adjuvant to the designed protein structure. The evaluation of the vaccine candidates' interaction with the immune system's receptors showed an appropriate interaction of the specially adjuvated protein with TLR2 and TLR4. The stability of the interactions was also studied by molecular dynamics (MD) for to 100 ns. All parameters showed that the structure of the candidate proteins alone and in complex with TLR2 and TLR4 are stable, especially the adjuvanted protein. Immune response simulations showed that both candidates induce acceptable protective immune responses. Overall, the LT-adjuvanted design protein may have the potential to induce more favorable protective immune responses. However, further in vitro and in vivo studies are required to obtain more definitive results.

Scientific ReportsVol. 15(1)
Hormozgan University of Medical Sciences (IR), Semnan University of Medical Sciences (IR), Bushehr University of Medical Sciences (IR)
Zero hunger
Openalex Percentile: Top 19%
vaccines and immunoinformatics approaches
1.61
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.