Immunoinformatics and molecular dynamics studies to predict T-cell-specific epitopes of four Klebsiella pneumoniae fimbriae antigens

Abstract

Klebsiella pneumoniae (K. pneumoniae) is a causative agent of severe infections in humans. There is no publically available vaccine for K. pneumoniae infections yet. Here, using comprehensive immunoinformatics methods, T-cell-specific epitopes of four type 1 fimbriae antigens of K. pneumoniae were predicted and evaluated as potential vaccine candidates. Both CD8+ (class I) and CD4+ (class II) T-cell-specific epitopes were predicted and the epitopes similar to human proteome were excluded. Subsequently, the windows of class-II epitopes containing class-I epitopes were determined. The immunogenicity, IFN-γ production and population coverage were also estimated. Using the 3D structure of HLA and epitopes, molecular docking was carried out. Two best epitopes were selected for molecular dynamics studies. Our prediction and analyses resulted in the several dominant epitopes for each antigen. The docking results showed that all selected epitopes can bind to their restricted HLA molecules with high affinity. The molecular dynamics results indicated the stability of system with minimum possible deviation, suggesting the selected epitopes can be promising candidates for stably binding to HLA molecules. Altogether, our results suggest that the selected T-cell-specific epitopes of K. pneumoniae fimbriae antigens, particularly the two epitopes confirmed by molecular dynamics, can be applied for vaccine development. However, the in vitro and in vivo studies are required to authenticate the results of the present study.

Communicated by Ramaswamy H. Sarma

Keywords:

• Klebsiella pneumoniae
• vaccine
• immunoinformatics
• type 1 fimbriae
• T-cell-specific epitope
• molecular dynamics

Acknowledgements

The supported of this work by Infectious Diseases Research Center of Kermanshah University of Medical Sciences and Clinical Research Development Center of Imam Reza Hospital is highly appreciated.

Disclosure statement

No potential conflicts of interest we disclosed.

Credit authorship contribution statement

Mosayeb Rostamian: Conceptualization, methodology, data curation, writing – review and editing.

Alireza Farasat: Methodology, data curation, roles/writing – original draft.

Roya Chegene Lorestani: Data curation, software.

Fatemeh Nemati Zargaran: Data curation, software.

Keyghobad Ghadiri: Funding acquisition, resources.

Alisha Akya: Project administration, supervision, writing – review and editing.

Additional information

Funding

This research was financially supported by the Kermanshah University of Medical Sciences.