Literature DB >> 31709929

Proteome-wide screening for designing a multi-epitope vaccine against emerging pathogen Elizabethkingia anophelis using immunoinformatic approaches.

Zulkar Nain1, Faruq Abdulla2, M Mizanur Rahman1, Mohammad Minnatul Karim1, Md Shakil Ahmed Khan1, Sifat Bin Sayed1, Shafi Mahmud3, S M Raihan Rahman1, Md Moinuddin Sheam1, Zahurul Haque1, Utpal Kumar Adhikari4.   

Abstract

Elizabethkingia anophelis is an emerging human pathogen causing neonatal meningitis, catheter-associated infections and nosocomial outbreaks with high mortality rates. Besides, they are resistant to most antibiotics used in empirical therapy. In this study, therefore, we used immunoinformatic approaches to design a prophylactic peptide vaccine against E. anophelis as an alternative preventive measure. Initially, cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes were predicted from the highest antigenic protein. The CTL and HTL epitopes together had a population coverage of 99.97% around the world. Eventually, six CTL, seven HTL, and two LBL epitopes were selected and used to construct a multi-epitope vaccine. The vaccine protein was found to be highly immunogenic, non-allergenic, and non-toxic. Codon adaptation and in silico cloning were performed to ensure better expression within E. coli K12 host system. The stability of the vaccine structure was also improved by disulphide bridging. In addition, molecular docking and dynamics simulation revealed strong and stable binding affinity between the vaccine and toll-like receptor 4 (TLR4) molecule. The immune simulation showed higher levels of T-cell and B-cell activities which was in coherence with actual immune response. Repeated exposure simulation resulted in higher clonal selection and faster antigen clearance. Nevertheless, experimental validation is required to ensure the immunogenic potency and safety of this vaccine to control E. anophelis infection in the future.Communicated by Ramaswamy H. Sarma.

Entities:  

Keywords:  Elizabethkingia anophelis; dynamics simulation; immune simulation; immunoinformatics; multi-epitope vaccine

Mesh:

Substances:

Year:  2019        PMID: 31709929     DOI: 10.1080/07391102.2019.1692072

Source DB:  PubMed          Journal:  J Biomol Struct Dyn        ISSN: 0739-1102


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