Biology subjects

Sayed, S. B.

Publications and source records attributed to Sayed, S. B..

2 recordsLinked to original sources

bioRxiv2019

Computational Approach for Screening the Whole Proteome of Hantavirus and Designing a Multi-Epitope Subunit Vaccine

Hantaviruses are a newly zoonotic emerging group of rodent-borne viruses that have a significant impact on global public health by increasing amplitude and magnitude of outbreaks. As no permanent cure yet, it is now growing and challenging interest to develop a vaccine against Hantavirus. This study endeavored to design a robust subunit vaccine using a novel immunoinformatics approach. After meticulous evaluation, top ones from predicted CTL, HTL, and B-cell epitopes were considered as potential vaccine candidates. Among generated four vaccine models with different adjuvant, the model with TLR-4 agonist adjuvant was selected for its high antigenicity, non-allergenicity, and structural quality. The conformational B-cell epitope prediction assured its humoral response inducing ability. Thereafter, the molecular docking and dynamics simulation confirmed a good binding affinity with immune receptor TLR-4 and stability of the vaccine-receptor complex. In immune simulation, significantly high levels of IgM and IgG1 immunoglobulins, TC and TH-cell populations, and various cytokines (i.e. IFN-{gamma}, IL-2 etc.) are coherence with actual immune response and also showed faster antigen clearance for repeated exposures. Finally, disulfide engineering enhanced vaccine stability and in silico cloning confirmed the better expression in E. coli K12. Nonetheless, experimental validation can proof the proposed vaccines safety and ability to control Hantavirus infection.

bioinformatics↗

bioRxiv2019

Immunoinformatic and dynamic simulation-based designing of a multi-epitope vaccine against emerging pathogen Elizabethkingia anophelis

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 an epitope-based vaccine against E. anophelis as an alternative preventive measure. Initially, T-cell (CTL and HTL) and B-cell (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, 6 CTL, 7 HTL, and 2 LBL epitopes were selected and used to construct a multiepitope 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 dynamic simulation revealed good and stable binding affinity between the vaccine and receptor. 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.

bioinformatics↗