Biology subjects

Nain, Z.

Publications and source records attributed to Nain, Z..

3 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

Structural Basis and Designing of Peptide Vaccine using PE-PGRS Family Protein of Mycobacterium ulcerans - An Integrated Vaccinomics Approach

Buruli ulcer is an emerging-necrotizing skin infection, responsible for permanent deformity if untreated, caused by the pathogen Mycobacterium ulcerans (M. ulcerans). Despite this debilitating condition, no specific disease-modifying therapeutics or vaccination is available. Therefore, we aimed to design an effective multi-epitope vaccine against M. ulcerans through an integrated vaccinomics approach. Briefly, the highest antigenic PE-PGRS protein was selected from which the promiscuous T- and B-cell epitopes were predicted. After rigorous assessment, 15 promising CTL, HTL and LBL epitopes were selected. The identified T-cell epitopes showed marked interactions towards the HLA binding alleles and provided 99.8% world population coverage. Consequently, a vaccine chimera was designed by connecting these epitopes with suitable linkers and adjuvant (LprG). The vaccine construct was antigenic and immunogenic as well as non-allergenic; hence, subjected to homology modelling. The molecular docking and dynamic simulation revealed strong and stable binding affinity between the vaccine and TLR2 receptor. The binding energy ({Delta}G) and dissociation constant (Kd) were -15.3 kcal/mol and 5.9x10-12 M, respectively. Further, disulfide engineering was applied to improve vaccine stability and higher expression in Escherichia coli K12 system was ensured by codon optimization and cloning in silico. The computer-simulated immune responses were characterized by higher levels of IgM and IgG antibodies, helper T-cells with increased IFN-{gamma} production, and macrophage activity crucial for immunity against M. ulcerans. Therefore, our data suggest that, if the designed vaccine is validated experimentally, it will prevent Buruli ulcer by generating robust immune response against M. ulcerans.

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↗