Designing of a Multi-epitope Vaccine against the Structural Proteins of Marburg Virus Exploiting the Immunoinformatics Approach

Abstract

Marburg virus disease (MVD) caused by the Marburg virus (MARV) generally appears with flu-like symptoms and leads to severe hemorrhagic fever. It spreads via direct contact with infected individuals or animals. Despite being considered to be less threatening in terms of appearances and the number of infected patients, the high fatality rate of this pathogenic virus is a major concern. Until now, no vaccine has been developed to combat this deadly virus. Therefore, vaccination for this virus is necessary to reduce its mortality. Our current investigation focuses on the design and formulation of a multi-epitope vaccine based on the structural proteins of MARV employing immunoinformatics approaches. The screening of potential T-cell and B-cell epitopes from the seven structural proteins of MARV was carried out through specific selection parameters. Afterward, we compiled the shortlisted epitopes by attaching them to an appropriate adjuvant and linkers. Population coverage analysis, conservancy analysis, and MHC cluster analysis of the shortlisted epitopes were satisfactory. Importantly, physicochemical characteristics, human homology assessment, and structure validation of the vaccine construct delineated convenient outcomes. We implemented disulfide bond engineering to stabilize the tertiary or quaternary interactions. Furthermore, stability and physical movements of the vaccine protein were explored using normal-mode analysis. The immune simulation study of the vaccine complexes also exhibited significant results. Additionally, the protein–protein docking and molecular dynamics simulation of the final construct exhibited a higher affinity toward toll-like receptor-4 (TLR4). From simulation trajectories, multiple descriptors, namely, root mean square deviations (rmsd), radius of gyration (Rg), root mean square fluctuations (RMSF), solvent-accessible surface area (SASA), and hydrogen bonds, have been taken into account to demonstrate the inflexible and rigid nature of receptor molecules and the constructed vaccine. Inclusively, our findings suggested the vaccine constructs’ ability to regulate promising immune responses against MARV pathogenesis.

Design of a multi-epitope vaccine against SARS-CoV-2: immunoinformatic and computational methods

“… 111,112 During the prediction of spike glycoprotein epitopes, the server encompasses biological data of vaccine candidates. 111,113 Vary recent study Sami et al 114 used the VaxiJen server for assessing antigenicity of Marburg virus epitopes and they proposed a vaccine candidate that has the ability to generate an immune response against viral pathogenesis. The chemical and physical properties of the vaccine constructs were assessed by ExPASy.…”

In silico Designing of an Epitope-Based Vaccine Against Common E. coli Pathotypes

“…Firstly, EAAAK was employed to improve the bi-functional catalytic activity, give stiffness in addition to enhancing fusion protein stability (93). The second linker, GPGPG, was selected for its ability to induce HTL immune response and the ability to break the junctional immunogenicity, resulting in individual epitopes' restoration of immunogenicity (94). The final linker, KK, was employed because of its ability to bring the pH value close to the physiological range (95).…”

“…In addition to the epitopes, linkers, and adjuvant, the PADRE sequence was also added as it has been revealed that this sequence could minimize the polymorphism of HLA molecules in the population (96). Analyzing the results of the multitope vaccine assessment showed that, the current potential vaccine construct is antigenic with an antigenicity score of 1.07 which was more than the corresponding scores of the designed multitope vaccines against severe acute respiratory syndrome coronavirus 2 (97), Marburg virus (94), and Leptospira (98). Regarding the population coverage, the world coverage showed 100% for the constructed vaccine and that was similar to the corresponding coverage reported in (99).…”

Exploring whole proteome to contrive multi-epitope-based vaccine for NeoCoV: An immunoinformtics and in-silico approach

“…By activating innate immunity cells and attracting naïve T cells through the chemokine receptor CCR-6, β-defensin peptides stimulate innate immunity cells ( 91 ). The maturation of dendritic cells, HTLs, CTLs, and IFN-γ-producing cells is induced by the 50S ribosomal protein L7/L12 when naive T-cells are stimulated ( 61 ). HBHA is a novel TLR4 agonist with minimal systemic toxicity, in addition to possessing a strong immunostimulatory potential and the potential to induce dendritic cells maturation in a TLR4-dependent manner ( 92 ).…”

“…This server employs machine learning algorithms and a position-specific scoring matrix (PSSM) to predict epitope and assess immunological interactivities ( 60 ). The immunological simulation was carried out according to the procedure described elsewhere ( 61 ). For 1050 simulation steps (about 12 months), three in-silico doses were given at suggested 4-week intervals and at time steps of 1, 84, and 170 (one time step is 8 hours of everyday living).…”