Multi Epitopic Peptide Based Vaccine Development Targeting Immobilization Antigen of Ichthyophthirius multifiliis: A Computational Approach

Abstract

The white spot disease causes significant damage to global aquaculture production. A prominent vaccine, eliciting the immunogenicity of freshwater fishes against Ichthyophthirius multifiliis yet to be developed. Thus, an Immunoinformatic drive was implemented to find out the potential epitopes from the surface immobilization antigens. B-cell derived T-cell epitopes are promiscuous elements for new generation peptide-based vaccine designing. A total of eight common B and T-cell epitopes had filtered out with no overlapping manner. Subsequently, the common epitopes are linked up with EAAAKEAAAKEAAAK linker peptides, we also added L7/L12 ribosomal protein adjuvant at the N- terminal side of peptide sequence for eliciting the immune response in a better way. The secondary and tertiary structural properties of the modeled 3D protein revealed that the protein had all the properties required for a protective immunogen. Afterward, three globally used validation server: PROCKECK, ProSA and ERRAT were used to justify the proper coordinate. NMR, Crystallographic range and error plot calculation for vaccine model also been done respectively. This was followed by molecular docking, MD simulation, NMA analysis, in silico cloning and vaccine dose-based immune response simulation to evaluate the immunogenic potency of the vaccine construct. The in silico immune simulation in response to multi-epitopes show antibody generation and elevated levels of cell-mediated immunity during repeated exposure of the vaccine. The favourable results of the in silico analysis significantly specify that the vaccine construct is really a powerful vaccine candidate and ready to proceed to the next steps of experimental validation and efficacy studies.

Supplementary information: The online version contains supplementary material available at 10.1007/s10989-022-10475-1.

Keywords: B-cell; Docking; Immunoinformatics; MD simulation; NMA; Spot disease; T-cell.

Fig. 1

Schematic representation of the workflow for the development of multi-epitope vaccine against parasite Ichthyophthirius multifiliis

Fig. 2

The threshold level (antigenicity) of top B-cell linear epitopes

Fig. 3

Graphical representation of T − cell epitopes along with binding alleles

Fig. 4

The tertiary structure of the designed vaccine construct

Fig. 5

Structural arrangement of the final vaccine construct

Fig. 6

Solubility index of Vaccine construct showing in the plot

Fig. 7

Probability score graph of occurrence of helix (Purple), strand (Green), turn (Red), and coil (Light blue) at each amino acid position in the secondary structure of the final Vaccine construct. Each residue position is characterized by the greater probability score associated secondary structure

Fig. 8

Validation of the tertiary structure of the vaccine. A The Ramachandran plot statistics represent the most favorable, accepted, and disallowed regions with a percentage of 96.8%, 2.8%, and 0.5%, respectively, B Local quality assessment plot C The ProSA-web representing the Z-score of − 0.93 for the vaccine model. D ERRAT error plot showing percentage of error of the vaccine model protein

Fig. 9

Molecular docking between the vaccine and the TLR-2 receptor

Fig. 10

Molecular dynamics simulation A Root mean square deviation (RMSD) B root mean square fluctuation (RMSF) analysis of protein backbone and side chain residues of MD simulated vaccine construct C Radius of Gyration (Rg) plot in during MD simulation and D SASA plot

Fig. 11

Molecular dynamics analysis of vaccine protein-TLR2 complex; stability of the protein–protein complex was investigated through A NMA mobility showing with arrows B B-factor values C deformability plot D eigen value E covariance of residue index F Variance map and G elastic network analysis

Fig. 12

In silico immune response simulation of the multi-epitope-based vaccine construct. a Production of immuno globulins upon antigen exposure, b Population of B lymphocytes after three injections, c Population of B-cell per cell state, d cytotoxic T lymphocytes population, e Amount of Cytotoxic T lymphocytes population per state, f Population of Natural Killer cells, g Population of Macrophages, h Population of Dendritic cells, i Concentration of cytokines and interleukins with Simpson index [D]

Fig. 12

In silico immune response simulation of the multi-epitope-based vaccine construct. a Production of immuno globulins upon antigen exposure, b Population of B lymphocytes after three injections, c Population of B-cell per cell state, d cytotoxic T lymphocytes population, e Amount of Cytotoxic T lymphocytes population per state, f Population of Natural Killer cells, g Population of Macrophages, h Population of Dendritic cells, i Concentration of cytokines and interleukins with Simpson index [D]

Fig. 13

In silico restriction cloning of the multi-epitope vaccine sequence into the pET28a (+) expression vector. The red region represents the vaccine coding gene and the black circle represents the vector backbone