A computational approach to design a polyvalent vaccine against human respiratory syncytial virus

Abstract

Human Respiratory Syncytial Virus (RSV) is one of the leading causes of lower respiratory tract infections (LRTI), responsible for infecting people from all age groups-a majority of which comprises infants and children. Primarily, severe RSV infections are accountable for multitudes of deaths worldwide, predominantly of children, every year. Despite several efforts to develop a vaccine against RSV as a potential countermeasure, there has been no approved or licensed vaccine available yet, to control the RSV infection effectively. Therefore, through the utilization of immunoinformatics tools, a computational approach was taken in this study, to design a multi-epitope polyvalent vaccine against two major antigenic subtypes of RSV, RSV-A and RSV-B. Potential predictions of the T-cell and B-cell epitopes were followed by extensive tests of antigenicity, allergenicity, toxicity, conservancy, homology to human proteome, transmembrane topology, and cytokine-inducing ability. The peptide vaccine was modeled, refined, and validated. Molecular docking analysis with specific Toll-like receptors (TLRs) revealed excellent interactions with suitable global binding energies. Additionally, molecular dynamics (MD) simulation ensured the stability of the docking interactions between the vaccine and TLRs. Mechanistic approaches to imitate and predict the potential immune response generated by the administration of vaccines were determined through immune simulations. Subsequent mass production of the vaccine peptide was evaluated; however, there remains a necessity for further in vitro and in vivo experiments to validate its efficacy against RSV infections.

Figure 1

The result of the population coverage analysis of the most promising epitopes and their selected MHC alleles.

Figure 2

Designing of the vaccine construct. (A) Schematic representation of the potential vaccine construct with linkers (EAAAK, AAY, GPGPG, and KK), PADRE sequence, adjuvant (hBD-3) and epitopes (CTL, HTL, and LBL) in a sequential and appropriate manner. (B) Sequence of the vaccine protein. The letters in bold represent the linker sequences.

Figure 3

The results of the secondary structure prediction of the vaccine. (A) PRISPRED prediction, (B) GOR IV prediction, (C) SOPMA prediction, (D) SIMPA96 prediction.

Figure 4

Prediction, refinement and validation of the tertiary structure of vaccine. (A) The tertiary or 3D structure of the vaccine construct modelled, refined and visualized by RaptorX, GalaxyWEB server, and BIOVIA Discovery Studio Visualizer v. 17.2 respectively. (B) The results of the Ramachandran plot analysis generated by PROCHECK server and (C) quality score or z-score graph generated by the ProSA-web server of the refined vaccine construct. In the Ramachandran plots, the orange and deep yellow coloured regions are the allowed regions, the light yellow regions are the generously allowed regions and the white regions are the outlier regions and the glycine residues are represented as triangles.

Figure 5

Graphical representations of the predicted conformational B-cell epitopes of the modelled vaccine indicated by yellow coloured ball-shaped structures.

Figure 6

Snapshots of equilibrated (initial) systems and last trajectories. Vaccine bound complexes of (A) TLR1, (B) TLR2, (C) TLR3, (D) TLR4, and (E) TLR9 (For each snapshot the surface representation and cartoon representations are shown).

Figure 7

Results of the molecular dynamics simulation studies. (A) Root mean square deviations in the investigated systems, (B) Root mean square fluctuations in the side chain atoms of vaccine, and (C) Radius of gyration of the vaccine.

Figure 8

C-IMMSIMM representation of the immune simulation of the designed vaccine construct. (A) The immunoglobulin and immunocomplex response to the vaccine inoculations (lines hued in black) and specific subclasses are indicated by coloured lines, (B,C) elevation of the B-cell population throughout the three injections, (D) rise in the plasma B-cell population throughout the injections, (E,F) elevation of the helper T-cell population throughout the three injections, (G) decrease in the regulatory T lymphocyte concentration throughout the three injections, (H,I) augmentation in the cytotoxic T lymphocyte population throughout the injections, (J,K) augmentation in the population of active dendritic cell and macrophage respectively, per state throughout the three injections, (L) Rise in the concentration of different types of cytokines throughout the three injections.

Figure 9

In-silico cloning of the vaccine sequence in the pETite plasmid vector. The codon sequence of the final vaccine is presented in red generated by the JCat server. The pETite expression vector is in black.

Figure 10

The step-by-step procedures of immunoinformatics and molecular dynamics approaches used in the vaccine designing study.