Development of a candidate mRNA vaccine based on Multi-Peptide targeting VP4 of rotavirus A: an immunoinformatics and molecular dynamics approach

Abstract

Rotavirus (RV) is a common double-stranded RNA virus that causes diarrheal disease in young children. The prevalent species, Rotavirus A (RVA), is responsible for over 90% of human RV infections. With significant morbidity and mortality, this pathogen poses a serious global health challenge, particularly in underdeveloped countries. This study presents an immunoinformatics approach for designing an mRNA vaccine based on a multi-peptide construct to elicit robust immune responses against RVA. The VP4 was analyzed from 40 sequences using phylogenetic analysis. Prediction of cytotoxic (CTL) and helper T cell (HTL) epitopes was performed and validated. The 17 high-conservancy CTL/HTL epitopes were selected for vaccine construction. The mRNA vaccine based on multi-peptide was engineered with human beta-defensin 3 (hBD3) adjuvant and linkers to enhance immunogenicity. The designed mRNA vaccine product exhibited favorable physicochemical properties and was predicted to be a probable antigen, non-allergenic, and non-toxic. 2D and 3D structure validation demonstrated the quality of the model. Molecular docking with Toll-like receptor 2/3 (TLR2/3) indicated favorable interaction, and peptide docking with MHC-I/II alleles showed strong binding affinities and have significant Residue-Residue interactions. Simulation of immune responses revealed potent B-cell and T-cell activities, macrophage responses, and significant cytokine synthesis. Molecular dynamics simulation (MDS) confirmed the structural stability of the TLR3-vaccine complex, and MHC-peptide in 200ns and STQFTDFVSLNSLRF peptide have shown good interaction with MHC molecule. In addition, the MM/GBSA analysis yielded a binding free energy of - 89.77 kcal/mol, indicating a strong and stable interaction between the vaccine construct and the target receptor. Codon optimization and mRNA secondary structure prediction were carried out for efficient translation. Additionally, population coverage analysis indicated the vaccine's effectiveness worldwide with 100% value. Overall, this study showcases a promising immunoinformatics approach for designing an mRNA vaccine based on a multi-peptide construct targeting RVA. The findings support the potential of this vaccine design to elicit robust and widespread immune responses against RVA infection, paving the way for future vaccine development strategies and this study needs experimental validation.

Keywords: Computational immunology; Immunoinformatics; Molecular dynamics simulation; Multi-peptide; Rotavirus A; mRNA vaccine.

Fig. 1

The workflow of the study demonstrated the immunoinformatics approaches.

Fig. 2

(A) The secondary structure of multi-peptide that used PSIPRED server. (B) The detailed percent of secondary structure (Alpha helix, strand, Beta turn, and coil) (C) The 3D model of the final vaccine construct.

Fig. 3

The validation of vaccine 3D structure. (A) The Ramachandran plot (B) Z-score of 3D structure with 5.91 scores followed by ProSA-web. (C) The ERRAT plot showed an overall quality factor of 96.94 score.

Fig. 4

The result of molecular docking. (A) The TLR3 and multi-peptide vaccine docking (Blue: TLR3, Cyan: multi-peptide vaccine). (B) The TLR2 and multi-peptide vaccine result (Red: TLR2, Cyan: multi-peptide vaccine). The interaction analysis of molecular docking showed the residue’s contact, ion bridge, and hydrogen bond. The number of residues that have interaction (Chain A: TLR2/3, Chain B: multi-peptide vaccine).

Fig. 5

Visualization of MHC alleles and MHC I/II peptide docking. (A) The SFDDISAAV epitope and HLA-A*68:01 (Cyan) (B) The KYGGRIWTF epitope and HLA-A*24:02 allele (Green) (C) The STQFTDFVSLNSLRF epitope and HLA-DRB1*04:01 allele (Purple). The interaction of the peptide and MHC molecules is visualized by the PDBsum tool.

Fig. 6

(A) Alpha carbon: Root mean square deviation (RMSD) (B) Root mean square fluctuation (C) Radius of Gyration (D) Solvent- Accessible surface area (SASA) (E) Hydrogen bond (H-bond) (F) Free energy landscape (FEL). The definition of the secondary structure of the protein (DSSP) was used to analyze the 2D structure of the complex. (G) The TLR3 secondary structure (H) The multi-peptide vaccine secondary structure.

Fig. 7

The Molecular dynamics simulation of MHC-peptide. (A) RMSD (B) Rg (C) SASA (D) H-bond number (E) RMSF for MHC molecules (F) RMSF for peptide. (Peptide 1: STQFTDFVSLNSLRF, Peptide 2: KYGGRIWTF, Peptide 3: SFDDISAAV).

Fig. 8

(A) The general structure of mRNA vaccine that consists of 5’UTR, Kozak sequence, signal peptide, and multi-peptide. 3’UTR, and PolyA. In addition, the epitopes and linkers were demonstrated. (B) The secondary structure of mRNA vaccine and the 5’ of mRNA structure.

Fig. 9

The 3D structure of mRNA vaccine and molecular dynamics simulation analysis. (A) The tertiary structure and detailed position of mRNA vaccine. (B) The RMSD (C) RMSF (D) SASA.

Fig. 10

The computational immune response of multi-peptide vaccine that injected 5 doses. (A) The relation of antigen concentration and antibody responses showed the efficiency of vaccines that have high concentration of IgG. (B) indicates the equivalent number of antibody-producing plasma cells. (C-E) The HTL, CTL, and macrophage responses. (F) The releasing cytokines.