Immuno-informatics analyses of important esophageal cancer associated viruses for multi-epitope vaccine design

Abstract

Introduction: Esophageal cancer (EC) is a highly lethal malignancy characterized by the uncontrolled proliferation of cancerous cells within the esophagus. Despite recent advancements in therapeutic strategies, the prognosis remains poor, underscoring the urgent need for novel preventive and therapeutic approaches. Notably, several oncogenic viruses have been implicated in EC pathogenesis, prompting the exploration of epitope-based vaccines through immunoinformatics.

Methods: Using immunoinformatics and bioinformatics approaches, we designed a novel multi-epitope vaccine targeting viral agents associated with EC. Protein sequences of ten viral candidates were retrieved from the UniProt database and evaluated for antigenicity using the VaxiJen server. Five highly antigenic proteins derived from Human Cytomegalovirus (HCMV), Human Papillomavirus (HPV), Human Herpesvirus 8 (HHV-8), Human Immunodeficiency Virus (HIV), and Epstein-Barr Virus (EBV) were selected. T cell (CTL and HTL) and B cell (LBL) epitopes were predicted and screened for immunogenicity, allergenicity, and toxicity. The final vaccine construct incorporated β-defensin as an adjuvant and included 3 HTL, 8 CTL, and 8 LBL epitopes. Molecular docking and molecular dynamics (MD) simulations were conducted to assess the binding affinity of the vaccine with Toll-like receptor 3 (TLR3). In silico cloning was also performed using the pET-28a(+) vector in Escherichia coli strain K12.

Results: The designed vaccine was found to be antigenic, non-allergenic, and non-toxic. Molecular docking revealed strong binding affinity between the vaccine construct and TLR3, which was further supported by MD simulation results indicating stable complex formation. Codon optimization and in silico cloning confirmed the high expression potential of the vaccine in the E. coli expression system.

Discussion: The in silico analyses suggest that the developed multi-epitope vaccine construct is a promising candidate for preventing EC associated with viral infections. While these findings are encouraging, further experimental validation through in vitro and in vivo studies is essential to confirm the vaccine's safety, immunogenicity, and protective efficacy.

Keywords: Epstein-Barr virus (EBV); esophageal cancer; human cytomegalovirus (hcmv); human papillomavirus (HPV); molecular docking simulation; multi-epitope vaccine.

Figure 1

Graphical abstract.

Figure 2

Population coverage graph of the designed vaccine construct.

Figure 3

The designed vaccine construct is shown schematically.

Figure 4

Structural modeling and validation of the multi-epitope vaccine construct (A) Tertiary structure of vaccine predicted using 3dpro (B) Vaccine sequence with adjuvant and linkers highlighted (C, F) Ramachandran plots before and after refinement respectively (D, G) Prosa-web Z-score plots showing model quality before and after refinement (E, H) ERRAT quality factor plots before and after refinement, conforming improved structural reliability.

Figure 5

Conformational B cell epitopes of vaccine. (A-G) Presents the different B-Cell Epitopes with different colours.

Figure 6

Disulfide engineering of vaccine construct improves stability. A mutant pair selected based on X3 value and energy is shown by the color blue.

Figure 7

The vaccine’s immune profile. (A) Immunoglobulin concentrations in relation to antigens (B) Population of B-cell (C) Population of B-cell per state (D) Population of plasma B-cell (E) helper T-cell population (F) Population of helper T-cell per state (G) Cytotoxic T-cell population (H) Population of cytotoxic T-cell per state (I) T-regulatory cells reduced levels (J) Population of dendritic per state (K) Population of macrophage per state (L) The Simpson index of cytokine and interleukin production.

Figure 8

TLR-3 receptor and vaccine docked. TLR3 is shown in blue, while the vaccine is shown in rainbow colors. (A) 3D Structure visualization (B) Interaction analysis between vaccine and TLR3 (C) Docking score and common contacts (D) Energy calculations and RMSD (E) Haddock score and RMSD (F, G) Energy analysis including electrostatic, van deer waals.

Figure 9

Molecular dynamic simulation analysis (A) Secondary structure analysis (SSA): This panel illustrates the dynamic changes in the secondary structure elements (α-helices, β-strands, and loops) of the protein throughout the simulation time. The color-coded representation allows for an easy visual interpretation of the stability and transitions between different secondary structures (B) Root mean square deviation (RMSD): The RMSD plot depicts the deviation of the protein’s backbone atoms over the course of the simulation. The RMSD values are stable, fluctuating within a narrow range of 1 to 1.5 Å, indicating that the protein structure remains stable throughout the simulation (C) Root mean square fluctuation (RMSF): The RMSF plot shows the flexibility of individual residues during the simulation. Most residues exhibit minor fluctuations, with the majority maintaining stability. Notable minor fluctuations are observed between residues 250 to 300, which may correspond to flexible regions or loop areas of the protein (D) Residue index vs. secondary structure elements (SSE): This panel provides a detailed view of the secondary structure assignment for each residue throughout the simulation. It highlights the regions of the protein that maintain their secondary structure or undergo transitions, offering insights into the dynamic behavior of specific segments.

Figure 10

Cloning the vaccine in silico using the pET28a (+) expression vector. Cloned region is highlighted by red color.