Immunoinformatic Identification of Multiple Epitopes of gp120 Protein of HIV-1 to Enhance the Immune Response against HIV-1 Infection

Abstract

Acquired Immunodeficiency Syndrome is caused by the Human Immunodeficiency Virus (HIV), and a significant number of fatalities occur annually. There is a dire need to develop an effective vaccine against HIV-1. Understanding the structural proteins of viruses helps in designing a vaccine based on immunogenic peptides. In the current experiment, we identified gp120 epitopes using bioinformatic epitope prediction tools, molecular docking, and MD simulations. The Gb-1 peptide was considered an adjuvant. Consecutive sequences of GTG, GSG, GGTGG, and GGGGS linkers were used to bind the B cell, Cytotoxic T Lymphocytes (CTL), and Helper T Lymphocytes (HTL) epitopes. The final vaccine construct consisted of 315 amino acids and is expected to be a recombinant protein of approximately 35.49 kDa. Based on docking experiments, molecular dynamics simulations, and tertiary structure validation, the analysis of the modeled protein indicates that it possesses a stable structure and can interact with Toll-like receptors. The analysis demonstrates that the proposed vaccine can provoke an immunological response by activating T and B cells, as well as stimulating the release of IgA and IgG antibodies. This vaccine shows potential for HIV-1 prophylaxis. The in-silico design suggests that multiple-epitope constructs can be used as potentially effective immunogens for HIV-1 vaccine development.

Keywords: HIV-1; epitope; gp120; in silico.

Figure 1

B-cell epitopes were identified using various IEDB epitope servers. Epitopes exhibiting positive interactions are highlighted in yellow. (A) The surface accessibility of B-cell epitopes was assessed using the Emini tool. (B) The flexibility of selected epitopes was evaluated using the Karplus & Schulz tool. (C) The antigenic potential of the final epitopes was observed using the Kolaskar & Tongaonkar method. (D) The hydrophilicity of epitopes was examined using the Parker method. The residues with scores higher than the threshold were predicted to be part of an epitope, as indicated in yellow.

Figure 2

The final vaccine construct displays a three-dimensional representation of conformational or discontinuous epitopes (a–j) found within the highest antigenic polyprotein of gp120. The epitopes are depicted on the surface using various colors, while the bulk of the polyprotein is represented as sky blue sticks.

Figure 3

The population coverage (%) related to the selected epitopes’ HLA binding alleles was considered, taking into account both worldwide and average percentages. (a) For MHC class I restricted alleles, the selected epitopes represent a population coverage of 90.23% worldwide. (b) For MHC class II restricted alleles, the selected epitopes represent a population coverage of 72.95% worldwide. In the graph, the line (-o-) illustrates the cumulative percentage of population coverage for epitopes, while the bars depict the coverage for each individual epitope.

Figure 4

Cluster analysis was performed on the HLA alleles for both MHC molecules, represented through a heat map. (a) The cluster of the MHC-I (VTVYYGVPVW, RAKWNNTLK, SVNFTDNAK, APTKAKRRVV, FNSTWFNSTW, GVAPTKAKR, KVQKEYAFFY, QKEYAFFYKL, TIGKIGNMR, and WQKVGKAMY) epitopes was represented. (b) The cluster of the MHC-II molecules (EIKNCSFNISTSIRG, EPLGVAPTKAKRRVV, FYKLDIIPIDNDTTS, GKVQKEYAFFYKLDI, INCTRPNNNTRKRIR, and GFAILKCNNKTFNGT) epitopes was represented.

Figure 5

The sequences, locations, and representations of the immunodominant B-cell, CTL, and HTL epitopes in the final vaccine construct, as well as the 3D view and locations of the immunodominant epitopes of the gp120 monomer, are shown. (a) The sequences and positions of the immunodominant epitopes are depicted in a cartoon shape. (b) The immunodominant epitopes are represented in a 3D view using the PyMOL 2.3.4 program. The surface representation shows the locations of the immunodominant epitopes on the closed conformation of the 3D gp120 protein of HIV-1.

Figure 6

Representation of the HIV-1 gp120 construct schematic diagram, including B-cell, CTL, and HTL epitopes, linkers, and adjuvants. The Histidine-Tag is connected to the B-cell epitopes through a GTG linker. The B-cell epitopes are connected to the CTL epitopes using GGTGG linkers. The CTL epitopes, in turn, are connected to the HTL epitopes using GGGGS linkers. Finally, the HTL epitopes are connected to the adjuvant through a GTG linker.

Figure 7

Graphical representation of the secondary structure features of the final vaccine construct. The alpha helix residues are in pink, the beta strand residues are in yellow, and the coil residues are in grey. Upon analyzing the predicted secondary structure, it is revealed that the final vaccine comprises 10.2% alpha helix, 22.6% beta strand, and 60.2% coil.

Figure 8

Disorder regions in the secondary structure of the designed vaccine predicted via the PSIPRED Tool. This tool has provided valuable insights into the secondary structure of the designed vaccine. In particular, it has identified disorder regions within the protein sequence. According to the analysis, amino acids in the input sequence are considered disordered when the dotted line exceeds the cutoff value of 0.5, representing the confidence threshold.

Figure 9

Representation and Validation of the HIV-1 gp120 vaccine using in silico tools. (a) The HIV-1 gp120 vaccine construct was modeled in 3D, employing refined parameters through Galaxy Refine. (b) Prosa-web generated the Z-score and local model quality energy score, providing validation for our 3D vaccine construct. (c) The Ramachandran plot, associated with the vaccine’s 3D structure post-refinement, further validated the accuracy of our vaccine design. Additionally, the 3D prediction was verified through Verify 3D, indicating that the vaccine structure achieved a remarkable 92.70% residue score.

Figure 10

Stability of the vaccine construct through disulfide bond engineering. (a) The original form of the vaccine construct is represented without any mutations. (b) In the mutant form of the vaccine construct, six pairs of amino acids, including Gly11-Gln73, Ala122-Asn125, Trp153-Asp308, and Lys202-Tyr205, are depicted in yellow sticks. These specific amino acid pairs have undergone modifications to incorporate disulfide bonds.

Figure 11

Molecular docking of the TLR-2 complex and vaccine construct. (a) A cartoon representation of the Vaccine TLR-complex is depicted, with the TLR component shown in a vibrant magenta color, while the vaccine complex is represented in a striking cyan color. (b) Multiple interaction views of the TLR-2 and vaccine complex are generated using PyMOL. The interaction residues of the TLR-2 and vaccine complex are displayed in distinct colors, highlighting their respective roles in the binding interface.

Figure 12

This figure illustrates the binding interaction between the active residues of a docked complex involving human TLR-2 and a vaccine construct. (a) In this complex, chain A represents the active residues of TLR-2, while chain B represents the active residues of the vaccine construct. (b) The docked conformation and interaction of TLR-2 and the vaccine construct are depicted via Ligplot analysis, highlighting the presence of hydrogen bonding and hydrophobic interactions between the construct.

Figure 13

Molecular docking analysis was conducted to investigate the interaction between the HIV-1 gp120 vaccine construct and human toll-like receptors (TLRs). Cluspro was utilized to identify the docking regions between the vaccine construct and the TLRs. The figure displays the docking interaction between vaccine construct and TLRs, with a closer view of the interaction. (b) represents a closer view of TLR-3, while (d) depicts a closer view of TLR-4. Similarly, (f) illustrates a closer view of TLR-5, (h) portrays TLR-8 in closer detail, and (j) presents a closer view of TLR-9.

Figure 14

The vaccine−TLR-2 docked complex underwent molecular dynamics simulation. (a) A main-chain deformability simulation was performed, identifying regions with high deformability known as hinges. (b) B-factor values were calculated using normal mode analysis, providing a measure of uncertainty for each atom. (c) The eigenvalue of the docked complex was determined, indicating the energy required to deform the structure. (d) The covariance matrix between pairs of residues was analyzed, with red indicating correlation, white indicating no correlation, and blue indicating anti-correlation. (e,f) An elastic network model was generated to visualize the connections between atoms and springs. The springs are more rigid if their shades of grey are darker.

Figure 15

mRNA structure of the HIV-1 gp120 vaccine construct. The mRNA structure of the HIV-1 gp120 vaccine construct was determined using the RNAfold servers. The prediction yielded a minimal free energy score of −378.55 kcal/mol, indicating the stability of the vaccine design’s mRNA structure.

Figure 16

C−ImmSimm represents the immune stimulation of the best-predicted HIV-1 gp120 vaccine. (a) The immunoglobulin and immunocomplex responses to the HIV-1 gp120 vaccine inoculations are indicated by colored lines. (b–h) The number of plasma B cells, HTLs, and CTLs exhibited progressive increases, indicating the robust development of an immune response characterized by high potency, immunological memory, and efficient removal of antigens from the host. (i–l) The increase in DCs and macrophages exhibited greater antigen presentation by APCs, and the activation of helper T cells demonstrated the superior adaptive immunity of the vaccine. (m,n) The vaccine was shown to be capable of inducing the production of IFN-γ, IL-23, IL-10, IL-8 and IL-6, which are vital for triggering immune feedback and protecting the body against viruses.

Figure 16

C−ImmSimm represents the immune stimulation of the best-predicted HIV-1 gp120 vaccine. (a) The immunoglobulin and immunocomplex responses to the HIV-1 gp120 vaccine inoculations are indicated by colored lines. (b–h) The number of plasma B cells, HTLs, and CTLs exhibited progressive increases, indicating the robust development of an immune response characterized by high potency, immunological memory, and efficient removal of antigens from the host. (i–l) The increase in DCs and macrophages exhibited greater antigen presentation by APCs, and the activation of helper T cells demonstrated the superior adaptive immunity of the vaccine. (m,n) The vaccine was shown to be capable of inducing the production of IFN-γ, IL-23, IL-10, IL-8 and IL-6, which are vital for triggering immune feedback and protecting the body against viruses.