Orientation of Gp96 and Calreticulin T-cell epitopes in a multiepitope HPV16 E7 vaccine construct affects predicted immunostimulatory properties: An in silico and expression validation study

Giti Esmail Nia; Zahra Shahosseini; Elahe Akbari; Hadi Bamehr; Fatemeh Heidarnejad; Monireh Mohsenzadegan; Azam Bolhassani; Mohammadmorad Farajollahi

doi:10.1371/journal.pone.0353860

Abstract

Heat shock proteins (HSPs) can be used as adjuvants to develop therapeutic vaccines, as they enhance the cross-presentation of related tumor antigens and stimulate T cells. In this study, the immunostimulatory properties of gp96 and calreticulin was evaluated to enhance HPV16 E7-based vaccines effectiveness. In silico evaluation was performed to select epitopes from HSPs based on high binding affinity to MHC-I/II, strong immunogenicity, and population coverage. Six novel multiepitope constructs harboring conserved epitopes of E7, gp96, and calreticulin were designed in different orientations. Molecular docking was performed between these constructs and signaling (TLRs) and endocytic (CD14, CD91, LOX-1, and SREC-1) receptors. After determination of an effective construct in molecular docking and MD simulation, prokaryotic expression plasmid containing eight (CTL/HTL) epitopes from HPV16 E7, gp96, and calreticulin in suitable orientation was prepared, and the recombinant multiepitope peptide was generated in E. coli system. Our data showed that the gp96-CRT-E7 construct had superior docking scores with receptors (especially TLR2 and LOX-1), suggesting stronger stimulation of both innate and adaptive immunity than other constructs. It was predicted to be non-toxic, non-allergenic, antigenic, immunogenic, and structurally stable. Moreover, the multiepitope gp96-CRT-E7 fusion peptide was expressed in the Rosetta strain under conditions of OD₆₀₀: 0.6–0.7, 0.5 mM IPTG, temperature of 18ºC, and 24 hours after IPTG induction, and purified through affinity chromatography under native conditions. Generally, successful results of in silico and expression validation of the multiepitope gp96-CRT-E7 fusion peptide showed its strong potential as a novel candidate for HPV16 vaccine development.

Citation: Esmail Nia G, Shahosseini Z, Akbari E, Bamehr H, Heidarnejad F, Mohsenzadegan M, et al. (2026) Orientation of Gp96 and Calreticulin T-cell epitopes in a multiepitope HPV16 E7 vaccine construct affects predicted immunostimulatory properties: An in silico and expression validation study. PLoS One 21(7): e0353860. https://doi.org/10.1371/journal.pone.0353860

Editor: Paulo Lee Ho, Instituto Butantan, BRAZIL

Received: October 1, 2025; Accepted: June 30, 2026; Published: July 24, 2026

Copyright: © 2026 Esmail Nia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors declare no conflict of interest. The authors declare no competing interests.

1. Introduction

Therapeutic vaccines targeting HPV-associated cancers must trigger specific cellular immune responses to tumor antigens [1]. Heat shock proteins (HSPs) are crucial chaperone proteins involved in stress responses, conserved across species. They are produced in reaction to various stimuli and are being explored as potential therapeutics. HSPs significantly influence the immune system cells and improving the antigen presentation of tumor-associated antigens (TAA) [2,3]. They are protective of cells molecules which interact with an array of proteins to maintain cellular homeostasis and can act as natural adjuvants by enhancing the uptake of tumor antigens by antigen-presenting cells (APCs) and stimulating cytotoxic T lymphocytes (CTLs). The exceptionally high adjuvant properties of HSPs is driven via receptors for HSPs that are expressed by APCs. Generally, HSPs-based vaccines have superior application prospects and more potent immunological benefits in tumor therapy as compared to conventional tumor vaccinations [4–6]. HSPs activate the innate immune system and enhance presentation of tumor antigens to adaptive immune cells, thereby evoking synergic antitumor immunity. Consequently, they have been evaluated in new anticancer strategies such as vaccines [3,7]. Gp96 (a member of the HSP90 family) and calreticulin (CRT), two heat shock proteins, have been identified as effective immunological adjuvants that bind to several receptors on APCs such as CD91, LOX-1, and SREC-1 for antigen cross-presentation in tumor immunity among HSCs [8–10]. Calreticulin acts as an immunologic adjuvant by translocating to the cell surface with tumor-associated antigens (TAAs) and promoting tumor-specific immune responses, playing a key role in antigen recognition during cancer therapy [9]. Additionally, professional APC express CD91 that binds to gp96 and mediates the uptake of gp96–peptide complexes for optimal antigen presentation, which provides a rationale to develop therapeutic vaccines [5,10].

Computational tools allow rational design of multiepitope constructs that can be experimentally validated, accelerating the development of novel vaccine candidates [11]. Furthermore, computational biology allows scientists to precisely examine biomolecule characteristics and methods of action. The main techniques commonly employed in computational biology include pharmacophore, molecular docking, and molecular dynamics simulation [12].

While HSP-based vaccines including either calreticulin or gp96 have shown promise in preclinical studies [13–15], the potential synergistic effect of combining epitopes from both adjuvants within a single construct targeting HPV16 E7 has not been systematically investigated. The HPV16 E7 oncoprotein is an ideal antigen target due to its constitutive expression in HPV-associated cancers and its role in malignant transformation [16,17]. However, the optimal spatial arrangement of adjuvant and antigen epitopes within a multiepitope construct, and how this orientation affects immunostimulatory properties remain unexplored. To address this gap, we designed six multiepitope constructs incorporating conserved T-cell epitopes from HPV16 E7, gp96, and calreticulin in different orientations. To our knowledge, this is the first study to integrate both gp96- and calreticulin-derived epitopes in a single HPV-targeted construct with systematic evaluation of orientation effects on predicted immunogenicity.

The specific objectives of this study were to: (1) identify immunogenic T-cell epitopes from gp96 and calreticulin with high MHC binding affinity and broad population coverage; (2) design six multiepitope constructs with different epitope orientations and evaluate their interactions with immune receptors; (3) select an optimal construct based on docking scores and structural stability; (4) compare the selected multiepitope construct with its full-length counterpart; and (5) experimentally validate the expression of the final candidate in E. coli.

2. Materials and methods

2.1. General overview of the study

This study employed a multi-step approach: (1) identification and selection of immunogenic T-cell epitopes from gp96 and calreticulin; (2) design of six multiepitope constructs with different orientations of gp96, CRT, and E7 epitopes; (3) selection of the optimal construct through molecular docking with immune receptors; (4) comparative immunoinformatics analysis between the selected multiepitope construct and its full-length counterpart; (5) molecular dynamics simulation to assess complex stability; and (6) experimental validation through cloning and expression in E. coli. A detailed description of the materials and methods used in this study is provided in S1 File.

2.2. Epitope prediction of gp96 and calreticulin

The reference protein sequences for human gp96 (UniProt: P14625) and calreticulin (UniProt: P27797) were gained from the UniProt database. CTL epitopes (8–11 amino acids) were predicted by NetMHCpan 4.0 with binding affinity thresholds at the 0.5th percentile for strong binders and 2nd percentile for weak binders. HTL epitopes (14–16 amino acids) were predicted using NetMHCIIpan 4.0 with thresholds at 2% for strong binders and 10% for weak binders.

MHC-I immunogenicity was evaluated for selected epitopes utilizing the IEDB Class I Immunogenicity tool, and antigen processing (proteasomal cleavage and TAP transport) were measured using the IEDB processing prediction server. Population coverage was estimated using the IEDB population coverage tool. The IEDB conservancy analysis tool was used to analyze the cross-HPV subtype epitope conservancy. Antigenicity was determined by VaxiJen v2. 0 (threshold > 0.4), allergenicity was calculated following the criteria with AllergenFP v.1 0, and toxicity using ToxinPred. Cytokine induction (IFN-γ, IL-4, IL-10) was predicted using IFNepitope, IL4Pred, and IL10Pred servers, respectively. Antibody-specific epitopes were identified using IgPred, and linear B-cell epitopes were predicted using BepiPred-2.0.

2.3. Peptide-MHC molecular docking

Flexible molecular docking between selected epitopes and MHC alleles was performed using ClusPro 2.0. PDB structures for MHC class I alleles (HLA-B27:05 [1OGT], HLA-A24:02 [5HGA], HLA-A02:01 [4UQ3], HLA-A03:01 [3RL2], HLA-B35:01 [3LKN], HLA-A11:01 [1X7Q], HLA-B08:01 [3SPV], HLA-B07:02 [5EO1]) and MHC class II alleles (HLA-DRB1:0101 [4AH2], HLA-DRB1:0301 [2Q6W], HLA-DRB1:0401 [5LAX], HLA-DRB1:1101 [6CPL], HLA-DRB5:0101 [1H15]) were obtained from the RCSB database.

2.4. Multiepitope construct design

Based on comprehensive epitope analyses, four high-scoring epitopes (two from gp96: 192–208 and 378–389; two from calreticulin: 147–173 and 164–185) were selected and linked to previously characterized HPV16 E7 epitopes(49-57, 43-52, 71-79, and 7-15) [18]. Epitopes were connected using AAY proteolytic linkers. Six constructs with different orientations were designed using SnapGene® 3.2.1: gp96-E7-CRT, E7-gp96-CRT, gp96-CRT-E7, CRT-E7-gp96, CRT-gp96-E7, and E7-CRT-gp96.

2.5. Tertiary structure prediction and refinement

Three-dimensional structures of all six constructs were predicted using the I-TASSER server. The top models (based on C-score) were refined using GalaxyRefine. Refined structures were validated using ERRAT (overall quality factor >50% indicates high quality), PROCHECK (Ramachandran plot analysis), and Verify3D (≥70% residues with score >0.1)

2.6. Protein-protein docking with immune receptors

Molecular docking between each multiepitope construct (as ligand) and toll-like receptors (TLR2 [2Z7X], TLR3 [1ZIW], TLR4 [3FXI], TLR5 [3J0A], TLR8 [3W3G], TLR9 [3WPB]) and endocytic receptors (LOX-1, SREC-1, CD91, CD14) was performed using ClusPro 2.0. The construct with the most favorable docking scores was selected as the final candidate for further analysis.

2.7. Comparative analysis with full-length construct

The full-length protein sequence comprising complete gp96, calreticulin, and E7 proteins was assembled for comparison with the selected multiepitope construct. Both constructs were evaluated for: Physicochemical properties: Molecular weight, theoretical pI, amino acid composition, instability index, and half-life using ProtParam; solubility using Protein-Sol; allergenicity using AllerTOP 2.0.Secondary structure: Predicted using PSIPRED 4.0 and RaptorX.B-cell epitopes: Linear epitopes predicted using BepiPred; discontinuous epitopes predicted using Ellipro.Disulfide bonds: Predicted using DIpro scratch protein predictor. In silico cloning: Codon optimization for E. coli using JCat; CAI and GC content analysis; cloning simulation in pET-24a(+) vector using SnapGene.

2.8. Immune simulation

The immunogenicity and immune response profile of the final multiepitope construct were predicted using the C-ImmSim server. Simulations used homozygous host haplotypes (HLA-A0101, HLA-A0201, HLA-B0702, HLA-DRB10101, HLA-DRB1*0401) with three vaccine doses administered at days 1 (priming), 84 (first booster), and 100 (second booster). This immunization schedule was selected based on typical prime-boost regimens used in therapeutic HPV vaccine studies [15,18] and a standard protocol within the C-ImmSim simulation environment.

2.9. Normal mode analysis

The iMODS server was used to evaluate the movement and stability of the final construct complexed with key receptors (TLR2, TLR4, LOX-1, SREC-1). Parameters analyzed included deformability, B-factors, eigenvalues, covariance maps, and elastic networks.

2.10. Molecular dynamics simulation

Simulations using Gromacs 2021.5 with the CHARMM-36 force field were done to obtain trajectories lasting 50 ns for each of the constructs complexed with TLR2, TLR4, LOX-1, and SREC-1. The systems were prepared by solvating in TIP3P water, neutralizing with ions, and equilibrating in both NVT and NPT simulations.

2.11. Experimental expression validation

2.11.1. Construction of expression plasmid.

The gp96-CRT-E7 gene was optimized and constructed (Shine Gene, China) in vector pUC57. Subcloning of the insert to pET-24a (+) was performed via restriction sites SalI/HindIII. Confirmation of recombinant plasmids was done by PCR, restriction digestion, and sequencing of selected colonies.

2.11.2. Protein expression.

Transformed BL21 (DE3) and Rosetta E. coli strains harboring pET-24a (+)-gp96-CRT-E7 were used for expression induction. Cultures were grown at optimal temperature 18°C or 37°C, and expression was induced by addition of 0.5 mM IPTG at OD600 = 0.6–0.7. Induction time of 4 or 24 hours was applied. Expression of the target protein was confirmed by SDS-PAGE 12.5% and Western blotting with anti-His tag antibody (Abcam, 1:10,000 v/v).

2.11.3. Protein purification.

Cells were harvested, lysed by sonication, and subjected to centrifugation. The soluble fraction was purified with native HisPur Ni-NTA affinity chromatography. Protein was dialyzed in PBS, and protein concentration was determined by Bradford assay. Endotoxin levels were determined using LAL assay (< 0.5 EU/mg; QCL-1000).

2.12. Ethics approval

Not applicable. This article does not contain any studies with human participants or animals performed by any of the authors.

3. Results

3.1. Epitope selection from gp96 and calreticulin

Initial screening identified 19 CTL epitopes (11 from calreticulin, 8 from gp96) with high MHC-I binding affinity (Table 1). From these, two CTL epitopes from each protein were selected based on superior MHC-I processing scores, immunogenicity, and non-allergenic/non-toxic profiles. The selected epitopes were calreticulin 164–185 and 147–173, and gp96 378–389 and 270–285. (Detailed MHC-I processing scores, immunogenisity antigenicity, allergenicity and toxicity data for all CTL epitopes are provided in S2 File. Supplementary Tables(1-2).

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Table 1. Selected CTL epitopes of calreticulin and gp96.

https://doi.org/10.1371/journal.pone.0353860.t001

3.1.1. HTL epitope prediction.

HTL epitope prediction identified nine epitopes (three from calreticulin, six from gp96). The selected epitopes overlapped with CTL epitopes to enable balanced CD4⁺ and CD8 ⁺ T-cell responses. The overlapping epitopes calreticulin 147–173 and 164–185, and gp96 378–389 demonstrated the most favorable profiles (Table 2). (Complete HTL epitope data, including antigenicity, cytotoxicity and allergenicity is provided in S2 File.) Supplementary Table 3)

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Table 2. Selected HTL epitopes of calreticulin and gp96.

https://doi.org/10.1371/journal.pone.0353860.t002

3.1.2. Cytokine production and antibody-specific epitopes.

The cytokine profiles indicated that peptides gp96 378–389 and calreticulin 147–173 could induce IFN-γ, IL-4, and IL-10 responses, demonstrating a possible role in balanced Th1 and Th2 reactions. Epitopes for IgG antibodies were recognized in gp96 378–389 and calreticulin S2 File. Supplementary Tables(4-5)

3.1.3. Linear B-cell epitopes prediction.

The highest number of linear B cell epitope residues (19 residues) was found in CRT (147–173) S2 File. Supplementary Table 6

3.1.4.5 Molecular docking between the selected epitopes and MHC molecules. Molecular docking between selected epitopes and MHC molecules confirmed stable interactions, with the most favorable scores observed for gp96 378–389/HLA-B:0801 (−921.3) and calreticulin 164–185/HLA-DRB5:0101 (−910.9) (S2 File Supplementary Table 7).

S1 Fig indicates examples of successful peptide-protein docking between the selected MHC class I molecules and gp96 and calreticulin epitopes.

3.2. Design of multiepitope construct based on immunoinformatic analyses

Based on our previous findings [18], we identified a range of unique features in the selected HPV16 E7 epitopes, which have set the stage for further analyses. The identified E7 epitopes were antigenic, non-toxic and non-allergenic, and they had an ability to activate B cells and IFN-γ secretion(S2 File. Supplementary Table 8).

Six constructs with different epitope orientations were designed using AAY linkers: gp96-E7-CRT, E7-gp96-CRT, gp96-CRT-E7, CRT-E7-gp96, CRT-gp96-E7, and E7-CRT-gp96. four high-scoring CTL and HTL overlapping epitopes (two epitopes of 192–208 and 378–389 from gp96, and two epitopes of 164–185 and 147–173 from calreticulin), along with three CTL epitopes of 49–57, 43–52 and 71–79 and one HTL epitope of 7–15 from HPV-16 E7.

3.3. Selection of final multiepitope construct

3.3.1. Prediction, refinement, and validation of tertiary structures.

I-TASSER generated five 3D models for each construct. The gp96-CRT-E7 construct had the most favorable C-score (−1.55). Following refinement with GalaxyRefine, all structures showed >90% of residues in favored/additionally allowed regions of the Ramachandran plot and ERRAT overall quality factors >80%, indicating high-quality models.For stance, the optimal model’s C-score was −1.55 for the multiepitope gp96-CRT-E7 (S2A Fig). Each construct’s top model was improved via the Galaxy Refine server. Robetta server produced the chimeric vaccination construct’s 3D model. Over 90% of the residues in the selected area suggest sufficient stereochemical structure. Over 90% of the residues in our structures were located in the Ramachandran plot’s extra-permitted and preferred regions, indicating that these models have a high degree of amino acid conformation validity and tend to be of high quality. The findings demonstrated that all structures have an overall quality factor of greater than 80%. (S2B Fig).

3.3.2. Protein-protein docking between TLRs/ specific receptors and different multiepitope constructs.

Six designed constructs were docked with TLRs (TLR2, TLR3, TLR4, TLR5, TLR8, and TLR9) and endocytic receptors (LOX-1, SREC-1, CD91, and CD14). The gp96-CRT-E7 construct had higher binding affinities among most receptors, especially with TLR2 (−1129.8), TLR4 (−1139.8), TLR5 (−1546.4), TLR9 (−1384.9), LOX-1 (−1317.8), and SREC-1 (−1220.4) (Tables 3 and 4). The LOX-1/ gp96-CRT-E7 formed the most stable complex. LOX-1 can stimulate the immune system through its interaction with SREC-I, and CD14, suggesting that the gp96-CRT-E7 multiepitope construct may enhance antigen presentation (Table 4). In docking analysis, the strongest interactions with TLRs occurred when the gp96 and CRT epitopes were linked to the N-terminal of the E7 epitopes. Based on these results, the gp96-CRT-E7 construct was selected as the final vaccine candidate for further characterization. The complete amino acid sequence of this construct is shown in Fig 1A, with its full-length in Fig 1B. Molecular docking visualizations of gp96-CRT-E7 with TLR2, TLR4, LOX-1, and SREC-1 are presented in Fig 2.

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Table 3. Protein-Protein docking results (lowest energy in the best model) between different multiepitope constructs and TLRs.

https://doi.org/10.1371/journal.pone.0353860.t003

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Table 4. Protein-Protein docking results (lowest energy in the best model) between different multiepitope constructs and specific receptors.

https://doi.org/10.1371/journal.pone.0353860.t004

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Fig 1. The designed gp96-CRT-E7 multiepitope construct and its corresponding whole sequence construct: (a) gp96-CRT-E7 multiepitope construct, (b) gp96-CRT-E7 whole sequence construct.

https://doi.org/10.1371/journal.pone.0353860.g001

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Fig 2. Molecular docking of the gp96-CRT-E7 multiepitope construct and main receptors: (a) TLR-2, (b) TLR-4, (c) LOX-1, (d) SREC-1; Red indicated the gp96-CRT-E7 multiepitope vaccine structure and purple and green showed receptor.

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3.4. Comparative analyses of the gp96-CRT-E7 multiepitope construct with full-length construct

3.4.1. Physicochemical features.

The multiepitope gp96-CRT-E7 construct (18.57 kDa) was substantially smaller than its full-length counterpart (152.21 kDa), meeting the recommended <110 kDa criterion for vaccine development [19]; thus our final gp96-CRT-E7 multiepitope construct with a molecular weight of 18.57 kDa is suitable for further development. Both multiepitope and full-length gp96-CRT-E7 constructs had a half-life of 30 hours. The designed gp96-CRT-E7 multiepitope construct was stable, indicating its sufficient and favorable stability, whereas its full-length sequence was unstable (Table 5). The multiepitope construct was predicted to be stable (instability index: 24.16), while the full-length construct was unstable (44.88). Both constructs were soluble (solubility scores >0.45), non-allergenic, and antigenic (VaxiJen scores >0.4) (Table 5). In both multiepitope and full-length gp96-CRT-E7 constructs, the number of negatively charged residues is more than that of positively charged ones (i.e., 20 negative versus 14 positive residues in the multiepitope construct and 299 negative versus 171 positive residues in the full-length construct) indicating an overall acidic character for both proteins. This high negative charge can be advantageous in aspects of increasing solubility and hydrophilicity, which is valuable for vaccine formulation. The pI of the multiepitope construct (5.41) was more neutral than that of the pI of the full-length construct (4.54), suggesting a low negative charge at physiological pH.

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Table 5. Physicochemical properties of the multiepitope and full-length gp96-CRT-E7 constructs.

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3.4.2. Secondary prediction.

PSIPRED analysis showed that the multiepitope construct comprised 52% coil, 27% α-helix, and 20% β-sheet, with 36% exposed residues. The full-length construct showed 55% coil, 28% α-helix, and 16% β-sheet, with 51% exposed residues. The multiepitope construct exhibited less disorder (1% vs. 26%) (S3 Fig).

3.4.3. B-cell epitope prediction.

The multiepitope construct contained seven linear B-cell epitopes (scores 0.511–0.869) and five discontinuous epitopes (scores 0.638–0.828), indicating potential for humoral immune activation.

(Predicted linear and discontinues B-cell epitopes of the multiepitope gp96-CRT-E7 construct are presented in S2 File. Supplementary Tables 9-10. (S4 Fig).

3.4.4. Predicting disulfide-bonding state.

The multiepitope construct contained four cysteines, insufficient for disulfide bond formation. The full-length construct had 15 cysteines predicted to form seven disulfide bonds.

3.5. Confirmation of the multiepitope construct

3.5.1. Immune response simulation.

The immune system’s response to vaccination at various time points was predicted using the C-immune technique.The findings verified that the apparent immune response and actual immunological reactions such as the detection of B-cells, T-cytotoxic cells, T-helper cells, interleukin/interferon production, and the subsequent generation of antibodies were consistent. The intermittent dosing of our multiepitope gp96–CRT-E7 vaccine construct, administered three times on days 1, 84 and day100 resulting in elevated concentrations of activated B cell as well as increased levels or IgM plus combination urinary IgG + IgM antibodies (Fig 3), was found to be optimal at the lowest dose.

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Fig 3. Immune simulation prediction of the gp96-CRT-E7 multiepitope construct: (a) The evolution of B-cell populations following the three injections; (b) The active B-cell population is observed with the administration of vaccine; (c) The generation of the active T helper cell population, (d) T helper cell population is observed with the administration of vaccine; (e) The generation of T cells; (f) The cytokine profile shows the levels of IFN-γ and IL-2 induced upon administration of vaccine; (g) The generation of cytotoxic T cells was found after the vaccine injection.

The RESTING indicates the cells that were not shown to the antigens while ANERGIC indicates the tolerance level of antigen; (h) The immunoglobulins production represents B-cell proliferation and stimulation of immune response after the vaccine administration.

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The multiepitope vaccine construct also strongly upregulated secretion of IFNg and IL-2 known Th1-associated cytokines, together with marked enhancement in memory T cell populations as well cytotoxic T cells (Tc) development (Fig 3d,e,f). This profile of diverse cytokines illustrates a dominance of CTL and Th1 type responses to promote effective stimulation of cellular immunity. The third administration led to further increases in memory T cells, activated T cells and total T cell levels (Fig 3c,d,g).

In contrast, the population of non-memory T cells, resting T cells, and regulatory T cells (Treg) significantly decreased, highlighting high efficacy of construct and providing reassurance about the vaccine’s potential. Conversely, the levels of IL-10 and IL-4 cytokines did not differ significantly from baseline, indicating a low Th2-type immune response. Further, production of the TH1-polarizing cytokine IL-12 was also largely unchanged due to limited activation dendritic cells and macrophages. Indeed, however modest levels of IL-12 can augment antigen presentation and may actually reinforce a positive feedback loop that augments IFN-γ production.

3.5.2. Normal mode analysis of the multiepitope gp96-CRT-E7-receptor complexes.

A range of structural features was analyzed to evaluate the atomic mobility and stability of the gp96-CRT-E7 construct. The stability and dynamic behavior of the gp96-CRT-E7/ LOX-1 and gp96-CRT-E7/SREC-1 docked complexes were assessed using molecular dynamics simulations conducted through the iMODS service. Within the dynamic region, the covariance matrix illustrated the correlations between amino acid residues (S5A Fig (E & J)). Correlated residues were indicated in red, anti-correlated residues in white and uncorrelated residues in blue.

The elastic network model, which represents interactions between atoms as spring-connected pairs, identified stiffer regions of the structure through gray shading. As a result, the gp96-CRT-E7/SREC-1 complex was stiffer and structurally more stable than the gp96-CRT-E7/LOX-1 complex. The B-factor plots represent the atomic fluctuations, where lower values show more structural stability (S5A Fig (A & F)). The deformability graphs illustrate amino acid residues with greater mobility, signifying flexible regions within the complexes (S5A Fig (B & G)). The gp96-CRT-E7/SREC-1 complex showed better structural stability as compared to the gp96-CRT-E7/LOX-1 complex. Eigenvalues are directly proportional to the energy required for structural deformation (S5A Fig (C&H)). The gp96-CRT-E7/LOX-1 and gp96-CRT-E7/SREC-1 complexes yielded eigenvalues of 7.959 × 10^‒⁶ and 1.485 × 10^‒⁶, respectively indicating minimal energy requirements for structural rearrangement in the gp96-CRT-E7/SREC-1 complex. In comparison, the gp96-CRT-E7/TLR2 and gp96-CRT-E7/TLR4 complexes exhibited eigenvalues of 1.555 × 10^‒⁶ and 1.616 × 10^‒⁶, respectively (S5b Fig (C & H)). Indeed, the covariance maps for the gp96-CRT-E7/TLR2 and gp96-CRT-E7/TLR4 complexes visually depicted the relationships between residues, with red indicating correlated motion, white for uncorrelated, and blue for anti-correlated interactions (S5b Fig (E & J)). The elastic network maps revealed stiffer regions through darker gray areas (S5b Fig (D & I)). When we compared two complexes (gp96-CRT-E7/TLR-4 and gp96-CRT-E7/TLR-2) we found that atoms in gp96-CRT-E7/TLR-4 is far more flexible than atoms in gp96-CRT-E7/TLR-2 complex.

3.5.3. Molecular Dynamics (MD) simulation of the TLR2/TLR4/SREC-1/LOX-1-multiepitope gp96-CRT-E7 complexes.

Protein backbone stability is inversely related to the root mean square deviation (RMSD); higher RMSD values generally reflect increased structural instability. During the initial 50 ns of molecular dynamics (MD) simulations, all complexes showed a rise in RMSD due to the typical relaxation of proteins in an aqueous environment-a well-known occurrence in MD analyses. The gp96-CRT-E7/SREC-1 and gp96-CRT-E7/TLR4 complexes reached equilibrium at approximately 20 ns, whereas the gp96-CRT-E7/LOX-1 complex was stabilized around 45 ns. The gp96-CRT-E7/TLR2 complex remained consistently stable throughout the simulation (Fig 4a, b). Average RMSD values were recorded as 0.325 nm (range: 0.1–0.55 nm) for gp96-CRT-E7/SREC-1 and 0.425 nm (range: 0.5–3.5 nm) for gp96-CRT-E7/LOX-1. The gp96-CRT-E7/TLR2 and gp96-CRT-E7/TLR4 complexes showed average RMSDs of 0.445 nm (range: 0.39–0.5 nm) and 0.35 nm (range: 0.2–0.5 nm), respectively. All systems displayed RMSD averages below 0.2 nm, indicating that they achieved stable conformations during simulation. While minor variations occurred between replicate runs, all complexes demonstrated steady RMSD plateaus, suggesting that the structures oscillated around a stable mean conformation. This consistency supports the reliability of the simulations. Notably, the gp96-CRT-E7/SREC-1 complex exhibited greater stability than the gp96-CRT-E7/LOX-1 complex, as shown by RMSD data (Fig 4a, b). On the contrary, a high root mean square fluctuation (RMSF) signifies a flexible area, whereas a low RMSF suggests restricted movements throughout the MD simulation. A fluctuation value below 2Å is permissible for a small protein [20,21]. Comparison of the fluctuations between the gp96-CRT-E7/SREC-1 and gp96-CRT-E7/ LOX-1 complexes demonstrated the highest RMSF fluctuations in the regions of 595–610 and 50–90, respectively. The areas covering residues 710–800 in TLR-4 and 410–500 in TLR-2 showed notable fluctuations. The RMSF plots showed that each complex had residual fluctuations in several different areas. The gp96-CRT-E7/LOX-1 complex showed the largest amounts of dynamic variation in the areas between residues 280–300 and 700–720, excluding from the N- and C-terminal residues. Similarly, the region spanning residues 510–580 showed comparable fluctuations in the gp96-CRT-E7/SREC-1 complex. The average RMSF values were calculated as 0.6 for the gp96-CRT-E7/LOX-1 complex and 0.4 for the gp96-CRT-E7/SREC-1 complex, respectively. RMSF analysis confirmed that the overall structural integrity of complexes remained stable throughout the molecular dynamics simulation (Fig 4c, d). These findings suggest that all gp96-CRT-E7/receptors complexes possess considerable structural flexibility and stability, indicative of favorable interactions with immune receptors. In addition, to evaluate the compactness and rigidity of the complexes under study during the simulation, the radius of gyration (Rg) calculated from the molecular dynamics trajectory was used. Since lower values of radius of gyration are associated with a more stable system and greater compactness of structural units, the opposite is also true: higher values of Rg correspond to a looser and less stable arrangement of structural units. Rg analysis showed that the gP96-CRT-E7/LOX-1 complex had more radius of gyration than the one containing SREC-1. The gp96-CRT-E7/SREC-1 complex had higher structural stability. The average Rg values were determined to be approximately 1.87 Å (ranging from 0.75 to 1.5 Å) for the gp96-CRT-E7/LOX-1 complex and approximately 0.95 Å (ranging from 0.5 to 1.4 Å) for the gp96-CRT-E7/SREC-1 complex. Additionally, the TLR4/gp96-CRT-E7 complex exhibited an Rg range of 1.20 to 1.9 Å with an average of 1.55 Å, while the TLR2/gp96-CRT-E7 complex showed a range of 0.9 to 1.7 Å, averaging 1.3 Å. The Rg plots for all complexes displayed fluctuations of less than 2Å, suggesting that all of them maintained stable conformations throughout the MD simulations (Fig 4e, f).

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Fig 4. Molecular Dynamics (MD) simulation of the gp96-CRT-E7 vaccine construct/ receptor complexes: (a) Root mean square deviations (RMSD) plot of the gp96-CRT-E7 construct/ LOX-1 (blue color) and the gp96-CRT-E7 construct/SREC-1 (purple color) complexes; (b) RMSD plot of the gp96-CRT-E7 construct/ TLR4 (orange color) and the gp96-CRT-E7 construct/ TLR2 (green color) complexes; (c) Root Mean Square Fluctuation (RMSF) plot of the gp96-CRT-E7 construct/ LOX-1 (blue color) and the gp96-CRT-E7 construct/ SREC-1 (purple color) complexes; (d) RMSF plot of the gp96-CRT-E7 construct/ TLR4 (orange color) and the gp96-CRT-E7 construct/ TLR2 (green color) complexes; (e) Radius of gyration (Rg) plotted against simulation time of the gp96-CRT-E7 construct/ LOX-1 (blue color) and the gp96-CRT-E7 construct/ SREC-1 (purple color) complexes; (f) Rg plotted against simulation time of the gp96-CRT-E7 construct/ TLR4 (orange color) and the gp96-CRT-E7 construct/ TLR2 (green color) complexes.

https://doi.org/10.1371/journal.pone.0353860.g004

3.6. In silico cloning of the multiepitope gp96-CRT-E7 vaccine construct

The JCat server was used to assess the Codon Adaptation Index (CAI) and GC content. The CAI and GC content for our enhanced nucleotide sequence were 1.0 and 50.11%, respectively, indicating the feasibility of effective expression in a prokaryotic system. To compare, in silico cloning evaluation was conducted for the complete gp96-CRT-E7 construct. The CAI and GC content of the full-length gp96-CRT-E7 construct were 0.743 and 46.0%, respectively, indicating reduced expression in the host system relative to its multiepitope construct. The multiepitope gp96-CRT-E7 gene was cloned between the restriction sites of SalI and HindIII and the full-length gp96-CRT-E7 gene was cloned between the restriction sites of PaeR71 and Eco53kI (S6 Fig).

3.7. Experimental validation

3.7.1. Construction of the Plasmid DNA.

The gp96-CRT-E7 gene was successfully subcloned into the pET24a (+) vector. The confirmation of the recombinant pET24a-gp96-CRT-E7 was achieved through digestion and colony PCR, resulting in a distinct band of approximately 500 bp corresponding to the gp96-CRT-E7 gene on agarose gel (Fig 5).

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Fig 5. Confirmation of successful cloning in pET24a via restriction enzymes of SalI and HindIII digestion: DNA Ladder: 1 kb (Fermentas).

Lane 1: Undigested plasmid pET24a (showing a single supercoiled band; ~ 5810 bp); Lane 2: Double-digested plasmid showing two bands one at ~500 bp corresponding to the inserted fragment (gp96-CRT-E7) and one upper band representing the vector pET24a backbone (~ 5310 bp).

https://doi.org/10.1371/journal.pone.0353860.g005

3.7.2. Expression and purification of the multiepitope gp96-CRT-E7 gene in E.coli.

The expression of the multiepitope gp96-CRT-E7 gene was performed in E. coli BL21 (DE3) and Rosetta under various circumstances, and confirmed using SDS-PAGE and western blotting. The results showed that the multiepitope gp96-CRT-E7 gene was expressed in Rosetta strain under conditions of OD₆₀₀: 0.6–0.7, 0.5 mM IPTG, temperature of 18ºC and 24 h after IPTG induction as a clear band of ~ 20 kDa. The solubility test showed that the multiepitope peptide was found in soluble phase, thus it was purified using Ni-NTA affinity chromatography under native conditions and dialyzed against PBS1X (Fig 6A-C). The protein concentration was determined to be 0.320 mg/mL using the Bradford assay.

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Fig 6. Expression and purification of the gp96-CRT-E7 multiepitope peptide in E. coli BL21 and Rosetta strains before and 24 h after IPTG induction at 18°C: A) SDS-PAGE analysis of the expressed protein: Lane 1: protein expression in Rosetta before IPTG induction; Lane 2: protein expression in Rosetta after IPTG induction; Lane 3: protein expression in BL21 before IPTG induction; Lane 4: protein expression in BL21 after IPTG induction; B) Western blot analysis of the expressed protein: Lane 1: protein expression in Rosetta before IPTG induction; Lane 2: protein expression in Rosetta after IPTG induction.

MW is Thermo Scientific PageRuler™ Plus Prestained Protein Ladder (11–250 kDa); C) SDS-PAGE analysis of the purified protein: Lane 1: protein expression in Rosetta before IPTG induction; Lane 2: protein expression in Rosetta after IPTG induction; Lane 3: the purified protein.

https://doi.org/10.1371/journal.pone.0353860.g006

4. Discussion

Therapeutic vaccines targeting HPV-associated cancers must trigger a specific cellular immune response to tumor antigens [22]. HSP-TAA complexes could prove an effective formulation strategy for the development of therapeutic HPV vaccines based on DNA, protein or peptide [3,13,14,23,24] which emphasize the efficiency of HSP-E7 fusion vaccines in provoking durable antitumor immune responses.

This study presents the first systematic evaluation of epitope orientation effects in a multiepitope vaccine construct incorporating both gp96 and calreticulin as immunological adjuvants targeting HPV16 E7. Through comprehensive in silico analyses supported by expression validation, we identified the gp96-CRT-E7 construct as the optimal candidate with superior predicted immunostimulatory properties.

The immunostimulatory strength of HSPs may be due to their C- or N-terminal domains. Although the full-length HSPs can induce NK cell and DC proliferation, their C- or N-terminal fragments can also induce strong immunostimulatory activity [25–27]. A key finding of this study is that the arrangement of epitopes significantly affects predicted interactions with immune receptors.

Selecting overlapped CTL and HTL epitopes was aimed at enhancing T-cell response and achieving balanced immunogenicity [28]. The preferred HSP epitopes (gp96 378−389, gp96 192−208; calreticulin 147−173, calreticulin 164−185) demonstrated high MHC binding affinity, extensive population coverage (up to 97.78%), and satisfactory immunogenic properties. These findings align with previous studies identifying immunogenic regions in HSPs. Bergmann et al. (2021) suggested two monoclonal antibodies and suggested that 138–157, 108–127, 158–177 and 248–267 sequences of calreticulin can be considered in future therapeutic approaches [29]. These epitopes shared regional sequence similarity with our calreticulin peptides (164−185 and 147−173), although we have extended epitopes to longer peptides sequence, aiming to enhance their immunogenic potential. Additionally, Hong et al. investigated that a 39−272 fragment of CRT was reported to exhibit robust adjuvant properties when linked to polysaccharides or presented as a component of a fusion protein [30], which had similarity with our predicted CTL/HTL calreticulin epitopes (66−80, 78−97, 107−129, 147−173, 164−185, 223−266). Another vaccine candidate was potential for treatment of atherosclerosis through the induction of immune responses toward Th2. For calreticulin and HSP60, six new IL-4 inducers were determined [31]. This reflects how CRT epitopes have that capacity to regulate immune responses.

Our gp96-CRT-E7 construct showed even stronger binding affinities and potential for antigen presentation, indicating that adding CRT and a dual-adjuvant strategy might further increase CD8 ⁺ T-cell responses. Moreover, a chimeric DNA vaccine against HPV-16 E7 (SP-SA-E7-4–1BBL) with the endogenous signal peptide of Calreticulin showed prophylactic and therapeutic efficacy in mice with cervical cancer [15]. Based on these studies, CRT-derived peptides were considered as a promising candidate for inducing response in our multiepitope vaccine design.

On the other hand, gp96 or its N-terminal or C-terminal fragments were incorporated in several multiepitope vaccine constructs as an adjuvant. CD133 epitope vaccine with gp96 as adjuvant elicited an antitumor T cell response against leukemia [32], or in another study, liver- derived gp96-adjuvanted Influenza monovalent vaccine could broadly elicit CD8⁺ T cell immunity [10]. Zheng et al. (2019) demonstrated the immune adjuvant role of gp96 in DC-based vaccines, wherein it would also act as an antigen source [33]. Padula et al. (2023) studied the gp96-Ig vaccine platform, which combines antigen specificity and adjuvanticity to stimulate robust CD8 ⁺ T cell responses, including mucosal immunity [34]. Although they designed the gp96-Ig fusion protein, our study expands on the concept by linking CRT to possibly more increase the tumor immune response and antigen presentation.

Strong binding affinities were found, particularly for TLR2, TLR4, CD90, SREC-1, and LOX-1, suggesting innate and adaptive immune activation [35,36]. The gp96-CRT-E7 orientation was selected as final vaccine candidate due to its superior docking scores with TLRs and endocytic receptors, such as LOX-1 and SREC-1. This suggests that the N-terminal locating of gp96 might allow initial receptor engagement, whereas the central Calreticulin location adjusts following interactions a hypothesis supported by the strong performance of constructs with gp96 at the N-terminus (gp96-CRT-E7 and gp96-E7-CRT) compared to those with CRT at the N-terminus. The superior docking of gp96-CRT-E7 with TLR2 and TLR4 is predominantly considerable, as these receptors begins signaling cascades that result in the activation of DCs and generation of pro-inflammatory cytokines [35,37]. Strong interactions with SREC-1 and LOX-1 receptors implicated in HSP-mediated antigen cross-presentation also point to increased potential for guiding antigens into MHC class I pathways, which would boost CTL responses [38–40].

Molecular dynamics simulations provided critical validation of the predicted interactions. All gp96-CRT-E7/receptor complexes maintained stable conformations throughout 50 ns simulations, with RMSD values <0.55 nm and Rg fluctuations < 2 Å. The greater stability observed with SREC-1 and TLR2 compared to LOX-1 and TLR4 may reflect differential binding kinetics that could influence immune activation. Additionally, the full-length gp96-CRT-E7 construct was included for comparison with the multi-epitope construct in subsequent bioinformatics analyses. Physicochemical evaluation indicated that the multiepitope gp96-CRT-E7 construct (18.574 kDa, pI 5.41, and instability index 24.16) was more stable and antigenic than the full-length sequence of gp96-CRT-E7 construct (152.21 kDa, pI 4.54, and instability index 44.88). Both constructs were hydrophilic, and possessed half-lives of more than 10 hours in E. coli as well as more than 30 hours in mammalian cells. Secondary structure analysis provided evidence of a compact, helix-rich for gp96-CRT-E7 multiepitope construct that enhanced stability as compared to the full-sequence construct. The absence of disulfide bonds in the multiepitope construct simplifies proper folding in prokaryotic expression systems. Importantly, despite its smaller size, the multiepitope construct retained strong predicted antigenicity and immunogenicity, with multiple linear and conformational B-cell epitopes suggesting potential for humoral immunity.

Successful expression of the multiepitope gp96-CRT-E7 fusion peptide in E. coli Rosetta at 18°C, confirmed the practical feasibility of producing this candidate for future studies. Expression under native conditions is advantageous, as it preserves native conformation and simplifies purification. In vivo validation study examining its therapeutic potential is in progress, and this construct will be utilized for animal immunization in future studies.

While previous HSP-based HPV vaccines which have employed full-length HSPs or single HSP fragments showed promise in preclinical models, our dual-adjuvant multiepitope strategy offers several potential advantages: (1) focused immune response on immunodominant epitopes; (2) elimination of irrelevant HSP sequences; (3) smaller construct size facilitating production and (4) potential for synergistic effects from combining two distinct HSP-derived adjuvants. The strong docking scores with multiple immune receptors support this synergistic potential. While our comprehensive in silico analyses and expression validation provide strong support for the gp96-CRT-E7 construct and are promising, the transition to in vivo studies will necessitate further refinement of immunization protocols, optimization, and evaluation of safety and efficacy in appropriate animal models before clinical translation should be considered. In addition, no in vitro functional tests such as dendritic cell maturation, antigen presentation, T cell activation, or cytokine release (e.g., IFN-γ, IL-2, TNF-α), have been conducted. Indeed, all information concerning the immunostimulatory activity of the molecule was based on predictions made by immunoinformatics studies rather than any experimental data. On the other hand, the schedule of vaccine administration used in C-ImmSim simulations (three doses administered at days 1, 84, and 100) was chosen according to common practices, yet there is no experimental optimization performed specifically for this construct. Thus, functional in vitro tests involving dendritic cells co-cultured with the multiepitope gp96-CRT-E7 fusion peptide, along with in vivo animal studies, are our next studies to confirm the predicted immunogenic activity.

5. Conclusion

In summary, six novel multiepitope constructs employing conserved MHC-I/II epitopes from E7 and adjuvants gp96 and calreticulin were designed. The gp96-CRT-E7 multiepitope construct, with gp96 at the N-terminus followed by CRT and E7 epitopes, exhibited superior binding to key immune receptors, favorable physicochemical properties, and stable complex formation in MD simulations. The multiepitope gp96-CRT-E7 construct had greater Th1-inducing potential than its full-length counterpart through further immunoinformatics analysis. MD simulations revealed that the epitope-based gp96-CRT-E7 construct forms stable and compact complexes with immune receptors, indicating a strong potential for effective immune responses. The construct’s translational potential was confirmed using in silico study, and supported through its expression in E. coli Rosetta. Our integrated in silico and expression validation approach in this study suggests strong promise for HPV16 vaccine development.

Supporting information

S1 File. Supplementary Materials and Methods.

A detailed description of the materials and methods used in this study is provided in Supporting Information File 1.

https://doi.org/10.1371/journal.pone.0353860.s001

(DOCX)

S2 File. Supplementary Tables (1–10.

The supplementary tables supporting the findings of this study are provided in Supporting Information File 2.

https://doi.org/10.1371/journal.pone.0353860.s002

(DOCX)

S1 Fig. Molecular docking between epitopes and MHC class I alleles: (a) Successful peptide-protein docking between HLA-B:0801 and gp96 (378–389) with an interaction similarity score of −921.3, (b) Successful peptide-protein docking between gp96 (378–389) and HLA-B0702 with an interaction similarity score of −811.1, (c) Successful peptide-protein docking between CRT (164–185) and HLA-B0702 with an interaction similarity score of −732.4, and (d) Successful peptide-protein docking between CRT (147–173) and HLA-B0801 with an interaction similarity score of −660.1.

https://doi.org/10.1371/journal.pone.0353860.s003

(TIF)

S2 Fig. A: Predicted 3D structures of the gp96-CRT-E7 multiepitope construct by I-TASSER: (a) with C-score of −1.55, (b) with C-score of −2.25, (c) with C-score of −4.07, (d) with C-score of −4.16, and (e) with C-score of −3.34.

B: (a) The structure produced by the Robetta baker Server and improved by GalaxyRefine Server; (b) Analysis of the Ramachandran plot by PROCHECK.; (c) ERRAT error values graph.

https://doi.org/10.1371/journal.pone.0353860.s004

(TIF)

S3 Fig. Secondary structure study of the multiepitope and full-length gp96-CRT-E7 constructs: (a) gp96-CRT-E7 multiepitope secondary structure, (b) gp96-CRT-E7 full-length secondary structure.

https://doi.org/10.1371/journal.pone.0353860.s005

(TIF)

S4 Fig. Linear and discontinuous B-cell epitopes prediction of the gp96-CRT-E7 multiepitope construct (a, b & c) and the full-length gp96-CRT-E7 construct (d, e & f) using BepiPred: (a) Predicted linear B-cell epitopes; (b) Illustrated example of B-cell epitopes of the gp96-CRT-E7 multiepitope construct on 3D structure as shown in yellow color; (c) Illustrated conformational B-cell epitopes present in the gp96-CRT-E7 multiepitope vaccine construct; The light-yellow spheres show the epitopes; (d) Predicted linear B-cell epitopes; (e) Illustrated example of B-cell epitopes of the full-length gp96-CRT-E7 construct on 3D structure as shown in yellow color containing 12 residues (RPSKEVEEDEYK) with score of 0.636; (f) Illustrated conformational B-cell epitopes present in the full-length gp96-CRT-E7 vaccine construct containing 9 residues (R345, P346, S347, E349, V350, E351, E354 and Y355) with score of 0.649; The light-yellow spheres show the epitopes.

https://doi.org/10.1371/journal.pone.0353860.s006

(TIF)

S5 Fig. a) Normal-mode analysis of the multiepitope gp96-CRT-E7/ LOX-1 and SREC-1 complexes: (D&I) The elastic network model uses springs between atoms, indicated by colored dots for stiffness; (E&J) Covariance matrix shows paired residue mobility motions, i.e., uncorrelated (white), correlated (red), and anti-correlated (blue); (C&H) Eigenvalues; (A&F) Averaged RMS indicated by B-factor; (B&G) Deformability. b) Normal-mode analysis of the multiepitope gp96-CRT-E7/ TLR4 and TLR2 complexes: (D&I) The elastic network model uses springs between atoms, indicated by colored dots for stiffness; (E&J) Covariance matrix shows paired residue mobility motions, i.e., uncorrelated (white), correlated (red), and anti-correlated (blue); (C&H) Eigenvalues; (A&F) Averaged RMS indicated by B-factor; (B&G) Deformability

https://doi.org/10.1371/journal.pone.0353860.s007

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S6 Fig. Schematic representation of in silico cloning of the gp96-CRT-E7 fusion gene in pET24a (+) prokaryotic expression vector: (a) the multiepitope gp96-CRT-E7 gene cloned into pET24a (+) vector using SalI and HindIII restriction enzymes, (b) the full-length gp96-CRT-E7 gene cloned into pET24a (+) vector using PaeR71 and Eco53kI restriction enzymes.

https://doi.org/10.1371/journal.pone.0353860.s008

(TIF)

Acknowledgments

AI Disclosure: The language model ChatGPT-4 and Grammarly was used for editing sentence structure and fixing grammatical errors. After using these tools, the authors have fully reviewed and edited the article.

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Figures

Abstract

1. Introduction

2. Materials and methods

2.1. General overview of the study

2.2. Epitope prediction of gp96 and calreticulin

2.3. Peptide-MHC molecular docking

2.4. Multiepitope construct design

2.5. Tertiary structure prediction and refinement

2.6. Protein-protein docking with immune receptors

2.7. Comparative analysis with full-length construct

2.8. Immune simulation

2.9. Normal mode analysis

2.10. Molecular dynamics simulation

2.11. Experimental expression validation

2.11.1. Construction of expression plasmid.

2.11.2. Protein expression.

2.11.3. Protein purification.

2.12. Ethics approval

3. Results

3.1. Epitope selection from gp96 and calreticulin

3.1.1. HTL epitope prediction.

3.1.2. Cytokine production and antibody-specific epitopes.

3.1.3. Linear B-cell epitopes prediction.

3.2. Design of multiepitope construct based on immunoinformatic analyses

3.3. Selection of final multiepitope construct

3.3.1. Prediction, refinement, and validation of tertiary structures.

3.3.2. Protein-protein docking between TLRs/ specific receptors and different multiepitope constructs.

3.4. Comparative analyses of the gp96-CRT-E7 multiepitope construct with full-length construct

3.4.1. Physicochemical features.

3.4.2. Secondary prediction.

3.4.3. B-cell epitope prediction.

3.4.4. Predicting disulfide-bonding state.

3.5. Confirmation of the multiepitope construct

3.5.1. Immune response simulation.

3.5.2. Normal mode analysis of the multiepitope gp96-CRT-E7-receptor complexes.

3.5.3. Molecular Dynamics (MD) simulation of the TLR2/TLR4/SREC-1/LOX-1-multiepitope gp96-CRT-E7 complexes.

3.6. In silico cloning of the multiepitope gp96-CRT-E7 vaccine construct

3.7. Experimental validation

3.7.1. Construction of the Plasmid DNA.

3.7.2. Expression and purification of the multiepitope gp96-CRT-E7 gene in E.coli.

4. Discussion

5. Conclusion

Supporting information

S1 File. Supplementary Materials and Methods.

S2 File. Supplementary Tables (1–10.

S2 Fig. A: Predicted 3D structures of the gp96-CRT-E7 multiepitope construct by I-TASSER: (a) with C-score of −1.55, (b) with C-score of −2.25, (c) with C-score of −4.07, (d) with C-score of −4.16, and (e) with C-score of −3.34.

S3 Fig. Secondary structure study of the multiepitope and full-length gp96-CRT-E7 constructs: (a) gp96-CRT-E7 multiepitope secondary structure, (b) gp96-CRT-E7 full-length secondary structure.

Acknowledgments

References