Integrative bioinformatics approach to the mRNA vaccine development for the human papillomavirus using the capsid protein

Abstract

Human papillomavirus (HPV) is associated with several serious diseases, consisting of neck-related, lung, oropharyngeal, vaginal, penile, vulvar, and anal tumors. Potential candidates for mRNA vaccination include the capsid structural peptides L1 and L2, which are prominently recognized by the immune system. This recognition has resulted in the formation of mRNA vaccines targeting these capsid proteins. We employed various bioinformatics methods to predict epitopes for helper CD4 + lymphocytes, CD8 + lymphocytes, and B cells within these proteins, and to evaluate their allergenicity, toxicity, and antigenicity. An orthorhombic TIP3P water box with a buffer region of 10 Å was used for the experiment, and Na⁺/Cl⁻ counter-ions at physiological salt concentration (0.15 M) were included to counteract the system. After equilibration of the NVT and NPT ensembles, a 100 ns production run was conducted at 310 K and 1 atm. Our vaccine construct includes 24 epitopes, comprising both CTLs and HTLs. The vaccine exhibited enhanced hydrophilicity, with an average hydropathicity score of -0.811. The Ramachandran plot indicated remarkable stability, with 94.3% of residues located within the allowed and additionally allowed regions. The vaccine demonstrated significant affinity for the TLR3 receptor, as evidenced by a docking score of -363.44 and a confidence score of 0.9862. Following codon optimization, expression in E. coli vectors showed substantial improvement in vaccine production, reflected by an increased GC content of 58.12%. MM-GBSA analysis revealed a consistent binding affinity for TLR3 at -53.16 kcal/mol. Overall, the designed vaccines against HPV capsid proteins represented favorable outcomes through strong immune responses, supporting their progression to in vitro and in vivo clinical trials.

Introduction

Human mucosal epithelia are infected by a double-stranded DNA virus known as the human papillomavirus (HPV). It is a member of Papillomaviridae, and globally it is known as the most universally transmitted disease via sex [1]. HPV is classified into five major genera: alpha, beta, gamma, mu, and nu [2]. Depending on the danger of oncogenic transformation, the alpha genus contains the most significant HPVs, which are divided into high-risk and low-risk groups [3]. High-risk types are 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, and 68. According to scientific research, HPV16 is the most hazardous, accounting for around 70% of all cervical tumors [4]. The forms of HPV 6, 11, 40, 42, 43, 44, 54, 61, 70, 72, and 81 fall into the low-risk group. Human papillomavirus is a naked, approximately circular virus that contains genome of double-stranded DNA of around 8 kilobases [5]. Three different regions make up the HPV genetic code: The LCR, or long control region [6], the late section (L1, L2), and the early part (E1, E2, E4, E5, E6, and E7) [7]. The oncoproteins that are most important in promoting cellular transformation in high-risk HPV types are E6 and E7. They disrupt normal regulatory mechanisms, enabling infected epithelial cells to live longer, bypassing growth controls, and further dividing [8].

Cancer of the cervical area is a very frequent type of melanoma triggered by human HPV, accounting for almost 95% of incidences [9]. The World Health Organization documented that it is the fourteenth most prevalent cancer globally and ranks fourth in terms of prevalence amongst females [10]. Each year, around 660,000 new cases of cervical cancer are diagnosed worldwide, and about 350,000 of these cases result in death [11–13]. These variations are mostly caused by insufficient cervical cancer diagnosis and therapy techniques [4, 14]. Therefore, the only practical method for both preventing and reducing the chance of acquiring cervical cancer is vaccination.

Studies conducted in South Africa found a robust connection between throat cancer and increasing anti-HPV-16 immunoglobulin G antibody levels [15]. Approximately 30,416 instances of HPV-induced squamous cell carcinoma of the ass occur annually globally, with two-thirds of these events occurring in women [16]. The majority of the more than 200 HPV strains identified to date, which are divided into 29 genera, infect humans [17]. The female vaginal epithelium is the focus of almost half of these strains [18]. Notably, DNA from greater-risk HPV cohorts has been discovered in numerous cervical malignancies [19]. Two transformative peptides, E6 and E7, are expressed by these strains and bind to the tumour inhibitor factors p53 and retinoblastoma (Rb), respectively [20]. Even years after the original immortalising events, E6 and E7 are still produced in tumours and derived cell lines, indicating their critical function in maintaining the changed phenotype [4, 21–24]. In addition, the main capsid protein of HPV, the L1 protein, creates the outer icosahedral shell that is important for immune detection and self-assembles into virus-like particles. The L2 protein is the small capsid component that assists in packaging the viral genome and plays key roles during infection, including genome protection, endosomal escape, and delivery of viral DNA to the nucleus. Together, L1 and L2 ensure proper virion assembly, stability, and successful initiation of infection [25, 26]. VLPs mimic viral structures, but they lack the genetic information necessary for replication. Particularly in vulnerable populations like the elderly or those with compromised immunological mechanisms, this may lead to less potent immunological responses [26]. Taking these aspects into account, mRNA-based therapies might help treat cancer and viral disorders while addressing these issues [27]. Non-pathogenic, disintegrating mRNA vaccines are superior than conventional immunizations. Several HPV-targeting mRNA vaccines have been created, and preclinical and clinical research has shown promising outcomes [28–30].

In the post-genetic age, computational techniques for vaccine design have grown increasingly common with the development of immunoinformatics tools [31]. A revolutionary approach with several benefits for vaccine development is computational immunology [32]. In order to find potential vaccine candidates, it quickly analyzes a significant quantity of structural, genomic, and proteomic data using machine learning techniques [33, 34]. This method makes it easier to anticipate immune-triggering antigenic determinants and antigenic targets, which improves the safety and effectiveness of immunogen component selection [35]. By avoiding the need for costly and time-consuming clinical studies, this precision-oriented strategy saves money and speeds up the manufacture of vaccines [33, 36]. However, before using immunoinformatics in vaccine production, a few obstacles must be investigated. Although immunoinformatics relies heavily on data, disparities in data quantity and quality might compromise the precision of vaccination target determinations [37, 38]. Likewise, anticipated targets could not consistently elicit the desired immune responses or might have unfavorable consequences [36, 39]. Technological developments, multidisciplinary collaboration, and ongoing research to overcome the obstacles are necessary for using immunoinformatics in vaccine development [34].

This study identified potential vaccine targets in the HPV proteome using immunoinformatics techniques, focusing on capsid proteins. To meet the pressing public demand for HPV vaccinations, this study focuses on an in-silico approach for designing mRNA vaccines for HPV. Targeting the L1 and L2 capsid peptides, an mRNA vaccine has been designed for the treatment of high-threat HPV variants 16, 18, 31, 39, 51, 52, 56, 58, 66, and 68. To anticipate potential epitopes, including CD8 + lymphocytes, helper T lymphocytes (HTL), and B-cell epitopes generated from the L1 and L2 capsid proteins, we used advanced immunoinformatics techniques. The ultimate vaccine was created utilizing highly prioritized epitopes after being assessed for toxicity, allergenicity, and immunogenecity. The stability, functionality, and appropriateness of the vaccine were assessed through a sequence of computational studies, which included physicochemical profiling and structure prediction and validation, molecular docking, simulation studies, in-silico cloning, and immune response modeling.

Materials and methods

Target protein sequence retrieval

The sequences of L1 and L2 HPV capsid protein sequences have been retrieved from the National Center for Biotechnology Information (NCBI) in pattern of FASTA [40]. These were then further evaluated for immunogenicity by applying VaxiJen v2.0 software [41].

T cell epitope prediction

The CD8 + T-cell and HTL epitopes was determined through the NetCTL v1.2 [42] and NetMHCpan 4.0 [43] tools [44]. During vaccine development, the two matched the antigenic sites. IEDB tools having [45] NetMHCIIpan 4.0 pakage is employed to create the antigenic sites that link to MHC class-II and can induce antibody-mediated and cellular immune reactions [46]. Antigenic HTL and CTL epitopes were picked for the vaccine’s composition [47].

mRNA vaccine construction via in Silico

The chosen HTL, CTL, were combined with many supplementary co-translational amino acid units to create an HPV mRNA vaccine, as previously reported [48]. The 5′ cap was initially introduced to facilitate translation, nuclear cytoplasmic delivery, splitting, and stabilization of the mRNA vaccine design [49]. The 5(UTR) is known to ensure that the mRNA has stability as well as facilitates its effective translation, and the Kozak sequence facilitates correct translation at the start codon. The adjuvant that was added to boost the immune response was human beta-defensin 1 (HBD1). Human beta-defensin-1 (HBD-1) is a natural immunomodulatory adjuvant that boosts in-silico vaccine efficacy by eliciting an native immune and an adaptive immune reaction. Its origin in humans guarantees minimal toxicity and allergenicity, and computational analysis represents good stability and good affinity with immune receptors, which make it the best option when developing a multi-epitope vaccine [50]. GPGPG adaptors linked adjuvant and HTL antigen sites, EAAK spacers bind HTL and AAY link CTL antigen. The design included a tissue plasminogen activator (tPA), an MHC I-targeting domain (MITD), and a signaling peptide. While tPA promotes epitope circulation, MITD transports CTL epitopes to the endoplasmic reticulum’s MHC-I compartment. The 3′ untranslated region and poly-A tail were added to mRNA to improve its stability and translational efficiency [51].

Projection of allergenicity, antigenicity, and toxicity of vaccine construct

Using the proper bioinformatics techniques, the immunogenicity, allergenicity, and toxic nature of the mRNA vaccine model were assessed. Immunogenicity was estimated using VaxiJen 2.0 [41]. Possible allergenicity of the vaccine model was checked with the aid of the AllerTop 2.0 tool [52]. To check the vaccine design’s harmlessness, its toxicity was estimated using ToxinPred 2 [53].

Prediction of physicochemical properties of the vaccine construct

The ExPASy ProtParam analysis system was implemented to analyse the vaccine’s physical and chemical traits [54]. Web users might see projected values for the building’s length, molecular weight, aliphatic ratio, potential isoelectric point (pI), expected half-life, and grand average hydrophobia (GRAVY). Analyzing the vaccine design’s solubility with the Protein-Sol tool allowed us to estimate the ability to repel water and hydrophilic properties of the amino acid residues [55].

Prediction of secondary structure, improvement, and validation of tertiary structure

With the use of the SOPMA tool, the amino acids that make up the structure of the vaccine construct, an α-helix, β-sheet, and coil, were quantified. The 3-dimensional scaffolding of the vaccine model was created through the I-TESSER service [56]. The PBDsum was used to generated Ramachandran plot, which showed that most of the amino acids were in energetically accessible regions [57, 58]. The structure was further refine by using Galaxy WEB tool [59].

Molecular docking of the vaccine construct with TLRs

In the digestive tract, toll-like receptors (TLRs) are essential modulators of inflammatory mechanisms that link innate and adaptive immunity and control immune responses to various ligands produced from pathogens [60]. Hence, the tertiary structure of the vaccine was docked to TLR-3 using the HDOCK tool. Because it recognizes the viral double-stranded RNA and initiates the innate immune response, Toll-like receptor 3 (TLR-3) is important in the in-silico vaccine creation. The vaccine has the ability to generate significant antiviral responses, cytokine release, and an effective adaptive response, according on TLR-3 interaction and computational data. TLR-3 was retrieved from the RCSB PDB collection, respectively [61].

Molecular dynamics simulation via IMOD

We use computational modelling tool iMOD, an internal coordinate system normal mode computing technology [62]. This device duplicates the joint active motions of macromolecules in biological systems, unexpectedly by conducting Normal mode analysis (NMA) in internal (dihedral) coordinates. Even for big polymers, our technique generates workable transition paths between two homologous structures [47].

Immune response simulation

Immunological reactions modelling may be used to assess the immunogenicity of the vaccine’s standard DNA code of peptides. The C-immunosim platform was used to simulate the immunological response to the vaccination. The parameters of the C-IMMSIM server that are used to simulate a vaccine in silico are: simulation steps (time cycles), antigen dose and schedule of immunization, and volume of the immune system. Other settings like random seed, adjuvant inclusion, and HLA alleles can be used to predict very well antibody-mediated and cellular immune reaction [63].

Codon optimization and in Silico cloning

Using the E. coli strain K12 production framework, the vaccines codon were optimized applying the Java Codon Adaptation Tool (JCat) service (https://www.jcat.de/Start.jsp) [64]. The service utilize the codon adaptation index (CAI) and GC contents to assess the vaccines’ expression levels. While a perfect CAI score would be 1.0, a value of 0.8 is quite appropriate, and GC concentrations between 30% and 70% are just satisfactory [65, 66]. Utilizing EcoRI, BamHI, and NdeI restriction regions, the vaccine-optimized gene sequences were inserted into the pET28a (+) E. coli plasmid. Lastly, the vaccine optimization sequences were transferred to the plasmid pET-28a(+) employing the SnapGene software.

mRNA structure prediction

The RNAfold service was applied to determine the intermediate configuration of the HPV vaccine [67]. The tool supplied the query mRNA configurations, thermodynamically calculated minimum free energy (MFE) during the anticipation [68]. Before this experiment, the DNA > RNA conversion technique was used to transform the JCat improved genetic sequences into RNA sequences. These RNA sequences were then used to predict and validate secondary structures using the RNAfold service [69].

MD simulation and MMGBSA analysis

Molecular dynamics simulations were performed applying the Desmond Schrodinger suite, which offers a very effective way to apply classical or biomolecular MD [70]. Using the Protein Preparation Wizard, the TLR3-HPV vaccine complex was first created by adding hydrogens, defining protonation phases, refining hydrogen-bonding chains, and minimising steric disputes [71]. An orthorhombic TIP3P water box with a buffer area of 10 A was used for the experiment, and Na + / Cl - counter-ions at physiological salt concentration (0.15 M) were used to neutralise the results. The OPLS 2005 force field was applied to both the receptor and the multi-epitope vaccine construct. After the equilibration of the NVT and NPT ensembles, a 100 ns manufacturing run was applied at 310 K and 1 atm [72]. The Bio3D program in R was then used to perform Principal Component Analysis (PCA) on the complex, revealing the primary collective motions in the molecular dynamic trajectories. To evaluate the thermodynamic interaction between TLR3 and the immunogen, MM-GBSA analysis was applied to determine the molecular binding free energy of the complex through the obtained trajectory [73].

Results

Sequences retrieval of protein sequences

The NCBI service yields HPV major capsid (L1) sequences and minor (L2) sequences. The accession numbers of sequences, along with the consensus region, are shown in Table 1. Consensus was found in the L1 and L2 regions after all the sequences were aligned. These sequences were joined together and used to create an HPV mRNA vaccine.

Table 1.

Representation of the consensus sequence of in high-risk HPV subtypes in L1 and L2 regions

Accession No	Consensus Sequences
ASJ78776.1 L2 (HPV 16)	MWSEVYLPPVVTDYVRTGRLLVGPYKPKVQYRVRFRLP
ATL15246.1 L1 (HPV 18)	DPNKFPDSYNPDTRLVWCGVEGRGQPLGVGSGHPNKD
ASU09818.1 (HPV 31)	DTESDKQTQLCGEHWGCGDCPPLLDGDMDTGGMDFLQKVLDICKYPDYMYGFLRREQRHRGGPLYGTPSGSTSDFN
WAB53351.1 (HPV 39)	KPYWRAQGHNNGCWNQLFVTVDTTRSTNRHEEDLQFIF
XCN70924.1 (HPV 51)	QLCTLD
WAB54305.1 (HPV 52)	MYIHMILWPDYRAICQKDPWVLFSDQLGRKFLQKMRTKR
WAB54208.1 (PHV 56)	ASATLYTCKGTCPDKETADLGFGGLGGGGGRYPRPPVG
ADD23215.1 (HPV 58)	PDSIVEGAGFTTPANPDPSPEGTHYEIPTFSSTPLPRLYS
WAB54498.1 (HPV 66)	RQQVVPLTYNPAELPDDFDILHRPALTSRRRSRGTRSGIG
XAH03675.1 (HPV 68)	AVHYDSIPIEQNGLDYNGPDLPYDAA

Predications of CTL and HTL epitopes

Using two different software programs, NetCTL 1.2 and NetMHCpan 4.0, cytotoxic T lymphocyte (CTL) epitope anticipation was applied to all of the HPV antigenic proteins. The antigenic determinants screened by both methods were subsequently evaluated for immunogenicity, toxic nature, and sensitization. For the design of an mRNA vaccine, only those fourteen antigenic sites were picked that satisfied all the parameters for a vaccine, as demonstrated in Table 2.

Table 2.

Representations of CTLs along with antigenicity score

CTLs	MHC-I	Antigenicity	Allergenicity	Toxicity
DLGFGGLGGGGRRRS	HLA-DRB5*01:01	2.3462	Non-allergen	Non-toxic
ADLGFGGLGGGGRRR	HLA-DRB5*01:01	2.328
LGFGGLGGGGRRRSR	HLA-DRB5*01:01	2.2042
FPDSYNPGRGQPLGV	HLA-DRB1*09:01	0.5539
PLGVGSGHPNKDDTE	HLA-DQA1*05:01	1.1149
PPLLDGDMDTGQRHR	HLA-DRB4*01:01	0.4835
PYWRAQGHNNGRSTN	HLA-DQA1*04:01	0.7582
QPLGVGSGHPNKDDT	HLA-DQA1*05:01	1.1491
SYNPGRGQPLGVGSG	HLA-DQA1*05:01	1.1925
NPGRGQPLGVGSGHP	HLA-DQA1*05:01	1.1668
LGVGSGHPNKDDTES	HLA-DQB1*03:01	1.0612
GQPLGVGSGHPNKDD	HLA-DQA1*05:01	0.9889
GVGSGHPNKDDTESD	HLA-DQA1*05:01	0.7983
KPYWRAQGHNNGRST	HLA-DQA1*04:01	0.6981

Helper T lymphocyte (HTL) determinants of peptides of the HPV strains were predicted using two antigen identification programs, NetHTL and the IEDB MHC II binding software. The HTL antigen sites’ antigenic characteristics, toxicity, hypersensitivity, and ability to trigger IFN-γ, IL-4, and IL-10 cytokine reactions were further investigated using both approaches. 10 epitopes meet the criteria and are preferred for the HPV vaccine. As seen in Table 3, the final vaccine design included epitopes that met every selection criterion.

Table 3.

Representations of selected HTLs along with antigenicity score

HTLs	MHC-II	Antigenicity	Allergenicity	Cytotoxicity
ETADLGFRGL	HLA-A*03:01	2.0191	Non-Allergen	Non-Toxic
CPDKETADL	HLA-B*53:01	0.6569
RGTRSGIGAV	HLA-A*30:01	1.2606
DDTESDKQW	HLA-B*44:02	0.4113
GVGSGHPNK	HLA-A*11:01	1.0324
KPYWRAQGH	HLA-B*07:02	0.7064
NPGRGQPLGV	HLA-B*07:02	0.9191
RSTNRHEER	HLA-A*31:01	0.7809
SYNPGRGQPL	HLA-A*24:02	0.7078
YNPGRGQPL	HLA-A*24:02	0.4738

Construction of mRNA vaccine for HPV

For the mRNA vaccine design against HPV, about 24 epitopes were utilized. The vaccine model had 24 antigenic determinants, including 14 CD8 + lymphocyte (CTL), and 10 helper T lymphocyte (HTL) epitopes. To make sure accurate mRNA and peptide synthesis and immune susceptibility, crucial structural and regulatory components were introduced into the vaccine design, including the tissue plasminogen activator (tPA) signal peptide, Kozak sequence, 5′ cap, and 5′ untranslated region (UTR). β-defensin 1 was added as an immune-modulator and interacted with the HTL epitopes via GPGPG connectors to increase immunological stimulation. The spacers were applied to combine HTL and CTLs. This deliberate design was meant to ensure stability, significant expression, and robust immune system activation, as seen in Fig. 1.

Fig. 1.

Representation of an mRNA vaccine for HPV. (A) flowchart and sequence of mRNA vaccine (B) A labelled diagram of our HPV vaccine

Physicochemical features, antigenicity, allergenicity, and toxicity of vaccine construct

With an antigenic factor measure of 0.7297, respectively, Vaccine Constructs may elicit a potent antibody-mediated immunological reaction. Allergies and toxic nature: further analysis proved that neither design is non-toxic nor allergic. All these outputs represent that the synthesized mRNA vaccine prototypes may be safe and immunogenic, suggesting that more research on them is warranted.

The molecular mass of the vaccine designs has been determined to be 51780.69 Da, depend on their physical and chemical qualities. The theoretical isoelectric points (pI) of 9.25 for Construct demonstrate the fundamental nature of structures. Our HPV vaccine has a half-life of around 30 h in mammalian immature RBC, based on in vitro half-life projections. Constructs have found to be stable based on their analyzed instability indices of 33.43, respectively, which are below the 40 thresholds. Furthermore, HPV Constructs are hydrophilic, as shown by their respective grand average hydropathicity (GRAVY) values of -0.882. A summary of these results is given in Table 4.

Table 4.

Represents the physicochemical properties of our HPV vaccine

Criteria	Value (HIV Vaccine)
Cumulative amino acids	510
Molecular weight	51780.69
Number of atoms	7094
Formula	C2240H3436N704O706S8
Theoretical pI	9.25
half-life in mammalian reticulocytes, in vitro	30 h
Instability index	33.43
Aliphatic index	46.00
GRAVY value	-0.882
Antigenicity of vaccine	0.7297

The mRNA vaccine’s secondary structure determination and evaluation

For the determination of the two-dimensional components of the vaccine constructs, the SOPMA tool was used. There were 15.69% helices, 6.08% elongated chains, 0.00% beta-turns, and 78.24% random coils in our HPV vaccine construct. These findings indicate that designs exhibit a significant number of alpha helices and irregular coils in a structurally stable configuration. The anticipated secondary structures, as seen in Fig. 2, point to the possibility of structural flexibility, globular folding, and overall strength.

Fig. 2.

Represents the secondary structure of our HPV mRNA vaccine

Tertiary structure prediction, refinement, and validation

As seen in Fig. 3, the tertiary architecture of the mRNA vaccine constructs was determined through the i-TESSOR tool. An additional improvement was made through the Galaxy WEB software. The optimization of side-chain repacking is used in the improvement of protein 3D structures with the use of the algorithm, which is called the alpha-Landy, to optimize the amino acid side-chain conformations to minimize steric clashes. It relaxes the structure iteratively with the help of molecular dynamics to increase the robustness of the whole structure, and with the help of energy minimization, the geometry of the backbone structure is improved, and the quality of stereochemistry is enhanced. To assess structural quality and direct structural improvement, Ramachandran plot analysis was used. According to the results, 82.2% of amino acid units were identified in chosen areas, while 12.1% were detected in extra authorized places. Specifically, the lack of residues in the sections that were either generously allowed or prohibited demonstrated a high-quality structural model.

Fig. 3.

Representation of the 3D structure of our HPV vaccine. (A). Tertiary structure of our HPV vaccine (B), the refined structure of our HPV vaccine (C). Ramachandran plot of HPV vaccine construct

Molecular docking

Molecular docking was done through the HDOCK server. Our vaccine docked with Toll-like receptors TLR-3, and their 3D configuration was enhanced. For each vaccine–TLR interaction ligand confidence value and RMSD (Å), the top 20 docking models were ranked using the docking binding value. Construct was selected for both builds because of its highest docking score (-363.44) with a confidence score (0.9862). The docking tests demonstrated strong and long-lasting relationships between the vaccination candidates and the target receptors, the HPV vaccine model with TLR-3, as demonstrated in Fig. 4.

Fig. 4.

Representation of molecular docking between the TLR3 receptor and our HPV vaccine construct. The red color is TLR3 receptor, and the green colour is our HPV vaccine structure

Molecular dynamics simulation

To evaluate the structural stability and adaptability of the mRNA vaccine prototypes docked with TLR-3, molecular dynamics (MD) simulations were performed. The graphic shows the main-chain distortion capability, which represents each residue’s capacity to experience architectural dislocation. Significant distortion areas suggest possible hinge locations in the protein structure. The root mean square decreased energy needed for structural deformation is obtained using B-factor analysis, which is measured using Normal Mode Analysis (NMA) by multiplying atomic mobility by 8π². HPV vaccine models docked with TLR-3 had eigenvalues of 8.163487 × 10⁻², respectively, as shown in Fig. 5. The covariance matrix shown in Fig. 5 illustrates the extent of mobility between residue pairs that is correlated (red), uncorrelated (white), or anti-correlated (blue). The elastic framework model depicts the interaction between atom pairs via simulated springs; each dot is a spring, with deeper grey denoting more stiffness.

Fig. 5.

Representation of md simulation of our HPV mRNA vaccine construct and TLR3 via IMODS

Immune response simulation

The vaccine designs’ immune-stimulating efficacy was evaluated using immunological simulation and the C-ImmSim service. The simulation findings demonstrated that both structures efficiently triggered various immune system parts such as NK cells, macrophages, dendritic cell B-cells, CD4 T lymphocyte helper cell types, and CD8 lethal T-cells, particularly in the first few days following antigen contact Fig. 6.

Fig. 6.

(A-N) Representation of immune activation by our mRNA HPV vaccine––

Codon optimization

Using the Java Codon Adaptation Tool (JCat), the immunogen design was codon optimized to improve translation effectiveness in the E. coli K12 production setup. A sequence of 1530 nucleotides was generated by the refining process. With a GC content of 58.12% and an anticipated Codon Adaptation Index (CAI) of 1.0, the optimised construct demonstrated a favourable expression profile in E. coli. The recombinant construct was then created by inserting the refined gene into the pET28a(+) vector by applying the SnapGene tool. The inserted vaccine gene inside the pET28a(+) backbone is seen in the green-highlighted area of Fig. 7.

Fig. 7.

Representations of cloning of our HPV vaccine in a plasmid. The green segment represents the clone region of the HPV vaccine

mRNA vaccines and peptides’ structure

Two crucial configurations, the centroid model and the minimum free energy (MFE) algorithm, were provided by RNAfold, for forecasting the intermediate configuration of the mRNA used as target for vaccine. Out of all the structures in the thermodynamic ensemble, the centroid structure represents the conformation with the shortest average base-pair distance. The centroid structure had an energy value of − 557.10 kcal/mol in Fig. 8 (B). In contrast, the MFE structure showed an ideal folding energy of -–628.90 kcal/mol in Fig. 8 (A) upon submission of the codon-optimized sequence. Since lower free-energy scores equal better molecule longevity, these findings highlight the structural integrity of the suggested design. Since greater structural stability promotes resistance to chemical degradation and endonuclease cleavage, accurate prediction of mRNA folding is crucial.

Fig. 8.

Representation of RNA folding of our HPV vaccine construct. (A) (MFE) model (B) centroid structure

Molecular dynamics simulation and MMGBSA analysis

The RMSD figure clearly showed that both halves of the vaccine-TLR3 combo were fixed. After the initial equilibration phase, the receptor in blue color showed a consistent backbone RMSD, indicating a preserved global conformation [74]. Conversely, the HPV multiepitope vaccine in red color exhibited better values of RMSD, as it should be regarded because of its flexible loop-rich structure, as shown in Fig. 9 (A). The vaccination route ceased drifting, indicating a consistent binding direction for the course of the simulation’s 100 ns duration, even if this approach by itself permits some flexibility. The residue-wise stability was also corroborated by the RMSF profiles. The receptor in blue displayed in Fig. 9 (B) minor changes (< 2.5 A) in most of the residues, which is expected of a short, domain-packed immunological receptor [75]. The red-colored vaccine had higher RMSF values, particularly on looping and end terminal areas, indicating structural accessibility and flexibility. Notably, binding interface residues exhibited decreased fluctuations, which were referred to as stable interactions and anchoring within the TLR3 groove. Radius of gyration analysis was done to reveal that the receptor displayed structural compactness that was constantly stable, as shown in Fig. 9 (C). Stabilization of the vaccine showed RoG [76]. Small variations in vaccination RoG show active yet non-perturbative mobility of elastic loops of antigens, while the general size was maintained, demonstrating structural stability of the compound.

Fig. 9.

(A) RMSD study of the HPV vaccine-TLR3 complex exhibiting structural stability for 100ns, with red and blue hues denoting the vaccine construct and TLR3 receptor, respectively. (B) RMSF profile of the residue-wise flexibility of the vaccination (red) and TLR3 receptor (blue). (C) RoG study shows the compression of the size of the vaccine (red) and receptor (blue) along the 100 ns trajectory. (D) The simulation’s interactions become stable and consistent when H-bonds are formed. (E) Dynamic correlation map showing cross-correlated and anti-correlated movements at vaccine-TLR3 residues

The vaccine-TLR3 complex demonstrated considerable number of intermolecular hydrogen bonds that ranged between 18 and 35 throughout the course of the simulation Fig. 9 (D). Strong and stable binding at the binding interface is suggested by these H-bonds with high occupancy. The tightening of the vaccine structure against the receptor was also shown to be correlated with peaks in the number of hydrogen bonds, which is consistent with long-lasting anchoring as observed with successful immunological action [71]. Correlated dynamics, or positively correlated movements linked to structured structural stability in ligand recognition, were found in the core of the receptors by DCCM analysis as in Fig. 9 (E). The complex was observed to exhibit mixed correlations with the flexible sections to have anticorrelated movements as contrasted to the main core segments. Above important, the close and positive correlations were identified at the interface of the receptor and the vaccine, which shows the aligned mobility and continual contact dynamics. PCA was utilized to discover the major group of movements that contributed to vaccine-receptor dynamics. Significant conformational shifts were documented in PC1 and PC2, showing that the receptor suffered tiny and local domain alterations, whereas the vaccine adopted broader movement patterns as per its flexibility displayed in Fig. 10. The conformations’ clumping inside the PCA space indicated that the system’s large-scale structure did not change much over time [77].

Fig. 10.

Principal component analysis that illustrates the principal movements in the HPV vaccine-TLR3 complex

The average DG bind of -53. 16 kcal/mol shows a good and steady binding of the HPV vaccination to TLR3. The existence of large contributions by hydrogen-bonding terms reveals the importance of polar interaction while moderate packing energies imply presence of complementing non-polar connections [78]. In summary, the results demonstrate substantial energy stability consistent with the MD trajectories’ stable interactions displayed in Table 5.

Table 5.

MMGBSA energy calculations of the HPV vaccine-TLR3 complex

Energy Term (kcal/mol)	HPV-TLR3 Complex
ΔGbind	-53.16111393
ΔGbind vdW	-103.7924807
ΔGbind Covalent	-0.173909765
ΔGbind Hbond	-10.77033316
ΔGbind Packing	-1.031231415

In all the investigations, MD modeling reveals that the HPV vaccination can generate a stable and energetically favorable and dynamically stable complex with TLR3. Radius of gyration and hydrogen bonds verified the structural integrity and stability, while the graph of RMSD and RMSF demonstrated the receptor stiffness stable with vaccination flexibility. PCA and DCCM aid in the convergence to the stable conformational states, and MM-GBSA binding energies further validate significant affinity. When taken as a whole, our findings clearly show that this multiepitope vaccine design is suitable for effectively stimulating TLR3 and subsequent immunological activation.

Discussion

By preventing HPV infection and its associated health impacts, vaccination is essential for improving public health and increasing well-being worldwide. Three bivalents (Cervarix1, Cecolin1, and WalrinvaxV) [79–81], two quadrivalent (GARDASIL1 and Cervavac1) [82, 83], and one nine-valent (GARDASIL91) vaccine [84, 85]. They are one of six HPV vaccinations that have just been authorized and are available for purchase. All these vaccinations are of the virus-like particle (VLPs) type. More than 70% of cervical malignancies have been linked to HPV strains, which are protected against by the bivalent vaccinations [86, 87]. However, because these vaccines work by eliciting antibodies that specifically target the HPV capsid protein, they cannot treat pre-existing malignancies. These vaccinations are less effective at preventing the progression of preexisting lesions because this protein is expressed before the virus diffuses. Therapeutic vaccines, on the other hand, target and fight sick cells because they trigger a cellular immune response rather than generating antibodies [88, 89]. Despite mimicking the chemical structure of viruses, VLPs lack the genetic material necessary for replication. This makes them less likely to stimulate an allergic reaction than live attenuated or mRNA vaccines, which might be problematic for certain cohorts, including the elderly or people with weak defense mechanism of body [26].

To overcome this obstacle, we aimed to develop an in silico-based HPV vaccination that was safe, non-toxic, and responsive. Recently, the rapidly advancing sphere of mRNA-based therapeutics has become very promising as a way of creating vaccines against cancer and infectious diseases [27, 90]. mRNA is regarded as a superior vaccination option over live-attenuated, subunit, dead, and DNA-based vaccines because of its non-infectious and non-integrating nature [28–30, 91, 92]. Additionally, as mRNA is naturally degraded by biological mechanisms, its viability in living cells may be affected by a variety of changes and transportation techniques [28–30]. But mRNA vaccines could be delivered via systemic administration, which entails infusing the vaccine directly into the circulation, frequently by intravenous injections alternative to systemic distribution that limits undesirable effects is local injections, which are supplied locally at the target spot. Direct injection of the medicine into the desired tissue, such as an intranodal injection, allows for focused delivery. As a result, there are numerous ways to administer drugs, including intravenous, subcutaneous, intradermal, intramuscular, and intranodal pathways [89, 93–95]. There are now many mRNA-based cervical cancer vaccines undergoing preclinical and clinical studies. A new study found that an mRNA immunogen was created targeting the L1 and L2 capsid peptides of HPV. Using mice models with tumors implanted either subcutaneously or orthotopically, researchers found that mRNA immunization dramatically reduced tumor development and induced robust immune responses mediated by T cells. Furthermore, scientists found that a large number of immune cells were able to infiltrate tumor tissue after the immunization. A noteworthy mRNA-based vaccination that targets the HPV capsid peptides L1 and L2 was created in a different study. The vaccination showed a tailored adaptive immune system reaction that was specific to the antigen in a preclinical model of HPV 16-linked sores [96]. In light of this, we are now addressing the critical community demand for a cervical carcinoma vaccine by developing mRNA vaccines using the reverse vaccinology approach. The L1 and L2 peptides of HPV are targeted for making an effective and efficient mRNA vaccine in the analyses. The vaccine was developed using predictions of HTL, CTL, and B-cell epitopes made using a variety of bioinformatics approaches. Each of the preffered epitopes was further tested for toxicity, allergenicity, and antigenicity. Then, emplying the chosen epitopes, we built the mRNA vaccine using a few adjuvants and connectors. It was hypothesized that both vaccines’ components would be soluble proteins based on their physicochemical characteristics, which could render them functionally stable in the body [4, 97]. The theoretical isoelectric points (pI) of 9.25 for Construct demonstrate the fundamental nature of structures, suggesting that they are hydrophobic proteins with aliphatic side chains [4]. Our HPV vaccine has a half-life of around 30 h in mammalian immature red blood cells, based on in vitro half-life projections. Constructs are stable based on their analyzed instability indices of 33.43, respectively, which are below the 40 thresholds. Furthermore, HPV Constructs are hydrophilic, as shown by their respective grand average hydropathicity (GRAVY) values of -0.882. During the evaluation of their tertiary structures, the error was fixed. When creating a successful vaccination, it is essential to take into account how proteins fold into their secondary and tertiary structures. In response to infections, antibodies accumulate mostly against expanded and coiled protein antigens because these components are essential for protein-specific immune responses [98]. The mRNA vaccine’s anticipated secondary and tertiary structures were determined to be adequate and trustworthy. Most of the vaccination residues, as reported by the Ramachandran plot examination, were inside the favored areas, providing the tertiary structures’ structural stability.

A docking study was conducted to determine possible interactions of the immunogen with immune cell toll-like receptors (TLRs) using human TLR3 in HDOCK. For each vaccine–TLR interaction ligand confidence value and RMSD (Å), the top 20 docking models were ranked using the docking binding value. Construct was selected for both buildings because of its highest docking score (-363.44) with a confidence score (0.9862).

Molecular dynamics simulation provided further confirmation of the vaccines’ and vaccine-TLR aggregates’ durability. The graphic shows the main-chain distortion capability, which represents each residue’s capacity to experience architectural dislocation. Significant distortion areas suggest possible hinge locations in the protein structure. The root mean square decreased energy needed for structural deformation is obtained using B-factor analysis, which is measured using the production of engineered vaccines in the E. coli cloning plasmid, particularly the K12 strain, which was evaluated using codon optimization. The design vaccine demonstrated significant translation in the vector, according to the experimental findings. About 1530 nucleotides sequence was created for the refining process. The CAI value of the vaccine construct had 1.0, and the average GC content of the modified sequences was determined to be 58.12%. B-cell populations for vaccine significantly increased after three doses of vaccination, demonstrating persistent protection for a year. The vaccine also produced T-cell responses, including TH and TC, with persistent TC activity after immunization and increased expression of active TH cells.

This study concludes by highlighting the mRNA vaccine’s ability to induce strong antibody-mediated and cellular immune reactions to HPV. Additional in vitro and in vivo investigations are highly advised in light of the study’s facts and possible conclusions. As a result, our study will now concentrate on carrying out further laboratory tests to assess the reliability and efficacy of the developed vaccinations.

Shortcomings of the study

Although the computer-based vaccine design comes in handy, it also possesses certain significant pitfalls. Its predictions are highly dependent upon the quality of the available data and it is not able to fully replicate the complexity of actual immune responses. This implies that vaccine components that appear promising in silico may not perform well in real biological systems with respect to expression, stability, or immunogenicity. Due to this reason, extensive lab experiments and clinical trials are still required.

Strengths of the study

The transition of a bioinformatics-based vaccine into the preclinical and clinical development is a crucial phase, which assists in accelerating the process of vaccine development and makes the latter more targeted. Using the computational tools, researchers are able to predict much of what is important about the antigens they want to target, the stability of a protein they may be working with, and which epitopes are likely to cause an immune reaction, long before any laboratory work begins [99]. The computational vaccine design may also be used to gain an understanding of the immune pathways that a vaccine should induce in order to optimize its action and reduce its risks [100]. Once the laboratory tests verify such predictions, the vaccine design can be easily updated or modified to fit new variants or other similar pathogens. Such flexibility provides computationally guided vaccines with a potent response against rapid evolution in infectious diseases [101].

Conclusion

Our mRNA vaccine successfully inhibited infection by the high-risk HPV types: 16, 18, 31, 39, 51, 52, 56, 58, 66, and 68. Structural studies validated the stability and antigenicity of the vaccine after epitope identification, aided by bioinformatics methodologies. Docking studies revealed that robust interactions between the vaccination and Toll-like receptors (TLRs) are crucial for immunological activation. Molecular dynamics simulations demonstrated that the vaccination complexes exhibit both stability and flexibility. Codon optimization improved expression efficiency in E. coli vectors. Post-vaccination, the innate immune system was activated, and both B-cell and T-cell reactions were sustained. The vaccine’s efficacy depends on the stability of mRNA configurations, as predicted by secondary structure analysis. Overall, our vaccine shows promising potential in preventing HPV infections. Nonetheless, to validate its efficacy, safety, and promise in addressing HPV infection and associated malignancies, more in vitro, in vivo, and clinical investigations are required. This comprehensive investigation sheds light on the vaccine’s properties and establishes a base for future studies by focusing the need for clinical trials and labortary validation to determine the practical efficacy of these mRNA vaccines.

Author contributions

A. Z., S. H, F.A did the writing, manuscript, and analysis, while M.Y.S., N. A. and L. Z, did data curation.

Funding

This study was funded by Deanship of Research and Graduate Studies at King Khalid University through the Large Research Project under grant number RGP2/XXX/46.

Data availability

Data will be supplied upon request. The primary author, (Akmal Zubair) will supply the data upon request.

Declarations

Ethics approval and consent to participate

Not applicable.

Human research

This study excludes any human or animal subjects.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.