Design and In Silico Validation of a Novel Multi-Epitopes Subunit Vaccine Candidate against Lassa Virus Using Reverse Vaccinology Approach

Design and In Silico Validation of a Novel Multi-Epitopes Subunit Vaccine Candidate against Lassa Virus Using Reverse Vaccinology Approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Design and In Silico Validation of a Novel Multi-Epitopes Subunit Vaccine Candidate against Lassa Virus Using Reverse Vaccinology Approach Akeem Babatunde Sikiru, Ibrahim Shuaibu Harande, Nurulfiza Bint Mat Isa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7860035/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Lassa fever, caused by the Lassa virus (LASV), remains a significant public health threat in West Africa, characterised by annual outbreaks, substantial morbidity, and high case-fatality rates in hospitalized patients. The natural immune response to LASV is often marked by a delayed and weak neutralising antibody response, with survival correlating more strongly with robust cell-mediated immunity (CMI). This immunological profile, combined with the challenges of traditional vaccine development for a Biosafety Level 4 (BSL-4) pathogen, necessitates innovative strategies. This study employed a reverse vaccinology and immunoinformatics approach to design a multi-epitope subunit vaccine against LASV. The viral L segment proteins of LASV obtained from NCBI (NC_004297) were computationally screened for potent and conserved B-cell, cytotoxic T-lymphocyte (MHC-I), and helper T-lymphocyte (MHC-II) epitopes. The most promising epitopes were selected based on antigenicity, immunogenicity, non-allergenicity, and lack of homology to the human proteome. These were assembled into a single chimeric protein construct, which was then subjected to comprehensive in silico characterization, including analysis of its physicochemical properties, structural integrity, and safety profile. The potential immunogenicity was evaluated through computational immune simulation. A 24.38 kDa multi-epitope vaccine construct was designed, comprising highly antigenic B-cell and T-cell epitopes linked with appropriate spacers. Physicochemical analysis predicted the construct to be hydrophilic, highly antigenic, and non-allergenic, with a moderate potential for soluble expression in Escherichia coli . Immune simulations predicted that the vaccine could elicit a strong and balanced immune response, characterized by robust activation and proliferation of both CD4 + and CD8 + T-cell populations, induction of immunological memory, and a cytokine profile skewed towards a protective Th1 response (IFN-γ). Functional enrichment analysis carried out suggested that the vaccine construct possesses intrinsic immunomodulatory properties, with strong associations to gene expression regulation and nucleic acid binding. The computationally designed and validated multi-epitope construct represents a promising vaccine candidate against Lassa virus. Its design is rationally tailored to induce the CMI response critical for LASV clearance. This in silico study provides a strong foundation for subsequent pre-clinical development, including protein expression and in vivo immunogenicity and efficacy testing in appropriate animal models. Figures Figure 1 Figure 2 Figure 3 1. Introduction Lassa fever (LF) is an acute viral haemorrhagic illness caused by the Lassa virus (LASV), an arenavirus first identified in the town of Lassa, Nigeria, in 1969[ 1 ]. For over a period of five decades, the virus has been a persistent and remain a formidable public health challenge across West Africa. The disease is endemic in several countries, including Nigeria, Sierra Leone, Liberia, Guinea, and Benin, with sporadic cases and outbreaks reported in neighbouring nations of the listed countries. The annual burden of Lassa fever is substantial, with epidemiological estimates suggesting between 100,000 and 300,000 infections and approximately 5,000 deaths each year. These figures, however, are widely considered to be underestimates due to limited surveillance capacity and under-reporting in many rural, resource-constrained settings of most Low and Middle Income Countries (LIMCs) where the disease is endemic[ 1 ]. The clinical presentation of Lassa fever is highly variable, with an estimated 80% of LASV infections reported as asymptomatic or result in a mild, undifferentiated febrile illness, often mistaken for more common endemic diseases in the LIMCs such as malaria[ 2 , 3 ]. However, the remaining 20% of cases progress to a severe, multi-system disease characterized by high fever, facial edema, respiratory distress, and haemorrhagic manifestations such as bleeding from the gums, nose, or gastrointestinal tract[ 4 ]. The case-fatality rate (CFR) among hospitalized patients is alarmingly high, frequently cited at around 15% but capable of exceeding this during major outbreaks[ 2 ]. Certain populations are disproportionately affected. Lassa fever poses a grave risk during pregnancy, particularly in the third trimester, where it is associated with maternal mortality rates over 30% and fetal or neonatal loss in more than 80% of cases[ 5 ]. This devastating impact on maternal and child health call for an urgent need for effective preventative measures. Furthermore, the disease places an immense strain on the fragile healthcare infrastructure of the endemic regions. Healthcare workers are at high risk of nosocomial transmission, and outbreaks can disrupt essential health services, leading to broader socioeconomic consequences that impede development and stability. The combination of its high epidemic potential, significant mortality, and impact on vulnerable groups establishes Lassa fever as a major, unresolved public health crisis. Lassa fever is a classic zoonotic disease, with its persistence in nature intrinsically linked to its rodent reservoir. For decades, the primary host of the virus has been identified as the Natal multimammate mouse, Mastomys natalensis [ 6 ]. This rodent species is ubiquitous across sub-Saharan Africa and thrives in peridomestic environments, which means living in and around human dwellings and agricultural areas which makes it a crucial aspect of LASV epidemiology. However, M. natalensis do not become ill when infected; instead, they become asymptomatic, chronic carriers, shedding the virus in their urine and feces throughout their lifetime[ 7 ]. This persistent shedding of virus ensures continuous environmental contamination, leading to human infections through direct contact with rodents or, more commonly, through ingestion of food and water contaminated with rodent excreta[ 8 ]. Human outbreaks often exhibit seasonality, with cases typically peaking during the dry season (December-March), a period associated with agricultural practices and rodent movements that increase human-rodent contact[ 9 ]. While control efforts have historically focused on M. natalensis , a growing body of molecular evidence has revealed a more complex and challenging ecological landscape. The assumption of a single reservoir host is no longer tenable. Recent studies have definitively identified several other rodent species as competent hosts for LASV. These include the closely related Guinea multimammate mouse ( Mastomys erythroleucus ), the African wood mouse ( Hylomyscus pamfi ), the rusty-bellied brush-furred mouse ( Lophuromys sikapusi ), and even common species like the black rat ( Rattus rattus ) and house mouse ( Mus musculus ). These newly identified reservoirs occupy diverse ecological niches, from the commensal habitats of M. erythroleucus to the forest-dwelling preference of H. pamfi [ 10 ]. This discovery of expanded host range has profound implications for public health and vaccine development strategy against the disease ravaging large population. The existence of multiple, ecologically diverse reservoirs suggests that LASV may be maintained in complex transmission cycles, potentially including sylvatic cycles that are independent of the peridomestic cycle involving M. natalensis . This ecological complexity severely undermines the long-term efficacy of rodent control as a standalone prevention strategy. Eliminating or controlling multiple rodent species across varied landscapes is a far more daunting, if not impossible, task than targeting a single commensal species. This realization elevates the strategic importance of developing a human vaccine, shifting the focus from an intractable environmental problem to a tractable biomedical solution. Meanwhile, vaccine that confers durable immunity in humans represents the most viable and sustainable path to mitigating the threat of Lassa fever in the face of its complex and expanding zoonotic origins. The clinical outcome of LASV infection is largely determined by the nature and kinetics of the host immune response. The virus exhibits broad tissue tropism, infecting key cell types including endothelial cells, hepatocytes, and cells of the mononuclear phagocyte system, such as macrophages and dendritic cells[ 11 ]. The pathogenesis is driven not only by direct viral cytotoxicity, particularly in the liver where hepatocellular necrosis is a common finding, but also by profound immune dysregulation. Further, infection of endothelial cells and macrophages also occurs which can trigger the release of inflammatory mediators, leading to increased vascular permeability, fluid shifts, and the edema and hypotension characteristic of severe disease[ 8 , 11 ]. Unfortunately, a central and defining feature of Lassa fever immunobiology is the paradoxical nature of the antibody response. In many viral infections, the rapid production of neutralizing antibodies (NAbs) is critical for viral clearance and protection. In Lassa fever, however, NAbs appear late in convalescence, often weeks after the virus has been cleared from the bloodstream[ 12 , 13 ]. This temporal disconnect strongly suggests that antibodies play a minimal role in controlling the acute phase of the infection. While IgM antibodies do appear and correlate with viral clearance, their neutralizing capacity is limited, and their primary role may be in functions other than direct virus neutralization[ 14 ]. In stark contrast, survival from severe Lassa fever is strongly correlated with the induction of a robust and timely cell-mediated immune (CMI) response[ 15 ]. Specifically, the activation and expansion of LASV-specific cytotoxic CD8 + T-lymphocytes (CTLs) are considered paramount for identifying and eliminating virus-infected cells, thereby controlling viral replication and facilitating clearance[ 14 ]. The natural immune response to LASV can thus be viewed as sub-optimal, as the virus appears to have evolved mechanisms to delay or evade the production of an effective early neutralizing antibody response. Therefore, an effective vaccine should not necessarily aim to mimic this flawed natural response, but instead, a more rational strategy is required to design a vaccine that specifically elicits the type of immunity known to be protective. Hence, the primacy of CMI in controlling LASV infection provides a clear immunological directive including an ideal Lassa fever vaccine engineered to induce a potent, broad, and durable T-cell response, capable of rapidly recognizing and clearing infected cells upon exposure. This present study was carried out on this principle, aiming to design a vaccine candidate rich in T-cell epitopes to drive a protective CMI response. The confluence of factors associated with LASV include a significant and sustained disease burden, a complex and expanding reservoir ecology that makes environmental control untenable, and the limited efficacy of post-exposure therapeutics like Ribavirin which creates an undeniable imperative for the development of a safe and effective Lassa fever vaccine[ 16 – 18 ]. This need is globally recognized, with the World Health Organization (WHO) designating Lassa fever as a priority pathogen in its Research and Development Blueprint, highlighting it as a disease for which preventative countermeasures are urgently needed. However, traditional vaccine development for a BSL-4 pathogen like LASV is fraught with challenges. This is because working with the live virus is inherently dangerous, requiring expensive high-containment facilities and highly trained personnel. This makes the conventional approaches of virus attenuation or inactivation slow, costly, and resource-intensive especially in LIMCs[ 19 ]. These obstacles have historically impeded progress in the field, but modern biotechnological advances offer a powerful alternative. Reverse vaccinology represents a paradigm shift in vaccine design that can push development of vaccines against the LASV beyond the limit. This in silico approach leverages genomic, proteomic, and immunoinformatic tools to mine the pathogen's entire proteome for proteins and peptide sequences (epitopes) that are likely to be effective antigens. By computationally predicting and prioritizing vaccine targets, this strategy can be used to bypasses the need to culture live pathogen during the initial design and discovery phases, which could dramatically increasing speed and safety while reducing costs. This methodology is particularly well-suited for high-consequence pathogens like LASV. While several Lassa vaccine candidates are currently in various stages of development—including those based on recombinant vesicular stomatitis virus (rVSVΔG-LASV-GPC), DNA (INO-4500), and inactivated rabies virus (LASSARAB)—there is still no licensed vaccine, and the pipeline would benefit from diverse and innovative candidates[ 15 ]. Therefore, this study was carried out to employ a comprehensive reverse vaccinology and immunoinformatics pipeline to design and perform a rigorous in silico validation of a novel multi-epitope subunit vaccine candidate against Lassa virus. By specifically targeting the viral L segment proteins, the primary objective was to construct a chimeric protein engineered to elicit a robust, broad, and durable cell-mediated immune response, addressing the key immunological requirement for protection against Lassa fever. 2. Methods 2.1 Genomic Data Retrieval and Target Protein Selection The complete genomic sequence of the Lassa virus L segment (strain Josiah, GenBank accession no. NC_004297) was retrieved from the National Center for Biotechnology Information (NCBI) database. The L segment, approximately 7.2 kb in size, encodes the Z protein (a RING-finger matrix protein) and the L protein (an RNA-dependent RNA polymerase, RdRP) in an ambisense orientation[ 1 ]. These internal proteins were selected as the source for vaccine epitopes due to their high level of expression during the viral replication cycle and their established role as rich sources of T-cell epitopes, making them ideal targets for a vaccine designed to elicit a strong CMI response[ 11 ]. 2.2 Epitope Prediction and Prioritization There was an implementation of a systematic immunoinformatics workflow used to predict B-cell and T-cell epitopes from the amino acid sequences of the L and Z proteins, such as epitopes predictions, vaccine construction, physicochemical properties assessment, immnobioinformatic analyses, and functional enrichment analyses using packages in R studio Kousa Dogwood release (27771613, 2025-02-02) for windows and dedicated bioinformatics servers. The linear B-cell epitopes, which are contiguous amino acid sequences recognized by antibodies, were predicted using bioinformatics servers that analyze properties such as antigenicity, surface accessibility, and hydrophilicity. Peptides with high prediction scores were prioritized as potential candidates for inducing a humoral immune response[ 20 ]. Major Histocompatibility Complex (MHC) class I epitope which are peptides with the potential to bind major histocompatibility complex (MHC) class I molecules were predicted to identify candidate cytotoxic T-lymphocyte (CTL) epitopes. This was done using established prediction algorithms, that is the use of 9-mer peptides evaluated for their binding affinity to a comprehensive panel of common human leukocyte antigen (HLA) class I alleles; where high-affinity binders were considered strong candidates for recognition by CD8 + T-cells[ 21 ]. The MHC class II epitopes were used to identify helper T-lymphocyte (HTL) epitopes, where 15-mer peptides were screened for their predicted binding affinity to a panel of prevalent HLA class II alleles (including HLA-DR, -DP, and -DQ isotypes). These epitopes selected are crucial for activating CD4 + T-cells, which orchestrate and support both humoral and cytotoxic immune responses[ 20 , 22 ]. These led to generation of a large pool of predicted epitopes which were then subjected to a stringent, multi-parameter filtration process to select only the most promising candidates for inclusion in the final vaccine construct. These selection criteria included classification as high antigenicity which are epitopes predicted with ability to be recognized by immune receptors; and immunogenicity which are epitopes predicted with capacity to provoke a functional immune response. This was followed by a conservation analysis carried out across multiple LASV strains to ensure the selected epitopes are conserved, maximizing the potential for broad protection. The analysis include testing for non-homology to human proteome whereby each candidate epitope was subjected to a BLASTp search against the Homo sapiens proteome to eliminate any peptides with significant sequence similarity to human proteins, thereby minimizing the risk of inducing autoimmune reactions. Non-allergenicity and non-toxicity testing using computational tools to predict whether an epitope is likely to be allergenic or toxic. Cytokine induction potential carried out to further screened the epitopes for their predicted ability to induce the production of key cytokines, particularly interferon-gamma (IFN-γ), which is a hallmark of a protective Th1-type CMI response. 2.4 Multi-Epitopes Vaccine Construction and Design There was a final chimeric vaccine protein which was rationally designed by joining the top-scoring filtered epitopes into a single poly peptide chain. The construct was architected as follows; an adjuvant sequence was fused to the N-terminus of the construct to stimulate innate immune signaling and enhance the overall immunogenicity of the vaccine. The selected CTL (MHC-I) epitopes were linked sequentially using AAY linkers. These specific linkers are designed to facilitate proteasomal cleavage, promoting efficient processing and presentation of the individual epitopes on MHC class I molecules. The selected HTL (MHC-II) epitopes were joined using GPGPG linkers. These flexible linkers help to maintain the independent conformational and immunogenic integrity of each epitope, allowing for proper presentation on MHC class II molecules. The final arrangement of the domains (adjuvant, HTL cluster, CTL cluster) was optimized to ensure efficient expression, folding, and immunological processing. 2.5 Physicochemical, Structural, and Immunological Characterization of the Vaccine Construct The final amino acid sequence of the designed vaccine constructed was subjected to a series of different comprehensive in silico analyses to predict its viability as a vaccine candidate that can be scale from in silico design to further downstream evaluation for its suitability as a potential biopharmaceutical product. The physicochemical properties was determined using the ExPASy ProtParam server used to calculate fundamental physicochemical parameters, including molecular weight (MW), theoretical isoelectric point (pI), instability index, aliphatic index, and Grand Average of Hydropathicity (GRAVY). The solubility and expression potential of the construct's potential for being expressed as a soluble protein in an Escherichia coli system was predicted based on its physicochemical properties, particularly the GRAVY score and molecular weight. The overall antigenicity of the full-length construct was predicted based on sequence motifs and amino acid composition of the vaccine construct. 2.6 In Silico Immune Simulation To forecast the potential immune response that can be elicited by the vaccine candidate in vivo , a computational immune simulation was performed using the C-IMMSIM server[ 23 ]. The simulation was configured to model a standard prime-boost vaccination regimen, with three injections administered at four-week intervals. The simulation tracked key immunological parameters over a one-year period, generating predictive data on humoral immunity focusing on B-cell population dynamics, including memory B-cell formation and the production kinetics of immunoglobulin isotypes (IgM and IgG); cellular immunity focus on activation, proliferation, and differentiation of CD4+ (helper) and CD8+ (cytotoxic) T-cell populations, as well as the establishment of long-term T-cell memory. The cytokine response at the levels of key immunomodulatory cytokines, such as IL-2 and IFN-γ, to predict the polarization of the T-helper response (Th1 vs. Th2) was also analysed. 2.7 Functional Enrichment Analysis To gain insight into the potential biological mechanisms of action of the vaccine constructed, a Gene Ontology (GO) enrichment analysis was performed using PSIPRED protein server[ 24 ]. This analysis uses sequence-based prediction algorithms to associate the protein with terms from three major GO domains including biological processes, molecular functions and cellular components. The larger biological programmes of the protein indicates that the vaccine construct may participate in regulation of immune response. The molecular function focus on the specific biochemical activities of the protein, while cellular component focus on the sub-cellular locations where the protein may be found such as nucleus, cytoplasm, and cell membrane. 3. Results 3.1 Identification of Potent and Conserved B-Cell and T-Cell Epitopes The immunoinformatic screening of the LASV L segment proteome identified a large number of potential B-cell and T-cell epitopes. Following the application of a stringent multi-parameter filtration protocol, a final set of high-priority epitopes was selected for inclusion in the vaccine construct. These selected epitopes demonstrated high predicted antigenicity and immunogenicity, were conserved across LASV strains, and showed no significant homology to the human proteome. The selected candidates for each epitope class include top-ranked predicted linear B-cell epitopes (Table 1 ). These are top 10 predicted linear B-cell epitopes from the LASV L protein with their respective sequences which are predicted to be recognized by antibodies and are foundational to the humoral immunity component of the designed vaccine. In addition, additional top-ranked predicted MHC Class I epitopes (n = 15) with potential cytotoxic T-lymphocyte (CTL) potential were identified. These epitopes are 9-mer peptides which are predicted to bind MHC class I molecules and central to the vaccine's aim of inducing a potent CD8 + T-cell response to kill virus-infected cells (Table 2 ). The top-ranked predicted MHC class II epitopes as 15 predicted helper T-lymphocyte (HTL) epitopes. These 15-mer peptides are designed to be presented by MHC class II molecules to activate CD4 + T-cells, which are essential for coordinating and amplifying the overall adaptive immune response (Table 3 ). Table 1 Predicted High-Scoring Epitopes of the L-Protein from Lassa Fever Virus derived from complete genomic sequence of the Lassa virus L segment (strain Josiah, GenBank accession no. NC_004297) Peptide Sequence Position Score 1 PQKEPEKRRRREKPK 1121 0.87 2 QKEPEKRRRREKPKH 1122 0.87 3 KEPEKRRRREKPKHQ 1123 0.87 4 EKRRRREKPKHQAKR 1126 0.86 5 KRPEKRRKPTKTKRR 1215 0.86 6 RRNKRRAKGRKQRKG 669 0.86 7 RNKRRAKGRKQRKGR 670 0.86 8 NKRRAKGRKQRKGRR 671 0.86 9 PPPQKEPEKRRRREK 1119 0.86 10 PPQKEPEKRRRREKP 1120 0.86 The table shows the top-ranked epitope candidates predicted from the L-protein of Lassa fever virus. Each peptide is listed with its sequence, starting position in the protein, and corresponding prediction score. Peptides with scores ≥ 0.85 were considered high-confidence epitopes with potential targets for immune recognition and vaccine development. Table 2 Predicted L-Protein MHC Class I Epitope Candidates of Lassa Fever Virus derived from complete genomic sequence of the Lassa virus L segment (strain Josiah, GenBank accession no. NC_004297) Peptide Sequence Position Score 1 HRATAKSAA 37 0.44 2 RATAKSAAK 38 0.44 3 ATAKSAAKT 39 0.44 4 AKSAAKTRA 41 0.44 5 DAAPRAKRA 1496 0.44 6 AAPRAKRAR 1497 0.44 7 QAAHKKATA 1636 0.44 8 AAHKKATAT 1637 0.44 9 GDQARARPA 3 0.33 10 DQARARPAR 4 0.33 11 QARARPARP 5 0.33 12 ARARPARPQ 6 0.33 13 PRATHRATA 33 0.33 14 RATHRATAK 34 0.33 15 ATHRATAKS 35 0.33 Table presents predicted epitope candidates derived from the L-protein of Lassa fever virus. Each entry shows the peptide sequence, starting position within the protein, and the prediction score. Peptides with scores ranging from 0.33 to 0.44 are classified as moderate-scoring epitopes, which may contribute to immune recognition but require further experimental validation for immunogenic potential. Table 3 Predicted L-Protein MHC Class II Epitope Candidates of Lassa Fever Virus derived from complete genomic sequence of the Lassa virus L segment (strain Josiah, GenBank accession no. NC_004297) Peptide Sequence Position Score 1 KAHTSGKEKRNRDEP 794 2 2 QGRPEGANTNSHKDR 614 1.93 3 DKKRAPHEQNAGSPT 1045 1.93 4 SRKGEHKTQTRAKND 506 1.93 5 PRSNKTRHRNRDEGQ 534 1.93 6 RPEGANTNSHKDRRE 616 1.93 7 EEKAHTSGKEKRNRD 792 1.93 8 EKAHTSGKEKRNRDE 793 1.93 9 AHTSGKEKRNRDEPN 795 1.93 10 KPRSNKTRHRNRDEG 533 1.87 11 NQGRPEGANTNSHKD 613 1.87 12 GRPEGANTNSHKDRR 615 1.87 13 PEGANTNSHKDRREG 617 1.87 14 ANTNSHKDRREGHRQ 620 1.87 15 QENEEKAHTSGKEKR 789 1.87 The table presents predicted epitope candidates of the L-protein from Lassa fever virus associated with MHC II and their peptide sequence, starting position, and prediction score. The listed peptides represent high-scoring epitopes (Score ≥ 1.87), suggesting strong potential for antigenicity and immune recognition. Several peptides, such as those spanning positions 789–795 and 613–620, occur in overlapping clusters, indicating conserved immunogenic regions within the protein. These epitopes are considered promising candidates for further validation in experimental studies and may serve as potential targets for vaccine or therapeutic design. 3.2 Design and Physicochemical Characterization of the Multi-Epitope Vaccine Construct The epitopes were used to construct a final multi-epitope vaccine construct assembled by linking the selected B-cell, HTL, and CTL epitopes with an N-terminal adjuvant sequence. The resulting chimeric protein was subjected to a comprehensive physicochemical analysis to assess its suitability as a vaccine candidate. The analysis revealed a protein with a molecular weight of 24.38 kDa, a size well within the optimal range for efficient recombinant protein expression and purification. The theoretical isoelectric point (pI) was calculated to be 11.82, indicating a strongly basic protein. This high pI may influence its solubility characteristics and interactions with cellular components. The Grand Average of Hydropathicity (GRAVY) score was − 1.70, signifying a highly hydrophilic nature, which is generally favorable for solubility in aqueous buffers and for avoiding aggregation[ 25 ]. The physicochemical properties of the final LASV multi-epitope vaccine construct including a summary of the key biophysical parameters of the designed vaccine, offering a preliminary assessment of its manufacturability and stability are presented in Table 4 . Table 4 Physicochemical properties of the multi-epitopes of Lassa Fever Virus vaccine candidate derived from complete genomic sequence of the Lassa virus L segment (strain Josiah, GenBank accession no. NC_004297) Property Value Interpretation Molecular Weight (kDa) 24.38 Optimal size for recombinant expression. Isoelectric Point (pI) 11.82 Strongly basic protein; may influence solubility and purification. Aliphatic Index 18.1 Low value suggests low thermostability. Instability Index 72.57 Predicts the protein is unstable in vitro. Hydrophobicity (GRAVY) -1.7 Highly hydrophilic, favorable for solubility. Net Charge at pH 7 39.74 High positive charge at physiological pH. Molecular weight between 10–100 kDa is generally favorable for recombinant protein expression and purification. The isoelectric point (pI) indicates the pH at which the protein carries no net charge; a pI above 9 denotes a strongly basic protein. The aliphatic index reflects the relative volume occupied by aliphatic side chains; higher values (> 70) indicate greater thermostability. The instability index predicts protein stability in vitro, where values ≥ 40 suggest instability. The grand average of hydropobility (GRAVY) score implies hydrophilic character, typically associated with improved solubility. Net charge at physiological pH (7.0) influences molecules interactions. 3.3 Predicted Stability, Expression, and Safety Profile Further analysis was conducted to predict the construct's performance in a biotechnological context and to assess its safety profile. The instability index of 72.57 classifies the protein as unstable, while the low aliphatic index of 18.10 suggests it is likely to be thermolabile. These findings indicate that formulation with stabilizing agents or lyophilization may be required for long-term storage. Despite these stability concerns, the combination of a high GRAVY score and a molecular weight well below 60 kDa supports a moderate likelihood of successful soluble expression in an E. coli system[ 26 ]. From a safety perspective, the construct yielded highly favorable predictions. The antigenicity score of 0.385 indicates a high probability of eliciting a robust immune response. Critically, the construct was predicted to be a non-allergen. This prediction was based on its lack of cysteine residues and a glycine content of 18.18%, which is below the 20% threshold sometimes associated with allergenicity. 24 This combination of high predicted antigenicity and low allergenic risk is a highly desirable profile for a vaccine candidate. The predicted solubility, expression potential, and safety assessment of the vaccine construct are presented in Table 5 . Table 5 Predictive stability, expression and safety of the multi-epitopes of Lassa Fever Virus vaccine candidate derived from complete genomic sequence of the Lassa virus L segment (strain Josiah, GenBank accession no. NC_004297) Parameter Value Threshold Prediction Status GRAVY Score -1.7 <=0.4 Likely Soluble Favorable Instability Index 72.57 =70 Thermolabile Unfavorable Molecular Weight (kDa) 24.38 <=60 Good Expression Potential Favorable Antigenicity Score 0.39 - Likely Antigenic Favorable Allergenicity Prediction - - Non-Allergen Favorable GRAVY (Grand Average of Hydropathicity) values ≤ 0.4 indicate hydrophilicity and higher solubility, an essential feature for recombinant expression. Instability Index predicts in vitro protein stability, where values ≤ 40 indicate stability and values > 40 suggest instability. Aliphatic Index is a measure of thermostability; proteins with values ≥ 70 are considered thermally stable. Molecular weight ≤ 60 kDa is generally optimal for efficient recombinant expression in heterogeneous systems. Antigenicity score > 0.4 indicates a protein is likely antigenic. 3.4. Amino acid enrichment analysis Amino acid enrichment and physicochemical property analyses were performed to evaluate the suitability of the predicted multi-epitope vaccine construct against Lassa virus. The amino acid enrichment profile (Fig. 1A) revealed significant over representation of Proline (P), Methionine (M), and Phenylalanine (F), whereas Glycine (G), Histidine (H), and Lysine (K) were markedly under represented. These patterns suggest a structural bias toward rigidity and stability while reducing excessive flexibility or charged residue content. Physicochemical predictions further supported the vaccine’s favorable properties (Fig. 1B–E). Peptide binding affinity analysis showed most epitopes with high affinity (IC50 < 50 nM) and strong ranking across predicted alleles (Fig. 1B). The peptide length distribution was dominated by epitopes of 8–10 amino acids (Fig. 1C), consistent with the optimal length for MHC class I binding. Molecular weight distribution of predicted epitopes peaked between 1,000–1,500 Da (Fig. 1D), aligning with expected epitope sizes. Hydrophobicity distribution analysis revealed that the majority of peptides exhibited moderate hydrophobicity indices (0.2–0.4; Fig. 1E), suggesting good solubility and favorable interaction potential. Together, these findings indicate that the designed multi-epitope vaccine construct possesses an amino acid composition and physicochemical features conducive to stability, antigen presentation, and recombinant expression efficiency. 3.5. In Silico Simulation of the Immune Response The computational immune simulation provided strong predictive evidence of the vaccine's immunogenic potential. Following a simulated three-dose vaccination schedule, the model predicted a classic primary and secondary immune response. A rapid increase in IgM levels was observed after the first dose, followed by a robust, class-switched IgG response that was significantly boosted by subsequent doses and remained elevated for the duration of the simulation, indicating the successful generation of B-cell memory. The simulation predicted a potent cellular immune response. Both CD4 + helper T-cell and CD8 + cytotoxic T-cell populations showed significant activation and clonal expansion following each vaccination. Importantly, the model indicated the establishment of a stable and long-lasting population of memory T-cells, suggesting the potential for durable protection. The predicted cytokine profile was highly encouraging, showing prominent spikes in IL-2, which drives T-cell proliferation, and IFN-γ, the signature cytokine of a Th1-type response. A strong Th1 response is considered essential for controlling intracellular pathogens like LASV, further supporting the vaccine's rational design. The simulated immune response to the Lassa Fever Virus vaccine candidate demonstrated distinct cellular dynamics over a 35-day period. As shown in Fig. 1, B cells exhibited class switching from IgM to IgG1 and IgG2, while T helper (TH) cells expanded rapidly before stabilizing into memory subsets. Functional states of both B and TH cells revealed transitions from activation to resting and anergic phases. Plasma B cells showed transient antibody secretion, whereas regulatory T (TR) cells displayed an early rise followed by a gradual decline, reflecting their role in immune modulation. Collectively, these results highlight the coordinated humoral and cellular responses elicited by the vaccine construct (Fig. 2). The simulated immune response dynamics following antigen exposure in the Lassa Fever Virus vaccine candidate model over a 35-day period (Fig. 3). The results show fluctuations in cytotoxic T cell subsets (total, non-memory, and memory), dendritic cell states (internalized, antigen-presenting, active, and resting), epithelial cell activity (active, infected, and antigen-presenting), natural killer (NK) cell populations, and macrophage states (internalized, antigen-presenting, active, and total). Cytokine profiles, including IFN-γ, IL-2, IL-4, IL-6, IL-10, IL-12, IL-18, IL-23, TNF-α, and TGF-β, further illustrate the regulatory environment driving immune expansion, antigen presentation, and effector functions. Together, these results highlight the interplay between innate and adaptive immune components in shaping vaccine-induced responses. 3.6 Functional Annotation of the Vaccine Construct The Gene Ontology (GO) enrichment analysis provided novel insights into the potential biological activities of the vaccine construct beyond simple epitope presentation. The analysis revealed significant associations with fundamental cellular regulatory processes. The construct was most strongly associated with regulation of gene expression (GO:0010468) and regulation of transcription, DNA-templated (GO:0006355). The enrichment of both positive and negative regulatory terms suggests a capacity to modulate host immune gene activity in a controlled manner. The analysis predicted dominant functions related to nucleic acid binding (GO:0003676), poly(A) RNA binding (GO:0044822), and transcription factor activity (GO:0001071). These predictions suggest the construct may have the ability to directly interact with host genetic material or regulatory proteins within the cell nucleus. The construct also predicted that the vaccine construct can be localise to the nucleolus (GO:0005730) and could have a significant association with extracellular vesicular exosome (GO:0070062), hinting at a potential role in intercellular immune signalling (Supplementary Tables). 4. Discussion The results of this in silico investigation demonstrate a successful design and validation of a highly promising multi-epitope vaccine candidate against Lassa virus. The strength of this candidate lies not only in its favourable predicted properties but in the rational, hypothesis-driven approach that guided its creation. The entire design process was informed by a deep understanding of the immunopathogenesis of Lassa fever. The central problem in natural LASV infection is the failure of the host to mount a timely and effective neutralizing antibody response, with viral clearance and survival being critically dependent on the CMI arm of the immune system[ 27 ]. Therefore, this study deliberately eschewed a design focused solely on antibody induction and instead prioritised the elicitation of a potent T-cell response as the significant focus of its efficacy. By selecting a diverse array of highly immunogenic CTL and HTL epitopes from the internal L protein and assembling them into a single chimeric antigen, the vaccine is specifically engineered to activate the precise immune mechanisms required for protection. The immune simulation results corroborate this strategy, predicting robust activation of both CD8 + and CD4 + T-cells and the production of IFN-γ, a key cytokine for a Th1-polarised response that is essential for controlling intracellular viral infections[ 28 ]. This tailored design represents a strategic advantage, as it aims to induce a type of immunity that is superior to the one generated during natural infection, which can directly address the key immunological challenge of delayed neutralising antibody production posed by LASV. The novelty of the vaccine construct is in its immunomodulatory properties and the potential for self-adjuvancy; perhaps this can be considered as the most intriguing finding of this study emerging as shown in the functional enrichment analysis. The strong and high-probability associations of the vaccine construct with fundamental molecular functions like nucleic acid binding and transcription factor activity are highly atypical for a simple subunit vaccine, which is generally considered immunologically inert without an external adjuvant[ 29 , 30 ]. This raises a novel and compelling hypothesis that the vaccine construct may possess intrinsic immunomodulatory properties, allowing it to function as its own adjuvant. The biophysical characteristics of the constructed vaccine lend plausibility to this hypothesis. It has a strongly basic nature (pI 11.82) and high net positive charge (+ 39.74) at physiological pH which could facilitate electrostatic interactions with the negatively charged phosphate which is the backbone of nucleic acids (DNA and RNA) or other anionic macromolecules within the nucleus and cytoplasm of an antigen-presenting cell[ 31 ]. This types of interactions could potentially trigger innate immune sensing pathways (such as theToll-like receptors, RIG-I-like receptors) or directly influence the host cell's transcriptional machinery to upregulate the expression of co-stimulatory molecules, cytokines, and other genes involved in mounting a powerful immune response – leveraging the mechanisms and pathways of innate immunity response[ 32 , 33 ]. The validation of this self-adjuvanting potential experimentally would represent a significant advance in vaccine design, suggesting that the precise sequence and biophysical nature of a multi-epitope construct can be engineered not only for antigenicity but also for active immunomodulation. This concept directly bridges the vaccine design work with the research themes of investigating gene expression in response to LASV components[ 34 ]. Since a critical and objective assessment of any vaccine candidate requires acknowledging its potential limitations; the in silico analysis predicted that this construct is likely to be unstable and thermolabile, given its instability index..This represents a significant practical challenge, particularly for a vaccine intended for use in West Africa, where maintaining a consistent cold chain can be logistically difficult. However, this predicted instability should be viewed not as a fatal flaw but as a defined engineering problem with established solutions. This finding provides crucial guidance for the next phase of preclinical process development. Several standard biopharmaceutical strategies can be employed to overcome this challenge. First, the protein can be formulated with stabilising excipients (e.g., sugars, amino acids) that protect its structure. Second, lyophilization (freeze-drying) can be used to convert the liquid vaccine into a stable powder that can be reconstituted before use, which can greatly enhance its shelf life at ambient temperatures[ 35 ]. Third, targeted site-directed mutagenesis can be employed to rationally replace specific amino acid residues that contribute to instability without compromising the integrity of the critical epitopes. By identifying this challenge at the design stage, resources can be efficiently directed towards developing a stable and practical formulation, ensuring the candidate's viability for real-world application. The multi-epitope subunit vaccine designed in this study offers a distinct and valuable addition to the global Lassa fever vaccine pipeline. While candidates based on viral vectors (rVSV, rabies) and nucleic acids (DNA, mRNA) have shown promise, they also carry platform-specific considerations regarding pre-existing vector immunity, reactogenicity, and complex manufacturing[ 15 ]. Therefore, a well-designed subunit vaccine constructed in this study, by contrast, can offer an excellent safety profile, avoiding the use of any viral components and focusing the immune response precisely on the desired protective epitopes. The unique focus of this construction on a broad array of T-cell epitopes from the L protein further distinguishes it from many GPC-focused candidates[ 36 – 38 ]. However, it is imperative to recognise the inherent limitations of a purely computational study; that i n silico predictions, no matter how sophisticated, they are hypotheses that require rigorous experimental validation. Hence, the successful computational design and validation presented in this study serves as critical step in LASV vaccine development pathway. 5. Conclusion This study successfully leveraged a comprehensive reverse vaccinology and immunoinformatics framework to computationally designed and validated a novel multi-epitope subunit vaccine candidate against Lassa virus. The resulting construct is predicted to be safe, non-allergenic, and highly antigenic. Its design is rationally tailored to induce a potent and broad T-cell-dominant immune response, which is widely held to be the key immunological correlate of protection against severe Lassa fever. Furthermore, functional analysis suggests the candidate subunit vaccine may possess unique, intrinsic immunomodulatory properties that could enhance its efficacy. While acknowledging that there are possible challenges related to protein stability and the absolute requirement for experimental validation, this in silico study provides a foundation and a promising, rationally designed subunit vaccine candidate against LASV. The subunit vaccine construct warrants advancement into preclinical evaluation and in vivo testing as part of the global effort to develop a much-needed vaccine to combat the enduring public health threat of Lassa fever in West Africa and across the world. Declarations Ethical approval Not Applicable Consent to participate Not Applicable Consent to publish Not Applicable Data Availability Statement All data used and analysed for this study are publicly available at GenBank accession no. NC_004297 was retrieved from the National Center for Biotechnology Information (NCBI) database. Declaration of Competing Interests The authors declare no known competing financial interests or personal interests. Funding Sources This research did not receive any grant from funding agencies in the public, commercial, or not-for-profit sectors. Clinical trial number Not applicable . Authors Contributions A.B.S wrote the first draft, contributed to the figures with I.S.H. The sequences and analyses pipelines were validated by N.M.I. All authors reviewed the manuscript and approved for submission. References Asogun D, Arogundade B, Unuabonah F, Olugbenro O, Asogun J, Aluede F, et al. A Review of the Epidemiology of Lassa Fever in Nigeria. Microorganisms. 2025;13:1419. Gomerep S, Nuwan M, Butswat S, Bartekwa J, Thliza S, Akude C et al. Epidemiological review of confirmed Lassa fever cases during 2016–2018, in Plateau State, North Central Nigeria. Spinicci M, editor. PLOS Glob Public Health. 2022;2:e0000290. Besson ME, Pépin M, Metral P-A. Lassa Fever: Crit Rev Prospects Control TropicalMed. 2024;9:178. Richmond JK. Lassa fever: epidemiology, clinical features, and social consequences. BMJ. 2003;327:1271–5. Kayem ND, Benson C, Aye CYL, Barker S, Tome M, Kennedy S, et al. Lassa fever in pregnancy: a systematic review and meta-analysis. Trans R Soc Trop Med Hyg. 2020;114:385–96. John RS, Fatoyinbo HO, Hayman DTS. Modelling Lassa virus dynamics in West African Mastomys natalensis and the impact of human activities. J R Soc Interface. 2024;21:20240106. Munjita SM, Kalonda A, Mubemba B, Vanaerschot M, Tato C, Mwakibete L, et al. Evidence of multiple bacterial, viral, and parasitic infectious disease agents in Mastomys natalensis rodents in riverine areas in selected parts of Zambia. Infect Ecol Epidemiol. 2025;15:2441537. Sikiru A, Makinde J. A Preliminary outcome of data mining exploration on genetic and functional basis of Lassa virus neutralizing antibodies production in multimammate rats. Omu-Aran: Nigerian Bioinformatics and Genomics Network;: Landmark University; 2021. p. 28. McKendrick JQ, Tennant WSD, Tildesley MJ. Modelling seasonality of Lassa fever incidences and vector dynamics in Nigeria. Nzelu C, editor. PLoS Negl Trop Dis. 2023;17:e0011543. Olayemi A, Cadar D, Magassouba N, Obadare A, Kourouma F, Oyeyiola A, et al. New Hosts of The Lassa Virus. Sci Rep. 2016;6:25280. Shieh W-J, Demby A, Jones T, Goldsmith CS, Rollin PE, Ksiazek TG, et al. Pathology and Pathogenesis of Lassa Fever: Novel Immunohistochemical Findings in Fatal Cases and Clinico-pathologic Correlation. Clin Infect Dis. 2022;74:1821–30. Enriquez AS, Avalos RD, Parekh D, Cooper CL, Morrow G, Geisbert TW, et al. Mapping the antibody response to Lassa virus vaccination of non-human primates. eBioMedicine. 2025;114:105673. Brouwer PJM, Perrett HR, Beaumont T, Nijhuis H, Kruijer S, Burger JA, et al. Defining bottlenecks and opportunities for Lassa virus neutralization by structural profiling of vaccine-induced polyclonal antibody responses. Cell Rep. 2024;43:114708. Fischer WA, Wohl DA. Moving Lassa Fever Research and Care Into the 21st Century. J Infect Dis. 2017;215:1779–81. Ly H. Progress toward the development of Lassa vaccines. Expert Rev Vaccines. 2024;23:5–7. Salam AP, Duvignaud A, Jaspard M, Malvy D, Carroll M, Tarning J et al. Ribavirin for treating Lassa fever: A systematic review of pre-clinical studies and implications for human dosing. Marzi A, editor. PLoS Negl Trop Dis. 2022;16:e0010289. Cheng H-Y, French CE, Salam AP, Dawson S, McAleenan A, McGuinness LA, et al. Lack of Evidence for Ribavirin Treatment of Lassa Fever in Systematic Review of Published and Unpublished Studies1. Emerg Infect Dis. 2022;28:1559–68. Eberhardt KA, Mischlinger J, Jordan S, Groger M, Günther S, Ramharter M. Ribavirin for the treatment of Lassa fever: A systematic review and meta-analysis. Int J Infect Dis. 2019;87:15–20. Sulis G, Peebles A, Basta NE. Lassa fever vaccine candidates: A scoping review of vaccine clinical trials. Trop Med Int Health. 2023;28:420–31. Baral P, Pavadai E, Gerstman BS, Chapagain PP. In-silico identification of the vaccine candidate epitopes against the Lassa virus hemorrhagic fever. Sci Rep. 2020;10:7667. Sakabe S, Hartnett JN, Ngo N, Goba A, Momoh M, Sandi JD, et al. Identification of Common CD8 + T Cell Epitopes from Lassa Fever Survivors in Nigeria and Sierra Leone. Heise MT, editor. J Virol. 2020;94:e00153–20. Ahmadi N, Aghasadeghi M, Hamidi-fard M, Motevalli F, Bahramali G. Reverse Vaccinology and Immunoinformatic Approach for Designing a Bivalent Vaccine Candidate Against Hepatitis A and Hepatitis B Viruses. Mol Biotechnol. 2024;66:2362–80. Rapin N, Lund O, Bernaschi M, Castiglione F. Computational Immunology Meets Bioinformatics: The Use of Prediction Tools for Molecular Binding in the Simulation of the Immune System. Brusic V, editor. PLoS ONE. 2010;5:e9862. McGuffin LJ, Bryson K, Jones DT. The PSIPRED protein structure prediction server. Bioinformatics. 2000;16:404–5. Ptak-Kaczor M, Banach M, Stapor K, Fabian P, Konieczny L, Roterman I. Solubility and Aggregation of Selected Proteins Interpreted on the Basis of Hydrophobicity Distribution. IJMS. 2021;22:5002. Samiei H, Nazarian S, Hajizade A, Kordbacheh E. In silico design, production and immunization evaluation of a recombinant bivalent fusion protein candidate vaccine against E. coli O157:H7. Int Immunopharmacol. 2023;114:109464. Fischer WA, Wohl DA. Moving Lassa Fever Research and Care Into the 21st Century. J Infect Dis. 2017;215:1779–81. Bangura U, Davis C, Lamin J, Bangura J, Soropogui B, Davison AJ, et al. Spatio-temporal spread of Lassa virus and a new rodent host in the Mano River Union area, West Africa. Emerg Microbes Infections. 2024;13:2290834. Van Der Weken H, Cox E, Devriendt B. Advances in Oral Subunit Vaccine Design. Vaccines. 2020;9:1. Wilson-Welder JH, Torres MP, Kipper MJ, Mallapragada SK, Wannemuehler MJ, Narasimhan B. Vaccine adjuvants: Current challenges and future approaches. J Pharm Sci. 2009;98:1278–316. Xiao F, Chen Z, Wei Z, Tian L. Hydrophobic Interaction: A Promising Driving Force for the Biomedical Applications of Nucleic Acids. Adv Sci. 2020;7:2001048. Cui J, Chen Y, Wang HY, Wang R-F. Mechanisms and pathways of innate immune activation and regulation in health and cancer. Hum Vaccines Immunotherapeutics. 2014;10:3270–85. Duan T, Du Y, Xing C, Wang HY, Wang R-F. Toll-Like Receptor Signaling and Its Role in Cell-Mediated Immunity. Front Immunol. 2022;13:812774. Malhotra S, Yen JY, Honko AN, Garamszegi S, Caballero IS, Johnson JC et al. Transcriptional Profiling of the Circulating Immune Response to Lassa Virus in an Aerosol Model of Exposure. Geisbert T, editor. PLoS Negl Trop Dis. 2013;7:e2171. Preston KB, Randolph TW. Stability of lyophilized and spray dried vaccine formulations. Adv Drug Deliv Rev. 2021;171:50–61. Schaap-Johansen A-L, Vujović M, Borch A, Hadrup SR, Marcatili P. T Cell Epitope Prediction and Its Application to Immunotherapy. Front Immunol. 2021;12:712488. Liu B, Bai M, Zheng F, Yan M, Huang E, Wen J, et al. The Identification of Dual T-Cell and B-Cell Epitopes Within Viral Proteins Utilizing a Comprehensive Peptide Array Approach. Vaccines. 2025;13:239. Hensen L, Illing PT, Rowntree LC, Davies J, Miller A, Tong SYC, et al. T Cell Epitope Discovery in the Context of Distinct and Unique Indigenous HLA Profiles. Front Immunol. 2022;13:812393. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 28 Nov, 2025 Reviews received at journal 25 Nov, 2025 Reviews received at journal 23 Nov, 2025 Reviews received at journal 16 Nov, 2025 Reviews received at journal 15 Nov, 2025 Reviewers agreed at journal 15 Nov, 2025 Reviewers agreed at journal 15 Nov, 2025 Reviewers agreed at journal 14 Nov, 2025 Reviewers agreed at journal 14 Nov, 2025 Reviewers invited by journal 14 Nov, 2025 Editor assigned by journal 03 Nov, 2025 Submission checks completed at journal 31 Oct, 2025 First submitted to journal 31 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7860035","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":549717010,"identity":"76cd5437-4196-4d5e-addc-9781dff19f44","order_by":0,"name":"Akeem Babatunde 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07:03:50","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":153860,"visible":true,"origin":"","legend":"","description":"","filename":"c2891d4eff7840f18ad11067f069f5a21structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7860035/v1/46a77654b3cd50e5bf0d6909.xml"},{"id":96792476,"identity":"5b815e84-499f-4d40-a4cb-a7629209df94","added_by":"auto","created_at":"2025-11-26 07:03:50","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":159528,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7860035/v1/9e58ebdc41e7f9f1f52c4e7b.html"},{"id":96792469,"identity":"1b4435c9-dc14-4868-a6b9-5ad874c9a3e1","added_by":"auto","created_at":"2025-11-26 07:03:50","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":628357,"visible":true,"origin":"","legend":"\u003cp\u003eAmino acid enrichment and physicochemical properties of the Lassa virus multi-epitope vaccine candidate. (A) Amino acid enrichment analysis showing over represented and under represented residues. (B) Peptide binding affnity vs. rank across predicted alleles. (C) Peptide length distribution highlighting predominance of 8–10 amino acid epitopes. (D) Molecular weight distribution of predicted epitopes. (E) Hydrophobicity distribution indicating moderate indices consistent with solubility and favorable antigen presentation potential.\u003c/p\u003e","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7860035/v1/3058eb36b2bf418f1812c7d9.jpg"},{"id":96915511,"identity":"e1fca74e-d535-43b4-9fc0-27e588156945","added_by":"auto","created_at":"2025-11-27 14:07:21","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":689418,"visible":true,"origin":"","legend":"\u003cp\u003eKinetics of immune cell populations and functional states following antigen exposure in the Lassa Fever Virus vaccine candidate model. The figure illustrates simulated dynamics of immune cell populations over a 35-day period post-antigen exposure. (Top left) B cell population kinetics showing total B cells, memory B cells, and isotype class switching (IgM, IgG1, IgG2). (Top right) T helper (TH) cell dynamics, including total, non-memory, and memory subsets. (Middle left) B cell functional states, including activated, antigen-presenting, duplicating, and anergic cells. (Middle right) TH cell functional states, showing activated, duplicating, resting, and anergic subsets. (Bottom left) Plasma B (PLB) cell populations categorized by antibody isotype (IgM, IgG1, IgG2, IgA). (Bottom right) Regulatory T (TR) cell dynamics across functional states (active, resting, memory, and total). The results highlight differential expansion, activation, and decline phases, reflecting coordinated humoral and cellular immune responses to the vaccine candidate.\u003c/p\u003e","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7860035/v1/6d5016b9ad9e2da54e1db1c3.jpg"},{"id":96792472,"identity":"1d9e10cf-f6bd-49fd-87ef-212146bd4555","added_by":"auto","created_at":"2025-11-26 07:03:50","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":683838,"visible":true,"origin":"","legend":"\u003cp\u003eDynamics of Cytotoxic T Cells, Antigen-Presenting Cells, Cytokines, and Innate Immune Populations Following Antigen Exposure in the Lassa Fever Virus Vaccine Candidate Model . The figure illustrates simulated immune responses over 35 days post-antigen exposure. (Top left) Cytotoxic T cell (TC) populations, including total, non-memory, and memory subsets. (Top right) Dendritic cell (DC) states showing internalized, antigen-presenting (types 1 and 2), active, and resting populations. (Middle left) Cytokine concentration profiles, highlighting IFN-γ, IL-2 (inset), IL-4, IL-6, IL-10, IL-12, IL-18, IL-23, TNF-α, and TGF-β. (Middle right) Epithelial (EP) cell states, including active, actively infected, and antigen-presenting cells. (Bottom left) Natural killer (NK) cell population dynamics. (Bottom right) Macrophage (MA) states, including internalized, antigen-presenting (types 1 and 2), active, and total populations. The results demonstrate coordinated activity of adaptive and innate immune responses, characterized by cytokine-driven expansion, antigen presentation, and regulation of effector functions in response to the vaccine candidate.\u003c/p\u003e","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7860035/v1/c529cd667b9aa62238715e3e.jpg"},{"id":96922753,"identity":"f6dc1dbf-530d-4754-9c59-a8f316c11f7e","added_by":"auto","created_at":"2025-11-27 14:19:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3001309,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7860035/v1/852f3099-7d57-42e6-a4af-dcc983a1b8d6.pdf"},{"id":96916582,"identity":"217bd7bf-8c4f-47ce-9882-01c78ac1a95a","added_by":"auto","created_at":"2025-11-27 14:08:45","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23076,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7860035/v1/8edcddc6f44d9c428eaff6de.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Design and In Silico Validation of a Novel Multi-Epitopes Subunit Vaccine Candidate against Lassa Virus Using Reverse Vaccinology Approach","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLassa fever (LF) is an acute viral haemorrhagic illness caused by the Lassa virus (LASV), an arenavirus first identified in the town of Lassa, Nigeria, in 1969[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. For over a period of five decades, the virus has been a persistent and remain a formidable public health challenge across West Africa. The disease is endemic in several countries, including Nigeria, Sierra Leone, Liberia, Guinea, and Benin, with sporadic cases and outbreaks reported in neighbouring nations of the listed countries. The annual burden of Lassa fever is substantial, with epidemiological estimates suggesting between 100,000 and 300,000 infections and approximately 5,000 deaths each year. These figures, however, are widely considered to be underestimates due to limited surveillance capacity and under-reporting in many rural, resource-constrained settings of most Low and Middle Income Countries (LIMCs) where the disease is endemic[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe clinical presentation of Lassa fever is highly variable, with an estimated 80% of LASV infections reported as asymptomatic or result in a mild, undifferentiated febrile illness, often mistaken for more common endemic diseases in the LIMCs such as malaria[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, the remaining 20% of cases progress to a severe, multi-system disease characterized by high fever, facial edema, respiratory distress, and haemorrhagic manifestations such as bleeding from the gums, nose, or gastrointestinal tract[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The case-fatality rate (CFR) among hospitalized patients is alarmingly high, frequently cited at around 15% but capable of exceeding this during major outbreaks[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCertain populations are disproportionately affected. Lassa fever poses a grave risk during pregnancy, particularly in the third trimester, where it is associated with maternal mortality rates over 30% and fetal or neonatal loss in more than 80% of cases[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This devastating impact on maternal and child health call for an urgent need for effective preventative measures. Furthermore, the disease places an immense strain on the fragile healthcare infrastructure of the endemic regions. Healthcare workers are at high risk of nosocomial transmission, and outbreaks can disrupt essential health services, leading to broader socioeconomic consequences that impede development and stability. The combination of its high epidemic potential, significant mortality, and impact on vulnerable groups establishes Lassa fever as a major, unresolved public health crisis.\u003c/p\u003e\u003cp\u003eLassa fever is a classic zoonotic disease, with its persistence in nature intrinsically linked to its rodent reservoir. For decades, the primary host of the virus has been identified as the \u003cem\u003eNatal multimammate\u003c/em\u003e mouse, \u003cem\u003eMastomys natalensis\u003c/em\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This rodent species is ubiquitous across sub-Saharan Africa and thrives in peridomestic environments, which means living in and around human dwellings and agricultural areas which makes it a crucial aspect of LASV epidemiology. However, \u003cem\u003eM. natalensis\u003c/em\u003e do not become ill when infected; instead, they become asymptomatic, chronic carriers, shedding the virus in their urine and feces throughout their lifetime[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This persistent shedding of virus ensures continuous environmental contamination, leading to human infections through direct contact with rodents or, more commonly, through ingestion of food and water contaminated with rodent excreta[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Human outbreaks often exhibit seasonality, with cases typically peaking during the dry season (December-March), a period associated with agricultural practices and rodent movements that increase human-rodent contact[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile control efforts have historically focused on \u003cem\u003eM. natalensis\u003c/em\u003e, a growing body of molecular evidence has revealed a more complex and challenging ecological landscape. The assumption of a single reservoir host is no longer tenable. Recent studies have definitively identified several other rodent species as competent hosts for LASV. These include the closely related Guinea multimammate mouse (\u003cem\u003eMastomys erythroleucus\u003c/em\u003e), the African wood mouse (\u003cem\u003eHylomyscus pamfi\u003c/em\u003e), the rusty-bellied brush-furred mouse (\u003cem\u003eLophuromys sikapusi\u003c/em\u003e), and even common species like the black rat (\u003cem\u003eRattus rattus\u003c/em\u003e) and house mouse (\u003cem\u003eMus musculus\u003c/em\u003e). These newly identified reservoirs occupy diverse ecological niches, from the commensal habitats of \u003cem\u003eM. erythroleucus\u003c/em\u003e to the forest-dwelling preference of \u003cem\u003eH. pamfi\u003c/em\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This discovery of expanded host range has profound implications for public health and vaccine development strategy against the disease ravaging large population. The existence of multiple, ecologically diverse reservoirs suggests that LASV may be maintained in complex transmission cycles, potentially including sylvatic cycles that are independent of the peridomestic cycle involving \u003cem\u003eM. natalensis\u003c/em\u003e. This ecological complexity severely undermines the long-term efficacy of rodent control as a standalone prevention strategy. Eliminating or controlling multiple rodent species across varied landscapes is a far more daunting, if not impossible, task than targeting a single commensal species. This realization elevates the strategic importance of developing a human vaccine, shifting the focus from an intractable environmental problem to a tractable biomedical solution. Meanwhile, vaccine that confers durable immunity in humans represents the most viable and sustainable path to mitigating the threat of Lassa fever in the face of its complex and expanding zoonotic origins.\u003c/p\u003e\u003cp\u003eThe clinical outcome of LASV infection is largely determined by the nature and kinetics of the host immune response. The virus exhibits broad tissue tropism, infecting key cell types including endothelial cells, hepatocytes, and cells of the mononuclear phagocyte system, such as macrophages and dendritic cells[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The pathogenesis is driven not only by direct viral cytotoxicity, particularly in the liver where hepatocellular necrosis is a common finding, but also by profound immune dysregulation. Further, infection of endothelial cells and macrophages also occurs which can trigger the release of inflammatory mediators, leading to increased vascular permeability, fluid shifts, and the edema and hypotension characteristic of severe disease[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eUnfortunately, a central and defining feature of Lassa fever immunobiology is the paradoxical nature of the antibody response. In many viral infections, the rapid production of neutralizing antibodies (NAbs) is critical for viral clearance and protection. In Lassa fever, however, NAbs appear late in convalescence, often weeks after the virus has been cleared from the bloodstream[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This temporal disconnect strongly suggests that antibodies play a minimal role in controlling the acute phase of the infection. While IgM antibodies do appear and correlate with viral clearance, their neutralizing capacity is limited, and their primary role may be in functions other than direct virus neutralization[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn stark contrast, survival from severe Lassa fever is strongly correlated with the induction of a robust and timely cell-mediated immune (CMI) response[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Specifically, the activation and expansion of LASV-specific cytotoxic CD8\u0026thinsp;+\u0026thinsp;T-lymphocytes (CTLs) are considered paramount for identifying and eliminating virus-infected cells, thereby controlling viral replication and facilitating clearance[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The natural immune response to LASV can thus be viewed as sub-optimal, as the virus appears to have evolved mechanisms to delay or evade the production of an effective early neutralizing antibody response. Therefore, an effective vaccine should not necessarily aim to mimic this flawed natural response, but instead, a more rational strategy is required to design a vaccine that specifically elicits the type of immunity known to be protective. Hence, the primacy of CMI in controlling LASV infection provides a clear immunological directive including an ideal Lassa fever vaccine engineered to induce a potent, broad, and durable T-cell response, capable of rapidly recognizing and clearing infected cells upon exposure. This present study was carried out on this principle, aiming to design a vaccine candidate rich in T-cell epitopes to drive a protective CMI response.\u003c/p\u003e\u003cp\u003eThe confluence of factors associated with LASV include a significant and sustained disease burden, a complex and expanding reservoir ecology that makes environmental control untenable, and the limited efficacy of post-exposure therapeutics like Ribavirin which creates an undeniable imperative for the development of a safe and effective Lassa fever vaccine[\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This need is globally recognized, with the World Health Organization (WHO) designating Lassa fever as a priority pathogen in its Research and Development Blueprint, highlighting it as a disease for which preventative countermeasures are urgently needed. However, traditional vaccine development for a BSL-4 pathogen like LASV is fraught with challenges. This is because working with the live virus is inherently dangerous, requiring expensive high-containment facilities and highly trained personnel. This makes the conventional approaches of virus attenuation or inactivation slow, costly, and resource-intensive especially in LIMCs[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These obstacles have historically impeded progress in the field, but modern biotechnological advances offer a powerful alternative.\u003c/p\u003e\u003cp\u003eReverse vaccinology represents a paradigm shift in vaccine design that can push development of vaccines against the LASV beyond the limit. This \u003cem\u003ein silico\u003c/em\u003e approach leverages genomic, proteomic, and immunoinformatic tools to mine the pathogen's entire proteome for proteins and peptide sequences (epitopes) that are likely to be effective antigens. By computationally predicting and prioritizing vaccine targets, this strategy can be used to bypasses the need to culture live pathogen during the initial design and discovery phases, which could dramatically increasing speed and safety while reducing costs. This methodology is particularly well-suited for high-consequence pathogens like LASV. While several Lassa vaccine candidates are currently in various stages of development\u0026mdash;including those based on recombinant vesicular stomatitis virus (rVSVΔG-LASV-GPC), DNA (INO-4500), and inactivated rabies virus (LASSARAB)\u0026mdash;there is still no licensed vaccine, and the pipeline would benefit from diverse and innovative candidates[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Therefore, this study was carried out to employ a comprehensive reverse vaccinology and immunoinformatics pipeline to design and perform a rigorous \u003cem\u003ein silico\u003c/em\u003e validation of a novel multi-epitope subunit vaccine candidate against Lassa virus. By specifically targeting the viral L segment proteins, the primary objective was to construct a chimeric protein engineered to elicit a robust, broad, and durable cell-mediated immune response, addressing the key immunological requirement for protection against Lassa fever.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Genomic Data Retrieval and Target Protein Selection\u003c/h2\u003e\u003cp\u003eThe complete genomic sequence of the Lassa virus L segment (strain Josiah, GenBank accession no. NC_004297) was retrieved from the National Center for Biotechnology Information (NCBI) database. The L segment, approximately 7.2 kb in size, encodes the Z protein (a RING-finger matrix protein) and the L protein (an RNA-dependent RNA polymerase, RdRP) in an ambisense orientation[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These internal proteins were selected as the source for vaccine epitopes due to their high level of expression during the viral replication cycle and their established role as rich sources of T-cell epitopes, making them ideal targets for a vaccine designed to elicit a strong CMI response[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Epitope Prediction and Prioritization\u003c/h2\u003e\u003cp\u003eThere was an implementation of a systematic immunoinformatics workflow used to predict B-cell and T-cell epitopes from the amino acid sequences of the L and Z proteins, such as epitopes predictions, vaccine construction, physicochemical properties assessment, immnobioinformatic analyses, and functional enrichment analyses using packages in R studio Kousa Dogwood release (27771613, 2025-02-02) for windows and dedicated bioinformatics servers. The linear B-cell epitopes, which are contiguous amino acid sequences recognized by antibodies, were predicted using bioinformatics servers that analyze properties such as antigenicity, surface accessibility, and hydrophilicity. Peptides with high prediction scores were prioritized as potential candidates for inducing a humoral immune response[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMajor Histocompatibility Complex (MHC) class I epitope which are peptides with the potential to bind major histocompatibility complex (MHC) class I molecules were predicted to identify candidate cytotoxic T-lymphocyte (CTL) epitopes. This was done using established prediction algorithms, that is the use of 9-mer peptides evaluated for their binding affinity to a comprehensive panel of common human leukocyte antigen (HLA) class I alleles; where high-affinity binders were considered strong candidates for recognition by CD8\u0026thinsp;+\u0026thinsp;T-cells[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The MHC class II epitopes were used to identify helper T-lymphocyte (HTL) epitopes, where 15-mer peptides were screened for their predicted binding affinity to a panel of prevalent HLA class II alleles (including HLA-DR, -DP, and -DQ isotypes). These epitopes selected are crucial for activating CD4\u0026thinsp;+\u0026thinsp;T-cells, which orchestrate and support both humoral and cytotoxic immune responses[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These led to generation of a large pool of predicted epitopes which were then subjected to a stringent, multi-parameter filtration process to select only the most promising candidates for inclusion in the final vaccine construct. These selection criteria included classification as high antigenicity which are epitopes predicted with ability to be recognized by immune receptors; and immunogenicity which are epitopes predicted with capacity to provoke a functional immune response.\u003c/p\u003e\u003cp\u003eThis was followed by a conservation analysis carried out across multiple LASV strains to ensure the selected epitopes are conserved, maximizing the potential for broad protection. The analysis include testing for non-homology to human proteome whereby each candidate epitope was subjected to a BLASTp search against the \u003cem\u003eHomo sapiens\u003c/em\u003e proteome to eliminate any peptides with significant sequence similarity to human proteins, thereby minimizing the risk of inducing autoimmune reactions. Non-allergenicity and non-toxicity testing using computational tools to predict whether an epitope is likely to be allergenic or toxic. Cytokine induction potential carried out to further screened the epitopes for their predicted ability to induce the production of key cytokines, particularly interferon-gamma (IFN-γ), which is a hallmark of a protective Th1-type CMI response.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Multi-Epitopes Vaccine Construction and Design\u003c/h2\u003e\u003cp\u003eThere was a final chimeric vaccine protein which was rationally designed by joining the top-scoring filtered epitopes into a single poly peptide chain. The construct was architected as follows; an adjuvant sequence was fused to the N-terminus of the construct to stimulate innate immune signaling and enhance the overall immunogenicity of the vaccine. The selected CTL (MHC-I) epitopes were linked sequentially using AAY linkers. These specific linkers are designed to facilitate proteasomal cleavage, promoting efficient processing and presentation of the individual epitopes on MHC class I molecules. The selected HTL (MHC-II) epitopes were joined using GPGPG linkers. These flexible linkers help to maintain the independent conformational and immunogenic integrity of each epitope, allowing for proper presentation on MHC class II molecules. The final arrangement of the domains (adjuvant, HTL cluster, CTL cluster) was optimized to ensure efficient expression, folding, and immunological processing.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Physicochemical, Structural, and Immunological Characterization of the Vaccine Construct\u003c/h2\u003e\u003cp\u003eThe final amino acid sequence of the designed vaccine constructed was subjected to a series of different comprehensive \u003cem\u003ein silico\u003c/em\u003e analyses to predict its viability as a vaccine candidate that can be scale from in silico design to further downstream evaluation for its suitability as a potential biopharmaceutical product. The physicochemical properties was determined using the ExPASy ProtParam server used to calculate fundamental physicochemical parameters, including molecular weight (MW), theoretical isoelectric point (pI), instability index, aliphatic index, and Grand Average of Hydropathicity (GRAVY). The solubility and expression potential of the construct's potential for being expressed as a soluble protein in an \u003cem\u003eEscherichia coli\u003c/em\u003e system was predicted based on its physicochemical properties, particularly the GRAVY score and molecular weight. The overall antigenicity of the full-length construct was predicted based on sequence motifs and amino acid composition of the vaccine construct.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.6 \u003cem\u003eIn Silico\u003c/em\u003e Immune Simulation\u003c/h2\u003e\u003cp\u003eTo forecast the potential immune response that can be elicited by the vaccine candidate \u003cem\u003ein vivo\u003c/em\u003e, a computational immune simulation was performed using the C-IMMSIM server[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The simulation was configured to model a standard prime-boost vaccination regimen, with three injections administered at four-week intervals. The simulation tracked key immunological parameters over a one-year period, generating predictive data on humoral immunity focusing on B-cell population dynamics, including memory B-cell formation and the production kinetics of immunoglobulin isotypes (IgM and IgG); cellular immunity focus on activation, proliferation, and differentiation of CD4+ (helper) and CD8+ (cytotoxic) T-cell populations, as well as the establishment of long-term T-cell memory. The cytokine response at the levels of key immunomodulatory cytokines, such as IL-2 and IFN-γ, to predict the polarization of the T-helper response (Th1 vs. Th2) was also analysed.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Functional Enrichment Analysis\u003c/h2\u003e\u003cp\u003eTo gain insight into the potential biological mechanisms of action of the vaccine constructed, a Gene Ontology (GO) enrichment analysis was performed using PSIPRED protein server[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This analysis uses sequence-based prediction algorithms to associate the protein with terms from three major GO domains including biological processes, molecular functions and cellular components. The larger biological programmes of the protein indicates that the vaccine construct may participate in regulation of immune response. The molecular function focus on the specific biochemical activities of the protein, while cellular component focus on the sub-cellular locations where the protein may be found such as nucleus, cytoplasm, and cell membrane.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Identification of Potent and Conserved B-Cell and T-Cell Epitopes\u003c/h2\u003e\u003cp\u003eThe immunoinformatic screening of the LASV L segment proteome identified a large number of potential B-cell and T-cell epitopes. Following the application of a stringent multi-parameter filtration protocol, a final set of high-priority epitopes was selected for inclusion in the vaccine construct. These selected epitopes demonstrated high predicted antigenicity and immunogenicity, were conserved across LASV strains, and showed no significant homology to the human proteome. The selected candidates for each epitope class include top-ranked predicted linear B-cell epitopes (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These are top 10 predicted linear B-cell epitopes from the LASV L protein with their respective sequences which are predicted to be recognized by antibodies and are foundational to the humoral immunity component of the designed vaccine. In addition, additional top-ranked predicted MHC Class I epitopes (n\u0026thinsp;=\u0026thinsp;15) with potential cytotoxic T-lymphocyte (CTL) potential were identified. These epitopes are 9-mer peptides which are predicted to bind MHC class I molecules and central to the vaccine's aim of inducing a potent CD8\u0026thinsp;+\u0026thinsp;T-cell response to kill virus-infected cells (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The top-ranked predicted MHC class II epitopes as 15 predicted helper T-lymphocyte (HTL) epitopes. These 15-mer peptides are designed to be presented by MHC class II molecules to activate CD4\u0026thinsp;+\u0026thinsp;T-cells, which are essential for coordinating and amplifying the overall adaptive immune response (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePredicted High-Scoring Epitopes of the L-Protein from Lassa Fever Virus derived from complete genomic sequence of the Lassa virus L segment (strain Josiah, GenBank accession no. NC_004297)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePeptide Sequence\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePosition\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eScore\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePQKEPEKRRRREKPK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQKEPEKRRRREKPKH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1122\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKEPEKRRRREKPKHQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEKRRRREKPKHQAKR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKRPEKRRKPTKTKRR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRRNKRRAKGRKQRKG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e669\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRNKRRAKGRKQRKGR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e670\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNKRRAKGRKQRKGRR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e671\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePPPQKEPEKRRRREK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePPQKEPEKRRRREKP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe table shows the top-ranked epitope candidates predicted from the L-protein of Lassa fever virus. Each peptide is listed with its sequence, starting position in the protein, and corresponding prediction score. Peptides with scores\u0026thinsp;\u0026ge;\u0026thinsp;0.85 were considered high-confidence epitopes with potential targets for immune recognition and vaccine development.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePredicted L-Protein MHC Class I Epitope Candidates of Lassa Fever Virus derived from complete genomic sequence of the Lassa virus L segment (strain Josiah, GenBank accession no. NC_004297)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePeptide Sequence\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePosition\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eScore\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHRATAKSAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRATAKSAAK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATAKSAAKT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAKSAAKTRA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDAAPRAKRA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1496\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAAPRAKRAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQAAHKKATA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1636\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAAHKKATAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1637\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGDQARARPA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDQARARPAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQARARPARP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eARARPARPQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePRATHRATA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRATHRATAK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATHRATAKS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable presents predicted epitope candidates derived from the L-protein of Lassa fever virus. Each entry shows the peptide sequence, starting position within the protein, and the prediction score. Peptides with scores ranging from 0.33 to 0.44 are classified as moderate-scoring epitopes, which may contribute to immune recognition but require further experimental validation for immunogenic potential.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePredicted L-Protein MHC Class II Epitope Candidates of Lassa Fever Virus derived from complete genomic sequence of the Lassa virus L segment (strain Josiah, GenBank accession no. NC_004297)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePeptide Sequence\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePosition\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eScore\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKAHTSGKEKRNRDEP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e794\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQGRPEGANTNSHKDR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDKKRAPHEQNAGSPT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSRKGEHKTQTRAKND\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e506\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePRSNKTRHRNRDEGQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e534\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRPEGANTNSHKDRRE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e616\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEEKAHTSGKEKRNRD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e792\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEKAHTSGKEKRNRDE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e793\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAHTSGKEKRNRDEPN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e795\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKPRSNKTRHRNRDEG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e533\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNQGRPEGANTNSHKD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGRPEGANTNSHKDRR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e615\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePEGANTNSHKDRREG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e617\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eANTNSHKDRREGHRQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e620\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQENEEKAHTSGKEKR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e789\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe table presents predicted epitope candidates of the L-protein from Lassa fever virus associated with MHC II and their peptide sequence, starting position, and prediction score. The listed peptides represent high-scoring epitopes (Score\u0026thinsp;\u0026ge;\u0026thinsp;1.87), suggesting strong potential for antigenicity and immune recognition. Several peptides, such as those spanning positions 789\u0026ndash;795 and 613\u0026ndash;620, occur in overlapping clusters, indicating conserved immunogenic regions within the protein. These epitopes are considered promising candidates for further validation in experimental studies and may serve as potential targets for vaccine or therapeutic design.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Design and Physicochemical Characterization of the Multi-Epitope Vaccine Construct\u003c/h2\u003e\u003cp\u003eThe epitopes were used to construct a final multi-epitope vaccine construct assembled by linking the selected B-cell, HTL, and CTL epitopes with an N-terminal adjuvant sequence. The resulting chimeric protein was subjected to a comprehensive physicochemical analysis to assess its suitability as a vaccine candidate. The analysis revealed a protein with a molecular weight of 24.38 kDa, a size well within the optimal range for efficient recombinant protein expression and purification. The theoretical isoelectric point (pI) was calculated to be 11.82, indicating a strongly basic protein. This high pI may influence its solubility characteristics and interactions with cellular components. The Grand Average of Hydropathicity (GRAVY) score was \u0026minus;\u0026thinsp;1.70, signifying a highly hydrophilic nature, which is generally favorable for solubility in aqueous buffers and for avoiding aggregation[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The physicochemical properties of the final LASV multi-epitope vaccine construct including a summary of the key biophysical parameters of the designed vaccine, offering a preliminary assessment of its manufacturability and stability are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysicochemical properties of the multi-epitopes of Lassa Fever Virus vaccine candidate derived from complete genomic sequence of the Lassa virus L segment (strain Josiah, GenBank accession no. NC_004297)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProperty\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eValue\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterpretation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMolecular Weight (kDa)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e24.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOptimal size for recombinant expression.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIsoelectric Point (pI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStrongly basic protein; may influence solubility and purification.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAliphatic Index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLow value suggests low thermostability.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInstability Index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e72.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePredicts the protein is unstable in vitro.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHydrophobicity (GRAVY)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHighly hydrophilic, favorable for solubility.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNet Charge at pH 7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e39.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh positive charge at physiological pH.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eMolecular weight between 10\u0026ndash;100 kDa is generally favorable for recombinant protein expression and purification. The isoelectric point (pI) indicates the pH at which the protein carries no net charge; a pI above 9 denotes a strongly basic protein. The aliphatic index reflects the relative volume occupied by aliphatic side chains; higher values (\u0026gt;\u0026thinsp;70) indicate greater thermostability. The instability index predicts protein stability in vitro, where values\u0026thinsp;\u0026ge;\u0026thinsp;40 suggest instability. The grand average of hydropobility (GRAVY) score implies hydrophilic character, typically associated with improved solubility. Net charge at physiological pH (7.0) influences molecules interactions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Predicted Stability, Expression, and Safety Profile\u003c/h2\u003e\u003cp\u003eFurther analysis was conducted to predict the construct's performance in a biotechnological context and to assess its safety profile. The instability index of 72.57 classifies the protein as unstable, while the low aliphatic index of 18.10 suggests it is likely to be thermolabile. These findings indicate that formulation with stabilizing agents or lyophilization may be required for long-term storage. Despite these stability concerns, the combination of a high GRAVY score and a molecular weight well below 60 kDa supports a moderate likelihood of successful soluble expression in an \u003cem\u003eE. coli\u003c/em\u003e system[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. From a safety perspective, the construct yielded highly favorable predictions. The antigenicity score of 0.385 indicates a high probability of eliciting a robust immune response. Critically, the construct was predicted to be a non-allergen. This prediction was based on its lack of cysteine residues and a glycine content of 18.18%, which is below the 20% threshold sometimes associated with allergenicity.\u003csup\u003e24\u003c/sup\u003e This combination of high predicted antigenicity and low allergenic risk is a highly desirable profile for a vaccine candidate. The predicted solubility, expression potential, and safety assessment of the vaccine construct are presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePredictive stability, expression and safety of the multi-epitopes of Lassa Fever Virus vaccine candidate derived from complete genomic sequence of the Lassa virus L segment (strain Josiah, GenBank accession no. NC_004297)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eValue\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThreshold\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePrediction\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStatus\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGRAVY Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;=0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLikely Soluble\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFavorable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInstability Index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;=40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnstable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUnfavorable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAliphatic Index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;=70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThermolabile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUnfavorable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMolecular Weight (kDa)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;=60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGood Expression Potential\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFavorable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntigenicity Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLikely Antigenic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFavorable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAllergenicity Prediction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-Allergen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFavorable\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eGRAVY (Grand Average of Hydropathicity) values\u0026thinsp;\u0026le;\u0026thinsp;0.4 indicate hydrophilicity and higher solubility, an essential feature for recombinant expression. Instability Index predicts in vitro protein stability, where values\u0026thinsp;\u0026le;\u0026thinsp;40 indicate stability and values\u0026thinsp;\u0026gt;\u0026thinsp;40 suggest instability. Aliphatic Index is a measure of thermostability; proteins with values\u0026thinsp;\u0026ge;\u0026thinsp;70 are considered thermally stable. Molecular weight\u0026thinsp;\u0026le;\u0026thinsp;60 kDa is generally optimal for efficient recombinant expression in heterogeneous systems. Antigenicity score\u0026thinsp;\u0026gt;\u0026thinsp;0.4 indicates a protein is likely antigenic.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Amino acid enrichment analysis\u003c/h2\u003e\u003cp\u003eAmino acid enrichment and physicochemical property analyses were performed to evaluate the suitability of the predicted multi-epitope vaccine construct against Lassa virus. The amino acid enrichment profile (Fig.\u0026nbsp;1A) revealed significant over representation of Proline (P), Methionine (M), and Phenylalanine (F), whereas Glycine (G), Histidine (H), and Lysine (K) were markedly under represented. These patterns suggest a structural bias toward rigidity and stability while reducing excessive flexibility or charged residue content. Physicochemical predictions further supported the vaccine\u0026rsquo;s favorable properties (Fig.\u0026nbsp;1B\u0026ndash;E). Peptide binding affinity analysis showed most epitopes with high affinity (IC50\u0026thinsp;\u0026lt;\u0026thinsp;50 nM) and strong ranking across predicted alleles (Fig.\u0026nbsp;1B). The peptide length distribution was dominated by epitopes of 8\u0026ndash;10 amino acids (Fig.\u0026nbsp;1C), consistent with the optimal length for MHC class I binding. Molecular weight distribution of predicted epitopes peaked between 1,000\u0026ndash;1,500 Da (Fig.\u0026nbsp;1D), aligning with expected epitope sizes. Hydrophobicity distribution analysis revealed that the majority of peptides exhibited moderate hydrophobicity indices (0.2\u0026ndash;0.4; Fig.\u0026nbsp;1E), suggesting good solubility and favorable interaction potential. Together, these findings indicate that the designed multi-epitope vaccine construct possesses an amino acid composition and physicochemical features conducive to stability, antigen presentation, and recombinant expression efficiency.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.5. \u003cem\u003eIn Silico\u003c/em\u003e Simulation of the Immune Response\u003c/h2\u003e\u003cp\u003eThe computational immune simulation provided strong predictive evidence of the vaccine's immunogenic potential. Following a simulated three-dose vaccination schedule, the model predicted a classic primary and secondary immune response. A rapid increase in IgM levels was observed after the first dose, followed by a robust, class-switched IgG response that was significantly boosted by subsequent doses and remained elevated for the duration of the simulation, indicating the successful generation of B-cell memory. The simulation predicted a potent cellular immune response. Both CD4\u0026thinsp;+\u0026thinsp;helper T-cell and CD8\u0026thinsp;+\u0026thinsp;cytotoxic T-cell populations showed significant activation and clonal expansion following each vaccination. Importantly, the model indicated the establishment of a stable and long-lasting population of memory T-cells, suggesting the potential for durable protection. The predicted cytokine profile was highly encouraging, showing prominent spikes in IL-2, which drives T-cell proliferation, and IFN-γ, the signature cytokine of a Th1-type response. A strong Th1 response is considered essential for controlling intracellular pathogens like LASV, further supporting the vaccine's rational design. The simulated immune response to the Lassa Fever Virus vaccine candidate demonstrated distinct cellular dynamics over a 35-day period. As shown in Fig.\u0026nbsp;1, B cells exhibited class switching from IgM to IgG1 and IgG2, while T helper (TH) cells expanded rapidly before stabilizing into memory subsets. Functional states of both B and TH cells revealed transitions from activation to resting and anergic phases. Plasma B cells showed transient antibody secretion, whereas regulatory T (TR) cells displayed an early rise followed by a gradual decline, reflecting their role in immune modulation. Collectively, these results highlight the coordinated humoral and cellular responses elicited by the vaccine construct (Fig.\u0026nbsp;2). The simulated immune response dynamics following antigen exposure in the Lassa Fever Virus vaccine candidate model over a 35-day period (Fig.\u0026nbsp;3). The results show fluctuations in cytotoxic T cell subsets (total, non-memory, and memory), dendritic cell states (internalized, antigen-presenting, active, and resting), epithelial cell activity (active, infected, and antigen-presenting), natural killer (NK) cell populations, and macrophage states (internalized, antigen-presenting, active, and total). Cytokine profiles, including IFN-γ, IL-2, IL-4, IL-6, IL-10, IL-12, IL-18, IL-23, TNF-α, and TGF-β, further illustrate the regulatory environment driving immune expansion, antigen presentation, and effector functions. Together, these results highlight the interplay between innate and adaptive immune components in shaping vaccine-induced responses.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Functional Annotation of the Vaccine Construct\u003c/h2\u003e\u003cp\u003eThe Gene Ontology (GO) enrichment analysis provided novel insights into the potential biological activities of the vaccine construct beyond simple epitope presentation. The analysis revealed significant associations with fundamental cellular regulatory processes. The construct was most strongly associated with regulation of gene expression (GO:0010468) and regulation of transcription, DNA-templated (GO:0006355). The enrichment of both positive and negative regulatory terms suggests a capacity to modulate host immune gene activity in a controlled manner. The analysis predicted dominant functions related to nucleic acid binding (GO:0003676), poly(A) RNA binding (GO:0044822), and transcription factor activity (GO:0001071). These predictions suggest the construct may have the ability to directly interact with host genetic material or regulatory proteins within the cell nucleus. The construct also predicted that the vaccine construct can be localise to the nucleolus (GO:0005730) and could have a significant association with extracellular vesicular exosome (GO:0070062), hinting at a potential role in intercellular immune signalling (Supplementary Tables).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe results of this \u003cem\u003ein silico\u003c/em\u003e investigation demonstrate a successful design and validation of a highly promising multi-epitope vaccine candidate against Lassa virus. The strength of this candidate lies not only in its favourable predicted properties but in the rational, hypothesis-driven approach that guided its creation. The entire design process was informed by a deep understanding of the immunopathogenesis of Lassa fever. The central problem in natural LASV infection is the failure of the host to mount a timely and effective neutralizing antibody response, with viral clearance and survival being critically dependent on the CMI arm of the immune system[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Therefore, this study deliberately eschewed a design focused solely on antibody induction and instead prioritised the elicitation of a potent T-cell response as the significant focus of its efficacy.\u003c/p\u003e\u003cp\u003eBy selecting a diverse array of highly immunogenic CTL and HTL epitopes from the internal L protein and assembling them into a single chimeric antigen, the vaccine is specifically engineered to activate the precise immune mechanisms required for protection. The immune simulation results corroborate this strategy, predicting robust activation of both CD8\u0026thinsp;+\u0026thinsp;and CD4\u0026thinsp;+\u0026thinsp;T-cells and the production of IFN-γ, a key cytokine for a Th1-polarised response that is essential for controlling intracellular viral infections[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This tailored design represents a strategic advantage, as it aims to induce a type of immunity that is superior to the one generated during natural infection, which can directly address the key immunological challenge of delayed neutralising antibody production posed by LASV.\u003c/p\u003e\u003cp\u003eThe novelty of the vaccine construct is in its immunomodulatory properties and the potential for self-adjuvancy; perhaps this can be considered as the most intriguing finding of this study emerging as shown in the functional enrichment analysis. The strong and high-probability associations of the vaccine construct with fundamental molecular functions like nucleic acid binding and transcription factor activity are highly atypical for a simple subunit vaccine, which is generally considered immunologically inert without an external adjuvant[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This raises a novel and compelling hypothesis that the vaccine construct may possess intrinsic immunomodulatory properties, allowing it to function as its own adjuvant.\u003c/p\u003e\u003cp\u003eThe biophysical characteristics of the constructed vaccine lend plausibility to this hypothesis. It has a strongly basic nature (pI 11.82) and high net positive charge (+\u0026thinsp;39.74) at physiological pH which could facilitate electrostatic interactions with the negatively charged phosphate which is the backbone of nucleic acids (DNA and RNA) or other anionic macromolecules within the nucleus and cytoplasm of an antigen-presenting cell[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This types of interactions could potentially trigger innate immune sensing pathways (such as theToll-like receptors, RIG-I-like receptors) or directly influence the host cell's transcriptional machinery to upregulate the expression of co-stimulatory molecules, cytokines, and other genes involved in mounting a powerful immune response \u0026ndash; leveraging the mechanisms and pathways of innate immunity response[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The validation of this self-adjuvanting potential experimentally would represent a significant advance in vaccine design, suggesting that the precise sequence and biophysical nature of a multi-epitope construct can be engineered not only for antigenicity but also for active immunomodulation. This concept directly bridges the vaccine design work with the research themes of investigating gene expression in response to LASV components[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSince a critical and objective assessment of any vaccine candidate requires acknowledging its potential limitations; the \u003cem\u003ein silico\u003c/em\u003e analysis predicted that this construct is likely to be unstable and thermolabile, given its instability index..This represents a significant practical challenge, particularly for a vaccine intended for use in West Africa, where maintaining a consistent cold chain can be logistically difficult. However, this predicted instability should be viewed not as a fatal flaw but as a defined engineering problem with established solutions. This finding provides crucial guidance for the next phase of preclinical process development. Several standard biopharmaceutical strategies can be employed to overcome this challenge.\u003c/p\u003e\u003cp\u003eFirst, the protein can be formulated with stabilising excipients (e.g., sugars, amino acids) that protect its structure. Second, lyophilization (freeze-drying) can be used to convert the liquid vaccine into a stable powder that can be reconstituted before use, which can greatly enhance its shelf life at ambient temperatures[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Third, targeted site-directed mutagenesis can be employed to rationally replace specific amino acid residues that contribute to instability without compromising the integrity of the critical epitopes. By identifying this challenge at the design stage, resources can be efficiently directed towards developing a stable and practical formulation, ensuring the candidate's viability for real-world application.\u003c/p\u003e\u003cp\u003eThe multi-epitope subunit vaccine designed in this study offers a distinct and valuable addition to the global Lassa fever vaccine pipeline. While candidates based on viral vectors (rVSV, rabies) and nucleic acids (DNA, mRNA) have shown promise, they also carry platform-specific considerations regarding pre-existing vector immunity, reactogenicity, and complex manufacturing[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Therefore, a well-designed subunit vaccine constructed in this study, by contrast, can offer an excellent safety profile, avoiding the use of any viral components and focusing the immune response precisely on the desired protective epitopes. The unique focus of this construction on a broad array of T-cell epitopes from the L protein further distinguishes it from many GPC-focused candidates[\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. However, it is imperative to recognise the inherent limitations of a purely computational study; that i\u003cem\u003en silico\u003c/em\u003e predictions, no matter how sophisticated, they are hypotheses that require rigorous experimental validation. Hence, the successful computational design and validation presented in this study serves as critical step in LASV vaccine development pathway.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study successfully leveraged a comprehensive reverse vaccinology and immunoinformatics framework to computationally designed and validated a novel multi-epitope subunit vaccine candidate against Lassa virus. The resulting construct is predicted to be safe, non-allergenic, and highly antigenic. Its design is rationally tailored to induce a potent and broad T-cell-dominant immune response, which is widely held to be the key immunological correlate of protection against severe Lassa fever. Furthermore, functional analysis suggests the candidate subunit vaccine may possess unique, intrinsic immunomodulatory properties that could enhance its efficacy. While acknowledging that there are possible challenges related to protein stability and the absolute requirement for experimental validation, this \u003cem\u003ein silico\u003c/em\u003e study provides a foundation and a promising, rationally designed subunit vaccine candidate against LASV. The subunit vaccine construct warrants advancement into preclinical evaluation and \u003cem\u003ein vivo\u003c/em\u003e testing as part of the global effort to develop a much-needed vaccine to combat the enduring public health threat of Lassa fever in West Africa and across the world.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll data used and analysed for this study are publicly available at GenBank accession no. NC_004297 was retrieved from the National Center for Biotechnology Information (NCBI) database.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no known competing financial interests or personal interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Sources\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research did not receive any grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.B.S wrote the first draft, contributed to the figures with I.S.H. The sequences and analyses pipelines were validated by N.M.I. All authors reviewed the manuscript and approved for submission.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAsogun D, Arogundade B, Unuabonah F, Olugbenro O, Asogun J, Aluede F, et al. A Review of the Epidemiology of Lassa Fever in Nigeria. Microorganisms. 2025;13:1419.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGomerep S, Nuwan M, Butswat S, Bartekwa J, Thliza S, Akude C et al. Epidemiological review of confirmed Lassa fever cases during 2016\u0026ndash;2018, in Plateau State, North Central Nigeria. Spinicci M, editor. PLOS Glob Public Health. 2022;2:e0000290.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBesson ME, P\u0026eacute;pin M, Metral P-A. Lassa Fever: Crit Rev Prospects Control TropicalMed. 2024;9:178.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRichmond JK. Lassa fever: epidemiology, clinical features, and social consequences. 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A Preliminary outcome of data mining exploration on genetic and functional basis of Lassa virus neutralizing antibodies production in multimammate rats. Omu-Aran: Nigerian Bioinformatics and Genomics Network;: Landmark University; 2021. p. 28.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcKendrick JQ, Tennant WSD, Tildesley MJ. Modelling seasonality of Lassa fever incidences and vector dynamics in Nigeria. Nzelu C, editor. PLoS Negl Trop Dis. 2023;17:e0011543.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOlayemi A, Cadar D, Magassouba N, Obadare A, Kourouma F, Oyeyiola A, et al. New Hosts of The Lassa Virus. Sci Rep. 2016;6:25280.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShieh W-J, Demby A, Jones T, Goldsmith CS, Rollin PE, Ksiazek TG, et al. Pathology and Pathogenesis of Lassa Fever: Novel Immunohistochemical Findings in Fatal Cases and Clinico-pathologic Correlation. Clin Infect Dis. 2022;74:1821\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEnriquez AS, Avalos RD, Parekh D, Cooper CL, Morrow G, Geisbert TW, et al. Mapping the antibody response to Lassa virus vaccination of non-human primates. eBioMedicine. 2025;114:105673.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrouwer PJM, Perrett HR, Beaumont T, Nijhuis H, Kruijer S, Burger JA, et al. Defining bottlenecks and opportunities for Lassa virus neutralization by structural profiling of vaccine-induced polyclonal antibody responses. Cell Rep. 2024;43:114708.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFischer WA, Wohl DA. Moving Lassa Fever Research and Care Into the 21st Century. J Infect Dis. 2017;215:1779\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLy H. Progress toward the development of Lassa vaccines. Expert Rev Vaccines. 2024;23:5\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalam AP, Duvignaud A, Jaspard M, Malvy D, Carroll M, Tarning J et al. Ribavirin for treating Lassa fever: A systematic review of pre-clinical studies and implications for human dosing. Marzi A, editor. PLoS Negl Trop Dis. 2022;16:e0010289.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCheng H-Y, French CE, Salam AP, Dawson S, McAleenan A, McGuinness LA, et al. Lack of Evidence for Ribavirin Treatment of Lassa Fever in Systematic Review of Published and Unpublished Studies1. Emerg Infect Dis. 2022;28:1559\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEberhardt KA, Mischlinger J, Jordan S, Groger M, G\u0026uuml;nther S, Ramharter M. Ribavirin for the treatment of Lassa fever: A systematic review and meta-analysis. Int J Infect Dis. 2019;87:15\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSulis G, Peebles A, Basta NE. Lassa fever vaccine candidates: A scoping review of vaccine clinical trials. Trop Med Int Health. 2023;28:420\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaral P, Pavadai E, Gerstman BS, Chapagain PP. In-silico identification of the vaccine candidate epitopes against the Lassa virus hemorrhagic fever. Sci Rep. 2020;10:7667.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSakabe S, Hartnett JN, Ngo N, Goba A, Momoh M, Sandi JD, et al. Identification of Common CD8\u003csup\u003e+\u003c/sup\u003e T Cell Epitopes from Lassa Fever Survivors in Nigeria and Sierra Leone. Heise MT, editor. J Virol. 2020;94:e00153\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAhmadi N, Aghasadeghi M, Hamidi-fard M, Motevalli F, Bahramali G. Reverse Vaccinology and Immunoinformatic Approach for Designing a Bivalent Vaccine Candidate Against Hepatitis A and Hepatitis B Viruses. Mol Biotechnol. 2024;66:2362\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRapin N, Lund O, Bernaschi M, Castiglione F. Computational Immunology Meets Bioinformatics: The Use of Prediction Tools for Molecular Binding in the Simulation of the Immune System. Brusic V, editor. PLoS ONE. 2010;5:e9862.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcGuffin LJ, Bryson K, Jones DT. The PSIPRED protein structure prediction server. Bioinformatics. 2000;16:404\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePtak-Kaczor M, Banach M, Stapor K, Fabian P, Konieczny L, Roterman I. Solubility and Aggregation of Selected Proteins Interpreted on the Basis of Hydrophobicity Distribution. 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Vaccines. 2020;9:1.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilson-Welder JH, Torres MP, Kipper MJ, Mallapragada SK, Wannemuehler MJ, Narasimhan B. Vaccine adjuvants: Current challenges and future approaches. J Pharm Sci. 2009;98:1278\u0026ndash;316.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXiao F, Chen Z, Wei Z, Tian L. Hydrophobic Interaction: A Promising Driving Force for the Biomedical Applications of Nucleic Acids. Adv Sci. 2020;7:2001048.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCui J, Chen Y, Wang HY, Wang R-F. Mechanisms and pathways of innate immune activation and regulation in health and cancer. Hum Vaccines Immunotherapeutics. 2014;10:3270\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDuan T, Du Y, Xing C, Wang HY, Wang R-F. Toll-Like Receptor Signaling and Its Role in Cell-Mediated Immunity. Front Immunol. 2022;13:812774.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMalhotra S, Yen JY, Honko AN, Garamszegi S, Caballero IS, Johnson JC et al. Transcriptional Profiling of the Circulating Immune Response to Lassa Virus in an Aerosol Model of Exposure. Geisbert T, editor. PLoS Negl Trop Dis. 2013;7:e2171.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePreston KB, Randolph TW. Stability of lyophilized and spray dried vaccine formulations. Adv Drug Deliv Rev. 2021;171:50\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchaap-Johansen A-L, Vujović M, Borch A, Hadrup SR, Marcatili P. T Cell Epitope Prediction and Its Application to Immunotherapy. Front Immunol. 2021;12:712488.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu B, Bai M, Zheng F, Yan M, Huang E, Wen J, et al. The Identification of Dual T-Cell and B-Cell Epitopes Within Viral Proteins Utilizing a Comprehensive Peptide Array Approach. Vaccines. 2025;13:239.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHensen L, Illing PT, Rowntree LC, Davies J, Miller A, Tong SYC, et al. T Cell Epitope Discovery in the Context of Distinct and Unique Indigenous HLA Profiles. Front Immunol. 2022;13:812393.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-viruses","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Viruses](https://link.springer.com/journal/44370)","snPcode":"44370","submissionUrl":"https://submission.nature.com/new-submission/44370/3","title":"Discover Viruses","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7860035/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7860035/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLassa fever, caused by the Lassa virus (LASV), remains a significant public health threat in West Africa, characterised by annual outbreaks, substantial morbidity, and high case-fatality rates in hospitalized patients. The natural immune response to LASV is often marked by a delayed and weak neutralising antibody response, with survival correlating more strongly with robust cell-mediated immunity (CMI). This immunological profile, combined with the challenges of traditional vaccine development for a Biosafety Level 4 (BSL-4) pathogen, necessitates innovative strategies. This study employed a reverse vaccinology and immunoinformatics approach to design a multi-epitope subunit vaccine against LASV. The viral L segment proteins of LASV obtained from NCBI (NC_004297) were computationally screened for potent and conserved B-cell, cytotoxic T-lymphocyte (MHC-I), and helper T-lymphocyte (MHC-II) epitopes. The most promising epitopes were selected based on antigenicity, immunogenicity, non-allergenicity, and lack of homology to the human proteome. These were assembled into a single chimeric protein construct, which was then subjected to comprehensive \u003cem\u003ein silico\u003c/em\u003e characterization, including analysis of its physicochemical properties, structural integrity, and safety profile. The potential immunogenicity was evaluated through computational immune simulation. A 24.38 kDa multi-epitope vaccine construct was designed, comprising highly antigenic B-cell and T-cell epitopes linked with appropriate spacers. Physicochemical analysis predicted the construct to be hydrophilic, highly antigenic, and non-allergenic, with a moderate potential for soluble expression in \u003cem\u003eEscherichia coli\u003c/em\u003e. Immune simulations predicted that the vaccine could elicit a strong and balanced immune response, characterized by robust activation and proliferation of both CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T-cell populations, induction of immunological memory, and a cytokine profile skewed towards a protective Th1 response (IFN-γ). Functional enrichment analysis carried out suggested that the vaccine construct possesses intrinsic immunomodulatory properties, with strong associations to gene expression regulation and nucleic acid binding. The computationally designed and validated multi-epitope construct represents a promising vaccine candidate against Lassa virus. Its design is rationally tailored to induce the CMI response critical for LASV clearance. This \u003cem\u003ein silico\u003c/em\u003e study provides a strong foundation for subsequent pre-clinical development, including protein expression and \u003cem\u003ein vivo\u003c/em\u003e immunogenicity and efficacy testing in appropriate animal models.\u003c/p\u003e","manuscriptTitle":"Design and In Silico Validation of a Novel Multi-Epitopes Subunit Vaccine Candidate against Lassa Virus Using Reverse Vaccinology Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-26 07:03:45","doi":"10.21203/rs.3.rs-7860035/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-28T12:22:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-25T23:36:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-23T14:11:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-16T09:29:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-15T22:10:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"297689276561064663473235093404354353592","date":"2025-11-15T21:49:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"167279066903580011251775772744014706979","date":"2025-11-15T15:29:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"241004432670009481454489741582007457757","date":"2025-11-14T13:06:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"50599856315876069390826683496673630904","date":"2025-11-14T09:17:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-14T08:01:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-03T13:12:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-31T12:10:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Viruses","date":"2025-10-31T12:05:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-viruses","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Viruses](https://link.springer.com/journal/44370)","snPcode":"44370","submissionUrl":"https://submission.nature.com/new-submission/44370/3","title":"Discover Viruses","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"489fead6-1adb-4224-bab9-c835b726ee08","owner":[],"postedDate":"November 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-13T13:10:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-26 07:03:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7860035","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7860035","identity":"rs-7860035","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}