Multi-epitope Vaccine Candidate Research Articles

A novel multi-epitope peptide vaccine candidate targeting hepatitis E virus: An in silico approach.

Hepatitis E virus (HEV) is a foodborne virus transmitted through the faecal-oral route that causes viral hepatitis in humans worldwide. Ever since its discovery as a zoonotic agent, HEV was isolated from several species with an expanding range of hosts. HEV possesses several features of other RNA viruses but also has certain HEV-specific traits that make its viral-host interactions inimitable. HEV leads to severe morbidity and mortality in immunocompromised people and pregnant women across the world. The situation in underdeveloped countries is even more alarming. Even after creating a menace across the world, we still lack an effective vaccine against HEV. Till date, there is only one licensed vaccine for HEV available only in China. The development of an anti-HEV vaccine that can reduce HEV-induced morbidity and mortality is required. Live attenuated and killed vaccines against HEV are not accessible due to the lack of a tolerant cell culture system, slow viral replication kinetics and varying growth conditions. Thus, the main focus for anti-HEV vaccine development is now on the molecular approaches. In the current study, we have designed a multi-epitope vaccine against HEV through a reverse vaccinology approach. For the first time, we have used viral ORF3, capsid protein and polyprotein altogether for epitope prediction. These are crucial for viral replication and persistence and are major vaccine targets against HEV. The proposed in silico vaccine construct comprises of highly immunogenic and antigenic T-cell and B-cell epitopes of HEV proteins. The construct is capable of inducing an effective and long-lasting host immune response as evident from the simulation results. In addition, the construct is stable, non-allergic and antigenic for the host. Altogether, our findings suggest that the in silico vaccine construct may be useful as a vaccine candidate for preventing HEV infections.

Decoding bovine coronavirus immune targets: an epitope informatics approach

Bovine coronavirus (BCoV) poses a significant threat to the global cattle industry, causing both respiratory and gastrointestinal infections in cattle populations. This necessitates the development of efficacious vaccines. While several inactivated and live BCoV vaccines exist, they are predominantly limited to calves. The immunization of adult cattle is imperative for BCoV infection control, as it curtails viral transmission to calves and ameliorates the impact of enteric and respiratory ailments across all age groups within the herd. This study presents an in silico methodology for devising a multiepitope vaccine targeting BCoV. The spike glycoprotein (S) and nucleocapsid (N) proteins, which are integral elements of the BCoV structure, play pivotal roles in the viral infection cycle and immune response. We constructed a remarkably effective multiepitope vaccine candidate specifically designed to combat the BCoV population. Using immunoinformatics technology, B-cell and T-cell epitopes were predicted and linked together using linkers and adjuvants to efficiently trigger both cellular and humoral immune responses in cattle. The in silico construct was characterized, and assessment of its physicochemical properties revealed the formation of a stable vaccine construct. After 3D modeling of the vaccine construct, molecular docking revealed a stable interaction with the bovine receptor bTLR4. Moreover, the viability of the vaccine’s high expression and simple purification was demonstrated by codon optimization and in silico cloning expression into the pET28a (+) vector. By applying immunoinformatics approaches, researchers aim to better understand the immune response to bovine coronavirus, discover potential targets for intervention, and facilitate the development of diagnostic tools and vaccines to mitigate the impact of this virus on cattle health and the livestock industry. We anticipate that the design will be useful as a preventive treatment for BCoV sickness in cattle, opening the door for further laboratory studies.

A novel multi-epitope peptide vaccine candidate against prostate cancer: An in silico approach

A novel multi-epitope peptide vaccine candidate against prostate cancer: An in silico approach

Design of a multi-epitope-based vaccine candidate against Bovine Genital Campylobacteriosis using a reverse vaccinology approach

BackgroundBovine Genital Campylobacteriosis (BGC), a worldwide distributed venereal disease caused by Campylobacter fetus subsp. venerealis (Cfv), has a relevant negative economic impact in cattle herds. The control of BGC is hampered by the inexistence of globally available effective vaccines. The present in silico study aimed to develop a multi-epitope vaccine candidate against Cfv through reverse vaccinology.ResultsThe analysis of Cfv strain NCTC 10354 proteome allowed the identification of 9 proteins suitable for vaccine development. From these, an outer membrane protein, OmpA, and a flagellar protein, FliK, were selected for prediction of B-cell and T-cell epitopes. The top-ranked epitopes conservancy was assessed in 31 Cfv strains. The selected epitopes were integrated to form a multi-epitope fragment of 241 amino acids, which included 2 epitopes from OmpA and 13 epitopes from FliK linked by GPGPG linkers and connected to the cholera toxin subunit B by an EAAAK linker. The vaccine candidate was predicted to be antigenic, non-toxic, non-allergenic, and soluble upon overexpression. The protein structure was predicted and optimized, and the sequence was successfully cloned in silico into a plasmid vector. Additionally, immunological simulations demonstrated the vaccine candidate’s ability to stimulate an immune response.ConclusionsThis study developed a novel vaccine candidate suitable for further in vitro and in vivo experimental validation, which may become a useful tool for the control of BGC.

Designing a novel multi-epitope chimeric vaccine candidate for human papillomavirus by vaccinomic approach

Designing a novel multi-epitope chimeric vaccine candidate for human papillomavirus by vaccinomic approach

Designing a Novel Multiepitope Vaccine from the Human Papilloma Virus E1 and E2 Proteins for Indonesia with Immunoinformatics and Molecular Dynamics Approaches.

One of the deadliest malignant cancer in women globally is cervical cancer. Specifically, cervical cancer is the second most common type of cancer in Indonesia. The main infectious agent of cervical cancer is the human papilloma virus (HPV). Although licensed prophylactic vaccines are available, cervical cancer cases are on the rise. Therapy using multiepitope-based vaccines is a very promising therapy for cervical cancer. This study aimed to develop a multiepitope vaccine based on the E1 and E2 proteins of HPV 16, 18, 45, and 52 using in silico. In this study, we develop a novel multiepitope vaccine candidate using an immunoinformatic approach. We predicted the epitopes of the cytotoxic T lymphocyte (CTL) and helper T lymphocyte (HTL) and evaluated their immunogenic properties. Population coverage analysis of qualified epitopes was conducted to determine the successful use of the vaccine worldwide. The epitopes were constructed into a multiepitope vaccine by using AAY linkers between the CTL epitopes and GPGPG linkers between the HTL epitopes. The tertiary structure of the multiepitope vaccine was modeled with AlphaFold and was evaluated by Prosa-web. The results of vaccine construction were analyzed for B-cell epitope prediction, molecular docking with Toll like receptor-4 (TLR4), and molecular dynamics simulation. The results of epitope prediction obtained 4 CTL epitopes and 7 HTL epitopes that are eligible for construction of multiepitope vaccines. Prediction of the physicochemical properties of multiepitope vaccines obtained good results for recombinant protein production. The interaction showed that the interaction of the multiepitope vaccine-TLR4 complex is stable based on the binding free energy value -106.5 kcal/mol. The results of the immune response simulation show that multiepitope vaccine candidates could activate the adaptive and humoral immune systems and generate long-term B-cell memory. According to these results, the development of a multiepitope vaccine with a reverse vaccinology approach is a breakthrough to develop potential cervical cancer therapeutic vaccines.

Construction of an aerolysin-based multi-epitope vaccine against Aeromonas hydrophila: an in silico machine learning and artificial intelligence-supported approach.

Aeromonas hydrophila, a gram-negative coccobacillus bacterium, can cause various infections in humans, including septic arthritis, diarrhea (traveler's diarrhea), gastroenteritis, skin and wound infections, meningitis, fulminating septicemia, enterocolitis, peritonitis, and endocarditis. It frequently occurs in aquatic environments and readily contacts humans, leading to high infection rates. This bacterium has exhibited resistance to numerous commercial antibiotics, and no vaccine has yet been developed. Aiming to combat the alarmingly high infection rate, this study utilizes in silico techniques to design a multi-epitope vaccine (MEV) candidate against this bacterium based on its aerolysin toxin, which is the most toxic and highly conserved virulence factor among the Aeromonas species. After retrieval, aerolysin was processed for B-cell and T-cell epitope mapping. Once filtered for toxicity, antigenicity, allergenicity, and solubility, the chosen epitopes were combined with an adjuvant and specific linkers to create a vaccine construct. These linkers and the adjuvant enhance the MEV's ability to elicit robust immune responses. Analyses of the predicted and improved vaccine structure revealed that 75.5%, 19.8%, and 1.3% of its amino acids occupy the most favored, additional allowed, and generously allowed regions, respectively, while its ERRAT score reached nearly 70%. Docking simulations showed the MEV exhibiting the highest interaction and binding energies (-1,023.4 kcal/mol, -923.2 kcal/mol, and -988.3 kcal/mol) with TLR-4, MHC-I, and MHC-II receptors. Further molecular dynamics simulations demonstrated the docked complexes' remarkable stability and maximum interactions, i.e., uniform RMSD, fluctuated RMSF, and lowest binding net energy. In silico models also predict the vaccine will stimulate a variety of immunological pathways following administration. These analyses suggest the vaccine's efficacy in inducing robust immune responses against A. hydrophila. With high solubility and no predicted allergic responses or toxicity, it appears safe for administration in both healthy and A. hydrophila-infected individuals.

Designing a conjugate vaccine targeting Klebsiella pneumoniae ST258 and ST11

Klebsiella pneumoniae (K. pneumoniae) is a common bacterium that can cause iatrogenic infection. Recently, the rise of antibiotic resistance among K. pneumoniae strains is one key factor associated with antibiotic treatment failure. Hencefore, there is an urgent need for effective K. pneumoniae vaccines. This study aimed to design a multi-epitope vaccine (MEV) candidate against K. pneumonia by utilizing an immunoinformatics method. In this study, we obtained 15 cytotoxic T lymphocyte epitopes, 10 helper T lymphocyte epitopes, 6 linear B-cell epitopes, and 2 conformational B-cell epitopes for further research. Then, we designed a multi-epitope vaccine composed of a total of 743 amino acids, containing the epitopes linked by GPGPG flexible links and an EAAAK linker to the Cholera Toxin Subunit B coadjuvant.The observed properties of the MEV, including non-allergenicity, high antigenicity, and hydrophilicity, are noteworthy. The improvements in the tertiary structure through structural refinement and disulfide bonding, coupled with promising molecular interactions revealed by molecular dynamics simulations with TLR4, position the MEV as a strong candidate for further investigation against K. pneumoniae.

Multi-epitope mRNA vaccine candidate to combat HMPV virus: Comment

Multi-epitope mRNA vaccine candidate to combat HMPV virus: Comment

Immunoinformatics design of novel multi-epitope vaccine against Trueperella Pyogenes using collagen adhesion protein, fimbriae, and pyolysin.

Trueperella pyogenes (T. pyogenes) is an opportunistic pathogen that causes infertility, mastitis, and metritis in animals. T. pyogenes is also a zoonotic disease and is considered an economic loss agent in the livestock industry. Therefore, vaccine development is necessary. Using an immunoinformatics approach, this study aimed to construct a multi-epitope vaccine against T. pyogenes. The collagen adhesion protein, fimbriae, and pyolysin (PLO) sequences were initially retrieved. The HTL, CTL, and B cell epitopes were predicted. The vaccine was designed by binding these epitopes with linkers. To increase vaccine immunogenicity, profilin was added to the N-terminal of the vaccine construct. The antigenic features and safety of the vaccine model were investigated. Docking, molecular dynamics simulation of the vaccine with immune receptors, and immunological simulation were used to evaluate the vaccine's efficacy. The vaccine's sequence was then optimized for cloning. The vaccine construct was designed based on 18 epitopes of T. pyogenes. The computational tools validated the vaccine as non-allergenic, non-toxic, hydrophilic, and stable at different temperatures with acceptable antigenic features. The vaccine model had good affinity and stability to bovine TLR2, 4, and 5 as well as stimulation of IgM, IgG, IL-2, IFN-γ, and Th1 responses. This vaccine also increased long-lived memory cells, dendritic cells, and macrophage population. In addition, codon optimization was done and cloned in the E. coli K12 expression vector (pET-28a). For the first time, this study introduced a novel multi-epitope vaccine candidate based on collagen adhesion protein, fimbriae, and PLO of T. pyogenes. It is expected this vaccine stimulates an effective immune response to prevent T. pyogenes infection.

Multi-epitope vaccine design against leishmaniasis using IFN-γ inducing epitopes from immunodominant gp46 and gp63 proteins

There is no currently approved human vaccine against leishmaniasis. Utilization of immunogenic antigens and their epitopes capable of enhancing immune responses against leishmaniasis is a crucial step for rational in silico vaccine design. The objective of this study was to generate and evaluate a potential vaccine candidate against leishmaniasis, designed by immunodominant proteins from gp46 and gp63 of Leishmania major, which can stimulate helper T-lymphocytes (HTL) and cytotoxic T-lymphocytes (CTL). For this aim, the IFN-γ-inducing MHC-I and MHC-II binders were predicted for each examined protein (gp46 and gp63) and connected with appropriate linkers, along with an adjuvant (Mycobacterium tuberculosis L7/L12) and a histidine tag. The vaccine’s stability, antigenicity, structure, and interaction with the TLR-4 receptor were evaluated in silico. The resulting chimeric vaccine was composed of 344 amino acids and had a molecular weight of 35.64 kDa. Physico-chemical properties indicated that it was thermotolerant, soluble, highly antigenic, and non-allergenic. Predictions of the secondary and tertiary structures were made, and further analyses confirmed that the vaccine construct could interact with the human TLR-4 receptor. Virtual immune simulation demonstrated strong stimulation of T-cell responses, particularly by an increase in IFN-γ, following vaccination. In summary, the in silico data indicated that the vaccine candidate showed high antigenicity in humans. It was also found to trigger significant levels of clearance mechanisms and other components of the cellular immune profile. Nevertheless, further wet experiments are required to properly assess the efficacy of this multi-epitope vaccine candidate against leishmaniasis.

Combined Immunoinformatics to Design and Evaluate a Multi-Epitope Vaccine Candidate against Streptococcus suis Infection.

Streptococcus suis (S. suis) is a zoonotic pathogen with multiple serotypes, and thus, multivalent vaccines generating cross-protection against S. suis infections are urgently needed to improve animal welfare and reduce antibiotic abuse. In this study, we established a systematic and comprehensive epitope prediction pipeline based on immunoinformatics. Ten candidate epitopes were ultimately selected for building the multi-epitope vaccine (MVSS) against S. suis infections. The ten epitopes of MVSS were all derived from highly conserved, immunogenic, and virulence-associated surface proteins in S. suis. In silico analyses revealed that MVSS was structurally stable and affixed with immune receptors, indicating that it would likely trigger strong immunological reactions in the host. Furthermore, mice models demonstrated that MVSS elicited high titer antibodies and diminished damages in S. suis serotype 2 and Chz infection, significantly reduced sequelae, induced cytokine transcription, and decreased organ bacterial burdens after triple vaccination. Meanwhile, anti-rMVSS serum inhibited five important S. suis serotypes in vitro, exerted beneficial protective effects against S. suis infections and significantly reduced histopathological damage in mice. Given the above, it is possible to develop MVSS as a universal subunit vaccine against multiple serotypes of S. suis infections.

Immunoinformatics approaches in developing a novel multi-epitope chimeric vaccine protective against Saprolegnia parasitica

Saprolegnia parasitica is responsible for devastating infections in fish and poses a tremendous threat to the global aquaculture industry. Presently, no safe and effective control measures are available, on the contrary, use of banned toxic compounds against the pathogen is affecting humans via biomagnification routes. This pioneering study aims to design an effective multi-epitope multi-target vaccine candidate against S. parasitica by targeting key proteins involved in the infection process. The proteins were analyzed and linear B-cell epitopes, MHC class I, and class II epitopes were predicted. Subsequently, highly antigenic epitopes were selected and fused to a highly immunogenic adjuvant, 50S ribosomal protein L7/L12, to design a multi-epitope chimeric vaccine construct. The structure of the vaccine was generated and validated for its stereochemical quality, physicochemical properties, antigenicity, allergenicity, and virulence traits. Molecular docking analyses demonstrated strong binding interactions between the vaccine and piscine immune receptors (TLR5, MHC I, MHC II). Molecular dynamics simulations and binding energy calculations of the complexes, further, reflected the stability and favorable interactions of the vaccine and predicted its cytosolic stability. Immune simulations predicted robust and consistent kinetics of the immune response elicited by the vaccine. The study posits the vaccine as a promising solution to combat saprolegniasis in the aquaculture industry.

In-silico design of a new multi-epitope vaccine candidate against SARS-CoV-2

Frequent, and sometimes more dangerous, mutations in SARS-CoV-2 indicate that a stronger strategy is needed to produce an effective vaccine—a vaccine that contains a wider range of virus factors and remains effective if one or more mutations have occurred in a part of the genome. In this study, four important virus proteins were used to make a multi-epitope protein vaccine. For this purpose, antigenic determinant of 4 proteins were selected and a protein structure was designed using 4 domains containing epitopes. After examining its antigenic potential, its three-dimensional structure was designed and then docked with immune system receptors. Finally, using the dynamic molecular (MD) simulation, complexes and interactions were investigated and their interaction energies were measured. The results of the study showed that the designed structure has good relative stability and interacts well with its receptors and can be used as a vaccine candidate for further studies.

Designing of a new multi-epitope vaccine against Leishmania major using Leish-F1 epitopes: An In-silico study.

Cutaneous leishmaniasis (CL) is the most common form of the disease which can cause malignant lesions on the skin. Vaccination for the prevention and treatment of leishmaniasis can be the most effective way to combat this disease. In this study, we designed a novel multi-epitope vaccine against Leishmania major (L. major) using immunoinformatics tools to assess its efficacy in silico. Sequences of Leish-F1 protein (TSA, Leif, and LMSTI1) of L. major were taken from GenBank. The helper T (Th) and cytotoxic T (Tc) epitopes of the protein were predicted. The final multi-epitope consisted of 18 CTL epitopes joined by AAY linker. There were also nine HTL epitopes in the structure of the vaccine construct, joined by GPGPG linker. The profilin adjuvant (the toll-like receptor 11 agonist) was also added into the construct by AAY Linker. There were 613 residues in the structure of the vaccine construct. The multi-epitope vaccine candidate was stable and non-allergic. The data obtained from the binding of final multi-epitope vaccine-TLR11 residues (band lengths and weighted scores) unveiled the ligand and the receptor high score of binding affinity. Moreover, in silico assessment of the vaccine construct cloning achieved its suitable expression in E. coli host. Based on these results, the current multi-epitope vaccine prevents L. major infection in silico, while further confirmatory assessments are required.

Design and computational analysis of an effective multi-epitope vaccine candidate using subunit B of cholera toxin as a build-in adjuvant against urinary tract infections.

Urinary tract infection (UTI) is one of the most common infections, usually caused by uropathogenic Escherichia coli (UPEC). However, antibiotics are a usual treatment for UTIs; because of increasing antibiotic-resistant strains, vaccination can be beneficial in controlling UTIs. Using immunoinformatics techniques is an effective and rapid way for vaccine development. Three conserved protective antigens (FdeC, Hma, and UpaB) were selected to develop a novel multi-epitope vaccine consisting of subunit B of cholera toxin (CTB) as a mucosal build-in adjuvant to enhance the immune responses. Epitopes-predicted B and T cells and suitable linkers were used to separate them and effectively increase the vaccine's immunogenicity. The vaccine protein's primary, secondary, and tertiary structures were evaluated, and the best 3D model was selected. Since CTB is the TLR2 ligand, molecular docking was made between the vaccine protein and TLR2. Molecular dynamic (MD) simulation was employed to evaluate the stability of the vaccine protein-TLR2 complex. The vaccine construct was subjected to in silico cloning. The designed vaccine protein has multiple properties in the analysis. The HADDOCK outcomes show an excellent interaction between vaccine protein and TLR2. The MD results confirm the stability of the vaccine protein- TLR2 complex during the simulation. In silico cloning verified the expression efficiency of our vaccine protein. The results of this study suggest that our designed vaccine protein could be a promising vaccine candidate against UTI, but further in vitro and in vivo studies are needed.

Designing a Multiepitope Vaccine against Eastern Equine Encephalitis Virus: Immunoinformatics and Computational Approaches.

Eastern equine encephalitis virus (EEEV) is a significant threat to human and animal populations, causing severe encephalitis, often leading to long-term neurological complications and even mortality. Despite this, no approved antiviral treatments or EEEV human vaccines currently exist. In response, we utilized immunoinformatics and computational approaches to design a multiepitope vaccine candidate for EEEV. By screening the structural polyprotein of EEEV, we predicted both T-cell and linear B-cell epitopes. These epitopes underwent comprehensive evaluations for their antigenicity, toxicity, and allergenicity. From these evaluations, we selected ten epitopes highly suitable for vaccine design, which were connected with adjuvants using a stable linker. The resulting vaccine construct demonstrated exceptional antigenic, nontoxic, nonallergenic, and physicochemical properties. Subsequently, we employed molecular docking and molecular dynamics simulations to reveal a stable interaction pattern between the vaccine candidate and Toll-like receptor 5. Besides, computational immune simulations predicted the vaccine's capability to induce robust immune responses. Our study addresses the urgent need for effective EEEV preventive strategies and offers valuable insights for EEEV vaccine development. As EEEV poses a severe threat with potential spread due to climate change, our research provides a crucial step in enhancing public health defenses against this menacing zoonotic disease.

Development of a novel multi-epitope mRNA vaccine candidate to combat HMPV virus

ABSTRACT Human metapneumovirus (HMPV) is one of the main pathogens causing severe respiratory infections in children, as a common cause of immunodeficiency-related deaths in children and elderly individuals, the prevalence of HMPV has been showing an increasing trend during the last years. However, no vaccines or effective treatment plans are available currently. In this present, based on candidate proteins highly associated with viral virulence and has promising protective potential, we screened for immunodominant cytotoxic T cells, helper T cells, and Linear B-cell epitopes from the most promising candidate Fusion protein, together with G, SH, M, and M2. All epitopes were predicted to have strong antigenicity by Vaxijen and pose no potential toxicity, allergenicity, or hormonology to human proteins by Toxinpred, Allerpred, and Blast analysis, meanwhile, high conservancy is demanded to cover different subtypes. adjuvants β-defensin II and Pam2Cys was attached with EAAAK linkers to improve vaccine’s efficiency. Then, calculation of physicochemical properties proved the protein vaccine as a product can stably exist in the human body. Besides, we assessed the docking between the vaccine and immune receptors to evaluate its ability to stimulate immune responses, and the dynamic simulation further confirmed that the vaccine can tightly bind with immune receptors, which approved that the construction has the potential to induce strong humoral and cellular immune response. Finally, the vaccine was constructed into a multi-epitope mRNA vaccine, the immune simulations suggest that this is a vaccine candidate for controlling HMPV infection.

In silico design of a trivalent multi-epitope global-coverage vaccine-candidate protein against influenza viruses: evaluation by molecular dynamics and immune system simulation

Hemagglutinin (HA), a variable viral surface protein, is essential for influenza vaccine development. Annually, traditional trivalent vaccines containing influenza A/H1N1, A/H3N2 and B viruses are administered globally, which are not very effective for the mutations in HA protein. The aim of this study was to design a multi-epitope vaccine containing epitopes of the HA protein of H1N1, H3N2 and B viruses using immunoinformatics methods. The HA protein epitope prediction was performed using Immune Epitope Database. Toxicity, antigenicity and conservancy of the epitopes were evaluated using ToxinPred, VaxiJen and Epitope Conservancy Analysis tools, respectively. Then, nontoxic, antigenic and high conserved epitopes with high prediction scores were selected. Their binding affinity was evaluated against human and mouse MHC class I and II molecules using the HPEPDOCK tool. Physicochemical properties and post-translational modifications were evaluated using ProtParam, SOLpro and MusiteDeep tools, respectively. Top selected epitopes were joined using linkers to produce the best effective recombinant trivalent vaccine candidate to elicit cellular and humoral immune responses in mouse and human host models. These sequences were modeled and verified. By evaluating the results of various analyses of all models and the most similarity to the native HA protein, model 5 was selected as the best model. Finally, in silico cloning of this model as vaccine candidate was performed in pET21. This study was a computer-aided analysis for a multi-epitope trivalent recombinant vaccine candidate against influenza viruses. The efficiency of our best model of vaccine candidates should be validated using in vitro and in vivo studies. Communicated by Ramaswamy H. Sarma

Immunoinformatics-aided rational design of a multi-epitope vaccine targeting feline infectious peritonitis virus.

Feline infectious peritonitis (FIP) is a grave and frequently lethal ailment instigated by feline coronavirus (FCoV) in wild and domestic feline species. The spike (S) protein of FCoV assumes a critical function in viral ingress and infection, thereby presenting a promising avenue for the development of a vaccine. In this investigation, an immunoinformatics approach was employed to ascertain immunogenic epitopes within the S-protein of FIP and formulate an innovative vaccine candidate. By subjecting the amino acid sequence of the FIP S-protein to computational scrutiny, MHC-I binding T-cell epitopes were predicted, which were subsequently evaluated for their antigenicity, toxicity, and allergenicity through in silico tools. Our analyses yielded the identification of 11 potential epitopes capable of provoking a robust immune response against FIPV. Additionally, molecular docking analysis demonstrated the ability of these epitopes to bind with feline MHC class I molecules. Through the utilization of suitable linkers, these epitopes, along with adjuvants, were integrated to design a multi-epitope vaccine candidate. Furthermore, the stability of the interaction between the vaccine candidate and feline Toll-like receptor 4 (TLR4) was established via molecular docking and molecular dynamics simulation analyses. This suggests good prospects for future experimental validation to ascertain the efficacy of our vaccine candidate in inducing a protective immune response against FIP.