Epitope-based Vaccine Research Articles

Bioinformatics Approaches in the Development of Antifungal Therapeutics and Vaccines.

Fungal infections are considered a great threat to human life and are associated with high mortality and morbidity, especially in immunocompromised individuals. Fungal pathogens employ various defense mechanisms to evade the host immune system, which causes severe infections. The available repertoire of drugs for the treatment of fungal infections includes azoles, allylamines, polyenes, echinocandins, and antimetabolites. However, the development of multidrug and pandrug resistance to available antimycotic drugs increases the need to develop better treatment approaches. In this new era of -omics, bioinformatics has expanded options for treating fungal infections. This review emphasizes how bioinformatics complements the emerging strategies, including advancements in drug delivery systems, combination therapies, drug repurposing, epitope-based vaccine design, RNA-based therapeutics, and the role of gut-microbiome interactions to combat anti-fungal resistance. In particular, we focused on computational methods that can be useful to obtain potent hits, and that too in a short period.

Immunoinformatics investigation on pathogenic Escherichia coli proteome to develop an epitope-based peptide vaccine candidate.

Escherichia coli (E. coli), a gram-negative bacterium, quickly colonizes in the human gastrointestinal tract after birth and typically sustains a long-term, symbiotic relationship with the host. However, certain virulent strains of E. coli can cause diseases such as urinary tract infections, meningitis, and enteric disorders. The rising antibiotic resistance among these strains has heightened the urgency for an effective vaccine. This study employs immunoinformatics and a reverse vaccinology technique to identify prospective antigens and create an efficient vaccine construct. In this study, we reported the "Attaching and Effacing Protein" a novel outer-membrane protein conserved in all pathogenic E. coli strains, based on proteome screening. We developed an in silico multi-epitope vaccine that includes helper T lymphocyte (HTL), cytotoxic T lymphocyte (CTL), B cell lymphocyte (BCL), and pan HLA DR-binding reactive epitope (PADRE) sequences, along with appropriate linkers and adjuvants. Machine Learning algorithms were used to evaluate antigenicity, solubility, stability, and non-allergenicity of the vaccine construct. Additionally, molecular docking analysis revealed that vaccine construct has a strong predicted binding affinity for human toll-like receptors on the cell surface. In this context, laboratory validations are necessary to demonstrate the effectiveness of the possible vaccine design that showed encouraging findings through computational validation.

T-Cell Epitope-Based Vaccines: A Promising Strategy for Prevention of Infectious Diseases.

With the development of novel vaccine strategies, T-cell epitope-based vaccines have become promising prophylactic and therapeutic tools against infectious diseases that cannot be controlled via traditional vaccines. T-cell epitope-based vaccines leverage specific immunogenic peptides to elicit protective T-cell responses against infectious pathogens. Compared to traditional vaccines, they provide superior efficacy and safety, minimizing the risk of adverse side effects. In this review, we summarized and compared the prediction and identification methods of T-cell epitopes. By integrating bioinformatic prediction and experimental validation, efficient and precise screening of T-cell epitopes can be achieved. Importantly, we delved into the development approaches to diverse T-cell epitope-based vaccines, comparing their merits and demerits, as well as discussing the prevalent challenges and perspectives in their applications. This review offers fresh perspectives for the formulation of safe and efficacious epitope-based vaccines for the devastating diseases against which no vaccines are currently available.

Design of an Epitope-Based Vaccine Against MERS-CoV.

Background and Objectives: Middle East Respiratory Syndrome (MERS) is a viral respiratory illness caused by a coronavirus called Middle East respiratory syndrome. In the current study, immunoinformatics studies were applied to design an epitope-based vaccine construct against Middle East Respiratory Syndrome. Materials and Methods: In this study, epitopes base vaccine construct was designed against MERS using immunoinformatics approach. Results: In this approach, the targeted proteins were screened, and probable antigenic, non-allergenic, and good water-soluble epitopes were selected for vaccine construction. In vaccine construction, the selected epitopes were joined by GPGPG linkers, and a linear multi-epitope vaccine was constructed. The vaccine construct underwent a physiochemical property analysis. The 3D structure of the vaccine construct was predicted and subjected to refinement. After the refinement, the 3D model was subjected to a molecular docking analysis, TLRs (TLR-3 and TLR-9) were selected as receptors for vaccine construct, and the molecular docking analysis study determined that the vaccine construct has binding ability with the targeted receptor. Conclusions: The docking analysis also unveils that the vaccine construct can properly activate immune system against the target virus however experimental validation is needed to confirm the in silico findings further.

Application of Immunoinformatics for Efficient Epitope-Based Peptide Vaccine Development

As global public health continues to face evolving challenges, developing effective and safe vaccines has become increasingly crucial, with the design of epitope-based vaccines representing a significant breakthrough in the field. The design of epitope vaccines generally involves utilizing immunoinformatics tools and techniques to analyze known or newly identified amino acid sequences, allowing for pre-selecting and identifying potential dominant epitopes. Subsequently, peptide vaccines containing these epitopes are synthesized through chemical or genetic engineering. The rapid progress in Immunoinformatics has greatly expanded its application in vaccinology, making it the most efficient approach for developing epitope-based peptide vaccines. The review outlines the general workflow of Immunoinformatics in the design and validation of epitope vaccines, highlights the key Immunoinformatics tools used in epitope vaccine development, and discusses the specific applications of Immunoinformatics in epitope vaccine design. These insights aim to provide valuable references for the rational design and development of potent epitope vaccines.

NitraTh epitope-based neoantigen vaccines for effective tumor immunotherapy

Neoantigen vaccines represent an emerging and promising strategy in the field of tumor immunotherapy. Despite their potential, designing an effective neoantigen vaccine remains a challenge due to the current limitations in predicting CD4+ T cell epitopes with high accuracy. Here, we introduce a novel approach to neoantigen vaccine design that does not rely on computational prediction of CD4+ T cell epitopes. Utilizing nitrated helper T cell epitope containing p-nitrophenylalanine, termed “NitraTh epitope,” we have successfully engineered a series of tumor neoantigen vaccines capable of eliciting robust neoantigen-specific immune responses. With the help of NitraTh epitope, even mutations with low predicted affinity for MHC class I molecules were successfully induced to elicit neoantigen-specific responses. In H22 cell allograft and patient-derived xenograft (PDX) liver cancer mouse models, the NitraTh epitope-based neoantigen vaccines significantly suppressed tumor progression. More strikingly, through single-cell sequencing we found that the NitraTh epitope-based neoantigen vaccines regulate macrophage reprogramming and modulate macrophages to decrease the levels of the immunosuppressive molecule prostaglandin E2 (PGE2), which in turn reshapes the tumor immunosuppressive microenvironment. In summary, NitraTh epitope-based neoantigen vaccines possess the dual effects of potently activating neoantigen-specific immunity and alleviating immunosuppression, potentially providing a new paradigm for the design of tumor neoantigen vaccines.

Identification of three novel linear B-cell epitopes on VP7 of African horse sickness virus using monoclonal antibodies

African horse sickness (AHS) is an acute and subacute infectious disease of equine species caused by the African horse sickness virus (AHSV). The VP7 of AHSV is a group-specific protein conserved in all serotypes and is an excellent candidate for the serological diagnosis and an AHS vaccine component. However, to date, B-cell epitopes on the AHSV VP7 recognized by humoral immune responses remain unclear. This study expressed the recombinant AHSV VP7 soluble in Escherichia coli and purified it for mouse immunization. Four monoclonal antibodies (mAbs) were screened and identified by hybridoma cell fusion, clonal purification, and immunological assays. The B-cell epitopes, recognized by monoclonal antibodies 4B5, 3G10, 3D7, and 4D6, were identified by a series of truncated overlapping peptides expressed as glutathione S-transferase (GST)-fusion proteins. The results revealed that 4B5 recognized the 124VQTGRYAGA132 motif, 3G10 recognized the 140RYYVPQGRT148 motif, while 3D7 and 4D6 recognized the 292QPINPPIFP300 motif. Amino acid sequence alignment indicated that three novel B-cell epitopes were conserved among various AHSV serotypes but unconserved in other orbiviruses, such as the bluetongue and epidemic hemorrhagic disease viruses. This study informs on the antigenic epitopes of AHSV VP7, facilitating future investigations into the serological diagnosis method and epitope-based vaccines against AHSV.

Design of an epitope-based peptide vaccine against Cryptococcus neoformans.

Cryptococcus neoformans is the highest-ranked fungal pathogen in the Fungal Priority Pathogens List (FPPL) released by the World Health Organization (WHO). In this study, through in silico simulations, a multi-epitope vaccine against Cryptococcus neoformans was developed using the mannoprotein antigen (MP88) as a vaccine candidate. Following the retrieval of the MP88 protein sequences, these were used to predict antigenic B-cell and T-cell epitopes via the bepipred tool and the artificial neural network, respectively. Conserved B-cell epitopes AYSTPA, AYSTPAS, PASSNCK, and DSAYPP were identified as the most promising B-cell epitopes. While YMAADQFCL, VSYEEWMNY, and FQQRYTGTF were identified as the best candidates for CD8+ T-cell epitopes; and YARLLSLNA, ISYGTAMAV, and INQTSYARL were identified as the most promising CD4+ T-cell epitopes. The vaccine construct was modeled along with adjuvant and peptide linkers and the expasy protparam tool was used to predict the physiochemical properties. According to this, the construct vaccine was predicted to be antigenic, nontoxic, nonallergenic, soluble, stable, hydrophilic, and thermostable. Furthermore, the three-dimensional structure was also used in docking analyses with Toll-like receptor (TLR4). Finally, the cDNA of vaccine was successfully cloned into the E. coli pET-28a (+) expression vector. The results presented here could contribute towards the design of an effective vaccine against Cryptococcus neoformans.

TgVax452, an epitope-based candidate vaccine targeting Toxoplasma gondii tachyzoite-specific SAG1-related sequence (SRS) proteins: immunoinformatics, structural simulations and experimental evidence-based approaches

BackgroundThe highly expressed surface antigen 1 (SAG1)-related sequence (SRS) proteins of T. gondii tachyzoites, as a widespread zoonotic parasite, are critical for host cell invasion and represent promising vaccine targets. In this study, we employed a computer-aided multi-method approach for in silico design and evaluation of TgVax452, an epitope-based candidate vaccine against T. gondii tachyzoite-specific SRS proteins.MethodsUsing immunoinformatics web-based tools, structural modeling, and static/dynamic molecular simulations, we identified and screened B- and T-cell immunodominant epitopes and predicted TgVax452’s antigenicity, stability, safety, adjuvanticity, and physico-chemical properties.ResultsThe designed protein possessed 452 residues, a MW of 44.07 kDa, an alkaline pI (6.7), good stability (33.20), solubility (0.498), and antigenicity (0.9639) with no allergenicity. Comprehensive molecular dynamic (MD) simulation analyses confirmed the stable interaction (average potential energy: 3.3799 × 106 KJ/mol) between the TLR4 agonist residues (RS09 peptide) of the TgVax452 in interaction with human TLR4, potentially activating innate immune responses. Also, a dramatic increase was observed in specific antibodies (IgM and IgG), cytokines (IFN-γ), and lymphocyte responses, based on C-ImmSim outputs. Finally, we optimized TgVax452’s codon adaptation and mRNA secondary structure for efficient expression in E. coli BL21 expression machinery.ConclusionOur findings suggest that TgVax452 is a promising candidate vaccine against T. gondii tachyzoite-specific SRS proteins and requires further experimental studies for its potential use in preclinical trials.

The Development of Epitope-Based Recombinant Protein Vaccines against SARS-CoV-2.

The COVID-19 pandemic continues to cause infections and deaths, which are attributable to the SARS-CoV-2 Omicron variant of concern (VOC). Moderna's response to the declining protective efficacies of current SARS-CoV-2 vaccines against Omicron was to develop a bivalent booster vaccine based on the Spike (S) protein from the Wuhan and Omicron BA.4/BA.5 strains. This approach, while commendable, is unfeasible in light of rapidly emerging mutated viral strains. PubMed and Google Scholar were systematically reviewed for peer-reviewed papers up to January 2024. Articles included focused on specific themes such as the clinical history of recombinant protein vaccine development against different diseases, including COVID-19, the production of recombinant protein vaccines using different host expression systems, aspects to consider in recombinant protein vaccine development, and overcoming problems associated with large-scale recombinant protein vaccine production. In silico approaches to identify conserved and immunogenic epitopes could provide broad protection against SARS-CoV-2 VOCs but require validation in animal models. The recombinant protein vaccine development platform has shown a successful history in clinical development. Recombinant protein vaccines incorporating conserved epitopes may utilize a number of expression systems, such as yeast (Saccharomyces cerevisiae), baculovirus-insect cells (Sf9 cells), and Escherichia coli (E. coli). Current multi-epitope subunit vaccines against SARS-CoV-2 utilizing synthetic peptides are unfeasible for large-scale immunizations. Recombinant protein vaccines based on conserved and immunogenic proteins produced using E. coli offer high production yields, convenient purification, and cost-effective production of large-scale vaccine quantities capable of protecting against the SARS-CoV-2 D614G strain and its VOCs.

Identification and Characterization of a Novel B Cell Epitope of ASFV Virulence Protein B125R Monoclonal Antibody.

The African swine fever virus (ASFV) is an ancient, structurally complex, double-stranded DNA virus that causes African swine fever. Since its discovery in Kenya and Africa in 1921, no effective vaccine or antiviral strategy has been developed. Therefore, the selection of more suitable vaccines or antiviral targets is the top priority to solve the African swine fever virus problem. B125R, one of the virulence genes of ASFV, encodes a non-structural protein (pB125R), which is important in ASFV infection. However, the epitope of pB125R is not well characterized at present. We observed that pB125R is specifically recognized by inactivated ASFV-positive sera, suggesting that it has the potential to act as a protective antigen against ASFV infection. Elucidation of the antigenic epitope within pB125R could facilitate the development of an epitope-based vaccine targeting ASFV. In this study, two strains of monoclonal antibodies (mAbs) against pB125R were produced by using the B cell hybridoma technique, named 9G11 and 15A9. The antigenic epitope recognized by mAb 9G11 was precisely located by using a series of truncated ASFV pB125R. The 52DPLASQRDIYY62 (epitope on ASFV pB125R) was the smallest epitope recognized by mAb 9G11 and this epitope was highly conserved among different strains. The key amino acid sites were identified as D52, Q57, R58, and Y62 by the single-point mutation of 11 amino acids of the epitope by alanine scanning. In addition, the immunological effects of the epitope (pB125R-DY) against 9G11 were evaluated in mice, and the results showed that both full-length pB125R and the epitope pB125R-DY could induce effective humoral and cellular immune responses in mice. The mAbs obtained in this study reacted with the eukaryotic-expressed antigen proteins and the PAM cell samples infected with ASFV, indicating that the mAb can be used as a good tool for the detection of ASFV antigen infection. The B cell epitopes identified in this study provide a fundamental basis for the research and development of epitope-based vaccines against ASFV.

A novel vaccine construct against Zika virus fever: insights from epitope-based vaccine discovery through molecular modeling and immunoinformatics approaches.

The Zika virus (ZIKV) is an emerging virus associated with the Flaviviridae family that mainly causes infection in pregnant women and leads to several abnormalities during pregnancy. This virus has unique properties that may lead to pathological diseases. As the virus has the ability to evade immune response, a crucial effort is required to deal with ZIKV. Vaccines are a safe means to control different pathogenic infectious diseases. In the current research, a multi-epitope-based vaccination against ZIKV is being designed using in silico methods. For the epitope prediction and prioritization phase, ZIKV polyprotein (YP_002790881.1) and flavivirus polyprotein (>YP_009428568.1) were targeted. The predicted B-cell epitopes were used for MHC-I and MHC-II epitope prediction. Afterward, several immunoinformatics filters were applied and nine (REDLWCGSL, MQDLWLLRR, YKKSGITEV, TYTDRRWCF, RDAFPDSNS, KPSLGLINR, ELIGRARVS, AITQGKREE, and EARRSRRAV) epitopes were found to be probably antigenic in nature, non-allergenic, non-toxic, and water soluble without any toxins. Selected epitopes were joined using a particular GPGPG linker to create the base vaccination for epitopes, and an extra EAAAK linker was used to link the adjuvant. A total of 312 amino acids with a molecular weight (MW) of 31.62762 and an instability value of 34.06 were computed in the physicochemical characteristic analysis, indicating that the vaccine design is stable. The molecular docking analysis predicted a binding energy of -329.46 (kcal/mol) for TLR-3 and -358.54 (kcal/mol) for TLR-2. Moreover, the molecular dynamics simulation analysis predicted that the vaccine and receptor molecules have stable binding interactions in a dynamic environment. The C-immune simulation analysis predicted that the vaccine has the ability to generate both humoral and cellular immune responses. Based on the design, the vaccine construct has the best efficacy to evoke immune response in theory, but experimental analysis is required to validate the in silico base approach and ensure its safety.

Development of epitope-based vaccine to prevent Marburg virus infection: an in silico approach

Marburg virus (MARV) is one of the deadliest zoonotic viruses, causing severe hemorrhagic fever in humans with high mortality rates. The development of an effective vaccine is crucial to prevent potential Marburg virus outbreaks. In this study, an in silico approach was employed to design an epitope-based vaccine to prevent MARV infections. The MARV proteins nominating NP, VP24, VP35, VP30, VP40, GP & Polymerase L was analyzed for antigenicity and non-allergenicity prediction, among these proteins VP30 protein has a 0.5636 (Probable Antigen) score and it was non-allergen. For that reason, VP30 was selected for further in silico analysis. After analysis it is found that the top ranked T–cell (MHC-I) epitopes LSKPPPPPK, ESSPTNHIPR, TQLPSKPHY, SPQDCGSPSL, FEAALWQGW, T-Cell (MHC-II) epitopes IHLDKGGQF, INTMTELHM, VTPTIYHET, YTNYHPRAR, YTGIHLDKG was epitopes & B-Cell epitopes SEIGKLDET, IHLDKGGQF, MNHENLPQDQNGV, PTCNRDHDLDNLTN was found non-toxic and non-allergen. The T-Cell (MHC-I)epitope TQLPSKPHY,T-Cell (MHC-II)epitope YTNYHPRAR & B-Cell epitope SEIGKLDET was found highly antigenic, non-toxic as well as non-allergen and it was selected for molecular docking analysis. The T-Cell (MHC-I) epitope TQLPSKPHY,T-Cell (MHC-II)epitope YTNYHPRAR shows strong structural similarity and potential binding affinity with antibody. The B-Cell epitope SEIGKLDET shows poor affinity towards antibody. In silico analysis indicate that both T-Cell epitopes becomes an effective peptide vaccine to prevent MARV infection. Our findings highlight the promise of in silico vaccine design in accelerating the development of vaccines against MARV, a highly pathogenic virus with no effective cure currently available

Harnessing Immunoinformatics for Precision Vaccines: Designing Epitope-Based Subunit Vaccines against Hepatitis E Virus

Background/Objectives: Hepatitis E virus (HEV) is an RNA virus recognized to be spread mainly by fecal-contaminated water. Its infection is known to be a serious threat to public health globally, mostly in developing countries, in which Africa is one of the regions sternly affected. An African-based vaccine is necessary to actively prevent HEV infection. Methods: This study developed an in silico epitope-based subunit vaccine, incorporating CTL, HTL, and BL epitopes with suitable linkers and adjuvants. Results: The in silico-designed vaccine construct proved immunogenic, non-allergenic, and non-toxic and displayed appropriate physicochemical properties with high solubility. The 3D structure was modeled and subjected to protein docking with Toll-like receptors 2, 3, 4, 6, 8, and 9, which showed a stable binding efficacy, and the dynamics simulation indicated steady interaction. Furthermore, the immune simulation predicted that the designed vaccine would instigate immune responses when administered to humans. Lastly, using a codon adaptation for the E. coli K12 bacterium produced optimum GC content and a high CAI value, which was followed by in silico integration into a pET28 b (+) cloning vector. Conclusions: Generally, these results propose that the design of an epitope-based subunit vaccine can function as an outstanding preventive vaccine candidate against HEV, although validation techniques via in vitro and in vivo approaches are required to justify this statement.

VOE: automated analysis of variant epitopes of SARS-CoV-2 for the development of diagnostic tests or vaccines for COVID-19.

The development of serodiagnostic tests and vaccines for COVID-19 depends on the identification of epitopes from the SARS-CoV-2 genome. An epitope is the specific part of an antigen that is recognized by the immune system and can elicit an immune response. However, when the genetic variants contained in epitopes are used to develop rapid antigen tests (Ag-RDTs) and DNA or RNA vaccines, test sensitivity and vaccine efficacy can be low. Here, we developed a "variant on epitope (VOE)" software, a new Python script for identifying variants located on an epitope. Variant analysis and sensitivity calculation for seven recommended epitopes were processed by VOE. Variants in 1,011 Omicron SRA reads from two variant databases (BCFtools and SARS-CoV-2-Freebayes) were processed by VOE. A variant with HIGH or MODERATE impact was found on all epitopes from both variant databases except the epitopes KLNDLCFTNV, RVQPTES, LKPFERD, and ITLCFTLKRK on the S gene and ORF7a gene. All epitope variants from the BCFtools and SARS-CoV-2 Freebayes variant databases showed about 100% sensitivity except epitopes APGQTGK and DSKVGGNYN on the S gene, which showed respective sensitivities of 28.4866% and 6.8249%, and 87.7349% and 71.1177%. Therefore, the epitopes KLNDLCFTNV, RVQPTES, LKPFERD, and ITLCFTLKRK may be useful for the development of an epitope-based peptide vaccine and GGDGKMKD on the N gene may be useful for the development of serodiagnostic tests. Moreover, VOE can also be used to analyze other epitopes, and a new variant database for VOE may be further established when a new variant of SARS-CoV-2 emerges.

Integrating 16S rRNA profiling and in-silico analysis for an epitope-based vaccine strategy against Achromobacter xylosoxidans infection

Achromobacter xylosoxidans is an aerobic, catalase-positive, non-pigment-forming, Gram-negative, and motile bacterium. It potentially causes a wide range of human infections in cystic fibrosis and non-cystic fibrosis patients. However, developing a safe preventive or therapeutic solution against A. xylosoxidans remains challenging. This study aimed to construct an epitope-based vaccine candidate using immunoinformatic techniques. A. xylosoxidans was isolated from an auto workshop in Lahore, and its identification was confirmed through 16S rRNA amplification and bioinformatic analysis. Two protein targets with GenBank accession numbers AKP90890.1 and AKP90355.1 were selected for the vaccine construct. Both proteins exhibited antigenicity, with scores of 0.757 and 0.580, respectively and the epitopes were selected based on the IC50 value using the ANN 4.0 and NN-align 2.3 epitope prediction method for MHC I and MHC II epitopes respectively and predicted epitopes were analyzed for antigenicity, allergenicity and pathogenicity. The vaccine construct demonstrated structural stability, thermostability, solubility, and hydrophilicity. The vaccine produced 250 B-memory cells per mm3 and approximately 16,000 IgM + IgG counts, indicating an effective immune response against A. xylosoxidans. Moreover, the vaccine candidate interacted stably with toll-like receptor 5, a pattern recognition receptor, with a confidence score of 0.98. These results highlight the potency of the designed vaccine candidate, suggesting its potential to withstand rigorous in vitro and in vivo clinical trials. This epitope-based vaccine could serve as the first preventive immunotherapy against A. xylosoxidans infections, addressing this bacterium’s health and financial burdens. The findings demonstrate the value of employing immunoinformatic tools in vaccine development, paving the way for more precise and tailored approaches to combating microbial threats.

Immunogenicity and immunodominant linear B-cell epitopes of a new DNA-based tetravalent vaccine against four major enteroviruses causing hand, foot, and mouth disease

Hand, foot, and mouth disease (HFMD) poses a significant public health threat primarily caused by four major enteroviruses: enterovirus 71 (EV71), coxsackieviruses A16, A10, and A6. Broadly protective immune responses are essential for complete protection against these major enteroviruses. In this study, we designed a new tetravalent immunogen for HFMD, validated it in silico, in vivo evaluated the immunogenicity of the DNA-based tetravalent vaccine in mice, and identified immunogenic B-cell and T-cell epitopes. A new tetravalent immunogen, VP1me, was designed based on the chimeric protein and epitope-based vaccine principles. It contains a complete EV71 VP1 protein and six reported neutralizing B-cell epitopes derived from the four major enteroviruses causing HFMD. In silico validation using multiple immunoinformatic tools indicated good attributes of the VP1me immunogen suitable for vaccine development. The VP1me-based DNA vaccine efficiently induced both humoral and cellular immune responses in BALB/cAJcl mice. A combination of in silico prediction and immunoassays enabled the identification of immunogenic linear B-cell and CD8 T-cell epitopes within the VP1me immunogen. Immunodominant linear B-cell epitopes were identified in six regions of VP1me, with one epitope located at the N-terminus of the VP1 protein (aa 9–23) regarded as a novel epitope. Interestingly, some B-cell epitopes could also induce the CD8 T-cell response, suggesting their dual functions in immune stimulation. These results lay the groundwork for further development of VP1me as a new vaccine candidate.

Computational Prediction of Potential Vaccine Candidates From tRNA Encoded peptides (tREP) Using a Bioinformatic Workflow and Molecular Dynamics Validations.

Transfer RNAs (tRNA) are non-coding RNAs. Encouraged by biological applications discovered for peptides derived from other non-coding genomic regions, we explore the possibility of deriving epitope-based vaccines from tRNA encoded peptides (tREP) in this study. Epitope-based vaccines have been identified as an effective strategy to mitigate safety and specificity concerns observed in vaccine development. In this study, we explore the potential of tREP as a source for epitope-based vaccines for virus pathogens. We present a computational workflow that uses verified data sources and community-validated predictive tools to produce a ranked list of plausible epitope-based vaccines starting from tRNA sequences. The top epitope, bound to the predicted HLA molecule, for the virus pathogen is computationally validated through 200 ns molecular dynamics (MD) simulations followed by binding free energy calculations. The simulation results indicate that two tRNA encoded epitope-based vaccines, RRHIDIVV and IMVRFSAE for Mamastrovirus 3 and Norovirus GII, respectively, are likely candidates. Peptides originating from tRNAs provide unexplored opportunities for vaccine design. Encouraged by our previous experimental study, which established the inhibitory properties of tREPs against infectious parasites, we have proposed a computationally validated set of peptides derived from tREPs as vaccines for viral pathogens.

Escalating Dose Immunization Regimen in Non-Human Primates to Improve Immunogen-Specific Responses

Abstract HIV-1 remains a major health threat, highlighting the need for a vaccine that induces broadly neutralizing antibodies. Epitope-based vaccine designs that focus humoral responses to vulnerable sites on the HIV-1 Env trimer protein are promising approaches, including those targeting the HIV-1 fusion peptide (FP). Escalating dose (ED) immunizations are a strategy to increase immunogen uptake into germinal centers and boost affinity maturation of the antiviral antibody response. In this study, we tested the impact of an ED immunization scheme on enhancing the FP-directed humoral response. Five groups of non-human primates were immunized: four received an ED immunization of either FP or a cocktail of FP+trimer, and one control group was dosed with a bolus FP+trimer cocktail. Two ED groups were adjuvanted with SMNP. The remaining groups used 3M052/alum. Fourteen weeks post-immunization, all ED groups had higher anti-FP IgG titers compared to the control, with the cocktail ED group adjuvanted with 3M052/alum characterized by 14.5-fold higher titers than the bolus control. While the ED cocktail and bolus groups had similar anti-trimer IgG titers, the ED groups had a higher non-base trimer response, shown by an 8.6-fold IgG increase between the 3M052/alum cocktail ED group and its bolus control. ED prime seems promising in raising anti-immunogen titers and lowering responses to the artificial trimer base, and further boosts will be administered to elicit serum neutralizing activity.

Precision Vaccine Development: Unraveling the Immunoinformatics Code Against Epstein-Barr Virus's T41 Glycoprotein 350/220

Epstein-Barr Virus (EBV) poses a substantial global health threat, with a 90% morbidity rate in adults worldwide. Linked to infectious mononucleosis, autoimmune diseases, and cancers, there is an imperative for effective preventive measures, given the absence of current vaccines or medications. This study employs a bioinformatics strategy to design an epitope vaccine targeting EBV. The primary target for immunity is the EBV glycoprotein 350/220 (gp350), which mediates attachment to B cells through complement receptor 2 (CR2/CD21). The selected protein, EBV glycoprotein 350/220 was chosen based on its role in pathogenicity. In the post-therapeutic approach, three-dimensional structure prediction, validation, and verification processes were conducted, followed by molecular docking studies to identify potential drug-binding sites and suitable therapeutic inhibitors for the target protein. The protein's ability to stimulate humoral and cell-mediated immunity was assessed, leading to the identification of a peptide segment ATNLFLLEL from positions 342 to 356 as the predominant T cell epitope. This epitope demonstrated compatibility with various HLA profiles, enhanced by its interaction with eight HLA-A and HLA-B alleles. Population coverage analysis revealed broad responsiveness across geographies, suggesting its potential as a widely applicable vaccine component. Its non-allergic classification further supports its potential efficacy for diverse individuals. Docking studies with HLA-B*3501 confirmed its significant affinity for MHC-I molecules, establishing it as a promising vaccination candidate. Additionally, a region from amino acid positions 253 to 310 was identified as containing potential B-cell epitopes, with the sequence "LGAGELALTMRSKKLP" showing promise due to its antigenic potential. This computational approach to epitope-based peptide vaccine design and target site prediction against EBV represents a pioneering advancement in EBV virus research, emphasizing the need for validation through <i>in vitro</i> and <i>in vivo</i> trials.