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The Mokola Virus belongs to the family Rhabdoviridae and is genotype 3 of the Lyssavirus genera. A small number of cases of animal and human encephalomyelitis, mainly scattered over sub-Saharan Africa, have been linked to the Mokola Virus (MOKV). Currently there is no vaccine to protect against MOKV infection in people or animals. It has been proven that rabies vaccination does not confer immunity against MOKV infection, even though MOKV and the rabies virus are related. Using immunoinformatics approaches, this study designed an mRNA vaccine that can protect against all the five glycoproteins of the Mokola virus. NCBI was used to obtain the viral sequences, which were then screened for antigenicity, allergenicity, toxicity, B-cell epitopes, CD8 + T lymphocytes (CTL), and CD4 + T lymphocytes (HTL). These epitopes were used in the construction of the vaccine. Some extra co-translational residues were added to the mRNA vaccine construct. Its molecular weight is 129.19083 kDa, and its estimated pI is 8.58. It interacts rather steadily and with limited deformability with TLR 3, among other human innate immune receptors. Overall, the results show that the produced candidate vaccine is non-allergen, non-toxic, and can elicit T–cell and B–cell immune responses. These findings can further be subjected to in-vivo and in-vitro techniques for validation. [ABSTRACT FROM AUTHOR]

Cryptosporidium parvum (C. parvum) is an apicomplexan protozoan known as a frequent cause of diarrhea. Because of its severe outbreaks and the association with different types of gastrointestinal cancers, it became an urgent need to develop effective solutions against that parasite. In the current study, the complete proteome of C. parvum was analyzed, and after applying several filtration steps, two proteins, namely Glycoprotein 60 (gp40/15) and thrombospondin-related adhesive protein (TRAP C-1), were selected as the protein candidates for epitope prediction. Next, CTL, HTL and BCL epitopes of each protein candidate were defined, and the best epitopes of each category were assembled alongside suitable linkers and adjuvants to initiate a potential multitope vaccine construct finally. That construct was evaluated for several properties, including its antigenicity, allergenicity, stability, secondary and tertiary structure, and the ability of that 3D predicted model to bind to TLR4. Furthermore, the stability of the constructed vaccine ligand in the TLR4 receptor was deeply investigated through a molecular dynamics simulation. The current study describes the stages of the multitope construct design. It demonstrates the results of that construct computational evaluation where the generated scores support the nomination of that potential vaccine as a solution for C. parvum infection, and further wet lab experiments are required to validate our current findings. [ABSTRACT FROM AUTHOR]

Viral nervous necrosis (VNN) poses a significant threat to the aquaculture industry, causing substantial losses and economic burdens. The disease, attributed to nervous necrosis viruses within the Betanodavirus genus, is particularly pervasive in the Mediterranean region, affecting various fish species across all production stages with mortality rates reaching 100%. Developing effective preventive measures against VNN is imperative. In this study, we employed rigorous immunoinformatics techniques to design a novel multi-epitope vaccine targeting VNN. Five RNA-directed RNA polymerases, crucial to the lifecycle of Betanodavirus, were selected as vaccine targets. The antigenicity and favorable physicochemical properties of these proteins were confirmed, and epitope mapping identified cytotoxic T lymphocyte, helper T lymphocyte, and linear B lymphocyte epitopes essential for eliciting a robust immune response. The selected epitopes, characterized by high antigenicity, non-allergenicity, and non-toxicity, were further enhanced by adding PADRE sequences and hBD adjuvants to increase immunogenicity. Two vaccine constructs were developed by linking epitopes using appropriate linkers, demonstrating high antigenicity, solubility, and stability. Molecular dynamics simulations revealed stable interactions between the vaccine constructs and Toll-like receptors (TLRs), essential for pathogen recognition and immune response activation in fish. Notably, vaccine construct V2 exhibited superior stability and binding affinity with TLR8, suggesting its potential as a promising candidate for VNN prevention. Overall, our study presents a comprehensive approach to VNN vaccine design utilizing immunoinformatics, offering safe, immunogenic, and effective solutions across multiple Betanodavirus species. Further experimental validation in model animals is recommended to fully assess the vaccine's efficacy. This research contributes to improved vaccine development against diverse fish pathogens by addressing emerging challenges and individualized immunization requirements in aquaculture. [ABSTRACT FROM AUTHOR]

Aeromonas hydrophila, a gram-negative bacterium, is a major pathogen responsible for various diseases in mammals, reptiles, amphibians, fish, and humans. Targeting the specific toxin aerolysin in A. hydrophila is crucial to address antibiotic resistance and the lack of adequate and protective vaccines against this intracellular and extracellular pathogen. This study aimed to identify a multi-epitope vaccine (MEV) candidate targeting the aerolysin toxin to combat the disease effectively. Standard biochemical characterization methods, detection of PCR, and sequencing of the 16S rRNA, rpoB, and aerA genes identified the isolate AHSA1 as A. hydrophila isolated from O. goramy. Subsequently, we identified B and T cell epitopes on the aerolysin protein and predicted MHC-I and MHC-II epitopes. The epitopes were then evaluated for toxicity, antigenicity, allergenicity, and solubility. The vaccine design integrated multi-epitope constructs, utilizing specialized linkers (GPGPG and EAAAK) to connect epitope peptides with the cholera toxin B subunit as an adjuvant, thereby enhancing immunogenicity. Ramachandran plots showed that 85.25% of the residues were in the most favorable regions, followed by additionally allowed regions (10.80%), generously allowed regions (1.30%), and disallowed regions (2.65%), confirming the feasibility of the modeled vaccine design. Based on docking simulations, the MEV had strong binding energies with TLR-4 (-1081.4 kcal/mol), TLR-9 (-723.2 kcal/mol), MHC-I (-866.2 kcal/mol), and MHC-II (-9043.3 kcal/mol). Based on computational modeling, we expect the aerolysin MEV candidate to activate diverse immune mechanisms, stimulate robust responses against A. hydrophila, and maintain safety. The significant solubility, absence of toxicity and allergic response contribute to the potential clinical utility of this vaccine candidate. [ABSTRACT FROM AUTHOR]

Computational biology involves applying computer science and informatics techniques in biology to understand complex biological data. It allows us to collect, connect, and analyze biological data at a large scale and build predictive models. In the twenty first century, computational resources along with Artificial Intelligence (AI) have been widely used in various fields of biological sciences such as biochemistry, structural biology, immunology, microbiology, and genomics to handle massive data for decision-making, including in applications such as drug design and vaccine development, one of the major areas of focus for human and animal welfare. The knowledge of available computational resources and AI-enabled tools in vaccine design and development can improve our ability to conduct cutting-edge research. Therefore, this review article aims to summarize important computational resources and AI-based tools. Further, the article discusses the various applications and limitations of AI tools in vaccine development. PLAIN LANGUAGE SUMMARY: The application of vaccines is one of the most promising treatments for numerous infectious diseases. However, the design and development of effective vaccines involve huge investments and resources, and only a handful of candidates successfully reach the market. Only relying on traditional methods is both time-consuming and expensive. Various computational tools and software have been developed to accelerate the vaccine design and development. Further, AI-enabled computational tools have revolutionized the field of vaccine design and development by creating predictive models and data-driven decision-making processes. Therefore, information and awareness of these AI-enabled computational resources will immensely facilitate the development of vaccines against emerging pathogens. In this review, we have meticulously summarized the available computational tools for each step of in-silico vaccine design and development, delving into the transformative applications of AI and ML in this domain, which would help to choose appropriate tools for each step during vaccine development, and also highlighting the limitations of these tools to facilitate the selection of appropriate tools for each step of vaccine design. [ABSTRACT FROM AUTHOR]

Fasciolosis is a zoonotic infection and is considered a developing deserted tropical illness threatening ruminant productivity and causing financial losses. Herein, we applied immunoinformatics and biophysics studies to develop an epitopes vaccine against Fasciola hepatica using glutathione transferase and Cathepsin L-like proteinase as possible vaccine candidates. Using the selected proteins, B- and Tcell epitopes were predicted. After epitopes prediction, the epitopes were clarified over immunoinformatics screening, and only five epitopes, EFGRWQQEKCTIDLD, RRNIWEKNVKHIQEH, FKAKYLTEMSRASDI, TDMTFEEFKAKYLTE, and YTAVEGQCR were selected for vaccine construction; selected epitopes were linked with the help of a GPGPG linker and attached with an adjuvant through another linker, EAAAK linker. Cholera toxin B subunit was used as an adjuvant. The ExPASy ProtParam tool server predicted 234 amino acids, 25.86257 kDa molecular weight, 8.54 theoretical pI, 36.86 instability index, and -0.424 grand average of hydropathicity. Molecular docking analysis predicted that the vaccine could activate the immune system against F. hepatica. We calculated negative binding energy values. A biophysics study, likely molecular docking molecular dynamic simulation, further validated the docking results. In molecular dynamic simulation analysis, the top hit docked compounds with the lowest binding energy values were subjected to MD simulation; the simulation analysis showed that the vaccine and immune cell receptors are stable and can activate the immune system. MMGBSA of -146.27 net energy (kcal/mol) was calculated for the vaccine-TLR2 complex, while vaccine-TLR4 of -148.11 net energy (kcal/mol) was estimated. Furthermore, the C-ImmSim bioinformatics tool predicted that the vaccine construct can activate the immune system against F. hepatica, eradicate the infection caused by F. hepatica, and reduce financial losses that need to be spent while protecting against infections of F. hepatica. The computational immune simulation unveils that the vaccine model can activate the immune system against F. hepatica; hence, the experimental scientist can validate the finding accomplished through computational approaches. [ABSTRACT FROM AUTHOR]

Influenza continues to be one of the top public health problems since it creates annual epidemics and can start a worldwide pandemic. The virus's rapid evolution allows the virus to evade the host defense, and then seasonal vaccines need to be reformulated nearly annually. However, it takes almost half a year for the influenza vaccine to become accessible. This delay is especially concerning in the event of a pandemic breakout. By producing the vaccine through reverse vaccinology and phage display vaccines, this time can be reduced. In this study, epitopes of B lymphocytes, cytotoxic T lymphocytes, and helper T lymphocytes of HA, NA, NP, and M2 proteins from two strains of Influenza A were anticipated. We found two proper epitopes (ASFIYNGRL and LHLILWITDRLFFKC) in Influenza virus proteins for CTL and HTL cells, respectively. Optimal epitopes and linkers in silico were cloned into the N-terminal end of M13 protein III (pIII) to create a multi-epitope-pIII construct, i.e., phage display vaccine. Also, prediction of tertiary structure, molecular docking, molecular dynamics simulation, and immune simulation were performed and showed that the designed multi-epitope vaccine can bind to the receptors and stimulate the immune system response. [ABSTRACT FROM AUTHOR]

Crimean–Congo hemorrhagic fever virus (CCHFV) belongs to Nairoviridae family and has tripartite RNA genome. It is endemic in various countries of Asia, Africa, and Europe and is primarily transmitted by Hyalomma ticks but nosocomial transmission also been reported. Vaccines for CCHF are in early phase of clinical trial; therefore, this work is centered on identification of potential immunogenic peptide as vaccine candidates with application of different immunoinformatics approaches. Eleven conserved (>90%) peptides of CCHFV nucleoprotein were selected for CD8+ T‐cell (NetMHCpan 4.1b and NetCTLpan 1.1 server) and CD4+ T‐cell (NetMHCIIpan‐4.0 server and Tepitool) epitope prediction. Three peptides containing multiple CD8+ and CD4+ T‐cell and B‐cell epitopes were identified on basis of consensus prediction approach. Peptides displayed good antigenicity score of 0.45–0.68 and predicted to bind with diverse human leukocyte antigen (HLA) alleles. Molecular docking was performed with epitopes to HLA and HLA‐epitopes complex to T‐cell receptor (TCR). In most of the cases, docked complex of HLA‐epitope and HLA‐epitopes‐TCR have the binding energy close to respective natural bound peptide complex with HLA and TCR. Molecular dynamic simulation also revealed that HLA‐peptide complexes have minimum fluctuation and deviation than HLA‐peptide‐TCR docked over 50 ns simulation run. Considering these findings, identified peptides can serve as potential vaccine candidates for CCHFV disease. [ABSTRACT FROM AUTHOR]

The B cell lineage tree encapsulates the successive phases of B cell differentiation and maturation, transitioning from hematopoietic stem cells to mature, antibody-secreting cells within the immune system. Mathematically, this lineage can be conceptualized as an evolutionary tree, where each node represents a distinct stage in B cell development, and the edges reflect the differentiation pathways. To compare these lineage trees, a rigorous mathematical metric is essential. Analyzing B cell lineage trees mathematically and quantifying changes in lineage attributes over time necessitates a comparison methodology capable of accurately assessing and measuring these changes. Addressing the intricacies of multiple B cell lineage tree comparisons, this study introduces a novel metric that enhances the precision of comparative analysis. This metric is formulated on principles of metric theory and evolutionary biology, quantifying the dissimilarities between lineage trees by measuring branch length distance and weight. By providing a framework for systematically classifying lineage trees, this metric facilitates the development of predictive models that are crucial for the creation of targeted immunotherapy and vaccines. To validate the effectiveness of this new metric, synthetic datasets that mimic the complexity and variability of real B cell lineage structures are employed. We demonstrated the ability of the new metric method to accurately capture the evolutionary nuances of B cell lineages. [ABSTRACT FROM AUTHOR]

The Puumala orthohantavirus is present in the body of the bank vole (Myodes glareolus). Humans infected with this virus may develop hemorrhagic fever accompanying renal syndrome. In addition, the infection may further lead to the failure of an immune system completely. The present study aimed to propose a possible vaccine by employing bioinformatics techniques to identify B and T‐cell antigens. The best multi‐epitope of potential immunogenicity was generated by combining epitopes. Additionally, the linkers EAAAK, AAY, and GPGPG were utilized in order to link the epitopes successfully. Further, C‐ImmSim was used to perform in silico immunological simulations upon the vaccine. For the purpose of conducting expression tests in Escherichia coli, the chimeric protein construct was cloned using Snapgene into the pET‐9c vector. The designed vaccine showed adequate results, evidenced by the global population coverage and favorable immune response. The developed vaccine was found to be highly effective and to have excellent population coverage in a number of computer‐based assessments. This work is fully dependent on the development of nucleoprotein‐based vaccines, which would constitute a significant step forward if our findings were used in developing a global vaccination to combat the Puumala virus. [ABSTRACT FROM AUTHOR]

Dental caries, a persistent oral health challenge primarily linked to Streptococcus mutans, extends its implications beyond dental decay, affecting over 4 billion individuals globally. Despite its historical association with childhood, dental caries often persists into adulthood with prevalence rates ranging from 60 to 90% in children and 26 to 85% in adults. Currently, there is a dearth of multiepitope vaccines (MEVs) specifically designed to combat S. mutans. To address this gap, we employed an immunoinformatics approach for MEV design, identifying five promising vaccine candidates (PBP2X, PBP2b, MurG, ATP-F, and AGPAT) based on antigenicity and conservation using several tools including CELLO v.2.5, Vaxign, v2.0, ANTIGENpro, and AllerTop v2.0 tools. Subsequent identification of linear B-cell and T-cell epitopes by SVMTrip and NetCTL/NetMHC II tools, respectively, guided the construction of a MEV comprising 10 Cytotoxic T Lymphocyte (CTL) epitopes, 5 Helper T Lymphocyte (HTL) epitopes, and 5 linear B-cell epitopes, interconnected by suitable linkers. The resultant MEV demonstrated high antigenicity, solubility, and structural stability. In silico immune simulations showcased the MEV's potential to elicit robust humoral and cell-mediated immune responses. Molecular docking studies revealed strong interactions between the MEV construct and Toll-Like Receptors (TLRs) and Major Histocompatibility Complex (MHC) molecules. Remarkably, the MEV–TLR-4 complexes exhibited a low energy score, high binding affinity, and a low dissociation constant. The Molecular Dynamic (MD) simulation analysis suggested that MEV–TLR-4 complexes had the highest stability and minimal conformational changes indicating equilibrium within 40 nanosecond time frames. Comprehensive computational analyses strongly support the potential of the proposed MEV to combat dental caries and associated infections. The study's computational assays yielded promising results, but further validation through in vitro and in vivo experiments is needed to assess its efficacy and safety. [ABSTRACT FROM AUTHOR]

Human schistosomiasis, caused by the Schistosoma trematode, is a neglected parasitic disease affecting over 250 million people worldwide. There is no vaccine, and the single available drug is threatened by drug resistance. This study presents a computational approach to designing multiepitope vaccines (MEVs) targeting the cercarial (CMEV) and schistosomular (SMEV) stages of schistosomes, and identifies potential schistosomicidal compounds from the Medicine for Malaria Ventures (MMV) and SuperNatural Database (SND) libraries. The designed vaccines (CMEV and SMEV) are engineered to provoke robust immune responses by incorporating a blend of T- and B-cell epitopes. Structural and immunoinformatics evaluations predicted robust interactions of CMEV and SMEV with key immune receptors and prolonged immune responses. In addition, molecular docking identified several compounds from the MMV and SND libraries with strong binding affinities to vital Schistosoma cathepsin proteases, indicating their potential as schistosomicidal agents. Our findings contribute to the potential development of effective vaccines and drugs against schistosomiasis. [ABSTRACT FROM AUTHOR]

Background: Current treatments and prevention strategies for echinococcosis are inadequate. Recent advancements in molecular vaccine development show promise against Echinococcus granulosus; however, Echinococcus multilocularis remains a challenge. A Multi-epitope Vaccine could potentially induce specific B and T lymphocyte responses, thereby offering protection against Echinococcus multilocularis infection. Methods: This study aimed to develop a MEV against alveolar echinococcosis. Key epitopes from the Echinococcus multilocularis proteins EmTSP3 and EmTIP were identified using immunoinformatics analyses. These analyses were conducted to assess the MEV feasibility, structural characteristics, molecular docking, molecular dynamics simulations, and immune simulations. The immunogenicity and antigenicity of the vaccine were evaluated through in vitro and in vivo experiments, employing ELISA, Western blotting, FCM, challenge infection experiments, and ELISPOT. Results: The effective antigenicity and immunogenicity of MEV were demonstrated through immunoinformatics, as well as in vitro and in vivo experiments. In vitro experiments revealed that MEV increased the secretion of IFN-g and IL-4 in PBMC and successfully bound to specific antibodies in patient serum. Furthermore, mice immunized with MEV developed a robust immune response, characterized by elevated levels of CD4+ and CD8+ T-cells, increased secretion of IFN-g and IL-4 by specific Th1 and Th2 cells, and heightened serum antibody levels. Importantly, MEV reduced the weight of cysts by conferring resistance against echinococcosis. These findings suggest that MEV is a promising candidate for the prevention of Echinococcus multilocularis infection. Conclusion: A total of 7 CTL, 7 HTL, 5 linear B-cell, and 2 conformational B-cell epitopes were identified. The vaccine has demonstrated effective antigenicity and immunogenicity against AE through molecular docking, immune simulation, molecular dynamics studies, and both in vitro and in vivo experiments. It provides effective protection against Echinococcus multilocularis infection, thereby laying a foundation for further development. [ABSTRACT FROM AUTHOR]

The metabolic disorder Type 2 Diabetes Mellitus (T2DM) is characterized by hyperglycaemia, causing increased mortality and healthcare burden globally. Recent studies emphasize the impact of metabolites in the gut microbiome on T2DM pathogenesis. One such microbial metabolite, imidazole propionate (Imp) derived from histidine metabolism, is shown to interfere with insulin signalling and other key metabolic processes. The key enzyme urocanate reductase (UrdA) is involved in ImP production. Hence, we propose to develop a novel therapeutic vaccine against the gut microbe producing Imp based on UrdA as a target for treating T2DM using immunoinformatics approach. Antigenic, non-allergic, non-toxic, and immunogenic B cell and T cell potential epitopes were predicted using immunoinformatics servers and tools. These epitopes were adjoined using linker sequences, and to increase immunogenicity, adjuvants were added at the N-terminal end of the final vaccine construct. Further, to confirm the vaccine’s safety, antigenic and non-allergic characteristics of the developed vaccine construct were assessed. The tertiary structure of the UrdA vaccine sequence was predicted using molecular modelling tools. A molecular docking study was utilized to understand the vaccine construct interaction with immune receptors, followed by molecular dynamics simulation and binding free energy calculations to assess stability of the complex. In silico cloning techniques were employed to evaluate the expression and translation effectiveness of the developed vaccine in pET vector. In conclusion, this study developed an in silico epitope-based vaccine construct as a novel adjunct therapeutic for T2DM. [ABSTRACT FROM AUTHOR]

Despite its medical relevance, there is no commercial vaccine that protects the population at risk from multidrug-resistant (MDR) Klebsiella pneumoniae infections. The availability of massive omic data and novel algorithms may improve antigen selection to develop effective prophylactic strategies. Up to 133 exposed proteins in the core proteomes, between 516 and 8666 genome samples, of the six most relevant MDR clonal groups (CGs) carried conserved B-cell epitopes, suggesting minimized future evasion if utilized for vaccination. Antigens showed a range of epitopicity, functional constraints, and potential side effects. Eleven antigens, including three sugar porins, were represented in all MDR-CGs, constitutively expressed, and showed limited reactivity with gut microbiota. Some of these antigens had important interactomic interactions and may elicit adhesion-neutralizing antibodies. Synergistic bivalent to pentavalent combinations that address expression conditions, interactome location, virulence activities, and clone-specific proteins may overcome the limiting protection of univalent vaccines. The combination of five central antigens accounted for 41% of all non-redundant interacting partners of the antigen dataset. Specific antigen mixtures represented in a few or just one MDR-CG further reduced the chance of microbiota interference. Rational antigen selection schemes facilitate the design of high-coverage and "magic bullet" multivalent vaccines against recalcitrant K. pneumoniae lineages. [ABSTRACT FROM AUTHOR]

Helicobacter pylori (H. pylori) is an infectious bacterium that colonizes the stomach of approximately half of the global population. It has been classified as a Group I carcinogen by the World Health Organization due to its strong association with an increased incidence of gastric cancer and exacerbation of stomach diseases. The primary treatment for H. pylori infection currently involves triple or quadruple therapy, primarily consisting of antibiotics and proton pump inhibitors. However, the increasing prevalence of antibiotic resistance poses significant challenges to this approach, underscoring the urgent need for an effective vaccine. In this study, a novel multi-epitope H. pylori vaccine was designed using immunoinformatics. The vaccine contains epitopes derived from nine essential proteins. Software tools and online servers were utilized to predict, evaluate, and analyze the physiochemical properties, secondary and tertiary structures, and immunogenicity of the candidate vaccine. These comprehensive assessments ultimately led to the formulation of an optimal design scheme for the vaccine. Through constructing a novel multi-epitope vaccine based on immunoinformatics, this study offers promising prospects and great potential for the prevention of H. pylori infection. This study also provides a reference strategy to develop multi-epitope vaccines for other pathogens. [ABSTRACT FROM AUTHOR]

Tropical theileriosis is a lymphoproliferative disease caused by Theileria annulata and is transmitted by Ixodid ticks of the genus Hyalomma. It causes significant losses in livestock, especially in exotic cattle. The existing methods for controlling it, chemotherapeutic agents and a vaccine based on an attenuated schizont stage parasite, have several limitations. A promising solution to control this disease is the use of molecular vaccines based on potential immunogenic proteins of T. annulata. For this purpose, we selected five antigenic sequences of T. annulata, i.e. SPAG-1, Tams, TaSP, spm2, and Ta9. These were subjected to epitope prediction for cytotoxic T lymphocytes, B-cells, and helper T lymphocytes. CTL and B-cell epitopes with a higher score whereas those of HTL with a lower score, were selected for the construct. A single protein was constructed using specific linkers and evaluated for high antigenicity and low allergenicity. The construct was acidic, hydrophobic, and thermostable in nature. Secondary and tertiary structures of this construct were drawn using the PSIPRED and RaptorX servers, respectively. A Ramachandran plot showed a high percentage of residues in this construct in favorable, allowed, and general regions. Molecular docking studies suggested that the complex was stable and our construct could potentially be a good candidate for immunization trials. Furthermore, we successfully cloned it into the pET-28a plasmid and transformed it into the BL21 strain. A restriction analysis was performed to confirm the transformation of our plasmid. After expression and purification, recombinant protein of 49 kDa was confirmed by western blotting. An ELISA detected increased specific antibody levels in the sera of the immunized animals compared with the control group, and flow cytometric analysis showed a stronger cell-mediated immune response. We believe our multi-epitope recombinant protein has the potential for the large-scale application for disease prevention globally in the bovine population. This study will act as a model for similar parasitic challenges. [ABSTRACT FROM AUTHOR]

Background: The architecture and dynamics of T cell populations are critical in orchestrating the immune response to SARS-CoV-2. In our study, we used T Cell Receptor sequencing (TCRseq) to investigate TCR repertoires in 173 post-infection COVID-19 patients. Methods: The cohort included 98 mild and 75 severe cases with a median age of 53. We amplified and sequenced the TCR β chain Complementary Determining Region 3 (CDR3b) and performed bioinformatic analyses to assess repertoire diversity, clonality, and V/J allelic usage between age, sex and severity groups. CDR3b amino acid sequence inference was performed by clustering structural motifs and filtering validated reactive CDR3b to COVID-19. Results: Our results revealed a pronounced decrease in diversity and an increase in clonal expansion in the TCR repertoires of severe COVID-19 patients younger than 55 years old. These results reflect the observed trends in patients older than 55 years old (both mild and severe). In addition, we identified a significant reduction in the usage of key V alleles (TRBV14, TRBV19, TRBV15 and TRBV6-4) associated with disease severity. Notably, severe patients under 55 years old had allelic patterns that resemble those over 55 years old, accompanied by a skewed frequency of COVID-19-related motifs. Conclusions: Present results suggest that severe patients younger than 55 may have a compromised TCR repertoire contributing to a worse disease outcome. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

A novel tick-borne orthonairovirus called the Yezo virus (YEZV), primarily transmitted by the Ixodes persulcatus tick, has been recently discovered and poses significant threats to human health. The YEZV is considered endemic in Japan and China. Clinical symptoms associated with this virus include thrombocytopenia, fatigue, headache, leukopenia, fever, depression, and neurological complications ranging from mild febrile illness to severe outcomes like meningitis and encephalitis. At present, there is no treatment or vaccine readily accessible for this pathogenic virus. Therefore, this research employed an immunoinformatics approach to pinpoint potential vaccine targets within the YEZV through an extensive examination of its structural proteins. Three structural proteins were chosen using specific criteria to pinpoint T-cell and B-cell epitopes, which were subsequently validated through interferon-gamma induction. Six overlapping epitopes for cytotoxic T-lymphocytes (CTL), helper T-lymphocytes (HTL), and linear B-lymphocytes (LBL) were selected to construct a multi-epitope vaccine, achieving a 92.29% coverage of the global population. These epitopes were then fused with the 50S ribosomal protein L7/L12 adjuvant to improve protection against international strains. The three-dimensional structure of the designed vaccine construct underwent an extensive evaluation through structural analysis. Following molecular docking studies, the YEZV vaccine construct emerged as a candidate for further investigation, showing the lowest binding energy (−78.7 kcal/mol) along with favorable physiochemical and immunological properties. Immune simulation and molecular dynamics studies demonstrated its stability and potential to induce a strong immune response within the host cells. This comprehensive analysis indicates that the designed vaccine construct could offer protection against the YEZV. It is crucial to conduct additional in vitro and in vivo experiments to verify its safety and effectiveness. [ABSTRACT FROM AUTHOR]

Pseudomonas aeruginosa is a complex nosocomial infectious agent responsible for numerous illnesses, with its growing resistance variations complicating treatment development. Studies have emphasized the importance of virulence factors OprE and OprF in pathogenesis, highlighting their potential as vaccine candidates. In this study, B-cell, MHC-I, and MHC-II epitopes were identified, and molecular linkers were active to join these epitopes with an appropriate adjuvant to construct a vaccine. Computational tools were employed to forecast the tertiary framework, characteristics, and also to confirm the vaccine's composition. The potency was weighed through population coverage analysis and immune simulation. This project aims to create a multi-epitope vaccine to reduce P. aeruginosa –related illness and mortality using immunoinformatics resources. The ultimate complex has been determined to be stable, soluble, antigenic, and non-allergenic upon inspection of its physicochemical and immunological properties. Additionally, the protein exhibited acidic and hydrophilic characteristics. The Ramachandran plot, ProSA-web, ERRAT, and Verify3D were employed to ensure the final model's authenticity once the protein's three-dimensional structure had been established and refined. The vaccine model showed a significant binding score and stability when interacting with MHC receptors. Population coverage analysis indicated a global coverage rate of 83.40%, with the USA having the highest coverage rate, exceeding 90%. Moreover, the vaccine sequence underwent codon optimization before being cloned into the Escherichia coli plasmid vector pET-28a (+) at the EcoRI and EcoRV restriction sites. Our research has developed a vaccine against P. aeruginosa that has strong binding affinity and worldwide coverage, offering an acceptable way to mitigate nosocomial infections. [ABSTRACT FROM AUTHOR]

Efforts towards an effective HIV-1 vaccine have remained mainly unsuccessful. There is increasing evidence for a potential role of HLA-C-restricted CD8+ T cell responses in HIV-1 control, including our recent report of HLA-C*03:02 among African children. However, there are no documented optimal HIV-1 CD8+ T cell epitopes restricted by HLA-C*03:02; additionally, the structural influence of HLA-C*03:02 on epitope binding is undetermined. Immunoinformatics approaches provide a fast and inexpensive method to discover HLA-restricted epitopes. Here, we employed immunopeptidomics to identify HLA-C*03:02 CD8+ T cell epitopes. We identified a clade-specific Gag-derived GY9 (GTEELRSLY) HIV-1 p17 matrix epitope potentially restricted to HLA-C*03:02. Residues E62, T142, and E151 in the HLA-C*03:02 binding groove and positions p3, p6, and p9 on the GY9 epitope are crucial in shaping and stabilizing the epitope binding. Our findings support the growing evidence of the contribution of HLA-C molecules to HIV-1 control and provide a prospect for vaccine strategies. [ABSTRACT FROM AUTHOR]

Respiratory syncytial virus (RSV) poses a significant global health threat, especially affecting infants and the elderly. Addressing this, the present study proposes an innovative approach to vaccine design, utilizing immunoinformatics and computational strategies. We analyzed RSV's structural proteins across both subtypes A and B, identifying potential helper T lymphocyte, cytotoxic T lymphocyte, and linear B lymphocyte epitopes. Criteria such as antigenicity, allergenicity, toxicity, and cytokine-inducing potential were rigorously examined. Additionally, we evaluated the conservancy of these epitopes and their population coverage across various RSV strains. The comprehensive analysis identified six major histocompatibility complex class I (MHC-I) binding, five MHC-II binding, and three B-cell epitopes. These were integrated with suitable linkers and adjuvants to form the vaccine. Further, molecular docking and molecular dynamics simulations demonstrated stable interactions between the vaccine candidate and human Toll-like receptors (TLR4 and TLR5), with a notable preference for TLR4. Immune simulation analysis underscored the vaccine's potential to elicit a strong immune response. This study presents a promising RSV vaccine candidate and offers theoretical support, marking a significant advancement in vaccine development efforts. However, the promising in silico findings need to be further validated through additional in vivo studies. [ABSTRACT FROM AUTHOR]

Salmonella subsp. enterica (SE) presents a significant global health challenge in both developed and developing countries. Current SE vaccines have limitations, targeting specific strains and demonstrating moderate efficacy in adults, while also being unsuitable for young children and often unaffordable in regions with lower income levels where the disease is prevalent. To address these challenges, this study employed a computational approach integrating core proteomics, subtractive proteomics, and immunoinformatics to develop a universal SE vaccine and identify potential drug targets. Analysis of the core proteome of 185 SE strains revealed 1964 conserved proteins. Subtractive proteomics identified 9 proteins as potential vaccine candidates and 41 as novel drug targets. Using reverse vaccinology-based immunoinformatics, four multi-epitope-based subunit vaccine constructs (MESVCs) were designed, aiming to stimulate cytotoxic T lymphocyte, helper T lymphocyte, and linear B lymphocyte responses. These constructs underwent comprehensive evaluations for antigenicity, immunogenicity, toxicity, hydropathicity, and physicochemical properties. Predictive modeling, refinement, and validation were conducted to determine the secondary and tertiary structures of the SE-MESVCs, followed by docking studies with MHC-I, MHC-II, and TLR4 receptors. Molecular docking assessments showed favorable binding with all three receptors, with SE-MESVC-4 exhibiting the most promising binding energy. Molecular dynamics simulations confirmed the binding affinity and stability of SE-MESVC-4 with the TLR4/MD2 complex. Additionally, codon optimization and in silico cloning verified the efficient translation and successful expression of SE-MESVC-4 in Escherichia coli (E. coli) str. K12. Subsequent in silico immune simulation evaluated the efficacy of SE-MESVC-4 in triggering an effective immune response. These results suggest that SE-MESVC-4 may induce both humoral and cellular immune responses, making it a potential candidate for an effective SE vaccine. However, further experimental investigations are necessary to validate the immunogenicity and efficacy of SE-MESVC-4, bringing us closer to effectively combating SE infections. [ABSTRACT FROM AUTHOR]

Malaria, caused by Plasmodium falciparum, remains a pressing global health concern. Advancements in combating this parasite involve the development of a protein vaccine. This study employs immunoinformatics to identify potential vaccine candidates within the repertoire of 218 P. falciparum exported essential proteins identified through saturaturation mutagenesis study. Our screening approach narrows down to 65 Plasmodium-exported proteins with uncharacterized functions while exhibiting non-mutability in CDS (coding sequences). The transmembrane helix, antigenicity, allergenicity of the shortlisted proteins was assessed through diverse prediction algorithm, culminating in the identification of five promising vaccination contenders, based on probability scores. We discerned B-cell, helper T-lymphocyte, and cytotoxic T-lymphocyte epitopes. Two proteins with the most favorable epitope were harnessed to construct a multi-subunit vaccine, through judicious linker integration. Employing the I-TASSER software, three-dimensional models of the constituent proteins was obtained and was validated using diverse tools like ProSA, VERIFY3D, and ERRAT. The modelled proteins underwent Molecular Dynamics (MD) simulation in a solvent environment to evaluate the stability of the multi-subunit vaccine. Furthermore, we conducted molecular docking through the ClusPro web server to elucidate potential interactions with Toll-like receptors (TLR2 and TLR4). Docking scores revealed a pronounced affinity of the multi-subunit vaccine for TLR2. Significantly, 100 ns MD simulation of the protein-receptor complex unveiled a persistent hydrogen bond linkage between the ARG63 residue of the sub-unit vaccine and the GLU32 residue of the TLR2 receptor. These findings collectively advocate the potential efficacy of the first multi-subunit vaccine from the potential hypothetical proteins of P. falciparum. [ABSTRACT FROM AUTHOR]

Abstract Viral nervous necrosis (VNN) poses a significant threat to the aquaculture industry, causing substantial losses and economic burdens. The disease, attributed to nervous necrosis viruses within the Betanodavirus genus, is particularly pervasive in the Mediterranean region, affecting various fish species across all production stages with mortality rates reaching 100%. Developing effective preventive measures against VNN is imperative. In this study, we employed rigorous immunoinformatics techniques to design a novel multi-epitope vaccine targeting VNN. Five RNA-directed RNA polymerases, crucial to the lifecycle of Betanodavirus, were selected as vaccine targets. The antigenicity and favorable physicochemical properties of these proteins were confirmed, and epitope mapping identified cytotoxic T lymphocyte, helper T lymphocyte, and linear B lymphocyte epitopes essential for eliciting a robust immune response. The selected epitopes, characterized by high antigenicity, non-allergenicity, and non-toxicity, were further enhanced by adding PADRE sequences and hBD adjuvants to increase immunogenicity. Two vaccine constructs were developed by linking epitopes using appropriate linkers, demonstrating high antigenicity, solubility, and stability. Molecular dynamics simulations revealed stable interactions between the vaccine constructs and Toll-like receptors (TLRs), essential for pathogen recognition and immune response activation in fish. Notably, vaccine construct V2 exhibited superior stability and binding affinity with TLR8, suggesting its potential as a promising candidate for VNN prevention. Overall, our study presents a comprehensive approach to VNN vaccine design utilizing immunoinformatics, offering safe, immunogenic, and effective solutions across multiple Betanodavirus species. Further experimental validation in model animals is recommended to fully assess the vaccine’s efficacy. This research contributes to improved vaccine development against diverse fish pathogens by addressing emerging challenges and individualized immunization requirements in aquaculture.

Graphical Abstract Highlight Research • The study aims to develop a multi-epitope vaccine (MEV) against A. hydrophila by targeting the aerolysin toxin, a key virulence factor responsible for infections in fish and humans. • Computational methods identified and optimized B-cell and T-cell epitopes, focusing on their ability to trigger immune responses without causing toxicity or allergenicity. • In silico simulations demonstrated that the MEV has a strong binding affinity to immune receptors like TLR-4, MHC-I, and MHC-II, indicating its potential to induce robust cellular and humoral immunity. • Structural analysis of the MEV showed a stable 3D conformation, with most residues in favorable regions, ensuring stability during immune activation. • The MEV could enhance disease control in aquaculture and reduce human infection risks, offering a promising solution to address antibiotic resistance and the absence of effective vaccines. Abstract Aeromonas hydrophila, gram-negative, is a major pathogen responsible for various diseases in mammals, reptiles, amphibia, and vertebrates, including fish and humans. Targeting the specific toxin aerolysin in A. hydrophila is crucial to address antibiotic resistance and the lack of adequate and protective vaccines against this intracellular pathogen. This study aimed to identify a multi-epitope vaccination (MEV) candidate targeting A. hydrophila aerolysin toxin to combat the disease effectively. Standard biochemical characterization methods and sequencing of the 16S rRNA, rpoB, and aerA genes identified the isolate AHSA1 as A. hydrophila. Subsequently, we identified B and T cell epitopes on the aerolysin protein and separately predicted MHC-I and MHC-II epitopes. The epitopes are then evaluated for toxicity, antigenicity, allergenicity, and solubility. The vaccine design integrated multi-epitope-based constructs, utilizing specialized linkers (GPGPG) and EAAAK linkers to connect epitope peptides with adjuvants in the cholera toxin B component, thereby enhancing immunogenicity. Ramachandran plots showed that 85.25% of the residues were located in the most favorable regions, which was followed by the generously allowed zone (1.30%), the additional allowed regions (10.80%), and the forbidden regions (2.65%), thus confirming the feasibility of the modeled vaccine design. Based on docking simulations, MEV had the highest binding and interaction energies with TLR-4, TLR-9, MHC-I, and MHC-II (-1081.4, -723.2, 866.2, -9043.3 kcal/mol). Based on computational modelling, we expect the Aerolysin MEV candidate design to activate diverse immune mechanisms, stimulate robust responses against A. hydrophila, and maintain safety. The significant solubility, absence of toxicity or allergic response, and minimal side effects in animal testing all contribute to the potential clinical utility of this vaccine candidate.

Abstract Influenza continues to be one of the top public health problems since it creates annual epidemics and can start a worldwide pandemic. The virus’s rapid evolution allows the virus to evade the host defense, and then seasonal vaccines need to be reformulated nearly annually. However, it takes almost half a year for the influenza vaccine to become accessible. This delay is especially concerning in the event of a pandemic breakout. By producing the vaccine through reverse vaccinology and phage display vaccines, this time can be reduced. In this study, epitopes of B lymphocytes, cytotoxic T lymphocytes, and helper T lymphocytes of HA, NA, NP, and M2 proteins from two strains of Influenza A were anticipated. We found two proper epitopes (ASFIYNGRL and LHLILWITDRLFFKC) in Influenza virus proteins for CTL and HTL cells, respectively. Optimal epitopes and linkers in silico were cloned into the N-terminal end of M13 protein III (pIII) to create a multi-epitope-pIII construct, i.e., phage display vaccine. Also, prediction of tertiary structure, molecular docking, molecular dynamics simulation, and immune simulation were performed and showed that the designed multi-epitope vaccine can bind to the receptors and stimulate the immune system response.

Abstract The B cell lineage tree encapsulates the successive phases of B cell differentiation and maturation, transitioning from hematopoietic stem cells to mature, antibody-secreting cells within the immune system. Mathematically, this lineage can be conceptualized as an evolutionary tree, where each node represents a distinct stage in B cell development, and the edges reflect the differentiation pathways. To compare these lineage trees, a rigorous mathematical metric is essential. Analyzing B cell lineage trees mathematically and quantifying changes in lineage attributes over time necessitates a comparison methodology capable of accurately assessing and measuring these changes. Addressing the intricacies of multiple B cell lineage tree comparisons, this study introduces a novel metric that enhances the precision of comparative analysis. This metric is formulated on principles of metric theory and evolutionary biology, quantifying the dissimilarities between lineage trees by measuring branch length distance and weight. By providing a framework for systematically classifying lineage trees, this metric facilitates the development of predictive models that are crucial for the creation of targeted immunotherapy and vaccines. To validate the effectiveness of this new metric, synthetic datasets that mimic the complexity and variability of real B cell lineage structures are employed. We demonstrated the ability of the new metric method to accurately capture the evolutionary nuances of B cell lineages.

Abstract Background The architecture and dynamics of T cell populations are critical in orchestrating the immune response to SARS-CoV-2. In our study, we used T Cell Receptor sequencing (TCRseq) to investigate TCR repertoires in 173 post-infection COVID-19 patients. Methods The cohort included 98 mild and 75 severe cases with a median age of 53. We amplified and sequenced the TCR β chain Complementary Determining Region 3 (CDR3b) and performed bioinformatic analyses to assess repertoire diversity, clonality, and V/J allelic usage between age, sex and severity groups. CDR3b amino acid sequence inference was performed by clustering structural motifs and filtering validated reactive CDR3b to COVID-19. Results Our results revealed a pronounced decrease in diversity and an increase in clonal expansion in the TCR repertoires of severe COVID-19 patients younger than 55 years old. These results reflect the observed trends in patients older than 55 years old (both mild and severe). In addition, we identified a significant reduction in the usage of key V alleles (TRBV14, TRBV19, TRBV15 and TRBV6-4) associated with disease severity. Notably, severe patients under 55 years old had allelic patterns that resemble those over 55 years old, accompanied by a skewed frequency of COVID-19-related motifs. Conclusions Present results suggest that severe patients younger than 55 may have a compromised TCR repertoire contributing to a worse disease outcome. Graphical Abstract

Respiratory syncytial virus (RSV) poses a significant global health threat, especially affecting infants and the elderly. Addressing this, the present study proposes an innovative approach to vaccine design, utilizing immunoinformatics and computational strategies. We analyzed RSV's structural proteins across both subtypes A and B, identifying potential helper T lymphocyte, cytotoxic T lymphocyte, and linear B lymphocyte epitopes. Criteria such as antigenicity, allergenicity, toxicity, and cytokine-inducing potential were rigorously examined. Additionally, we evaluated the conservancy of these epitopes and their population coverage across various RSV strains. The comprehensive analysis identified six major histocompatibility complex class I (MHC-I) binding, five MHC-II binding, and three B-cell epitopes. These were integrated with suitable linkers and adjuvants to form the vaccine. Further, molecular docking and molecular dynamics simulations demonstrated stable interactions between the vaccine candidate and human Toll-like receptors (TLR4 and TLR5), with a notable preference for TLR4. Immune simulation analysis underscored the vaccine's potential to elicit a strong immune response. This study presents a promising RSV vaccine candidate and offers theoretical support, marking a significant advancement in vaccine development efforts. However, the promising in silico findings need to be further validated through additional in vivo studies.

ABSTRACTIntroduction Clinical trials of personalized cancer vaccines have shown that on-demand therapies that are manufactured for each patient, result in activated T cell responses against individual tumor neoantigens. However, their use has been traditionally restricted to adjuvant settings and late-stage cancer therapy. There is growing support for the implementation of PCV earlier in the cancer therapy timeline, for reasons that will be discussed in this review.Areas covered The efficacy of cancer vaccines may be to some extent dependent on treatment(s) given prior to vaccine administration. Tumors can undergo radical immunoediting following treatment with immunotherapies, such as checkpoint inhibitors, which may affect the presence of the very mutations targeted by cancer vaccines. This review will cover the topics of neoantigen cancer vaccines, tumor immunoediting, and therapy timing.Expert opinion Therapy timing remains a critical topic to address in optimizing the efficacy of personalized cancer vaccines. Most personalized cancer vaccines are being evaluated in late-stage cancer patients and after treatment with checkpoint inhibitors, but they may offer a greater benefit to the patient if administered in earlier clinical settings, such as the neoadjuvant setting, where patients are not facing T cell exhaustion and/or a further compromised immune system.

Clostridioides difficile (C. difficile), as the major pathogen of diarrhea in healthcare settings, has become increasingly prevalent within community populations, resulting in significant morbidity and mortality. However, the therapeutic options for Clostridioides difficile infection (CDI) remain limited, and as of now, no authorized vaccine is available to combat this disease. Therefore, the development of a novel vaccine against C. difficile is of paramount importance. In our study, the complete proteome sequences of 118 strains of C. difficile were downloaded and analyzed. We found four antigenic proteins that were highly conserved and can be used for epitope identification. We designed two vaccines, WLcd1 and WLcd2, that contain the ideal T-cell and B-cell epitopes, adjuvants, and the pan HLA DR-binding epitope (PADRE) sequences. The biophysical and chemical assessments of these vaccine candidates indicated that they were suitable for immunogenic applications. Molecular docking analyses revealed that WLcd1 bonded with higher affinity to Toll-like receptors (TLRs) than WLcd2. Furthermore, molecular dynamics (MD) simulations, performed using Gmx_MMPBSA v1.56, confirmed the binding stability of WLcd1 with TLR2 and TLR4. The preliminary findings suggested that this multi-epitope vaccine could be a promising candidate for protection against CDI; however, experimental studies are necessary to confirm these predictions.

Objectives This study aimed to identify the optimal protein construction for designing a multi-epitope vaccine with both prophylactic and therapeutic effects against cervical cancer, utilizing an immunoinformatics approach. The construction process involved using capsid epitopes L1 and L2, as well as oncoproteins E5, E6, and E7 from human papillomavirus (HPV) types 16 and 18. Methods An experimental in silico analysis with an immunoinformatics approach was used to develop 2 multi-epitope vaccine constructs (A and B). Further analysis was then conducted to compare the constructs and select the one with the highest potential against cervical cancer. Results This study produced 2 antigenic, non-allergenic, and nontoxic multi-epitope vaccine constructs (A and B), which exhibited the ideal physicochemical properties for a vaccine. Further analysis revealed that construct B effectively induced both cellular and humoral immune responses. Conclusion The multi-epitope vaccine construct B for HPV 16 and 18, designed for both prophylactic and therapeutic purposes, met the development criteria for a cervical cancer vaccine. However, these findings need to be validated through in vitro and in vivo experiments.

Recombinant technology-based vaccines have emerged as a highly effective way to prevent a wide range of illnesses. The technology improved vaccine manufacturing, rendering it more efficient and economical. These vaccines have multiple advantages compared to conventional vaccines. The pandemic has heightened awareness of the advantages of these vaccine technologies; trust and acceptance of these vaccines are steadily growing globally. This work offers an overview of the prospects and advantages associated with recombinant vaccines. Additionally, it discusses some of the challenges likely to arise in the future. Their ability to target diverse pathogen classes underscores their contributions to preventing previously untreatable diseases (especially vector-borne and emerging diseases) and hurdles faced throughout the vaccine development process, especially in enhancing the effectiveness of these vaccines. Moreover, their compatibility with emerging vaccination platforms of the future like virus-like particles and CRISPR/Cas9 for the production of next-generation vaccines may offer many prospects. This review also reviewed the hurdles faced throughout the vaccine development process, especially in enhancing the effectiveness of these vaccines against vector-borne diseases, emerging diseases, and untreatable diseases with high mortality rates like AIDS as well as cancer.

Abstract Porcine epidemic diarrhea virus (PEDV) is a serious disease that poses a significant threat to the pig industry. This study focused on analyzing the Spike protein of PEDV, which harbors crucial antigenic determinants, in identifying dominant epitopes. Immunoinformatics tools were used to screen for B-cell, CD4+ and CD8+ predominance epitopes. These epitopes were then connected to the N-terminal of ferritin to form a self-assembled nanoparticle vaccine. Various physical and chemical properties of the candidate vaccine were analyzed, including secondary structure prediction, tertiary structure modeling, molecular docking, immune response simulation and computer cloning. The results demonstrated that the candidate vaccine was antigenic, soluble, stable, non-allergic, and formed a stable complex with the target receptor TLR-3. Immune simulation analysis showed that the candidate vaccine effectively stimulated both cellular and humoral reactions, leading to increased related cytokines production. Furthermore, efficient and stable expression of the candidate vaccine was achieved through reverse translation in the Escherichia coli K12 expression system following codon optimization and in silico cloning. The developed nanoparticle candidate vaccine in this study holds promise as an effective PEDV vaccine candidate, offering a new approach for the research, development and improvement of vaccines targeting porcine enteric diarrhea coronavirus.

Abstract Helicobacter pylori (H. pylori) is responsible for various chronic or acute diseases, such as stomach ulcers, dyspepsia, peptic ulcers, gastroesophageal reflux, gastritis, lymphoma, and stomach cancers. Although specific drugs are available to treat the bacterium's harmful effects, there is an urgent need to develop a preventive or therapeutic vaccine. Therefore, the current study aims to create a multi-epitope vaccine against H. pylori using lipid nanoparticles. Five epitopes from five target proteins of H. pylori, namely, Urease, CagA, HopE, SabA, and BabA, were used. Immunogenicity, MHC (Major Histocompatibility Complex) bonding, allergenicity, toxicity, physicochemical analysis, and global population coverage of the entire epitopes and final construct were carefully examined. The study involved using various bioinformatic web tools to accomplish the following tasks: modeling the three-dimensional structure of a set of epitopes and the final construct and docking them with Toll-Like Receptor 4 (TLR4). In the experimental phase, the final multi-epitope construct was synthesized using the solid phase method, and it was then enclosed in lipid nanoparticles. After synthesizing the construct, its loading, average size distribution, and nanoliposome shape were checked using Nanodrop at 280 nm, dynamic light scattering (DLS), and atomic force microscope (AFM). The designed vaccine has been confirmed to be non-toxic and anti-allergic. It can bind with different MHC alleles at a rate of 99.05%. The construct loading was determined to be about 91%, with an average size of 54 nm. Spherical shapes were also observed in the AFM images. Further laboratory tests are necessary to confirm the safety and immunogenicity of the multi-epitope vaccine.

Given the critical role of human papillomavirus (HPV) in the cause of cervical cancer and other malignancies, there is aneed for innovative approaches to preventing this infection. It has been shown that immunoinformatics is an importantstrategy in computational vaccinology. It is used to design new multi-epitope vaccines against different types of HPVand subsequent cervical cancer. This paper reviews the scope of the entire computational pipeline of HPV vaccinedesign, starting from data analysis at the genomic and proteomic levels and continuing to epitope predictions of theinnate and adaptive immune systems. The search strategy was based on investigating original articles published in“Google Scholar" and “PubMed" from 2015 to 2023-2024. The terms "Immunoinformatics", "Bioinformatics", "Humanpapillomavirus (HPV)", "Vaccine design", "In silico vaccine design", "Multi-epitope vaccine design", "Vaccinology" and"HPV vaccine" were used to for this purpose. We discussed various essential tools involved in the computationaldesign of the vaccine process, e.g., sequence analysis, epitope prediction, conservancy analysis, tertiary structuremodeling, refinement, molecular docking, molecular dynamics (MD) simulation, and in silico cloning. This reviewarticle describes immunoinformatics methods that facilitate the design of a multi-epitope vaccine against HPV.However, this pipeline can also be used to design novel chimeric vaccines for other pathogens.

Abstract The available Epstein Barr virus vaccine has tirelessly harnessed the gp350 glycoprotein as its target epitope, but the result has not been preventive. Right here, we designed a global multi-epitope vaccine for EBV; with special attention to making sure all strains and preventive antigens are covered. Using a robust computational vaccine design approach, our proposed vaccine is armed with 6–16 mers linear B-cell epitopes, 4–9 mer CTL epitopes, and 8–15 mer HTL epitopes which are verified to induce interleukin 4, 10 & IFN-gamma. We employed deep computational mining coupled with expert intelligence in designing the vaccine, using human Beta defensin-3—which has been reported to induce the same TLRs as EBV—as the adjuvant. The tendency of the vaccine to cause autoimmune disorder is quenched by the assurance that the construct contains no EBNA-1 homolog. The protein vaccine construct exhibited excellent physicochemical attributes such as Aliphatic index 59.55 and GRAVY − 0.710; and a ProsaWeb Z score of − 3.04. Further computational analysis revealed the vaccine docked favorably with EBV indicted TLR 1, 2, 4 & 9 with satisfactory interaction patterns. With global coverage of 85.75% and the stable molecular dynamics result obtained for the best two interactions, we are optimistic that our nontoxic, non-allergenic multi-epitope vaccine will help to ameliorate the EBV-associated diseases—which include various malignancies, tumors, and cancers—preventively.

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.

Background and Aim: Staphylococcus aureus, with its diverse virulence factors and immune response evasion mechanisms, presents a formidable challenge as an opportunistic pathogen. Developing an effective vaccine against S. aureus has proven elusive despite extensive efforts. Autologous Staphylococcus lysate (ASL) treatment has proven effective in triggering an immune response against bovine mastitis. Peptides that stimulate the immune response can be the subject of further research. The study aimed to use immunoinformatics tools to identify epitopes on S. aureus surface and secretory proteins that can bind to major histocompatibility complex class I (MHC I) and CD8+ T-cells. This method aids in discovering prospective vaccine candidates and elucidating the rationale behind ASL therapy’s efficacy. Materials and Methods: Proteins were identified using both literature search and the National Center for Biotechnology Information search engine Entrez. Self and non-self peptides, allergenicity predictions, epitope locations, and physicochemical characteristics were determined using sequence alignment, AllerTOP, SVMTriP, and Protein-Sol tools. Hex was employed for simulating the docking interactions between S. aureus proteins and the MHC I + CD8+ T-cells complex. The binding sites of S. aureus proteins were assessed using Computer Atlas of Surface Topography of Proteins (CASTp) while docked with MHC I and CD8+ T-cells. Results: Nine potential S. aureus peptides and their corresponding epitopes were identified in this study, stimulating cytotoxic T-cell mediated immunity. The peptides were analyzed for similarity with self-antigens and allergenicity. 1d20, 2noj, 1n67, 1nu7, 1amx, and 2b71, non-self and stable, are potential elicitors of the cytotoxic T-cell response. The energy values from docking simulations of peptide-MHC I complexes with the CD8+ and T-cell receptor (TCR) indicate the stability and strength of the formed complexes. These peptides – 2noj, 1d20, 1n67, 2b71, 1nu7, 1yn3, 1amx, 2gi9, and 1edk – demonstrated robust MHC I binding, as evidenced by their low binding energies. Peptide 2gi9 exhibited the lowest energy value, followed by 2noj, 1nu7, 1n67, and 1d20, when docked with MHC I and CD8 + TCR, suggesting a highly stable complex. CASTp analysis indicated substantial binding pockets in the docked complexes, with peptide 1d20 showing the highest values for area and volume, suggesting its potential as an effective elicitor of immunological responses. These peptides – 2noj, 2gi9, 1d20, and 1n67 – stand out for vaccine development and T-cell activation against S. aureus. Conclusion: This study sheds light on the design and development of S. aureus vaccines, highlighting the significance of employing computational methods in conjunction with experimental verification. The significance of T-cell responses in combating S. aureus infections is emphasized by this study. More experiments are needed to confirm the effectiveness of these vaccine candidates and discover their possible medical uses.

Porcine epidemic diarrhea virus (PEDV) is a serious disease that poses a significant threat to the pig industry. This study focused on analyzing the Spike protein of PEDV, which harbors crucial antigenic determinants, in identifying dominant epitopes. Immunoinformatics tools were used to screen for B-cell, CD4+ and CD8+ predominance epitopes. These epitopes were then connected to the N-terminal of ferritin to form a self-assembled nanoparticle vaccine. Various physical and chemical properties of the candidate vaccine were analyzed, including secondary structure prediction, tertiary structure modeling, molecular docking, immune response simulation and computer cloning. The results demonstrated that the candidate vaccine was antigenic, soluble, stable, non-allergic, and formed a stable complex with the target receptor TLR-3. Immune simulation analysis showed that the candidate vaccine effectively stimulated both cellular and humoral reactions, leading to increased related cytokines production. Furthermore, efficient and stable expression of the candidate vaccine was achieved through reverse translation in the Escherichia coli K12 expression system following codon optimization and in silico cloning. The developed nanoparticle candidate vaccine in this study holds promise as an effective PEDV vaccine candidate, offering a new approach for the research, development and improvement of vaccines targeting porcine enteric diarrhea coronavirus. [ABSTRACT FROM AUTHOR]

Helicobacter pylori (H. pylori) is responsible for various chronic or acute diseases, such as stomach ulcers, dyspepsia, peptic ulcers, gastroesophageal reflux, gastritis, lymphoma, and stomach cancers. Although specific drugs are available to treat the bacterium's harmful effects, there is an urgent need to develop a preventive or therapeutic vaccine. Therefore, the current study aims to create a multi-epitope vaccine against H. pylori using lipid nanoparticles. Five epitopes from five target proteins of H. pylori, namely, Urease, CagA, HopE, SabA, and BabA, were used. Immunogenicity, MHC (Major Histocompatibility Complex) bonding, allergenicity, toxicity, physicochemical analysis, and global population coverage of the entire epitopes and final construct were carefully examined. The study involved using various bioinformatic web tools to accomplish the following tasks: modeling the three-dimensional structure of a set of epitopes and the final construct and docking them with Toll-Like Receptor 4 (TLR4). In the experimental phase, the final multi-epitope construct was synthesized using the solid phase method, and it was then enclosed in lipid nanoparticles. After synthesizing the construct, its loading, average size distribution, and nanoliposome shape were checked using Nanodrop at 280 nm, dynamic light scattering (DLS), and atomic force microscope (AFM). The designed vaccine has been confirmed to be non-toxic and anti-allergic. It can bind with different MHC alleles at a rate of 99.05%. The construct loading was determined to be about 91%, with an average size of 54 nm. Spherical shapes were also observed in the AFM images. Further laboratory tests are necessary to confirm the safety and immunogenicity of the multi-epitope vaccine. [ABSTRACT FROM AUTHOR]

Background: Messenger RNA (mRNA) vaccines emerged as a powerful tool in the fight against infections. Unlike traditional vaccines, this unique type of vaccine elicits robust and persistent innate and humoral immune response with a unique host cell‐mediated pathogen gene expression and antigen presentation. Methods: This offers a novel approach to combat poxviridae infections. From the genome of vaccinia and Mpox viruses, three key genes (E8L, E7R, and H3L) responsible for virus attachment and virulence were selected and employed for designing the candidate mRNA vaccine against vaccinia and Mpox viral infection. Various bioinformatics tools were employed to generate (B cell, CTL, and HTL) epitopes, of which 28 antigenic and immunogenic epitopes were selected and are linked to form the mRNA vaccine construct. Additional components, including a 5′ cap, 5′ UTR, adjuvant, 3′ UTR, and poly(A) tail, were incorporated to enhance stability and effectiveness. Safety measures such as testing for human homology and in silico immune simulations were implemented to avoid autoimmunity and to mimics the immune response of human host to the designed mRNA vaccine, respectively. The mRNA vaccine's binding affinity was evaluated by docking it with TLR‐2, TLR‐3, TLR‐4, and TLR‐9 receptors which are subsequently followed by molecular dynamics simulations for the highest binding one to predict the stability of the binding complex. Results: With a 73% population coverage, the mRNA vaccine looks promising, boasting a molecular weight of 198 kDa and a molecular formula of C8901H13609N2431O2611S48 and it is said to be antigenic, nontoxic and nonallergic, making it safe and effective in preventing infections with Mpox and vaccinia viruses, in comparison with other insilico‐designed vaccine for vaccinia and Mpox viruses. Conclusions: However, further validation through in vivo and in vitro techniques is underway to fully assess its potential. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to identify the optimal protein construction for designing a multiepitope vaccine with both prophylactic and therapeutic effects against cervical cancer, utilizing an immunoinformatics approach. The construction process involved using capsid epitopes L1 and L2, as well as oncoproteins E5, E6, and E7 from human papillomavirus (HPV) types 16 and 18. Methods: An experimental in silico analysis with an immunoinformatics approach was used to develop 2 multi-epitope vaccine constructs (A and B). Further analysis was then conducted to compare the constructs and select the one with the highest potential against cervical cancer. Results: This study produced 2 antigenic, non-allergenic, and nontoxic multi-epitope vaccine constructs (A and B), which exhibited the ideal physicochemical properties for a vaccine. Further analysis revealed that construct B effectively induced both cellular and humoral immune responses. Conclusion: The multi-epitope vaccine construct B for HPV 16 and 18, designed for both prophylactic and therapeutic purposes, met the development criteria for a cervical cancer vaccine. However, these findings need to be validated through in vitro and in vivo experiments. [ABSTRACT FROM AUTHOR]

Cryptococcus neoformans is a widely distributed opportunistic pathogenic fungus. While C. neoformans commonly infects immunocompromised individuals, it can also affect those who are immunocompetent. Transmission of C. neoformans primarily occurs through the respiratory tract, leading to the development of meningitis. The mortality rate of Cryptococcal meningitis is high, and treatment options are limited. Cryptococcus neoformans infections pose a significant public health threat and currently lack targeted and effective response strategies. This study aimed to screen T lymphocyte (cytotoxic T lymphocyte and helper T lymphocyte) and B lymphocyte epitopes derived from four C. neoformans antigens and develop two multi-epitope vaccines by combining them with various adjuvants. Molecular docking results demonstrated that the vaccines bind stably to Toll-like receptor 4 (and induce innate immunity. The credibility of the molecular docking results was validated through subsequent molecular dynamics simulations. Furthermore, the results of immune simulation analyses underscored the multi-epitope vaccine's capability to effectively induce robust humoral and cellular immune responses within the host organism. These two vaccines have demonstrated theoretical efficacy against C. neoformans infection as indicated by computer analysis. Nevertheless, additional experimental validation is essential to substantiate the protective efficacy of the vaccines. [ABSTRACT FROM AUTHOR]

The liver fluke O. viverrini (Opisthorchis viverrini), a neglected tropical disease (NTD), endemic to the Great Mekong Subregion (GMS), mainly afflicts the northeastern region of Thailand. It is a leading cause of cholangiocarcinoma (CCA) in humans. Presently, the treatment modalities for opisthorchiasis incorporate the use of the antihelminthic drug praziquantel, the rapid occurrence of reinfection, and the looming threat of drug resistance highlight the urgent need for vaccine development. Recent advances in "omics" technologies have proven to be a powerful tool for such studies. Utilizing candidate proteins identified through proteomics and refined via immunoproteomics, reverse vaccinology (RV) offers promising prospects for designing vaccines targeting essential antibody responses to eliminate parasite. Machine learning-based computational tools can predict epitopes of candidate protein/antigens exhibiting high binding affinities for B cells, MHC classes I and II, indicating strong potential for triggering both humoral and cellmediated immune responses. Subsequently, these vaccine designs can undergo population-specific testing and docking/dynamics studies to assess efficacy and synergistic immunogenicity. Hence, refining proteomics data through immunoinformatics and employing computational tools to generate antigenspecific targets for trials offers a targeted and efficient approach to vaccine development that applies to all domains of parasite infections. In this review, we delve into the strategic antigen selection process using omics modalities for the O. viverrini parasite and propose an innovative framework for vaccine design. We harness omics technologies to revolutionize vaccine development, promising accelerated discoveries and streamlined preclinical and clinical evaluations. [ABSTRACT FROM AUTHOR]

The available Epstein Barr virus vaccine has tirelessly harnessed the gp350 glycoprotein as its target epitope, but the result has not been preventive. Right here, we designed a global multi-epitope vaccine for EBV; with special attention to making sure all strains and preventive antigens are covered. Using a robust computational vaccine design approach, our proposed vaccine is armed with 6–16 mers linear B-cell epitopes, 4–9 mer CTL epitopes, and 8–15 mer HTL epitopes which are verified to induce interleukin 4, 10 & IFN-gamma. We employed deep computational mining coupled with expert intelligence in designing the vaccine, using human Beta defensin-3—which has been reported to induce the same TLRs as EBV—as the adjuvant. The tendency of the vaccine to cause autoimmune disorder is quenched by the assurance that the construct contains no EBNA-1 homolog. The protein vaccine construct exhibited excellent physicochemical attributes such as Aliphatic index 59.55 and GRAVY − 0.710; and a ProsaWeb Z score of − 3.04. Further computational analysis revealed the vaccine docked favorably with EBV indicted TLR 1, 2, 4 & 9 with satisfactory interaction patterns. With global coverage of 85.75% and the stable molecular dynamics result obtained for the best two interactions, we are optimistic that our nontoxic, non-allergenic multi-epitope vaccine will help to ameliorate the EBV-associated diseases—which include various malignancies, tumors, and cancers—preventively. [ABSTRACT FROM AUTHOR]

Introduction: Bluetongue (BT) poses a significant threat to the livestock industry, affecting various animal species and resulting in substantial economic losses. The existence of numerous BT virus (BTV) serotypes has hindered control efforts, highlighting the need for broad-spectrum vaccines. Methodology: In this study, we evaluated the conserved amino acid sequences within key non-structural (NS) proteins of BTV and identified numerous highly conserved murine- and bovine-specific MHC class I-restricted (MHC-I) CD8+ and MHC-II-restricted CD4+ epitopes. We then screened these conserved epitopes for antigenicity, allergenicity, toxicity, and solubility. Using these epitopes, we developed in silico-based broad-spectrum multiepitope vaccines with Toll-like receptor (TLR-4) agonists. The predicted proinflammatory cytokine response was assessed in silico using the C-IMMSIM server. Structural modeling and refinement were achieved using Robetta and GalaxyWEB servers. Finally, we assessed the stability of the docking complexes through extensive 100-nanosecond molecular dynamics simulations before considering the vaccines for codon optimization and in silico cloning. Results: We found many epitopes that meet these criteria within NS1 and NS2 proteins and developed in silico broad-spectrum vaccines. The immune simulation studies revealed that these vaccines induce high levels of IFN-γ and IL-2 in the vaccinated groups. Protein-protein docking analysis demonstrated promising epitopes with strong binding affinities to TLR-4. The docked complexes were stable, with minimal Root Mean Square Deviation and Root Mean Square Fluctuation values. Finally, the in silico-cloned plasmids have high % of GC content with > 0.8 codon adaptation index, suggesting they are suitable for expressing the protein vaccines in prokaryotic system. Discussion: These next-generation vaccine designs are promising and warrant further investigation in wet lab experiments to assess their immunogenicity, safety, and efficacy for practical application in livestock. Our findings offer a robust framework for developing a comprehensive, broad-spectrum vaccine, potentially revolutionizing BT control and prevention strategies in the livestock industry. [ABSTRACT FROM AUTHOR]

[Display omitted] Dengue becomes the most common life-threatening infectious arbovirus disease globally, with prevalence in the tropical and subtropical areas. The major clinical features include dengue haemorrhagic fever (DHF) and dengue shock syndrome (DSS), a condition of hypovolemic shock. Four different serotypes of the dengue virus, known as dengue virus serotype (DENV)- 1, 2, 3 and 4 can infect humans. Only one vaccine is available in the market, named Dengvaxia by Sanofi Pasteur, but there is no desired outcome of this treatment due the antibody dependent enhancement (ADE) of the multiple dengue serotypes. As of now, there is no cure against dengue disease. Our goal in this work was to create a subunit vaccine based on several epitopes that would be effective against every serotype of the dengue virus. Here, computational methods like- immunoinformatics and bioinformatics were implemented to find out possible dominant epitopes. A total of 21 epitopes were chosen using various in-silico techniques from the expected 133 major histocompatibility complex (MHC)- I and major histocompatibility complex (MHC)- II epitopes, along with 95 B-cell epitopes which were greatly conserved. Immune stimulant, non-allergenic and non-toxic immunodominant epitopes (super epitopes) with a suitable adjuvant (Heparin-Binding Hemagglutinin Adhesin, HBHA) were used to construct the vaccine. Following the physicochemical analysis, vaccine construct was docked with Toll-like receptors (TLRs) to predict the immune stimulation. Consequently, the optimal docked complex that demonstrated the least amount of ligand-receptor complex deformability was used to conduct the molecular dynamics analysis. By following the codon optimization, the final vaccine molecule was administered into an expressing vector to perform in-silico cloning. The robust immune responses were generated in the in-silico immune simulation analysis. Hence, this study provides a hope to control the dengue infections. For validation of the immune outcomes, in-vitro as well as in-vivo investigations are essential. [ABSTRACT FROM AUTHOR]