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Human cytomegalovirus (HCMV) infection can lead to congenital infections and severe complications, particularly in immunocompromised individuals. Current serological tests for diagnosing HCMV infection often face limitations in sensitivity and specificity. Developing multi‐epitope antigens for serological assays offers the potential for enhancing diagnostic accuracy. This study aimed to design a novel multi‐epitope antigen for HCMV infection diagnosis using immunoinformatic approaches. Five tegument proteins (universal protein resource [UniProt] ID: Po8318, Po6725, F5HC97, Q6RX10, and F5HC05) were selected based on their antigenic properties and literature review. Six linear B‐cell epitopes were predicted within conserved regions of each antigen sequence and linked with appropriate linkers. The designed multi‐epitope antigen underwent thorough evaluation for physicochemical properties, solubility, antigenicity, and cross‐reactivity. Additionally, the three‐dimensional structure of the antigen was predicted, refined, and validated. The nucleotide sequence of the designed antigen was optimized for successful expression in Escherichia coli and inserted into a pET23a (+) vector. Immunoinformatic analysis revealed that the multi‐epitope antigen exhibits stability, antigenicity, and lacks cross‐reactivity. Our findings suggest that this multi‐epitope antigen is a promising candidate for diagnosing HCMV infection. However, further validation through laboratory testing is required to confirm its diagnostic efficacy. [ABSTRACT FROM AUTHOR]

Simple Summary: The current study aimed to design a multiepitope subunit vaccine against the Omsk Hemorrhagic Fever Virus (OHFV). The predicted potent antigenic, non-allergenic, and nontoxic cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes were chosen considering several vaccine parameters. After screening, eight (8) CTL, five (5) HTL, and six (6) B cell epitopes were joined. The designed vaccine construct was predicted to generate robust primary and secondary immune responses. In addition, the vaccine construct was blindly docked to the TLR4 immune receptor and subjected to conformational dynamics simulation analysis to interpret its intermolecular binding affinity and time-dependent dynamic behavior. Omsk Hemorrhagic Fever Virus (OHFV) is an RNA virus with a single-stranded, positive-sense genome. It is classified under the Flaviviridae family. The genome of this virus is 98% similar to the Alkhurma hemorrhagic fever virus (AHFV), which belongs to the same family. Cases of the virus have been reported in various regions of Saudi Arabia. Both OHFV and AHFV have similarities in pathogenic polyprotein targets. No effective and licensed vaccines are available to manage OHFV infections. Therefore, an effective and safe vaccine is required that can activate protective immunity against OHFV. The current study aimed to design a multiepitope subunit vaccine against the OHFV utilizing several immunoinformatic tools. The polyprotein of OHFV was selected and potent antigenic, non-allergenic, and nontoxic cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes were chosen. After screening, eight (8) CTL, five (5) HTL, and six (6) B cell epitopes were joined with each other using different linkers. Adjuvant human beta defensin-2 was also linked to the epitopes to increase vaccine antigenic and immunogenic efficiency. The designed vaccine was docked with Toll-like receptor 4 (TLR4) as it activates and induces primary and secondary immune responses against OHFV. Codon optimization was carried out, which resulted in a CAI value of 0.99 and 53.4% GC contents. In addition, the construct was blindly docked to the TLR4 immune receptor and subjected to conformational dynamics simulation analysis to interpret the intricate affinity and comprehend the time-dependent behavior. Moreover, it was predicted that immune responses to the developed vaccine construct reported formation of strong humoral and cellular immune cells. Therefore, the proposed vaccine may be considered in experimental assays to combat OHFV infections. Laboratory experiments for the above predictions are essential in order to evaluate the effectiveness, safety, and protective properties of the subject in question. [ABSTRACT FROM AUTHOR]

Introduction: The current vaccine strategies to prevent cervical cancer are effective only for individuals unexposed to HPV, lacking therapeutic effects against pre-existing infections. Multiepitope vaccines, using an immunoinformatic approach, are promising against tumors and viral infections because of their high specificity, safety, and stability, as well as the cheap cost of development. Methods: This study employed computer-based immunoinformatic analysis to design therapeutic multiepitope vaccines against cervical cancer using oncoproteins E6 and E7 of HPV 16 and 18. Several immunoinformatic tools were applied to analyze potential vaccine constructs capable of stimulating immune responses against both oncoproteins. Results: The constructed vaccine exhibited antigenic, immunogenic, nonallergenic, nontoxic, stable, and soluble characteristics. Additionally, it effectively interacted with TLR2 and TLR4, showing high binding capacity. Computational analysis indicated the vaccine could induce immune responses through the elevation of cytokine levels after the third injection, antibody production, activation of memory B and T cells, and promotion of increased dendritic cell counts. Conclusion: The novel multiepitope vaccine based on E6 and E7 presented as a promising candidate for combating HPV infections and associated cervical cancer. Further in vitro and in vivo studies were essential to validate the efficacy and safety of the vaccine. [ABSTRACT FROM AUTHOR]

Hepatitis A and B are two crucial viral infections that still dramatically affect public health worldwide. Hepatitis A Virus (HAV) is the main cause of acute hepatitis, whereas Hepatitis B Virus (HBV) leads to the chronic form of the disease, possibly cirrhosis or liver failure. Therefore, vaccination has always been considered the most effective preventive method against pathogens. At this moment, we aimed at the immunoinformatic analysis of HAV-Viral Protein 1 (VP1) as the major capsid protein to come up with the most conserved immunogenic truncated protein to be fused by HBV surface antigen (HBs Ag) to achieve a bivalent vaccine against HAV and HBV using an AAY linker. Various computational approaches were employed to predict highly conserved regions and the most immunogenic B-cell and T-cell epitopes of HAV-VP1 capsid protein in both humans and BALB/c. Moreover, the predicted fusion protein was analyzed regarding primary and secondary structures and also homology validation. Afterward, the three-dimensional structure of vaccine constructs docked with various toll-like receptors (TLR) 2, 4 and 7. According to the bioinformatics tools, the region of 99–259 amino acids of VP1 was selected with high immunogenicity and conserved epitopes. T-cell epitope prediction showed that this region contains 32 antigenic peptides for Human leukocyte antigen (HLA) class I and 20 antigenic peptides in terms of HLA class II which are almost fully conserved in the Iranian population. The vaccine design includes 5 linear and 4 conformational B-cell lymphocyte (BCL) epitopes to induce humoral immune responses. The designed VP1-AAY-HBsAg fusion protein has the potency to be constructed and expressed to achieve a bivalent vaccine candidate, especially in the Iranian population. These findings led us to claim that the designed vaccine candidate provides potential pathways for creating an exploratory vaccine against Hepatitis A and Hepatitis B Viruses with high confidence for the identified strains. [ABSTRACT FROM AUTHOR]

Abstract Acinetobacter baumannii is a gram-negative bacillus prevalent in nature, capable of thriving under various environmental conditions. As an opportunistic pathogen, it frequently causes nosocomial infections such as urinary tract infections, bacteremia, and pneumonia, contributing to increased morbidity and mortality in clinical settings. Consequently, developing novel vaccines against Acinetobacter baumannii is of utmost importance. In our study, we identified 10 highly conserved antigenic proteins from the NCBI and UniProt databases for epitope mapping. We subsequently screened and selected 8 CTL, HTL, and LBL epitopes, integrating them into three distinct vaccines constructed with adjuvants. Following comprehensive evaluations of immunological and physicochemical parameters, we conducted molecular docking and molecular dynamics simulations to assess the efficacy and stability of these vaccines. Our findings indicate that all three multi-epitope mRNA vaccines designed against Acinetobacter baumannii are promising; however, further animal studies are required to confirm their reliability and effectiveness.

Background: Poultry industries play an important role in the human food supply. Newcastle disease virus (NDV), Infectious bronchitis virus (IBV), and Avian influenza virus (AIV) can cause epizootic outbreaks in poultry industries and lead to extensive economic losses. Furthermore, these viruses can also infect wild birds, and avian influenza virus is a serious threat to humans. Here, a multiepitope vaccine has been designed to induce an immune response against IBV, NDV, and AIV using extensive bioinformatics tools. Methods: To do so, the antigenic proteins, including the hemagglutinin of H5 and H7 subtypes of AIV, nucleocapsid and spike proteins of IBV, and fusion and hemagglutinin-neuraminidase proteins of NDV, have been studied to find immunodominant epitopes with MHC-I/MHC-II binding potential. Four antigenic and non-allergenic epitopes from each antigenic protein were connected to avian beta-defensin 1 as an adjuvant to construct the multiepitope vaccine. To investigate the potential of vaccine-induced activation of toll-like receptors (TLR-2, 5), the tertiary structure of the vaccine was modeled and docked to TLR-2/5 proteins. Results: Evaluation of the physicochemical properties of the vaccine construct has demonstrated the stability and solubility of the vaccine upon overexpression. The vaccine construct demonstrated antigenicity and was specified as a non-allergenic protein. The vaccine can induce significant cellular and humoral immune responses, and TLR proteins can recognize the vaccine in its three-dimensional form. Conclusion: Overall, the multiepitope vaccine designed in the present study against IBV, NDV, and AIV shows significant immunological potential that should be further investigated in wet laboratory experiments.

The increasing and ongoing issue of antibiotic resistance in bacteria is of huge concern globally, mainly to healthcare facilities. It is now crucial to develop a vaccine for therapeutic and preventive purposes against the bacterial species causing hospital-based infections. Among the many antibiotic- resistant bacterial pathogens, the Enterobacter cloacae complex (ECC) including six species, E. Colcae, E. absuriae, E. kobie, E. hormaechei, E. ludwigii, and E. nimipressuralis, are dangerous to public health and may worsen the situation. Vaccination plays a vital role in the prevention of infections and infectious diseases. This research highlighted the construction and design of a multi-epitope vaccine for the E. cloacae complex by retrieving their complete sequenced proteome. The retrieved proteome was assessed to opt for potential vaccine candidates using immunoinformatic tools. Both B and T-cell epitopes were predicted in order to create both humoral and cellular immunity and further scrutinized for antigenicity, allergenicity, water solubility, and toxicity analysis. The final potential epitopes were subjected to population coverage analysis. Major histocompatibility complex (MHC) class combined, and MHC Class I and II world population coverage was obtained as 99.74%, and 98.55% respectively while a combined 81.81% was covered. A multi-epitope peptide-based vaccine construct consisting of the adjuvant, epitopes, and linkers was subjected to the ProtParam tool to calculate its physiochemical properties. The total amino acids were 236, the molecular weight was 27.64kd, and the vaccine construct was stable with an instability index of 27.01. The Grand Average of Hydropathy (GRAVY) (hydrophilicity) value obtained was -0.659, being more negative and depicting the hydrophilic character. It was non-allergen antigenic with an antigenicity of 0.8913. The vaccine construct was further validated for binding efficacy with immune cell receptors MHC-I, MHC-II, and Toll-like receptor (TLR)-4. The molecular docking results depict that the designed vaccine has good binding potency with immune receptors crucial for antigen presentation and processing. Among the Vaccine-MHC-I, Vaccine-MHC-II, and Vaccine-TLR- 4 complexes, the best-docked poses were identified based on their lowest binding energy scores of -886.8, -995.6, and -883.6, respectively. Overall, we observed that the designed vaccine construct can evoke a proper immune response and the construct could help experimental researchers in the formulation of a vaccine against the targeted pathogens. [ABSTRACT FROM AUTHOR]

Acinetobacter baumannii is a gram-negative bacillus prevalent in nature, capable of thriving under various environmental conditions. As an opportunistic pathogen, it frequently causes nosocomial infections such as urinary tract infections, bacteremia, and pneumonia, contributing to increased morbidity and mortality in clinical settings. Consequently, developing novel vaccines against Acinetobacter baumannii is of utmost importance. In our study, we identified 10 highly conserved antigenic proteins from the NCBI and UniProt databases for epitope mapping. We subsequently screened and selected 8 CTL, HTL, and LBL epitopes, integrating them into three distinct vaccines constructed with adjuvants. Following comprehensive evaluations of immunological and physicochemical parameters, we conducted molecular docking and molecular dynamics simulations to assess the efficacy and stability of these vaccines. Our findings indicate that all three multi-epitope mRNA vaccines designed against Acinetobacter baumannii are promising; however, further animal studies are required to confirm their reliability and effectiveness. [ABSTRACT FROM AUTHOR]

Epstein–Barr Virus (EBV), structurally similar to other herpes viruses, possess significant global health challenges as it causes infectious mononucleosis and is also associated with various cancers. Due to this widespread impact, an effective messenger RNA (mRNA) vaccine is paramount to help curb its spread, further underscoring the need for its development. This study, following an immunoinformatic approach, aimed to design a comprehensive mRNA vaccine against the EBV by selecting antigenic proteins, predicting Linear B-cell epitopes, cytotoxic T-cell lymphocyte (CTL) and helper T-cell lymphocyte (HTL) epitopes, and assessing vaccine characteristics. Seventy-nine EBV isolates from diverse geographical regions were examined. Additionally, the vaccine construct's physicochemical properties, transmembrane domains, solubility, and secondary structures were analysed. Molecular docking was conducted with Toll-Like Receptor 5 (TLR-5). Population coverage was assessed for selected major histocompatibility complex (MHC) alleles, and immune response was simulated. The result of this study highlighted a vaccine construct with high antigenicity, non-toxicity, and non-allergenicity and possessed favourable physicochemical properties. The vaccine's 3D structure is native-like and strongly binds with TLR-5, indicating a solid affinity with TLR-5. The selected MHC alleles provided broad universal population coverage of 89.1%, and the immune simulations suggested a robust and wide-ranging immunogenic response, activating critical immune cells, antibodies, and cytokines. These findings provide a solid foundation for further development and testing of the EBV candidate vaccine, offering potential solutions for combating EBV infections. [ABSTRACT FROM AUTHOR]

Introduction: This immunoinformatic study identified potential epitopes from the envelopment polyprotein (Gn/Gc) of Rift Valley fever virus (RVFV), a pathogenic virus causing severe fever in humans and livestock. Effective vaccination is crucial for controlling RVFV outbreaks. The identification of suitable epitopes is crucial for the development of safe and effective vaccines. Methodology: Protein sequences were obtained from the UniProt database, and evaluated through VaxiJen v2.0 to predict the B and T-cell epitopes within the RVFV glycoprotein. Gn/Gc protein sequences were analyzed with bioinformatics tools and algorithms. The predicted T- cell and B-cell epitopes were evaluated for antigenicity, allergenicity, and toxicity by the VaxiJen v2.0 system, AllerTop v2.0, and ToxinPred server, respectively. Results: We employed computational methods to screen the RVFV envelopment polyprotein encompassing N-terminal and C-terminal glycoprotein segments, to discover antigenic T- and B-cell epitopes. Our analysis unveiled multiple potential epitopes within the RVFV glycoprotein, specifically within the Gn/Gc protein sequences. Subsequently, we selected eleven cytotoxic T-lymphocytes (CTL) and four helper T-lymphocytes (HTL) for population coverage analysis, which collectively extended to cover 97.04% of the world's population, representing diverse ethnicities and regions. Notably, the CTL epitope VQADLTLMF exhibited binding affinity to numerous human leukocyte antigen (HLA) alleles. The identification of glycoprotein (Gn/Gc) epitopes through this immunoinformatic study bears significant implications for advancing the development of an effective RVFV vaccine. Conclusions: These findings provide valuable insights into the immunological aspects of the disease and may contribute towards the development of broad-spectrum antiviral therapies targeting other RNA viruses with similar polymerase enzymes. [ABSTRACT FROM AUTHOR]

Despite advancements in vaccinology, there is currently no effective anti-HIV vaccine. One strategy under investigation is based on the identification of epitopes recognized by broadly neutralizing antibodies to include in vaccine preparation. Taking into account the benefits of anti-idiotype molecules and the diverse biological attributes of different antibody formats, our aim was to identify the most immunogenic antibody format. This format could serve as a foundational element for the development of an oligo-polyclonal anti-idiotype vaccine against HIV-1. For our investigation, we anchored our study on an established b12 anti-idiotype, referred to as P1, and proposed four distinct formats: two single chains and two minibodies, both in two different orientations. For a deeper characterization of these molecules, we used immunoinformatic tools and tested them on rabbits. Our studies have revealed that a particular minibody conformation, MbVHVL, emerges as the most promising candidate. It demonstrates a significant binding affinity with b12 and elicits a humoral anti-HIV-1 response in rabbits similar to the Fab format. This study marks the first instance where the minibody format has been shown to provoke a humoral response against a pathogen. Furthermore, this format presents biological advantages over the Fab format, including bivalency and being encoded by a monocistronic gene, making it better suited for the development of RNA-based vaccines. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus (S. aureus) is a bacterium capable of inducing a range of human infections, varying from mild skin infections to more serious diseases like pneumonia and bloodstream infections. Different studies have focused on designing epitope vaccines against S. aureus. Nevertheless, the primary drawback of epitope vaccines is their reduced ability to stimulate an immune response. Recently, self-assembled peptide nanoparticle (SAPN) vaccines have emerged as one of the latest innovations in vaccine design. This arises from their ability to have multiple functions, act as self-adjuvants, exhibit biocompatibility, and closely resemble the size of the pathogen. Therefore, this investigation aimed to design a new SAPN vaccine to combat S. aureus infection effectively through computational approaches. Antigenic proteins ClfA, IsdB, and Hla were selected to design the SAPN vaccine. Cytotoxic T lymphocyte (CTL) epitopes from ClfA and IsdB, helper T lymphocytes (HTL) from Hla, and linear B-cell epitopes from ClfA and IsdB were chosen. Subsequently, the chosen epitopes and the oligomeric domains of the pentamer and trimmer were employed as a self-assembled framework fused with suitable linkers. Physicochemical properties, solubility, antigenicity, and allergenic potential of the designed vaccine were examined. The obtained results indicate the SAPN vaccine was antigenic, stable, and non-allergenic. Afterward, the 3D structure of the construct was initially forecasted and subsequently refined and validated to reach the best 3D model. Finally, molecular docking and molecular dynamics (MD) simulation were conducted between the SAPN vaccine and toll-like receptor 4 (TLR4). The results of molecular dynamic simulation studies demonstrated the stable interactions between the construct and TLR4. In conclusion, we devised an in silico SAPN vaccine, which is anticipated to induce robust cellular and humoral immune responses against S. aureus, making it a noteworthy prospect for subsequent in vitro and in vivo studies related to immunology. [ABSTRACT FROM AUTHOR]

Abstract Yellow fever outbreaks are prevalent, particularly in endemic regions. Given the lack of an established treatment for this disease, significant attention has been directed toward managing this arbovirus. In response, we developed a multiepitope vaccine designed to elicit an immune response, utilizing advanced immunoinformatic and molecular modeling techniques. To achieve this, we predicted B- and T-cell epitopes using the sequences from all structural (E, prM, and C) and nonstructural proteins of 196 YFV strains. Through comprehensive analysis, we identified 10 cytotoxic T-lymphocyte (CTL) and 5T-helper (Th) epitopes that exhibited overlap with B-lymphocyte epitopes. These epitopes were further evaluated for their affinity to a wide range of human leukocyte antigen system alleles and were rigorously tested for antigenicity, immunogenicity, allergenicity, toxicity, and conservation. These epitopes were linked to an adjuvant ( $$\beta$$ β -defensin) and to each other using ligands, resulting in a vaccine sequence with appropriate physicochemical properties. The 3D structure of this sequence was created, improved, and quality checked; then it was anchored to the Toll-like receptor. Molecular Dynamics and Quantum Mechanics/Molecular Mechanics simulations were employed to enhance the accuracy of docking calculations, with the QM portion of the simulations carried out utilizing the density functional theory formalism. Moreover, the inoculation model was able to provide an optimal codon sequence that was inserted into the pET-28a( +) vector for in silico cloning and could even stimulate highly relevant humoral and cellular immunological responses. Overall, these results suggest that the designed multi-epitope vaccine can serve as prophylaxis against the yellow fever virus.

Yellow fever outbreaks are prevalent, particularly in endemic regions. Given the lack of an established treatment for this disease, significant attention has been directed toward managing this arbovirus. In response, we developed a multiepitope vaccine designed to elicit an immune response, utilizing advanced immunoinformatic and molecular modeling techniques. To achieve this, we predicted B- and T-cell epitopes using the sequences from all structural (E, prM, and C) and nonstructural proteins of 196 YFV strains. Through comprehensive analysis, we identified 10 cytotoxic T-lymphocyte (CTL) and 5T-helper (Th) epitopes that exhibited overlap with B-lymphocyte epitopes. These epitopes were further evaluated for their affinity to a wide range of human leukocyte antigen system alleles and were rigorously tested for antigenicity, immunogenicity, allergenicity, toxicity, and conservation. These epitopes were linked to an adjuvant (β -defensin) and to each other using ligands, resulting in a vaccine sequence with appropriate physicochemical properties. The 3D structure of this sequence was created, improved, and quality checked; then it was anchored to the Toll-like receptor. Molecular Dynamics and Quantum Mechanics/Molecular Mechanics simulations were employed to enhance the accuracy of docking calculations, with the QM portion of the simulations carried out utilizing the density functional theory formalism. Moreover, the inoculation model was able to provide an optimal codon sequence that was inserted into the pET-28a(+) vector for in silico cloning and could even stimulate highly relevant humoral and cellular immunological responses. Overall, these results suggest that the designed multi-epitope vaccine can serve as prophylaxis against the yellow fever virus. [ABSTRACT FROM AUTHOR]

Diagnosing canine visceral leishmaniasis (CVL) in Brazil faces challenges due to the limitations regarding the sensitivity and specificity of the current diagnostic protocol. Therefore, it is urgent to map new antigens or enhance the existing ones for future diagnostic techniques. Immunoinformatic tools are promising in the identification of new potential epitopes or antigen candidates. In this study, we evaluated peptides selected by epitope prediction for CVL serodiagnosis in ELISA assays. Ten B-cell epitopes were immunogenic in silico, but two peptides (peptides No. 45 and No. 48) showed the best performance in vitro. The selected peptides, both individually and in combination, were highly diagnostically accurate, with sensitivities ranging from 86.4% to 100% and with a specificity of approximately 90%. We observed that the combination of peptides showed better performance when compared to peptide alone, by detecting all asymptomatic dogs, showing lower cross-reactivity in sera from dogs with other canine infections, and did not detect vaccinated animals. Moreover, our data indicate the potential use of immunoinformatic tools associated with ELISA assays for the selection and evaluation of potential new targets, such as peptides, applied to the diagnosis of CVL. [ABSTRACT FROM AUTHOR]

The increasing and ongoing issue of antibiotic resistance in bacteria is of huge concern globally, mainly to healthcare facilities. It is now crucial to develop a vaccine for therapeutic and preventive purposes against the bacterial species causing hospital-based infections. Among the many antibiotic- resistant bacterial pathogens, the Enterobacter cloacae complex (ECC) including six species, E. Colcae, E. absuriae, E. kobie, E. hormaechei, E. ludwigii, and E. nimipressuralis, are dangerous to public health and may worsen the situation. Vaccination plays a vital role in the prevention of infections and infectious diseases. This research highlighted the construction and design of a multi-epitope vaccine for the E. cloacae complex by retrieving their complete sequenced proteome. The retrieved proteome was assessed to opt for potential vaccine candidates using immunoinformatic tools. Both B and T-cell epitopes were predicted in order to create both humoral and cellular immunity and further scrutinized for antigenicity, allergenicity, water solubility, and toxicity analysis. The final potential epitopes were subjected to population coverage analysis. Major histocompatibility complex (MHC) class combined, and MHC Class I and II world population coverage was obtained as 99.74%, and 98.55% respectively while a combined 81.81% was covered. A multi-epitope peptide-based vaccine construct consisting of the adjuvant, epitopes, and linkers was subjected to the ProtParam tool to calculate its physiochemical properties. The total amino acids were 236, the molecular weight was 27.64kd, and the vaccine construct was stable with an instability index of 27.01. The Grand Average of Hydropathy (GRAVY) (hydrophilicity) value obtained was -0.659, being more negative and depicting the hydrophilic character. It was non-allergen antigenic with an antigenicity of 0.8913. The vaccine construct was further validated for binding efficacy with immune cell receptors MHC-I, MHC-II, and Toll-like receptor (TLR)-4. The molecular docking results depict that the designed vaccine has good binding potency with immune receptors crucial for antigen presentation and processing. Among the Vaccine-MHC-I, Vaccine-MHC-II, and Vaccine-TLR-4 complexes, the best-docked poses were identified based on their lowest binding energy scores of -886.8, -995.6, and -883.6, respectively. Overall, we observed that the designed vaccine construct can evoke a proper immune response and the construct could help experimental researchers in the formulation of a vaccine against the targeted pathogens.

Omsk Hemorrhagic Fever Virus (OHFV) is an RNA virus with a single-stranded, positive-sense genome. It is classified under the Flaviviridae family. The genome of this virus is 98% similar to the Alkhurma hemorrhagic fever virus (AHFV), which belongs to the same family. Cases of the virus have been reported in various regions of Saudi Arabia. Both OHFV and AHFV have similarities in pathogenic polyprotein targets. No effective and licensed vaccines are available to manage OHFV infections. Therefore, an effective and safe vaccine is required that can activate protective immunity against OHFV. The current study aimed to design a multiepitope subunit vaccine against the OHFV utilizing several immunoinformatic tools. The polyprotein of OHFV was selected and potent antigenic, non-allergenic, and nontoxic cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes were chosen. After screening, eight (8) CTL, five (5) HTL, and six (6) B cell epitopes were joined with each other using different linkers. Adjuvant human beta defensin-2 was also linked to the epitopes to increase vaccine antigenic and immunogenic efficiency. The designed vaccine was docked with Toll-like receptor 4 (TLR4) as it activates and induces primary and secondary immune responses against OHFV. Codon optimization was carried out, which resulted in a CAI value of 0.99 and 53.4% GC contents. In addition, the construct was blindly docked to the TLR4 immune receptor and subjected to conformational dynamics simulation analysis to interpret the intricate affinity and comprehend the time-dependent behavior. Moreover, it was predicted that immune responses to the developed vaccine construct reported formation of strong humoral and cellular immune cells. Therefore, the proposed vaccine may be considered in experimental assays to combat OHFV infections. Laboratory experiments for the above predictions are essential in order to evaluate the effectiveness, safety, and protective properties of the subject in question.

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

Histoplasmosis is a widespread systemic disease caused by Histoplasma capsulatum, prevalent in the Americas. Despite its significant morbidity and mortality rates, no vaccines are currently available. Previously, five vaccine targets and specific epitopes for H. capsulatum were identified. Immunoinformatics has emerged as a novel approach for determining the main immunogenic components of antigens through in silico methods. Therefore, we predicted the main helper and cytotoxic T lymphocytes and B-cell epitopes for these targets to create a potential multi-epitope vaccine known as HistoVAC-TSFM. A total of 38 epitopes were found: 23 common to CTL and B-cell responses, 11 linked to HTL and B cells, and 4 previously validated epitopes associated with the B subunit of cholera toxin, a potent adjuvant. In silico evaluations confirmed the stability, non-toxicity, non-allergenicity, and non-homology of these vaccines with the host. Notably, the vaccine exhibited the potential to trigger both innate and adaptive immune responses, likely involving the TLR4 pathway, as supported by 3D modeling and molecular docking. The designed HistoVAC-TSFM appears promising against Histoplasma, with the ability to induce important cytokines, such as IFN-γ, TNF-α, IL17, and IL6. Future studies could be carried out to test the vaccine's efficacy in in vivo models. [ABSTRACT FROM AUTHOR]

The discovery of the first infectious variant in Wuhan, China, in December 2019, has posed concerns over global health due to the spread of COVID-19 and subsequent variants. While the majority of patients experience flu-like symptoms such as cold and fever, a small percentage, particularly those with compromised immune systems, progress from mild illness to fatality. COVID-19 is caused by a RNA virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our approach involved utilizing immunoinformatic to identify vaccine candidates with multiple epitopes and ligand-binding regions in reported SARS-CoV-2 variants. Through analysis of the spike glycoprotein, we identified dominant epitopes for T-cells and B-cells, resulting in a vaccine construct containing two helper T-cell epitopes, six cytotoxic T-cell epitopes, and four linear B-cell epitopes. Prior to conjugation with adjuvants and linkers, all epitopes were evaluated for antigenicity, toxicity, and allergenicity. Additionally, we assessed the vaccine Toll-Like Receptors complex (2, 3, and 4). The vaccine construct demonstrated antigenicity, non-toxicity, and non-allergenicity, thereby enabling the host to generate antibodies with favorable physicochemical characteristics. Furthermore, the 3D structure of the B-cell construct exhibited a ProSA-web z-score plot with a value of -1.71, indicating the reliability of the designed structure. The Ramachandran plot analysis revealed that 99.6% of the amino acid residues in the vaccine subunit were located in the high favored observation region, further establishing its strong candidacy as a vaccination option. [ABSTRACT FROM AUTHOR]

The Monkeypox virus, an Orthopoxvirus with zoonotic origins, has been responsible for a growing number of human infections reminiscent of smallpox since May 2022, as reported by the World Health Organization. As of now, there are no established medical treatments for managing Monkeypox infections. In this study, we used machine learning to select conserved epitopes. Proteins were determined using Reverse Vaccinology and Gene Ontology subcellular localization, and their epitopes were predicted. NextClade was used to calculate the number of mutations in each amino acid position using 2433 Monkeypox sequences. The Unsupervised Nearest Neighbor machine learning algorithm and ideal matrix [0 0] were used to calculate the conservancy score of epitopes. Six proteins were determined for epitope prediction. Finally, 47 MHC-I epitopes, 5 MHC-II epitopes, and 10 Linear B cell epitopes were discovered. Our method can select epitopes for vaccine design to prevent viruses with accelerated evolution and high mutation rate.

Introduction: The Bacillus Calmette-Guérin (BCG) vaccine, currently used against tuberculosis (TB), exhibits inconsistent efficacy, highlighting the need for more potent TB vaccines. Materials and methods: In this study, we employed reverse vaccinology techniques to develop a promising multi-epitope vaccine (MEV) candidate, called PP13138R, for TB prevention. PP13138R comprises 34 epitopes, including B-cell, cytotoxic T lymphocyte, and helper T lymphocyte epitopes. Using bioinformatics and immunoinformatics tools, we assessed the physicochemical properties, structural features, and immunological characteristics of PP13138R. Results: The vaccine candidate demonstrated excellent antigenicity, immunogenicity, and solubility without any signs of toxicity or sensitization. In silico analyses revealed that PP13138R interacts strongly with Toll-like receptor 2 and 4, stimulating innate and adaptive immune cells to produce abundant antigenspecific antibodies and cytokines. In vitro experiments further supported the efficacy of PP13138R by significantly increasing the population of IFN-γ+ T lymphocytes and the production of IFN-γ, TNF-α, IL-6, and IL-10 cytokines in active tuberculosis patients, latent tuberculosis infection individuals, and healthy controls, revealing the immunological characteristics and compare the immune responses elicited by the PP13138R vaccine across different stages of Mycobacterium tuberculosis infection. Conclusion: These findings highlight the potential of PP13138R as a promising MEV candidate, characterized by favorable antigenicity, immunogenicity, and solubility, without any toxicity or sensitization. [ABSTRACT FROM AUTHOR]

Antigenic changes in surface proteins of the influenza virus may cause the emergence of new variants that necessitate the reformulation of influenza vaccines every year. Universal influenza vaccine that relies on conserved regions can potentially be effective against all strains regardless of any antigenic changes and as a result, it can bring enormous public health impact and economic benefit worldwide. Here, a conserved peptide (HA288–107) on the stalk domain of hemagglutinin glycoprotein is identified among highly pathogenic influenza viruses. Five top-ranked B-cell and twelve T-cell epitopes were recognized by epitope mapping approaches and the corresponding Human Leukocyte Antigen alleles to T-cell epitopes showed high population coverage (>99%) worldwide. Moreover, molecular docking analysis indicated that VLMENERTL and WTYNAELLV epitopes have high binding affinity to the antigen-binding groove of the HLA-A*02:01 and HLA-A*68:02 molecules, respectively. Theoretical physicochemical properties of the peptide were assessed to ensure its thermostability and hydrophilicity. The results suggest that the HA288–107 peptide can be a promising antigen for universal influenza vaccine design. However, in vitro and in vivo analyses are needed to support and evaluate the effectiveness of the peptide as an immunogen for vaccine development. [ABSTRACT FROM AUTHOR]

Nipah virus (NiV) is an RNA virus, a pathogenic paramyxovirus that causes nonlethal respiratory illness in pigs. It was originally reported in Malaysia in 1998. NiV is considered a potential outbreak threat because it is zoonotic. However, no vaccines or antiviral drugs have been found against NiV. Therefore, the main objective is to develop effective vaccines by characterizing the fusion protein of NiV. We used a reference sequence retrieved from the National Center for Biotechnology Information (NCBI), then 3D modeled it to obtain the conserved region of the fusion protein. The interaction between the conserved region and B-cell receptors has been evaluated through a molecular docking approach. The B-cell epitope was identified using the Immune Epitope Database (IEDB) web server. As a result, we recommend Pep_D FANCISVTCQCQ as an epitope-based peptide vaccine candidate against Nipah virus. Pep D is highly immunogenic and does not cause autoimmune reactions. Pep D has the lowest binding energy for BCR molecular complexes, which can activate the transduction signal and direct B-cell immune response. However, further studies are required for confirmation (in vitro and in vivo). [ABSTRACT FROM AUTHOR]

Despite advancements in vaccinology, there is currently no effective anti-HIV vaccine. One strategy under investigation is based on the identification of epitopes recognized by broadly neutralizing antibodies to include in vaccine preparation. Taking into account the benefits of anti-idiotype molecules and the diverse biological attributes of different antibody formats, our aim was to identify the most immunogenic antibody format. This format could serve as a foundational element for the development of an oligo-polyclonal anti-idiotype vaccine against HIV-1. For our investigation, we anchored our study on an established b12 anti-idiotype, referred to as P1, and proposed four distinct formats: two single chains and two minibodies, both in two different orientations. For a deeper characterization of these molecules, we used immunoinformatic tools and tested them on rabbits. Our studies have revealed that a particular minibody conformation, MbVHVL, emerges as the most promising candidate. It demonstrates a significant binding affinity with b12 and elicits a humoral anti-HIV-1 response in rabbits similar to the Fab format. This study marks the first instance where the minibody format has been shown to provoke a humoral response against a pathogen. Furthermore, this format presents biological advantages over the Fab format, including bivalency and being encoded by a monocistronic gene, making it better suited for the development of RNA-based vaccines.

Diagnosing canine visceral leishmaniasis (CVL) in Brazil faces challenges due to the limitations regarding the sensitivity and specificity of the current diagnostic protocol. Therefore, it is urgent to map new antigens or enhance the existing ones for future diagnostic techniques. Immunoinformatic tools are promising in the identification of new potential epitopes or antigen candidates. In this study, we evaluated peptides selected by epitope prediction for CVL serodiagnosis in ELISA assays. Ten B-cell epitopes were immunogenic in silico, but two peptides (peptides No. 45 and No. 48) showed the best performance in vitro. The selected peptides, both individually and in combination, were highly diagnostically accurate, with sensitivities ranging from 86.4% to 100% and with a specificity of approximately 90%. We observed that the combination of peptides showed better performance when compared to peptide alone, by detecting all asymptomatic dogs, showing lower cross-reactivity in sera from dogs with other canine infections, and did not detect vaccinated animals. Moreover, our data indicate the potential use of immunoinformatic tools associated with ELISA assays for the selection and evaluation of potential new targets, such as peptides, applied to the diagnosis of CVL.

Introduction: Identification of tumor specific neoantigen (TSN) immunogenicity is crucial to develop peptide/mRNA based anti-tumoral vaccines and/or adoptive T-cell immunotherapies; thus, accurate in-silico classification/prioritization proves critical for cost-effective clinical applications. Several methods were proposed as TSNs immunogenicity predictors; however, comprehensive performance comparison is still lacking due to the absence of well documented and adequate TSN databases. Methods: Here, by developing a new curated database having 199 TSNs with experimentally-validated MHC-I presentation and positive/negative immune response (ITSNdb), sixteen metrics were evaluated as immunogenicity predictors. In addition, by using a dataset emulating patient derived TSNs and immunotherapy cohorts containing predicted TSNs for tumor neoantigen burden (TNB) with outcome association, the metrics were evaluated as TSNs prioritizers and as immunotherapy response biomarkers. Results: Our results show high performance variability among methods, highlighting the need for substantial improvement. Deep learning predictors were top ranked on ITSNdb but show discrepancy on validation databases. In overall, current predicted TNB did not outperform existing biomarkers. Conclusion: Recommendations for their clinical application and the ITSNdb are presented to promote development and comparison of computational TSNs immunogenicity predictors. [ABSTRACT FROM AUTHOR]

Streptococcus agalactiae (Group B Streptococcus, GBS) is a multi-host pathogen, even causing life-threatening infections in newborns. Vaccination with GBS crossed serotypes vaccine is one of the best options for long-term infection control. Here we built a comprehensive in silico epitope-prediction workflow pipeline to design a multivalent multiepitope-based subunit vaccine containing 11 epitopes against Streptococcus agalactiae (MVSA). All epitopes in MVSA came from the proteins which were antigenic-confirmed, virulent-associated, surface-exposed and conserved in ten GBS serotypes. The in-silico analysis showed MVSA had potential to evoke strong immune responses and enable worldwide population coverage. To validate MVSA protection efficacy against GBS infection, immune protection experiments were performed in a mouse model. Importantly, MVSA induced a high titre of antibodies, significant proliferation of mice splenocytes and elicited strong protection against lethal-dose challenge with a survival rate of 100% in mice after three vaccinations. Meanwhile, the polyclonal antibody against MVSA did not only inhibit for growth of GBS from six crucial serotypes in vitro, but also protect 100% naive mice from GBS lethal challenge. These active and passive immunity assay results suggested that MVSA could therefore be an efficacious multi-epitope vaccine against GBS infection.

The Nucleocapsid (N) protein is highlighted as the main target for COVID-19 diagnosis by antigen detection due to its abundance in circulation early during infection. However, the effects of the described mutations in the N protein epitopes and the efficacy of antigen testing across SARS-CoV-2 variants remain controversial and poorly understood. Here, we used immunoinformatics to identify five epitopes in the SARS-CoV-2 N protein (N(34–48), N(89–104), N(185–197), N(277–287), and N(378–390)) and validate their reactivity against samples from COVID-19 convalescent patients. All identified epitopes are fully conserved in the main SARS-CoV-2 variants and highly conserved with SARS-CoV. Moreover, the epitopes N(185–197) and N(277–287) are highly conserved with MERS-CoV, while the epitopes N(34–48), N(89–104), N(277–287), and N(378–390) are lowly conserved with common cold coronaviruses (229E, NL63, OC43, HKU1). These data are in accordance with the observed conservation of amino acids recognized by the antibodies 7R98, 7N0R, and 7CR5, which are conserved in the SARS-CoV-2 variants, SARS-CoV and MERS-CoV but lowly conserved in common cold coronaviruses. Therefore, we support the antigen tests as a scalable solution for the population-level diagnosis of SARS-CoV-2, but we highlight the need to verify the cross-reactivity of these tests against the common cold coronaviruses. [ABSTRACT FROM AUTHOR]

Hepatitis E Virus (HEV) is a major cause of acute and chronic hepatitis. The severity of HEV infection increases manyfold in pregnant women and immunocompromised patients. Despite the extensive research on HEV in the last few decades, there is no widely available vaccine yet. In the current study, immunoinformatic analyses were applied to predict a multi-epitope vaccine candidate against HEV. From the ORF2 region, 41 conserved and immunogenic epitopes were prioritized. These epitopes were further analyzed for their probable antigenic and non-allergenic combinations with several linkers. The stability of the vaccine construct was confirmed by molecular dynamic simulations. The vaccine construct is potentially antigenic and docking analysis revealed stable interactions with TLR3. These results suggest that the proposed vaccine can efficiently stimulate both cellular and humoral immune responses. However, further studies are needed to determine the immunogenicity of the vaccine construct. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus is a human bacterial pathogen that can cause a wide range of symptoms. As virulent and multi-drug-resistant strains of S. aureus have evolved, invasive S. aureus infections in hospitals and the community have become one of the leading causes of mortality and morbidity. The development of novel techniques is therefore necessary to overcome this bacterial infection. Vaccines are an appropriate alternative in this context to control infections. In this study, the collagen-binding protein (CnBP) from S. aureus was chosen as the target antigen, and a series of computational methods were used to find epitopes that may be used in vaccine development in a systematic way. The epitopes were passed through a filtering pipeline that included antigenicity, toxicity, allergenicity, and cytokine inducibility testing, with the objective of identifying epitopes capable of eliciting both T and B cell-mediated immune responses. To improve vaccine immunogenicity, the final epitopes and phenol-soluble modulin α4 adjuvant were fused together using appropriate linkers; as a consequence, a multiepitope vaccine was developed. The chosen T cell epitope ensemble is expected to cover 99.14% of the global human population. Furthermore, docking and dynamics simulations were used to examine the vaccine's interaction with the Toll-like receptor 2 (TLR2), revealing great affinity, consistency, and stability between the two. Overall, the data indicate that the vaccine candidate may be extremely successful, and it will need to be evaluated in experimental systems to confirm its efficiency. [ABSTRACT FROM AUTHOR]

IntroductionIdentification of tumor specific neoantigen (TSN) immunogenicity is crucial to develop peptide/mRNA based anti-tumoral vaccines and/or adoptive T-cell immunotherapies; thus, accurate in-silico classification/prioritization proves critical for cost-effective clinical applications. Several methods were proposed as TSNs immunogenicity predictors; however, comprehensive performance comparison is still lacking due to the absence of well documented and adequate TSN databases.MethodsHere, by developing a new curated database having 199 TSNs with experimentally-validated MHC-I presentation and positive/negative immune response (ITSNdb), sixteen metrics were evaluated as immunogenicity predictors. In addition, by using a dataset emulating patient derived TSNs and immunotherapy cohorts containing predicted TSNs for tumor neoantigen burden (TNB) with outcome association, the metrics were evaluated as TSNs prioritizers and as immunotherapy response biomarkers.ResultsOur results show high performance variability among methods, highlighting the need for substantial improvement. Deep learning predictors were top ranked on ITSNdb but show discrepancy on validation databases. In overall, current predicted TNB did not outperform existing biomarkers.ConclusionRecommendations for their clinical application and the ITSNdb are presented to promote development and comparison of computational TSNs immunogenicity predictors.

IntroductionBovine viral diarrhea virus (BVDV) significantly impacts the bovine industries, both dairy and beef sectors. BVDV can infect various domestic and wild animals, most notably cattle. The dynamic variations among BVDV serotypes due to the continuous genetic diversity, especially in BVDV1 (BVDV1), reduce the effectiveness of the currently available vaccines and reduce the specificity/sensitivity of the diagnostic assays. The development of novel, safe, and effective vaccines against BVDV requires deep knowledge of the antigenicity and virulence of the virus. Previous studies on the antigenicity and the virulence of BVDV serotypes have been mainly focused on one or a few BVDV proteins. While however, little is known about the orchestration of all BVDV in the context of viral virulence and immunogenicity. The main aim of the current study was to do a comparative computational evaluation of the immunogenicity, and virulence for all the encoded proteins of both BVDV1 and BVDV2 and their sub-genotypes.MethodsTo achieve this goal, 11,737 protein sequences were retrieved from Virus Pathogen Resource. The analysis involved a total of 4,583 sequences after the removal of short sequences and those with unknown collection time. We used the MP3 tool to map the pathogenic proteins across different BVDV strains. The potential protective and the epitope motifs were predicted using the VaxiJen and EMBOSS antigen tools, respectively.Results and discussionThe virulence prediction revealed that the NS4B proteins of both BVDV1 and BVDV2 likely have essential roles in BVDV virulence. Similarly, both the capsid (C) and the NS4-A proteins of BVDV1 and the Npro and P7 proteins of BVDV2 are likely important virulent factors. There was a clear trend of increasing predicted virulence with the progression of time in the case of BVDV1 proteins, but that was not the case for the BVDV2 proteins. Most of the proteins of the two BVDV serotypes possess antigens predicted immunogens except Npro, P7, and NS4B. However, the predicted antigenicity of the BVDV1 was significantly higher than that of BVDV2. Meanwhile, the predicted immunogenicity of the immunodominant-E2 protein has been decreasing over time. Based on our predicted antigenicity and pathogenicity studies of the two BVDV serotypes, the sub-genotypes (1a, 1f, 1k, 2a, and 2b) may represent ideal candidates for the development of future vaccines against BVDV infection in cattle. In summary, we identified some common differences between the two BVDV genotypes (BVDV1 and BVDV2) and their sub-genotypes regarding their protein antigenicity and pathogenicity. The data presented here will increase our understanding of the molecular pathogenesis of BVDV infection in cattle. It will also pave the way for developing some novel diagnostic assays and novel vaccines against BVDV in the near future.

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

Histoplasmosis is a widespread systemic disease caused by Histoplasma capsulatum, prevalent in the Americas. Despite its significant morbidity and mortality rates, no vaccines are currently available. Previously, five vaccine targets and specific epitopes for H. capsulatum were identified. Immunoinformatics has emerged as a novel approach for determining the main immunogenic components of antigens through in silico methods. Therefore, we predicted the main helper and cytotoxic T lymphocytes and B-cell epitopes for these targets to create a potential multi-epitope vaccine known as HistoVAC-TSFM. A total of 38 epitopes were found: 23 common to CTL and B-cell responses, 11 linked to HTL and B cells, and 4 previously validated epitopes associated with the B subunit of cholera toxin, a potent adjuvant. In silico evaluations confirmed the stability, non-toxicity, non-allergenicity, and non-homology of these vaccines with the host. Notably, the vaccine exhibited the potential to trigger both innate and adaptive immune responses, likely involving the TLR4 pathway, as supported by 3D modeling and molecular docking. The designed HistoVAC-TSFM appears promising against Histoplasma, with the ability to induce important cytokines, such as IFN-γ, TNF-α, IL17, and IL6. Future studies could be carried out to test the vaccine’s efficacy in in vivo models.

Sphingomyelin is a major constituent of eukaryotic cell membranes, and if degraded by bacteria sphingomyelinases may contribute to the pathogenesis of infection. Among Leptospira spp., there are five sphingomyelinases exclusively expressed by pathogenic leptospires, in which Sph2 is expressed during natural infections, cytotoxic, and implicated in the leptospirosis hemorrhagic complications. Considering this and the lack of information about associations between Sph2 and leptospirosis severity, we use a combination of immunoinformatics approaches to identify its B-cell epitopes, evaluate their reactivity against samples from leptospirosis patients, and investigate the role of antibodies anti-Sph2 in protection against severe leptospirosis. Two B-cell epitopes, Sph2(176-191) and Sph2(446-459), were predicted in Sph2 from L. interrogans serovar Lai, presenting different levels of identity when compared with other pathogenic leptospires. These epitopes were recognized by about 40% of studied patients with a prevalence of IgG antibodies against both Sph2(176-191) and Sph2(446-459). Remarkably, just individuals with low reactivity to Sph2(176-191) presented clinical complications, while high responders had only mild symptoms. Therefore, we identified two B-cell linear epitopes, recognized by antibodies of patients with leptospirosis, that could be further explored in the development of multi-epitope vaccines against leptospirosis. [ABSTRACT FROM AUTHOR]

T Nervous necrosis virus (NNV), a formidable pathogen in marine and freshwater fish, has inflicted enormous financial tolls on the aquaculture industry worldwide. Although capsid protein (CP) is the sole structural protein with pathogenicity and antigenicity, public information on immunodominant regions remains extremely scarce. Here, we employed neutralizing monoclonal antibodies (MAbs) specific for red-spotted grouper NNV (RGNNV) CNPgg2018 in combination with partially overlapping truncated proteins and peptides to identify two minimal B-cell epitope clusters on CP, 122GYVAGFL128 and 227SLYNDSL233. Site-directed mutational analysis confirmed residues Y123, G126, and L128 and residues L228, Y229, N230, D231, and L233 as the critical residues responsible for the direct interaction with ligand, respectively. According to homologous modeling and bioinformatic evaluation, 122GYVAGFL128 is harbored at the groove of the CP junction with strict conservation among all NNV isolates, while 227SLYNDSL233 is localized in proximity to the tip of a viral protrusion having relatively high evolutionary dynamics in different genotypes. Additionally, 227SLYNDSL233 was shown to be a receptor-binding site, since the corresponding polypeptide could moderately suppress RGNNV multiplication by impeding virion entry. In contrast, 122GYVAGFL128 seemed dedicated only to stabilizing viral native conformation and not to assisting initial virus attachment. Altogether, these findings contribute to a novel understanding of the antigenic distribution pattern of NNV and the molecular basis for neutralization, thus advancing the development of biomedical products, especially epitope-based vaccines, against NNV. IMPORTANCE NNV is a common etiological agent associated with neurological virosis in multiple aquatic organisms, causing significant hazards to the host. However, licensed drugs or vaccines to combat NNV infection are very limited to date. Toward the advancement of broad-spectrum prophylaxis and therapeutics against NNV, elucidating the diversity of immunodominant regions within it is undoubtedly essential. Here, we identified two independent B-cell epitopes on NNV CP, followed by the confirmation of critical amino acid residues participating in direct interaction. These two sites were distributed on the shell and protrusion domains of the virion, respectively, and mediated the neutralization exerted by MAbs via drastically distinct mechanisms. Our work promotes new insights into NNV antigenicity as well as neutralization and, more importantly, offers promising targets for the development of antiviral countermeasures. [ABSTRACT FROM AUTHOR]

Syphilis, a sexually transmitted infection, is a deadly disease caused by Treponema pallidum. It is a Gram-negative spirochete that can infect nearly every organ of the human body. It can be transmitted both sexually and perinatally. Since syphilis is the second most fatal sexually transmitted disease after AIDS, an efficient vaccine candidate is needed to establish long-term protection against infections by T. pallidum. This study used reverse-vaccinology-based immunoinformatic pathway subtractive proteomics to find the best antigenic proteins for multi-epitope vaccine production. Six essential virulent and antigenic proteins were identified, including the membrane lipoprotein TpN32 (UniProt ID: O07950), DNA translocase FtsK (UniProt ID: O83964), Protein Soj homolog (UniProt ID: O83296), site-determining protein (UniProt ID: F7IVD2), ABC transporter, ATP-binding protein (UniProt ID: O83930), and Sugar ABC superfamily ATP-binding cassette transporter, ABC protein (UniProt ID: O83782). We found that the multiepitope subunit vaccine consisting of 4 CTL, 4 HTL, and 11 B-cell epitopes mixed with the adjuvant TLR-2 agonist ESAT6 has potent antigenic characteristics and does not induce an allergic response. Before being docked at Toll-like receptors 2 and 4, the developed vaccine was modeled, improved, and validated. Docking studies revealed significant binding interactions, whereas molecular dynamics simulations demonstrated its stability. Furthermore, the immune system simulation indicated significant and long-lasting immunological responses. The vaccine was then reverse-transcribed into a DNA sequence and cloned into the pET28a (+) vector to validate translational activity as well as the microbial production process. The vaccine developed in this study requires further scientific consensus before it can be used against T. pallidum to confirm its safety and efficacy. [ABSTRACT FROM AUTHOR]

Spirocerca lupi is a parasitic nematode affecting predominantly domestic dogs. It causes spirocercosis, a disease that is often fatal. The assembled draft genome of S. lupi consists of 13,627 predicted protein-coding genes and is approximately 150 Mb in length. Several known anthelmintic gene targets such as for β-Tubulin, glutamate, and GABA receptors as well as known vaccine gene targets such as cysteine protease inhibitor and cytokines were identified in S. lupi by comparing orthologs of C. elegans anthelmintic gene targets as well as orthologs to known vaccine candidates. New anthelmintic targets were predicted through an inclusion-exclusion strategy and new vaccine targets were predicted through an immunoinformatics approach. New anthelminthic targets include DNA-directed RNA polymerases, chitin synthase, polymerases, and other enzymes. New vaccine targets include cuticle collagens. These gene targets provide a starting platform for new drug identification and vaccine design. [Display omitted] • The draft genome of Spirocerca lupi has been determined using genomic and transcriptomic sequencing data. • Known anthelmintic and vaccine gene targets have been identified through ortholog comparisons. • Novel anthelmintic targets and new vaccine targets were identified. [ABSTRACT FROM AUTHOR]

Antigenic changes in surface proteins of the influenza virus may cause the emergence of new variants that necessitate the reformulation of influenza vaccines every year. Universal influenza vaccine that relies on conserved regions can potentially be effective against all strains regardless of any antigenic changes and as a result, it can bring enormous public health impact and economic benefit worldwide. Here, a conserved peptide (HA288–107) on the stalk domain of hemagglutinin glycoprotein is identified among highly pathogenic influenza viruses. Five top-ranked B-cell and twelve T-cell epitopes were recognized by epitope mapping approaches and the corresponding Human Leukocyte Antigen alleles to T-cell epitopes showed high population coverage (>99%) worldwide. Moreover, molecular docking analysis indicated that VLMENERTL and WTYNAELLV epitopes have high binding affinity to the antigen-binding groove of the HLA-A*02:01 and HLA-A*68:02 molecules, respectively. Theoretical physicochemical properties of the peptide were assessed to ensure its thermostability and hydrophilicity. The results suggest that the HA288–107 peptide can be a promising antigen for universal influenza vaccine design. However, in vitro and in vivo analyses are needed to support and evaluate the effectiveness of the peptide as an immunogen for vaccine development.

Mastitis disease causes significant economic losses in dairy farms by reducing milk production, increasing production costs, and reducing milk quality. Streptococcus agalactiae continues to be a major cause of mastitis in dairy cattle. To date, there has been no approved multi-epitope vaccine against this pathogen in the market. In the present study, an efficient multi-epitope vaccine against S. agalactiae, the causative agent of mastitis, was designed using various immonoinformtics approaches. Potential epitopes were selected from Sip protein to improve vaccine immunogenicity. The designed vaccine is more antigenic in nature. Then, linkers and profilin adjuvant were added to enhance the immunity of vaccines. The designed vaccine was evaluated in terms of molecular weight, PI, immunogenicity, Toxicity, and allergenicity. Prediction of three-dimensional (3 D) structure of multi-epitope vaccine, followed by refinement and validation, was conducted to obtain a high-quality 3 D structure of the designed multi-epitope vaccine. The designed vaccine was then subjected to molecular docking with Toll-like receptor 11 (TLR11) receptor to evaluate its binding efficiency followed by dynamic simulation for stable interaction. In silico cloning approach was carried out to improve the expression of the vaccine construct. These analyses indicate that the designed multi-epitope vaccine may produce particular immune responses against S. agalactiae and may be further helpful to control mastitis after in vitro and in vivo immunological assays. [ABSTRACT FROM AUTHOR]

The therapeutic targeting of the immune system, for example in vaccinology and cancer treatment, is a challenging task and the subject of active research. Several in silico tools used for predicting immunogenicity are based on the analysis of peptide sequences binding to the Major Histocompatibility Complex (pMHC). However, few of these bioinformatics tools take into account the pMHC threedimensional structure. Here, we describe a new bioinformatics tool, MatchTope, developed for predicting peptide similarity, which can trigger cross-reactivity events, by computing and analyzing the electrostatic potentials of pMHC complexes. We validated MatchTope by using previously published data from in vitro assays. We thereby demonstrate the strength of MatchTope for similarity prediction between targets derived from several pathogens as well as for indicating possible cross responses between self and tumor peptides. Our results suggest that MatchTope can enhance and speed up future studies in the fields of vaccinology and cancer immunotherapy. [ABSTRACT FROM AUTHOR]

In recent years, several advances have been observed in vaccinology especially for neglected tropical diseases (NTDs). One of the tools employed is epitope prediction by immunoinformatic approaches that reduce the time and cost to develop a vaccine. In this scenario, immunoinformatics is being more often used to develop vaccines for NTDs, in particular visceral leishmaniasis (VL) which is proven not to have an effective vaccine yet. Based on that, in a previous study, two predicted T-cell multi-epitope chimera vaccines were experimentally validated in BALB/c mice to evaluate the immunogenicity, central and effector memory and protection against VL. Considering the results obtained in the mouse model, we assessed the immune response of these chimeras in Mesocricetus auratus hamster, which displays, experimentally, similar pathological status to human and dog VL disease. Our findings indicate that both chimeras lead to a dominant Th1 response profile, inducing a strong cellular response by increasing the production of IFN-γ and TNF-α cytokines associated with a decrease in IL-10. Also, the chimeras reduced the spleen parasite load and the weight a correlation between protector immunological mechanisms and consistent reduction of the parasitic load was observed. Our results demonstrate that both chimeras were immunogenic and corroborate with findings in the mouse model. Therefore, we reinforce the use of the hamster as a pre-clinical model in vaccination trials for canine and human VL and the importance of immunoinformatic to identify epitopes to design vaccines for this important neglected disease. [ABSTRACT FROM AUTHOR]

The therapeutic targeting of the immune system, for example in vaccinology and cancer treatment, is a challenging task and the subject of active research. Several in silico tools used for predicting immunogenicity are based on the analysis of peptide sequences binding to the Major Histocompatibility Complex (pMHC). However, few of these bioinformatics tools take into account the pMHC three-dimensional structure. Here, we describe a new bioinformatics tool, MatchTope, developed for predicting peptide similarity, which can trigger cross-reactivity events, by computing and analyzing the electrostatic potentials of pMHC complexes. We validated MatchTope by using previously published data from in vitro assays. We thereby demonstrate the strength of MatchTope for similarity prediction between targets derived from several pathogens as well as for indicating possible cross responses between self and tumor peptides. Our results suggest that MatchTope can enhance and speed up future studies in the fields of vaccinology and cancer immunotherapy.

Spike (S) proteins are an attractive target as it mediates the binding of the SARS-CoV-2 to the host through ACE-2 receptors. We hypothesize that the screening of the S protein sequences of all the seven known HCoVs would result in the identification of potential multi-epitope vaccine candidates capable of conferring immunity against various HCoVs. In the present study, several machine learning-based in-silico tools were employed to design a broad-spectrum multi-epitope vaccine candidate targeting the S protein of seven known strains of human coronaviruses. Herein, multiple B-cell epitopes and T-cell epitopes (CTL and HTL) were predicted from the S protein sequences of all seven known HCoVs. Post-prediction they were linked together with an adjuvant to construct a potential broad-spectrum vaccine candidate. Secondary and tertiary structures were predicted and validated, and the refined 3D-model was docked with an immune receptor. The vaccine candidate was evaluated for antigenicity, allergenicity, solubility, and its ability to achieve high-level expression in bacterial hosts. Finally, the immune simulation was carried out to evaluate the immune response after three vaccine doses. The designed vaccine is antigenic (with or without the adjuvant), non-allergenic, binds well with TLR-3 receptor and might elicit a diverse and strong immune response. [ABSTRACT FROM AUTHOR]

Enterobacter cloacae is mainly responsible for sepsis, urethritis, and respiratory tract infections. These bacteria may affect the transcription of the host and particularly their immune system by producing changes in their epigenetics. In the present study, four proteins of Enterobacter cloacae were used to predict the epitopes for the construction of an mRNA vaccine against Enterobacter cloacae infections. In order to generate cellular and humoral responses, various immunoinformatic-based approaches were used for developing the vaccine. The molecular docking analysis was performed for predicting the interaction among the chosen epitopes and corresponding MHC alleles. The vaccine was developed by combining epitopes (thirty-three total), which include the adjuvant Toll-like receptor-4 (TLR4). The constructed vaccine was analyzed and predicted to cover 99.2% of the global population. Additionally, in silico immunological modeling of the vaccination was also carried out. When it enters the cytoplasm of the human (host), the codon is optimized to generate the translated mRNA efficiently. Moreover, the peptide structures were analyzed and docked with TLR-3 and TLR-4. A dynamic simulation predicted the stability of the binding complex. The assumed construct was considered to be a potential candidate for a vaccine against Enterobacter cloacae infections. Hence, the proposed construct is suitable for in vitro analyses to validate its effectiveness. [ABSTRACT FROM AUTHOR]

Burkholderia cepacia is a Gram-negative nosocomial pathogen and is considered as a troublesome bacterium due to its resistance to many common antibiotics. There is no licensed vaccine available to prevent the pathogen infections, thus making the condition more alarming and warrant the search for novel therapeutic and prophylactic approaches. In order to identify protective antigens from pathogen proteome, substantial efforts are put forth to prioritized potential vaccine targets and antigens that can be easily evaluated experimentally. In this vaccine design investigation, it was found that B. cepacia completely sequenced proteomes available in NCBI genome database has a total of 28,966 core proteins. Out of total, 25,282 proteins were found redundant while 3,684 were non-redundant. Subcellular localization revealed that 18 proteins were extracellular, 31 were part of the outer membrane, 75 proteins were localized in the periplasm, and 23 were virulent proteins. Five proteins namely flagellar hook protein (FlgE), fimbria biogenesis outer membrane usher protein, Type IV pilus secretin (PilQ), cytochrome c4, flagellar hook basal body complex protein (FliE) were tested for positive for antigenic, non-toxic, and soluble epitopes during predication of B-cell derived T-cell epitopes. A vaccine peptide of 14 epitopes (joined together via GPGPG linkers) and cholera toxin B subunit (CTBS) adjuvant (joined to epitopes peptide via EAAAK linker) was constructed. Binding interaction of the modeled vaccine with MHC-I, MHC-II, and Toll-like receptor 4 (TLR-4) immune receptors was studied using molecular docking studies and further analyzed in molecular dynamics simulations that affirms strong intermolecular binding and stable dynamics. The maximum root mean square deviation (RMSD) score of complexes in the simulation time touches to 2 Å. Additionally, complexes binding free energies were determined that concluded robust interaction energies dominated by van der Waals. The total energy of each complex is < -190 kcal/mol. In summary, the designed vaccine showed promising protective immunity against B. cepacia and needs to be examined in experiments. [ABSTRACT FROM AUTHOR]

Human SARS coronavirus 2 (SARS-CoV-2) causes the current global COVID-19 pandemic. The production of an efficient vaccine against COVID-19 is under heavy investigation. In this study, we have designed a novel multiepitope DNA vaccine against SARS-CoV-2 using reverse vaccinology and DNA vaccine approaches. Applying these strategies led to reduce the time and costs of vaccine development and also improve the immune protective characteristics of the vaccine. For this purpose, epitopes of nucleocapsid, membrane glycoprotein, and ORF8 proteins of SARS-CoV-2 chose as targets for B and T-cell receptors. Accordingly, DNA sequences of selected epitopes have optimized for protein expression in the eukaryotic system. To this end, the Kozak and tissue plasminogen activator sequences were added into the epitope sequences for proper protein expression and secretion, respectively. Furthermore, interleukin-2 and beta-defensin 1 preproprotein sequences were incorporated to the designed DNA vaccine as an adjuvant. Modeling and refinement of fused protein composed of SARS-CoV-2 multiepitope antigens (fuspMA) have performed based on homology modeling of orthologous peptides, then constructed 3D model of fuspMA was more investigated during 50 ns of molecular dynamics simulation. Further bioinformatics predictions demonstrated that fuspMA is a stable protein with acceptable antigenic features and no allergenicity or toxicity characteristics. Finally, the affinity of fuspMA to the MHC I and II and TLRs molecules validated by the molecular docking procedure. In conclusion, it seems the designed multiepitope DNA vaccine could have a chance to be introduced as an efficient vaccine against COVID-19 after more in vivo evaluations. [ABSTRACT FROM AUTHOR]

This article is devoted to applying bioinformatics and immunoinformatics approaches for the development of a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. The study's relevance is dictated by the fact that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began its global threat at the end of 2019 and since then has had a devastating impact on the whole world. Measures to reduce threats from the pandemic include social restrictions, restrictions on international travel, and vaccine development. In most cases, vaccine development depends on the spike glycoprotein, which serves as a medium for its entry into host cells. Although several variants of SARS-CoV-2 have emerged from mutations crossing continental boundaries, about 6000 delta variants have been reported along the coast of more than 20 countries in Africa, with South Africa accounting for the highest percentage. This also applies to the omicron variant of the SARS-CoV-2 virus in South Africa. The authors suggest that bioinformatics and immunoinformatics approaches be used to develop a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. Various immunoinformatics tools have been used to predict T- and B-lymphocyte epitopes. The epitopes were further subjected to multiple evaluations to select epitopes that could elicit a sustained immunological response. The candidate vaccine consisted of seven epitopes, a highly immunogenic adjuvant, an MHC I-targeting domain (MITD), a signal peptide, and linkers. The molecular weight (MW) was predicted to be 223.1 kDa, well above the acceptable threshold of 110 kDa on an excellent vaccine candidate. In addition, the results showed that the candidate vaccine was antigenic, non-allergenic, non-toxic, thermostable, and hydrophilic. The vaccine candidate has good population coverage, with the highest range in East Africa (80.44%) followed by South Africa (77.23%). West Africa and North Africa have 76.65% and 76.13%, respectively, while Central Africa (75.64%) has minimal coverage. Among seven epitopes, no mutations were observed in 100 randomly selected SARS-CoV-2 spike glycoproteins in the study area. Evaluation of the secondary structure of the vaccine constructs revealed a stabilized structure showing 36.44% alpha-helices, 20.45% drawn filaments, and 33.38% random helices. Molecular docking of the TLR4 vaccine showed that the simulated vaccine has a high binding affinity for TLR-4, reflecting its ability to stimulate the innate and adaptive immune response. [ABSTRACT FROM AUTHOR]