Identification Of Vaccine Candidates Research Articles

Multiplexed LNP-mRNA vaccination against pathogenic coronavirus species.

Although COVID-19 vaccines have been developed, multiple pathogenic coronavirus species exist, urging on development of multispecies coronavirus vaccines. Here we develop prototype lipid nanoparticle (LNP)-mRNA vaccine candidates against SARS-CoV-2 Delta, SARS-CoV, and MERS-CoV, and we test how multiplexing LNP-mRNAs can induce effective immune responses in animal models. Triplex and duplex LNP-mRNA vaccinations induce antigen-specific antibody responses against SARS-CoV-2, SARS-CoV, and MERS-CoV. Single-cell RNA sequencing profiles the global systemic immune repertoires and respective transcriptome signatures of vaccinated animals, revealing a systemic increase in activated B cells and differential gene expression across major adaptive immune cells. Sequential vaccination shows potent antibody responses against all three species, significantly stronger than simultaneous vaccination in mixture. These data demonstrate the feasibility, antibody responses, and single-cell immune profiles of multispecies coronavirus vaccination. The direct comparison between simultaneous and sequential vaccination offers insights into optimization of vaccination schedules to provide broad and potent antibody immunity against three major pathogenic coronavirus species.

Designing vaccine candidates against dengue virus by in silico studies on structural and nonstructural domains

One-third of the world's population is at risk of Dengue infection. Envelope domain 3 (EDIII) and nonstructural protein1 (NS1) proteins as the potent antigenicity regions for humoral immunity in addition to the bc loop region as a completely conserved region have been used for designing protective vaccines. We aimed to design vaccine candidates according to the bc loop, EDIII, and NS1 regions of Dengue serotype2 to be used as vaccine candidates for all serotypes of Dengue virus especially serotype 2. Firstly the bc loop region with EDII fragments at both ends as well as EDIII and NS1 regions were used which were linked with the GGGGS linker to the bc loop region. In two other strategies, the bc loop with EDII and NS1 fragments at both ends was used to increase its structural stability. Tertiary structure prediction and validation of vaccine constructs indicated that all vaccine constructs were modeled with high quality and stable structure during molecular dynamics simulation. B cell epitope mapping by Bepipred and ElliPro methods confirmed the existence of high potent epitopes in the bc loop, EDIII, and NS1 regions in both linear and conformational B cell epitopes. Furthermore, molecular docking for the bc loop region demonstrated that all designed vaccines have a higher affinity to interact with 1C19 monoclonal antibody than only the bc loop region or bc loop epitope in the protein EII. Our data of in silico studies indicated that the designed vaccines could effectively induce humoral immunity against four dengue serotypes.

A Novel Design of Multi-epitope Peptide Vaccine Against Pseudomonas aeruginosa

Background: As an opportunistic pathogen, Pseudomonas aeruginosa causes many different hazardous infections. The high mortality rate resulting from infection with this antibiotic-resistant pathogen has made it a major challenge in clinical treatment; it has been listed as the most harmful bacterium to humans by the WHO. So far, no vaccine has been approved for P. aeruginosa. Objective: Infections performed by bacterial attachment and colonization with type IV pili (T4P), known as the most essential adhesive vital for adhesion, while pilQ is necessary for the biogenesis of T4P, also outer membrane proteins of a pathogen is also effective in stimulating the immune system; in this regard, pilQ, OprF, and OprI, are excellent candidate antigens for production of an effective vaccine against P. aeruginosa. Methods: In this research, various bioinformatics methods were employed in order to design a new multiepitope peptide vaccine versus P. aeruginosa. Since T CD4+ cell immunity is important in eradicating P. aeruginosa, OprF, OprI, and pilQ antigens were analyzed to determine Helper T cell Lymphocyte (HTL) epitopes by many different immunoinformatics servers. One of the receptor agonists 2 (TLR2), a segment of the Por B protein from Neisseria meningitides was used as an adjuvant in order to stimulate an effective cellular immune response, and suitable linkers were used to connect all the above mentioned parts. In the vaccine construct, linear B cell epitopes were also identified. Results: Conforming the bioinformatics forecasts, the designed vaccine possesses high antigenicity and is not allergen. Conclusion: In this regard, the designed vaccine candidate is strongly believed to possess the potential of inducing cellular and humoral immunity against P. aeruginosa.

Identification of Putative Vaccine and Drug Targets against the Methicillin-Resistant Staphylococcus aureus by Reverse Vaccinology and Subtractive Genomics Approaches.

Methicillin-resistant Staphylococcus aureus (MRSA) is an opportunistic pathogen and responsible for causing life-threatening infections. The emergence of hypervirulent and multidrug-resistant (MDR) S. aureus strains led to challenging issues in antibiotic therapy. Consequently, the morbidity and mortality rates caused by S. aureus infections have a substantial impact on health concerns. The current worldwide prevalence of MRSA infections highlights the need for long-lasting preventive measures and strategies. Unfortunately, effective measures are limited. In this study, we focus on the identification of vaccine candidates and drug target proteins against the 16 strains of MRSA using reverse vaccinology and subtractive genomics approaches. Using the reverse vaccinology approach, 4 putative antigenic proteins were identified; among these, PrsA and EssA proteins were found to be more promising vaccine candidates. We applied a molecular docking approach of selected 8 drug target proteins with the drug-like molecules, revealing that the ZINC4235426 as potential drug molecule with favorable interactions with the target active site residues of 5 drug target proteins viz., biotin protein ligase, HPr kinase/phosphorylase, thymidylate kinase, UDP-N-acetylmuramoyl-L-alanyl-D-glutamate-L-lysine ligase, and pantothenate synthetase. Thus, the identified proteins can be used for further rational drug or vaccine design to identify novel therapeutic agents for the treatment of multidrug-resistant staphylococcal infection.

Evaluation and identification of essential therapeutic proteins and vaccinomics approach towards multi-epitopes vaccine designing against Legionella pneumophila for immune response instigation

The Legionellaceae group comprises the Legionella, containing 58 species with 70 serotypes. For instance, Legionella pneumophila is the deadliest serotype to cause Legionnaires infectious and is responsible for 90% of the infections in humans. The bacterial pathogen is associated with a severe lung infection, known as legionaries' disease. It is resistant to multiple drugs, thus warranting novel vaccine candidates identification to immune the host against infections caused by the said pathogen. For this, we applied the subtractive proteomics and reverse vaccinology approaches to annotate the most essential genes suitable for vaccine designing. From the whole proteome, only five proteins (Q5ZVG4, Q5ZRZ1, Q5ZWE6, Q5ZT09, and Q5ZUZ8) as the best targets for further processing as they fulfill all the standard parameters set for in silico vaccine design. Immuno-informatics approaches were further applied to the selected protein sequences to prioritized antigenic epitopes for design a multi-epitope subunit vaccine. A multi-epitopes vaccine was designed by using suitable linkers to link the CTL (cytotoxic T lymphocytes), HTL (Helper T lymphocytes), B cell epitopes, and adjuvant to strengthen the vaccine's immunogenicity. The MEVC(multi-epitopes vaccine construct) was reported to interact with human immune receptor TLR-2 (toll-like receptor) robustly (docking score = −357.18 kcal/mol), and a higher expression was achieved in the Escherichia coli system (CAI = 0.88, and GC contents = 54.34%). Moreover, immune simulation revealed that on the 3rd day, the neutralization of the antigen started, while on the 5th day, the antigen was completely neutralized by the secreted immune factors. In conclusion, the designed vaccine candidate effectively triggered the immune response against eh pathogen; however, wet lab-based experimentations are highly recommended to prove the protective immunological proficiency of the vaccine against L. pneumophila.

Immunoinformatics guided design of a next generation epitope-based vaccine against Kaposi Sarcoma

Kaposi sarcoma-associated herpesvirus (KSHV) is the etiologic agent of Kaposi Sarcoma (KS) and other two B-cell originated malignancies. Despite its familiarity as a direct carcinogen, still there is no permanent treatment or approved vaccine. This work intended to develop a multi-epitope vaccine aiming KSHV's key glycoproteins involved in viral entry. After applying rigorous immunoinformatics algorithms and numerous immunological filters, a unique vaccine containing multiple CTL, HTL, and BCL epitopes was created. Further, the putative vaccine's overall stability was demonstrated by three molecular dynamics simulations, along with a series of computational evaluations. Docking experiments revealed that the vaccination can make stable interactions with Toll-Like Receptor. Codon optimization and insertion into the cloning vector revealed that the newly designed vaccine candidate could be proficiently expressed in the E. coli system. Finally, an immune simulation was carried out to calibrate the vaccine's potency to trigger an immune response of the host.

Panproteome Analysis of the Human Antibody Response to Bacterial Vaccines and Challenge.

High-density protein microarray is an established technology for characterizing host antibody profiles against entire pathogen proteomes. As one of the highest throughput technologies for antigen discovery, proteome microarrays are a translational research tool for identification of vaccine candidates and biomarkers of susceptibility or protection from microbial challenge. The application has been expanded in recent years due to increased availability of bacterial genomic sequences for a broader range of species and strain diversity. Panproteome microarrays now allow for fine characterization of antibody specificity and cross-reactivity that may be relevant to vaccine design and biomarker discovery, as well as a fuller understanding of factors underlying themes of bacterial evolution and host-pathogen interactions. In this chapter, we present a workflow for design of panproteome microarrays and demonstrate statistical analysis of panproteomic human antibody responses to bacterial vaccination and challenge. Focus is particularly drawn to the bioinformatics and statistical tools and providing nontrivial, real examples that may help foster hypotheses and rational design of panproteomic studies.

Immunoinformatics based designing a multi-epitope vaccine against pathogenic Chandipura vesiculovirus.

Chandipura vesiculovirus (CHPV) is a rapidly emerging pathogen responsible for causing acute encephalitis. Due to its widespread occurrence in Asian and African countries, this has become a global threat, and there is an urgent need to design an effective and nonallergenic vaccine against this pathogen. The present study aimed to develop a multi-epitope vaccine using an immunoinformatics approach. The conventional method of vaccine design involves large proteins or whole organism which leads to unnecessary antigenic load with increased chances of allergenic reactions. In addition, the process is also very time-consuming and labor-intensive. These limitations can be overcome by peptide-based vaccines comprising short immunogenic peptide fragments that can elicit highly targeted immune responses, avoiding the chances of allergenic reactions, in a relatively shorter time span. The multi-epitope vaccine constructed using CTL, HTL, and IFN-γ epitopes was able to elicit specific immune responses when exposed to the pathogen, in silico. Not only that, molecular docking and molecular dynamics simulation studies confirmed a stable interaction of the vaccine with the immune receptors. Several physicochemical analyses of the designed vaccine candidate confirmed it to be highly immunogenic and nonallergic. The computer-aided analysis performed in this study suggests that the designed multi-epitope vaccine can elicit specific immune responses and can be a potential candidate against CHPV.

In Silico Prediction of Epitopes in Virulence Proteins of Mycobacterium ulcerans for Vaccine Designing.

Background Mycobacterium ulcerans is the fundamental agent of the third most common Mycobacterial disease known as Buruli Ulcer (BU). It is an infection of the skin and soft tissue affecting the human population worldwide. Presently, the vaccine is not available against BU.ObjectiveThis study aimed to investigate the vaccine potential of virulence proteins of M. ulcerans computationally.MethodsChromosome encoded virulence proteins of Mycobacterium ulcerans strain Agy99 were selected, which were available at the VFDB database. These proteins were analyzed for their subcellular localization, antigenicity, and human non-homology analysis. Ten virulence factors were finally chosen and analyzed for further study. Three-dimensional structures for selected proteins were predicted using Phyre2. B cell and T cell epitope analysis was done using methods available at Immune Epitope Database and Analysis Resource. Antigenicity, allergenicity, and toxicity analysis were also done to predict epitopes. Molecular docking analysis was done for T cell epitopes, those showing overlap with B cell epitopes.ResultsSelected virulence proteins were predicted with B cell and T cell epitopes. Some of the selected proteins were found to be already reported as antigenic in other mycobacteria. Some of the predicted epitopes also had similarities with experimentally identified epitopes of M. ulcerans and M. tuberculosis which further supported our predictions.ConclusionIn-silico approach used for the vaccine candidate identification predicted some virulence proteins that could be proved important in future vaccination strategies against this chronic disease. Predicted epitopes require further experimental validation for their potential use as peptide vaccines.

Immunoinformatics design of a novel epitope-based vaccine candidate against dengue virus

Dengue poses a global health threat, which will persist without therapeutic intervention. Immunity induced by exposure to one serotype does not confer long-term protection against secondary infection with other serotypes and is potentially capable of enhancing this infection. Although vaccination is believed to induce durable and protective responses against all the dengue virus (DENV) serotypes in order to reduce the burden posed by this virus, the development of a safe and efficacious vaccine remains a challenge. Immunoinformatics and computational vaccinology have been utilized in studies of infectious diseases to provide insight into the host–pathogen interactions thus justifying their use in vaccine development. Since vaccination is the best bet to reduce the burden posed by DENV, this study is aimed at developing a multi-epitope based vaccines for dengue control. Combined approaches of reverse vaccinology and immunoinformatics were utilized to design multi-epitope based vaccine from the sequence of DENV. Specifically, BCPreds and IEDB servers were used to predict the B-cell and T-cell epitopes, respectively. Molecular docking was carried out using Schrödinger, PATCHDOCK and FIREDOCK. Codon optimization and in silico cloning were done using JCAT and SnapGene respectively. Finally, the efficiency and stability of the designed vaccines were assessed by an in silico immune simulation and molecular dynamic simulation, respectively. The predicted epitopes were prioritized using in-house criteria. Four candidate vaccines (DV-1–4) were designed using suitable adjuvant and linkers in addition to the shortlisted epitopes. The binding interactions of these vaccines against the receptors TLR-2, TLR-4, MHC-1 and MHC-2 show that these candidate vaccines perfectly fit into the binding domains of the receptors. In addition, DV-1 has a better binding energies of − 60.07, − 63.40, − 69.89 kcal/mol against MHC-1, TLR-2, and TLR-4, with respect to the other vaccines. All the designed vaccines were highly antigenic, soluble, non-allergenic, non-toxic, flexible, and topologically assessable. The immune simulation analysis showed that DV-1 may elicit specific immune response against dengue virus. Moreover, codon optimization and in silico cloning validated the expressions of all the designed vaccines in E. coli. Finally, the molecular dynamic study shows that DV-1 is stable with minimum RMSF against TLR4. Immunoinformatics tools are now applied to screen genomes of interest for possible vaccine target. The designed vaccine candidates may be further experimentally investigated as potential vaccines capable of providing definitive preventive measure against dengue virus infection.

Immunogenic Potency of a Chimeric Protein Comprising InvH and IpaD against Salmonella and Shigella spp

Shigella and Salmonella cause serious problems in many subjects, including young children and the elderly, especially in developing countries. Chimeric proteins carrying immunogens increase immune response. In-silico tools are applied to design vaccine candidates. Invasionplasmid antigens D (ipaD) gene is one of the Shigella virulence factors. The N-terminal region of the IpaD plays a significant role in invading the host cell. Invasion protein H (invH) gene plays important role in bacterial adherence and entry into epithelial cells. A recombinant chimeric construct, containing IpaD and InvH was designed and used as a vaccine candidate against Shigella and Salmonella enteritidis. After bioinformatics assessments, the construct was designed, synthesized, and expressed in E.coli. Chimeric protein, IpaD, and InvH were purified with Ni-NTA chromatography. Purified proteins were confirmed with western blotting and then were injected into separate mice groups. The antibody titer was estimated with an enzyme-linked immunosorbent assay (ELISA). Mice were challenged with 10, 100, and 1000 LD50 of Salmonella, and the sereny test was performed for Shigella. The Codon adaptation index of the chimeric gene was increased to 0.84. Validation results showed that 97.9% of residues lie in the favored or additional allowed region of the Ramachandran plot. A significant antibody rise was observed in all test groups. The immunized mice with chimer and InvH could tolerate 100 LD50 of Salmonella. In the sereny test, the application of bacteria treated with immunized mice sera of both antigens showed no infection in Guinea pigs' eyes. The recombinant protein could protect animal models against Salmonella and Shigella and therefore can be considered as a suitable vaccine candidate against these two pathogens.

Limited Evidence for a Relationship between HIV-1 Glycan Shield Features in Early Infection and the Development of Neutralization Breadth.

ABSTRACTIdentifying whether viral features present in acute HIV-1 infection predetermine the development of neutralization breadth is critical to vaccine design. Incorporating such features in vaccine antigens could initiate cross-reactive antibody responses that could sufficiently protect vaccinees from HIV-1 infection despite the uniqueness of each founder virus. To understand the relationship between Env determinants and the development of neutralization breadth, we focused on 197 individuals enrolled in two cohorts in Thailand and East Africa (RV144 and RV217) and followed since their diagnosis in acute or early HIV-1 infection. We analyzed the distribution of variable loop lengths and glycans, as well as the predicted density of the glycan shield, and compared these envelope features to the neutralization breadth data obtained 3 years after infection (n = 121). Our study revealed limited evidence for glycan shield features that associate with the development of neutralization breadth. While the glycan shield tended to be denser in participants who subsequently developed breadth, no significant relationship was found between the size of glycan holes and the development of neutralization breadth. The parallel analysis of 3,000 independent Env sequences showed no evidence of directional evolution of glycan shield features since the beginning of the epidemic. Together, our results highlight that glycan shield features in acute and early HIV-1 infection may not play a role determinant enough to dictate the development of neutralization breadth and instead suggest that the glycan shield’s reactive properties that are associated with immune evasion may have a greater impact.IMPORTANCE A major goal of HIV-1 vaccine research is to design vaccine candidates that elicit potent broadly neutralizing antibodies (bNAbs). Different viral features have been associated with the development of bNAbs, including the glycan shield on the surface of the HIV-1 Envelope (Env). Here, we analyzed data from two cohorts of individuals who were followed from early infection to several years after infection spanning multiple HIV-1 subtypes. We compared Env glycan features in HIV-1 sequences obtained in early infection to the potency and breadth of neutralizing antibodies measured 1 to 3 years after infection. We found limited evidence of glycan shield properties that associate with the development of neutralization breadth in these cohorts. These results may have important implications for antigen design in future vaccine strategies and emphasize that HIV-1 vaccines will need to rely on a complex set of properties to elicit neutralization breadth.

An Overview of Current Uses and Future Opportunities for Computer-Assisted Design of Vaccines for Neglected Tropical Diseases.

Neglected tropical diseases are infectious diseases that impose high morbidity and mortality rates over 1.5 billion people worldwide. Originally restricted to tropical and subtropical regions, changing climate conditions have increased their potential to emerge elsewhere. Control of their impact suffers from shortages like poor epidemiological surveillance or irregular drug distribution, and some NTDs still lack of appropriate diagnostics and/or efficient therapeutics. For these, availability of vaccines to prevent new infections, or the worsening of those already established, would mean a major breakthrough. However, only dengue and rabies count with approved vaccines at present. Herein, we review the state-of-the-art of vaccination strategies for NTDs, setting the focus on third generation vaccines and the concept of reverse vaccinology. Its capability to address pathogens´ biological complexity, likely contributing to save developmental costs is discussed. The use of computational tools is a fundamental aid to analyze increasingly large datasets aimed at designing vaccine candidates with the highest, possibly, opportunities to succeed. Ultimately, we identify and analyze those studies that took an in silico approach to find vaccine candidates, and experimentally assessed their immunogenicity and/or protection capabilities.

Designing of Nucleocapsid Protein Based Novel Multi-epitope Vaccine Against SARS-COV-2 Using Immunoinformatics Approach.

The COVID-19 disease is caused by SARS-CoV-2 and spreading rapidly worldwide with extremely high infection rate. Since effective and specific vaccine is not available to combat the deadly COVID-19, the objective of our study was to design a multi-epitope vaccine using immunoinformatics approach with translational implications. Nucleocapsid (N) protein of SARS-CoV-2 is stable, conserved and highly immunogenic along with being less prone to mutations during infection, which makes it a suitable candidate for designing vaccine. In our study, B- and T-cells epitopes were identified from N protein and screened based on crucial parameters to design the multi-epitope vaccine construct. Additionally, human beta-defensin-2 was incorporated into the vaccine construct as an adjuvant along with suitable linkers followed by its further evaluation based on crucial parameters including allergenicity, antigenicity, stability etc. Combined major histocompatibility complexes (MHC-I and MHC-II) binding epitopes presented broader population coverage of the vaccine throughout the world. The three-dimensional structure of vaccine candidate implied strong interaction with toll-like receptor 3 (TLR3) using molecular docking. The vaccine-TLR3 complex was observed to be highly stable during simulation and electrostatic free energy was foremost contributor for stabilization of the structure. Subsequently, in silico cloning of vaccine candidate was carried out to generate the construct into pET-28a(+) expression vector succeeded by its virtual confirmation. Altogether, our results advocate that the designed vaccine candidate could be an effective and promising weapon to fight with COVID-19 infection worldwide.

Multi-epitope vaccine against SARS-CoV-2 applying immunoinformatics and molecular dynamics simulation approaches

COVID-19, caused by SARS-CoV-2, is severe respiratory illnesses leading to millions of deaths worldwide in very short span. The high case fatality rate and the lack of medical counter measures emphasize for an urgent quest to develop safe and effective vaccine. Receptor-binding domain (RBD) of spike protein of SARS-CoV-2 binds to the ACE2 receptor on human host cell for the viral attachment and entry, hence considered as a key target to develop vaccines, antibodies and therapeutics. In this study, immunoinformatics approach was employed to design a novel multi-epitope vaccine using RBD of SARS-CoV-2 spike protein. The potential B- and T-cell epitopes were selected from RBD sequence using various bioinformatics tools to design the vaccine construct. The in silico designed multi-epitope vaccine encompasses 146 amino acids with an adjuvant (human beta-defensin-2), which was further computationally evaluated for several parameters including antigenicity, allergenicity and stability. Subsequently, three-dimensional structure of vaccine construct was modelled and then docked with various toll-like receptors. Molecular dynamics (MD) study of docked TLR3-vaccine complex delineated it to be highly stable during simulation time and the stabilization of interaction was majorly contributed by electrostatic energy. The docked complex also showed low deformation and increased rigidity in motion of residues during dynamics. Furthermore, in silico cloning of the multi-epitope vaccine was carried out to generate the plasmid construct for expression in a bacterial system. Altogether, our study suggests that the designed vaccine candidate containing RBD region could provide the specific humoral and cell-mediated immune responses against SARS-CoV-2. Communicated by Ramaswamy H. Sarma

Global distribution of single amino acid polymorphisms in Plasmodium vivax Duffy-binding-like domain and implications for vaccine development efforts.

Plasmodium vivax (Pv) malaria continues to be geographically widespread with approximately 15 million worldwide cases annually. Along with other proteins, Duffy-binding proteins (DBPs) are used by plasmodium for RBC invasion and the parasite-encoded receptor binding regions lie in their Duffy-binding-like (DBL) domains—thus making it a prime vaccine candidate. This study explores the sequence diversity in PvDBL globally, with an emphasis on India as it remains a major contributor to the global Pv malaria burden. Based on 1358 PvDBL protein sequences available in NCBI, we identified 140 polymorphic sites within 315 residues of PvDBL. Alarmingly, country-wise mapping of SAAPs from field isolates revealed varied and distinct polymorphic profiles for different nations. We report here 31 polymorphic residue positions in the global SAAP profile, most of which map to the PvDBL subdomain 2 (α1–α6). A distinct clustering of SAAPs distal to the DARC-binding sites is indicative of immune evasive strategies by the parasite. Analyses of PvDBL-neutralizing antibody complexes revealed that between 24% and 54% of interface residues are polymorphic. This work provides a framework to recce and expand the polymorphic space coverage in PvDBLs as this has direct implications for vaccine development studies. It also emphasizes the significance of surveying global SAAP distributions before or alongside the identification of vaccine candidates.

Immunoinformatics-guided design of an epitope-based vaccine against severe acute respiratory syndrome coronavirus 2 spike glycoprotein

AimsWith a large number of fatalities, coronavirus disease-2019 (COVID-19) has greatly affected human health worldwide. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes COVID-19. The World Health Organization has declared a global pandemic of this contagious disease. Researchers across the world are collaborating in a quest for remedies to combat this deadly virus. It has recently been demonstrated that the spike glycoprotein (SGP) of SARS-CoV-2 is the mediator by which the virus enters host cells. Main methodsOur group comprehensibly analyzed the SGP of SARS-CoV-2 through multiple sequence analysis and a phylogenetic analysis. We predicted the strongest immunogenic epitopes of the SGP for both B cells and T cells. Key findingsWe focused on predicting peptides that would bind major histocompatibility complex class I. Two optimal epitopes were identified, WTAGAAAYY and GAAAYYVGY. They interact with the HLA-B*15:01 allele, which was further validated by molecular docking simulation. This study also found that the selected epitopes are able to be recognized in a large percentage of the world's population. Furthermore, we predicted CD4+ T-cell epitopes and B-cell epitopes. SignificanceOur study provides a strong basis for designing vaccine candidates against SARS-CoV-2. However, laboratory work is required to validate our theoretical results, which would lay the foundation for the appropriate vaccine manufacturing and testing processes.

Immunoselective algorithm to devise multi-epitope subunit vaccine fighting against human cytomegalovirus infection

BackgroundHuman cytomegalovirus (HCMV) generally causes asymptomatic infection, but sometimes it may cause severe complications among immunocompromised individuals. It may also promote various malignancies like prostate cancer and breast cancer. However, even after having this severe illness, there is no effective cure yet. This situation urges the need for effective chemotherapeutics or vaccination to tackle this severe complication. MethodsA combinatorial screening algorithm was applied to design a subunit vaccine consisting of B-cell epitopes, CTL- and HTL epitopes along with a suitable adjuvant (TLR-4 agonist) and linkers. The conservancy of CTL, HTL, and B-cell epitopes was also determined. Further, physicochemical characterization, antigenicity, and allergenicity were determined to check the safety and immunogenic behavior of the designed vaccine candidate. Later on, the 3D structure of the vaccine protein was determined, followed by molecular docking and molecular dynamics simulation with TLR-4 to check their binding free energy and complex stability. ResultA subunit vaccine of 964 amino acid residues was developed, having good immunogenicity and non-allergenicity behavior. The designed subunit vaccine has HTL epitopes with their ability to induce the release of IFN-γ cytokine. The sorted HTL and CTL epitopes were found to be conserved among two available strains of HCMV. It has also shown an excellent binding affinity with the TLR-4 receptor along with the formation of the stable complex as determined by a molecular dynamics simulation study. ConclusionThe designed subunit vaccine may have the ability to induce an immunogenic response and memory cell formation to protect against the HCMV mediated disease conditions.

Proteomics and Leishmaniasis: Potential Clinical Applications.

Leishmaniases are diseases caused by protozoan parasites of the genus Leishmania. They are endemic in 98 countries, affect around 12 million people worldwide and may present several distinct clinical forms. Unfortunately, there are only a few drugs available for treatment of leishmaniasis, which are toxic and not always effective. Different parasite species and different clinical forms require optimization of the treatment or more specific therapies, which are not available. The emergence of resistance is also a matter of concern. Besides, diagnosis can sometimes be complicated due to atypical manifestations and associations with other pathologies. In this review, proteomic data are presented and discussed in terms of their application in important issues in leishmaniasis such as parasite resistance to chemotherapy, diagnosis of active disease in patients and dogs, markers for different clinical forms, identification of virulence factors, and their potential use in vaccination. It is shown that proteomics has contributed to the discovery of potential biomarkers for prognosis, diagnosis, therapeutics, monitoring of disease progression, treatment follow-up and identification of vaccine candidates for specific diseases. However, the authors believe its capabilities have not yet been fully explored for routine clinical analysis for several reasons, which will be presented in this review.

Strategic Development of a Next-Generation Multi-Epitope Vaccine To Prevent Nipah Virus Zoonotic Infection.

Nipah virus (NiV) is an emerging zoonotic pathogen, reported for the recent severe outbreaks of encephalitis and respiratory illness in humans and animals, respectively. Many antiviral drugs have been discovered to inhibit this pathogen, but none of them were that much efficient. To overcome the complications associated with this severe pathogenic virus, we have designed a multi-epitope subunit vaccine using computational immunology strategies. Identification of structural and nonstructural proteins of Nipah virus assisted in the vaccine designing. The selected proteins are known to be involved in the survival of the virus. The antigenic binders (B-cell, HTL, and CTL) from the selected proteins were prognosticated. These antigenic binders will be able to generate the humoral as well as cell-mediated immunity. All the epitopes were united with the help of suitable linkers and with an adjuvant at the N-terminal of the vaccine, for the enhancement of immunogenicity. The physiological characterization, along with antigenicity and allergenicity of the designed vaccine candidates, was estimated. The 3D structure prediction and its validation were performed. The validated vaccine model was then docked and simulated with the TLR-3 receptor to check the stability of the docked complex. This next-generation approach will provide a new vision for the development of a high immunogenic vaccine against the NiV.