Epitope-based peptide vaccine design and target site depiction against Ebola viruses: an immunoinformatics study

In Silico Analysis of a Candidate Multi-epitope Peptide Vaccine Against Human Brucellosis

Brucellosis is one of the neglected endemic zoonoses in the world. Vaccination appears to be a promising health strategy to prevent it. This study used advanced computational techniques to develop a potent multi-epitope vaccine for human brucellosis. Seven epitopes from four main brucella species that infect humans were selected. They had significant potential to induce cellular and humoral responses. They showed high antigenic ability without the allergenic characteristic. In order to improve its immunogenicity, suitable adjuvants were also added to the structure of the vaccine. The physicochemical and immunological properties of the vaccine were evaluated. Then its two and three-dimensional structure was predicted. The vaccine was docked with toll-like receptor4 to assess its ability to stimulate innate immune responses. For successful expression of the vaccine protein in Escherichia coli, in silico cloning, codon optimization, and mRNA stability were evaluated. The immune simulation was performed to reveal the immune response profile of the vaccine after injection. The designed vaccine showed the high ability to induce immune response, especially cellular responses to human brucellosis. It showed the appropriate physicochemical properties, a high-quality structure, and a high potential for expression in a prokaryotic system.

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

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

Computational identification of a multi-peptide vaccine candidate in E2 glycoprotein against diverse Hepatitis C virus genotypes

Hepatitis C Virus (HCV) is estimated to affect nearly 180 million people worldwide, culminating in ∼0.7 million yearly casualties. However, a safe vaccine against HCV is not yet available. This study endeavored to identify a multi-genotypic, multi-epitopic, safe, and globally competent HCV vaccine candidate. We employed a consensus epitope prediction strategy to identify multi-epitopic peptides in all known envelope glycoprotein (E2) sequences, belonging to diverse HCV genotypes. The obtained peptides were screened for toxicity, allergenicity, autoimmunity and antigenicity, resulting in two favorable peptides viz., P2 (VYCFTPSPVVVG) and P3 (YRLWHYPCTV). Evolutionary conservation analysis indicated that P2 and P3 are highly conserved, supporting their use as part of a designed multi-genotypic vaccine. Population coverage analysis revealed that P2 and P3 are likely to be presented by >89% Human Leukocyte Antigen (HLA) molecules from six geographical regions. Indeed, molecular docking predicted the physical binding of P2 and P3 to various representative HLAs. We designed a vaccine construct using these peptides and assessed its binding to toll-like receptor 4 (TLR-4) by molecular docking and simulation. Subsequent analysis by energy-based and machine learning tools predicted high binding affinity and pinpointed the key binding residues (i.e. hotspots) in P2 and P3. Also, a favorable immunogenic profile of the construct was predicted by immune simulations. We encourage the scientific community to validate our vaccine construct in vitro and in vivo.Communicated by Ramaswamy H. Sarma.

Antimicrobial peptides and their potential application in antiviral coating agents

Coronavirus pandemic has evidenced the importance of creating bioactive materials to mitigate viral infections, especially in healthcare settings and public places. Advances in antiviral coatings have led to materials with impressive antiviral performance; however, their application may face health and environmental challenges. Bio-inspired antimicrobial peptides (AMPs) are suitable building blocks for antimicrobial coatings due to their versatile design, scalability, and environmentally friendly features. This review presents the advances and opportunities on the AMPs to create virucidal coatings. The review first describes the fundamental characteristics of peptide structure and synthesis, highlighting the recent findings on AMPs and the role of peptide structure (α-helix, β-sheet, random, and cyclic peptides) on the virucidal mechanism. The following section presents the advances in AMPs coating on medical devices with a detailed description of the materials coated and the targeted pathogens. The use of peptides in vaccine formulations is also reported, emphasizing the molecular interaction of peptides with different viruses and the current clinical stage of each formulation. The role of several materials (metallic particles, inorganic materials, and synthetic polymers) in the design of antiviral coatings is also presented, discussing the advantages and the drawbacks of each material. The final section offers future directions and opportunities for using AMPs on antiviral coatings to prevent viral outbreaks.

In silico epitope-based vaccine design against influenza a neuraminidase protein: Computational analysis established on B- and T-cell epitope predictions

Objective

Influenza A virus belongs to the most studied virus and its mutant initiates epidemic and pandemics outbreaks. Inoculation is the significant foundation to diminish the risk of infection. To prevent an incidence of influenza from the transmission, various practical approaches require more advancement and progress. More efforts and research must take in front to enhance vaccine efficacy.

Methods

The present research emphasizes the development and expansion of a universal vaccine for the influenza virus. Research focuses on vaccine design with high efficacy. In this study, numerous computational approaches were used, covering a wide range of elements and ideas in bioinformatics methodology. Various B and T-cell epitopic peptides derived from the Neuraminidase protein N1 are recognized by these approaches. With the implementation of numerous obtained databases and bioinformatics tools, the different immune framework methods of the conserved sequences of N1 neuraminidase were analyzed. NCBI databases were employed to retrieve amino acid sequences. The antigenic nature of the neuraminidase sequence was achieved by the VaxiJen server and Kolaskar and Tongaonkar method. After screening of various B and T cell epitopes, one efficient peptide each from B cell epitope and T cell epitopes was assessed for their antigenic determinant vaccine efficacy. Identical two B cell epitopes were recognized from the N1 protein when analyzed using B-cell epitope prediction servers. The detailed examination of amino acid sequences for interpretation of B and T cell epitopes was achieved with the help of the ABCPred and Immune Epitope Database.

Results

Computational immunology via immunoinformatic study exhibited RPNDKTG as having its high conservancy efficiency and demonstrated as a good antigenic, accessible surface hydrophilic B-cell epitope. Among T cell epitope analysis, YVNISNTNF was selected for being a conserved epitope. T cell epitope was also analyzed for its allergenicity and cytotoxicity evaluation. YVNISNTNF epitope was found to be a non-allergen and not toxic for cells as well. This T-cell epitope with maximum world populace coverages was scrutinized for its association with the HLA-DRB1*0401 molecule. Results from docking simulation analyses showed YVNISNTNF having lower binding energy, the radius of gyration (Rg), RMSD values, and RMSE values which make the protein structure more stable and increase its ability to become an epitopic peptide for influenza virus vaccination.

Conclusions

We propose that this epitope analysis may be successfully used as a measurement tool for the robustness of an antigen-antibody reaction between mutant strains in the annual design of the influenza vaccine.

Novel In Silico mRNA vaccine design exploiting proteins of M. tuberculosis that modulates host immune responses by inducing epigenetic modifications

Tuberculosis is an airborne infectious disease caused by Mycobacterium tuberculosis. BCG is the only approved vaccine. However, it has limited global efficacy. Pathogens could affect the transcription of host genes, especially the ones related to the immune system, by inducing epigenetic modifications. Many proteins of M. tuberculosis were found to affect the host's epigenome. Nine proteins were exploited in this study to predict epitopes to develop an mRNA vaccine against tuberculosis. Many immunoinformatics tools were employed to construct this vaccine to elicit cellular and humoral immunity. We performed molecular docking between selected epitopes and their corresponding MHC alleles. Thirty epitopes, an adjuvant TLR4 agonist RpfE, constructs for subcellular trafficking, secretion booster, and specific linkers were combined to develop the vaccine. This proposed construct was tested to cover 99.38% of the population. Moreover, it was tested to be effective and safe. An in silico immune simulation of the vaccine was also performed to validate our hypothesis. It also underwent codon optimization to ensure mRNA's efficient translation once it reaches the cytosol of a human host. Furthermore, secondary and tertiary structures of the vaccine peptide were predicted and docked against TLR-4 and TLR-3.Molecular dynamics simulation was performed to validate the stability of the binding complex. It was found that this proposed construction can be a promising vaccine against tuberculosis. Hence, our proposed construct is ready for wet-lab experiments to approve its efficacy.

In silico analyses and experimental validation of the MHC class-I restricted epitopes of Ebolavirus GP

Ebolavirus (EBOV) causes an extremely high mortality and prevalence disease called Ebola virus disease (EVD). There is only one glycoprotein (GP) on the virus particle surface, which mediates entry into the host cell. MHC class-I restricted CD8 + T cell responses are important antiviral immune responses. Therefore, it is of great importance to understand EBOV GP-specific MHC class-I restricted epitopes within immunogenicity. In this study, computational approaches were employed to predict the dominant MHC class-I molecule epitopes of EBOV GP for mouse H2 and major alleles of HLA class-I supertypes. Our results yielded 42 dominant epitopes in H2 haplotypes and 301 dominant epitopes in HLA class-I haplotypes. After validation by ELISpot assay, in-depth analyses to ascertain their nature of conservation, immunogenicity, and docking with the corresponding MHC class-I molecules were undertaken. Our study predicted MHC class-I restricted epitopes that may aid the advancement of anti-EBOV immune responses. And the integrated strategy of epitope prediction, validation, and comparative analyses were postulated, promising for epitope-based immunotherapy development and application to viral epidemics.

A peptide-based subunit candidate vaccine against SARS-CoV-2 delivered by biodegradable mesoporous silica nanoparticles induced high humoral and cellular immunity in mice

Development of a rapidly scalable vaccine is still an urgent task to halt the spread of COVID-19. We have demonstrated biodegradable mesoporous silica nanoparticles (BMSNs) as a good drug delivery carrier for tumor therapy. In this study, seven linear B cell epitopes and three CD8⁺ T cell epitopes were screened from the spike (S) glycoprotein of SARS-CoV-2 by computer-based immunoinformatic approaches for vaccine design. A nanoparticle-based candidate vaccine (B/T@BMSNs) against SARS-CoV-2 was rapidly prepared by encapsulating these ten epitope peptides within BMSNs, respectively. BMSNs with potential biodegradability, proved to possess excellent safety in vitro and in vivo, could efficiently deliver epitope peptides into the cytoplasm of RAW264.7 cells. Strong Th1-biased humoral and cellular immunity were induced by B/T@BMSNs in mice and all the 10 selected epitopes were identified as effective antigen epitopes, which could induce robust peptide-specific immune response. The elicited functional antibody could bind to the recombinant S protein and block the binding of the S protein to the ACE-2 receptor. These results demonstrate the potential of a nanoparticles vaccine platform based on BMSNs to rapidly develop peptide-based subunit vaccine candidates against SARS-CoV-2.

Computational Design and Analysis of a Multi-epitope Against Influenza A virus

Influenza A viruses are among the most studied viruses, however no effective prevention against influenza infection has been developed. So, designing an effective vaccine against Influenza A virus is a critical issue in the field of medical biotechnology. For this reason, to combat this disease, we have designed a novel multi-epitope vaccine candidate based on the several conserved and potential linear B-cell and T-cell binding epitopes by using the in silico approach. This vaccine consists of an ER signal conserved sequence, the PADRE conserved epitope and two conserved epitopes of Influenza matrix protein 2. T-cell binding epitopes from Matrix protein 2 were predicted by in silico tools of epitope prediction. The selected epitopes were joined by flexible linkers and physicochemical properties, toxicity, and allergenecity were investigated. The designed vaccine was antigenic, immunogenic, and non-allergenic with suitable physicochemical properties and has higher solubility. The final multi-epitope construct was modeled, confirmed by different programs and the molecular interactions with immune receptors were considered. The molecular docking assay indicated the interactions with immune-stimulatory toll-like receptor 3 (TLR3) and major histocompatibility complex class I (MHCI). The HADDOCK and H DOCK servers were used to make docking analysis, respectively. The docking analysis indicated a strong and stable binding interaction between the vaccine construct with major histocompatibility complex (MHC) class I and toll-like receptor 3. Overall, the findings suggest that the current vaccine may be a promising vaccine to prevent Influenza infection.

Multi-epitope based subunit vaccine construction against Banna virus targeting on two outer proteins (VP4 and VP9): A computational approach

Recently, RNA viruses have gained a mammoth concern for causing various outbreaks, and due to pandemics, they are acquiring additional attention throughout the world. An emerging RNA as well as vector-borne Banna Virus (BAV) is a human pathogen resulting in encephalitis, fever, headache, muscle aches, and severe coma. Besides human, pathogenic BAV was also detected from pigs, cattle, ticks, midges, and mosquitoes in Indonesia, China, and Vietnam. Due to high mutation tendency and dearth of a species barrier, this virus will consider as a significant threat in the near future throughout the planet, particularly in Africa. Despite of severe human case fatalities in several countries, there are no specific therapeutics, available vaccines, and other preventive measures against BAV. Thus, to find out the effective therapeutics and preventive strategies are crying exigency. In the present study, a unique multi-epitope-based peptide vaccine candidate is constructed using bioinformatics' tools that efficiently instigate immune cells for generating BAV antibodies. The potential vaccine candidates were developed using both T and B -cell epitopes. UniprotKB database was used to retrieve of two outer proteins (VP9 and VP4), and homologous sequences of BAV taxid: 7763, 649,604, 77,763, and 8453 were searched by NCBI BLAST. These serotypes are the most closely associated with the disease. Then combining the best-selected epitopes in various combinations with different adjuvants, three distinct vaccine candidates were formed. The validity tests were performed for the screened vaccine candidate regarding stability, allergenicity, and antigenicity parameters. Moreover, molecular dynamic simulations of the selected vaccine with TLR-8 immune receptor confirmed the stability of the binding pose and showed a significant response to immune cells. Thus, the results established that the designed chimeric peptide vaccine could enhance the immune response against BAV.

Immunoinformatics prediction of potential B-cell and T-cell epitopes as effective vaccine candidates for eliciting immunogenic responses against Epstein-Barr virus

BACKGROUND

The ongoing search for viable treatment options to curtail Epstein Barr Virus (EBV) pathogenicity has necessitated a paradigmatic shift towards the design of peptide-based vaccines. Potential B-cell and T-cell epitopes were predicted for nine antigenic EBV proteins that mediate epithelial cell-attachment and spread, capsid self-assembly, DNA replication and processivity.

METHODS

Predictive algorithms incorporated in the Immune Epitope Database (IEDB) resources were used to determine potential B-cell epitopes based on their physicochemical attributes. These were combined with a string-kernel method and an antigenicity predictive AlgPred tool to enhance accuracy in the end-point selection of highly potential antigenic EBV B-cell epitopes. NetCTL 1.2 algorithms enabled the prediction of probable T-cell epitopes which were structurally modeled and subjected to blind peptide-protein docking with HLA-A*02:01. All-atom molecular dynamics (MD) simulation and Molecular Mechanics Generalized-Born Surface Area methods were used to investigate interaction dynamics and affinities of predicted T-cell peptide-protein complexes.

RESULTS

Computational predictions and sequence overlapping analysis yielded 18 linear (continuous) and discontinuous (conformational) subunit epitopes from the antigenic proteins with characteristic surface accessibility, flexibility and antigenicity, and predictive scores above the threshold value (1) set. A novel site was identified on HLA-A*02:01 with preferential affinity binding for modeled BMRF2, BXLF1 and BGLF4 T-cell epitopes. Interaction dynamics and energies were also computed in addition to crucial residues that mediated complex formation and stability.

CONCLUSION

This study implemented an integrative meta-analytical approach to model highly probable B-cell and T-cell epitopes as potential peptide-vaccine candidates for the treatment of EBV-related diseases.

Immunoinformatics approach for multi-epitope vaccine design against P. falciparum malaria

Plasmodium falciparum (P. falciparum) is a leading causative agent of malaria, an infectious disease that can be fatal. Unfortunately, control measures are becoming less effective over time. A vaccine is needed to effectively control malaria and lead towards the total elimination of the disease. There have been multiple attempts to develop a vaccine, but to date, none have been certified as appropriate for wide-scale use. In this study, an immunoinformatics method is presented to design a multi-epitope vaccine construct predicted to be effective against P. falciparum malaria. This was done through the prediction of 12 CD4+ T-cell, 10 CD8+ T-cell epitopes and, 1 B-cell epitope which were assessed for predicted high antigenicity, immunogenicity, and non-allergenicity through in silico methods. The Human Leukocyte Antigen (HLA) population coverage showed that the alleles associated with the epitopes accounted for 78.48% of the global population. The CD4+ and CD8+ T-cell epitopes were docked to HLA-DRB1*07:01 and HLA-A*32:01 successfully. Therefore, the epitopes were deemed to be suitable as components of a multi-epitope vaccine construct. Adjuvant RS09 was added to the construct to generate a stronger immune response, as confirmed by an immune system simulation. Finally, the structural stability of the predicted multi-epitope vaccine was assessed using molecular dynamics simulations. The results show a promising vaccine design that should be further synthesised and assessed for its efficacy in an experimental laboratory setting.

[In silico prediction of B- and T-cell epitopes in the CD2v protein of african swine fever virus (African swine fever virus, Asfivirus, Asfarviridae).]

INTRODUCTION

African swine fever virus (ASF) is a large DNA virus that is the only member of the Asfarviridae family. The spread of the ASF virus in the territory of the Russian Federation, Eastern Europe and China indicates the ineffectiveness of existing methods of combating the disease and reinforces the urgent need to create effective vaccines. One of the most significant antigens required for the formation of immune protection against ASF is a serotype-specific CD2v protein.

THE PURPOSE OF THE STUDY

This study presents the results of immuno-informatics on the identification of B- and T-cell epitopes for the CD2v protein of the ASF virus using in silico prediction methods.

MATERIAL AND METHODS

The primary sequence of the CD2v protein of the ASFV virus strain Georgia 2007/1 (IDFR682468) was analyzed in silico by programs BCPred, NetCTLpan, VaxiJen, PVS and Epitope Conservancy Analysis.

RESULTS

Using the BCPred and VaxiJen programs, 4 major B-cell immunogenic epitopes were identified. Analysis of the secretory region of ASF virus CD2v protein in NetCTLpan revealed 5 T-cell epitopes from the 32nd to the 197th position of amino acids that cross-link from the 1st to the 13th allele of the MHC-I of pig Discussion. This study presents the results in silico prediction to identify B- and T-cell epitopes of ASF virus CD2v protein. The soluble region of the CD2v protein can be included in the recombinant polyepitope vaccine against African swine fever.

CONCLUSION

B- and T-cell epitopes in the secretory region of the CD2v protein (from 17 to 204 aa) of ASF virus were identified by in silico prediction. An analysis of the conservatism of the identified B- and T-cell epitopes allowed us to develop a map of the distribution of immune epitopes in the CD2v protein sequence.

Implementation of in silico methods to predict common epitopes for vaccine development against Chikungunya and Mayaro viruses

Being a Positive sense RNA virus the recent reemergence of Chikungunya and Mayaro virus has taken the concern of the leading scientific communities of the world. Though the outbreak of Mayaro virus is limited to Neotropical region only, Chikungunya is already identified in over 60 countries around the world. Besides, the lack of a strong protective treatment, misdiagnosis issue and co-circulation of both the viruses calls for a new strategy which could potentially prevent these infections from spreading. In this study, we therefore, identified the peptide based vaccine candidates e.g. epitopes for B cell and T cell from Chikungunya virus which also showed to be homologous to the Mayaro virus through immuno-informatics and computational approaches. Final epitopes identified from the most antigenic structural polyprotein of both the viruses were 5 for CD8+ T cell Epitopes (²⁰⁹KPGDSGRPI²¹⁷, ²¹⁹TGTMGHFIL²²⁷, ²³⁹ALSVVTWNK²⁴⁷, ⁹⁸KPGRRERMC¹⁰⁶ and ¹⁰⁰GRRERMCMK¹⁰⁸), 2 epitopes for CD4+ T cell (¹⁰⁵MCMKIENDCIFEVKH¹¹⁹ and ⁵⁰²DRTLLSQQSGNVKIT⁵¹⁶) and a single epitope for B cell (⁵⁰⁴GGRFTIPTGAGKPGDSGRPI⁵¹⁸). Analysis of our predicted epitopes for population coverage showed prominent population coverage (92.43%) around the world. Finally, molecular docking simulation of the foreseen T cell epitopes with respondent HLA alleles secured good HLA-epitope interaction. This study was directed towards the discovery of potential antigenic epitopes which can open up a new skyline to design novel vaccines for combating both of the diseases at the same time.

Mining of Ebola virus genome for the construction of multi-epitope vaccine to combat its infection

Ebola virus is the primary causative agent of viral hemorrhagic fever that is an epidemic disease and responsible for the massive premature deaths in humans. Despite knowing the molecular mechanism of its pathogenesis, to date, no commercial or FDA approved multiepitope vaccine is available against Ebola infection. The current study focuses on designing a multi-epitope subunit vaccine for Ebola using a novel immunoinformatic approach. The best predicted antigenic epitopes of Cytotoxic-T cell (CTL), Helper-T cells (HTL), and B-cell epitopes (BCL) joined by various linkers were selected for the multi-epitope vaccine designing. For the enhanced immune response, two adjuvants were also added to the construct. Further analysis showed the vaccine to be immunogenic and non-allergenic, forming a stable and energetically favorable structure. The stability of the unbound vaccine construct and vaccine/TLR4 was elucidated via atomistic molecular dynamics simulations. The binding free energy analysis (ΔG_Bind = -194.2 ± 0.5 kcal/mol) via the molecular mechanics Poisson-Boltzmann docking scheme revealed a strong association and thus can initiate the maximal immune response. Next, for the optimal expression of the vaccine construct, its gene construct was cloned in the pET28a + vector system. In summary, the Ebola viral proteome was screened to identify the most potential HTLs, CTLs, and BCL epitopes. Along with various linkers and adjuvants, a multi-epitope vaccine is constructed that showed a high binding affinity with the immune receptor, TLR4. Thus, the current study provides a highly immunogenic multi-epitope subunit vaccine construct that may induce humoral and cellular immune responses against the Ebola infection.Communicated by Ramaswamy H. Sarma.

Genome based evolutionary lineage of SARS-CoV-2 towards the development of novel chimeric vaccine

The present study aimed to predict a novel chimeric vaccine by simultaneously targeting four major structural proteins via the establishment of ancestral relationship among different strains of coronaviruses. Conserved regions from the homologous protein sets of spike glycoprotein, membrane protein, envelope protein and nucleocapsid protein were identified through multiple sequence alignment. The phylogeny analyses of whole genome stated that four proteins reflected the close ancestral relation of SARS-CoV-2 to SARS-COV-1 and bat coronavirus. Numerous immunogenic epitopes (both T cell and B cell) were generated from the common fragments which were further ranked on the basis of antigenicity, transmembrane topology, conservancy level, toxicity and allergenicity pattern and population coverage analysis. Top putative epitopes were combined with appropriate adjuvants and linkers to construct a novel multiepitope subunit vaccine against COVID-19. The designed constructs were characterized based on physicochemical properties, allergenicity, antigenicity and solubility which revealed the superiority of construct V3 in terms safety and efficacy. Essential molecular dynamics and normal mode analysis confirmed minimal deformability of the refined model at molecular level. In addition, disulfide engineering was investigated to accelerate the stability of the protein. Molecular docking study ensured high binding affinity between construct V3 and HLA cells, as well as with different host receptors. Microbial expression and translational efficacy of the constructs were checked using pET28a(+) vector of E. coli strain K12. However, the in vivo and in vitro validation of suggested vaccine molecule might be ensured with wet lab trials using model animals for the implementation of the presented data.

Immunological Perspective for Ebola Virus Infection and Various Treatment Measures Taken to Fight the Disease

Ebolaviruses, discovered in 1976, belongs to the Filoviridae family, which also includes Marburg and Lloviu viruses. They are negative-stranded RNA viruses with six known species identified to date. Ebola virus (EBOV) is a member of Zaire ebolavirus species and can cause the Ebola virus disease (EVD), an emerging zoonotic disease that results in homeostatic imbalance and multi-organ failure. There are three EBOV outbreaks documented in the last six years resulting in significant morbidity (> 32,000 cases) and mortality (> 13,500 deaths). The potential factors contributing to the high infectivity of this virus include multiple entry mechanisms, susceptibility of the host cells, employment of multiple immune evasion mechanisms and rapid person-to-person transmission. EBOV infection leads to cytokine storm, disseminated intravascular coagulation, host T cell apoptosis as well as cell mediated and humoral immune response. In this review, a concise recap of cell types targeted by EBOV and EVD symptoms followed by detailed run-through of host innate and adaptive immune responses, virus-driven regulation and their combined effects contributing to the disease pathogenesis has been presented. At last, the vaccine and drug development initiatives as well as challenges related to the management of infection have been discussed.

Immunoinformatics approach for predicting epitopes in HN and F proteins of Porcine rubulavirus

Porcine rubulavirus (PRV), which belongs to the family Paramyxoviridae, causes blue eye disease in pigs, characterized by encephalitis and reproductive failure in newborn and adult pigs, respectively. There is no effective treatment against PRV and no information on the effectiveness of the available vaccines. Continuous outbreaks have occurred in Mexico since the early 1980s, which have caused serious economic losses to pig producers. Vaccination can be used to control this disease. Searching for effective antigen candidates against PRV, we first sequenced the PAC1 F protein, then we used various immunoinformatics tools to predict antigenic determinants of B-cells and T-cells against the two glycoproteins of the virus (HN and F proteins). Finally, we used AutoDock Vina to determine the binding energies. We obtained the F gene sequence of a PRV strain collected in the early 1990s in Mexico and compared its amino acid profile with previous and more recent strains, obtaining an identity similarity of 97.78 to 99.26%. For the F proteins, seven linear B-cell epitopes, six conformational B-cell epitopes and twenty-nine T-cell MHC class I epitopes were predicted. For the HN proteins, sixteen linear B-cell epitopes, seven conformational B-cell epitopes and thirty-four T-cell MHC class I epitopes were predicted. The ATRSETDYY and AAYTTTTCF epitopes of the HN protein might be important for neutralizing the viral infection. We determined the in silico binding energy between the predicted epitopes on the F and HN proteins and swine MHC-I molecules. The binding energy of these epitopes ranged from -5.8 to -7.8 kcal/mol. The present study aimed to assess the use of HN and F proteins as antigens, either as recombinant proteins or as a series of peptides that could activate different responses of the immune system. This may help identify relevant immunogens, saving time and costs in the development of new vaccines or diagnostic tools.

Analysis of Putative Epitope Candidates of Mycobacterium tuberculosis Against Pakistani Human Leukocyte Antigen Background: An Immunoinformatic Study for the Development of Future Vaccine

Tuberculosis (TB), a chronic disease caused by Mycobacterium tuberculosis (Mtb), is a global health issue across the world. Pakistan ranks fifth among the countries, which are facing, a significantly great number of mortalities and morbidities due to TB. Unfortunately, all previously reported treatments are not successful for the eradication of TB. Here in this study, we report an emerging treatment option for this disease. We have applied immunoinformatics to predict highly conserved B and T-cell epitopes from Mtb, showing significant binding affinities to the frequent HLA alleles in the Pakistani population. A total of ten highly referenced and experimentally validated epitopes were selected from the Immune Epitope Database (IEDB), followed by their conservancy analysis using weblogos. The consensus sequences and variants derived from these sequences were examined, for their binding affinities, with prevalent HLA alleles of Pakistan. Moreover, the antigenic and allergenic natures of these peptides were also evaluated via Vaxijen and AllerTOP, respectively. Consequently, all potentially allergenic and non-antigenic, peptide fragments, were excluded from the analysis. Among all putative epitopes, three CD8 + T-cell epitopes were selected, as ideal vaccine candidates and, population coverage analysis revealed that the combination of these three peptides was covering, 67.28% Pakistani Asian and 57.15% mixed Pakistani populations. Likewise, eleven linear and six conformational or discontinuous B-cell epitopes were also marked as potential vaccine candidates based on their prediction score, non-allergenic nature, and antigenic properties. These epitopes, however, need the final validation via wet-lab studies. After their approval, these epitopes would be effective candidates for the future designing of epitope-based vaccines against Mtb infections in Pakistan.

An immunoinformatics study on the spike protein of SARS-CoV-2 revealing potential epitopes as vaccine candidates

Background

The pandemic situation of SARS-CoV-2 infection has sparked global concern due to the disease COVID-19 caused by it. Since the first cluster of confirmed cases in China in December 2019, the infection has been reported across the continents and inflicted upon a substantial number of populations.

Method

This study is focused on immunoinformatics analyses of the SARS-CoV-2 spike glycoprotein (S protein) which is key for the viral attachment to human host cells. Computational analyses were carried out for the prediction of B-cell and T-cell (MHC class I and II) epitopes of S protein and the analyses were extended further for the prediction of their immunogenic properties. The interaction and binding affinity of T-cell epitopes with HLA-B7 were also investigated by molecular docking.

Result

Three distinct epitopes for vaccine design were predicted from the sequence of S protein. The potential B-cell epitope was KNHTSPDVDLG possessing the highest antigenicity score of 1.4039 among other B-cell epitopes. T-cell epitope for human MHC class I was VVVLSFELL with an antigenicity score of 1.0909 and binding ability to 29 MHC-I alleles. The predicted T-cell epitope for human MHC class II molecule was VVIGIVNNT with a corresponding 1.3063 antigenicity score, less digesting enzymes, and 7 MHC-II alleles binding ability. All these three peptides were predicted to be highly antigenic, non-allergenic, and non-toxic. Analyses of the physiochemical properties of these predicted epitopes indicate their stable nature for plausible vaccine design. Furthermore, molecular docking investigation between the MHC class-I epitopes and human HLA-B7 reflects the stable interaction with high affinity among them.

Conclusion

The present study posits three potential epitopes of S protein of SARS-CoV-2 predicted by immunoinformatic methods based on their immunogenic properties and interactions with the host counterpart that can facilitate the development of vaccine against SARS-CoV-2. This study can act as the springboard for the future development of the COVID-19 vaccine.

An overview of in silico vaccine design against different pathogens and cancer

INTRODUCTION

Due to overcome the hardness of the vaccine design, computational vaccinology is emerging widely. Prediction of T cell and B cell epitopes, antigen processing analysis, antigenicity analysis, population coverage, conservancy analysis, allergenicity assessment, toxicity prediction, and protein-peptide docking are important steps in the process of designing and developing potent vaccines against various viruses and cancers. In order to perform all of the analyses, several bioinformatics tools and online web servers have been developed. Scientists must take the decision to apply more suitable and precise servers for each part based on their accuracy.

AREAS COVERED

In this review, a wide-range list of different bioinformatics tools and online web servers has been provided. Moreover, some studies were proposed to show the importance of various bioinformatics tools for predicting and developing efficient vaccines against different pathogens including viruses, bacteria, parasites, and fungi as well as cancer.

EXPERT OPINION

Immunoinformatics is the best way to find potential vaccine candidates against different pathogens. Thus, the selection of the most accurate tools is necessary to predict and develop potent preventive and therapeutic vaccines. To further evaluation of the computational and in silico vaccine design, in vitro/in vivo analyses are required to develop vaccine candidates.

Designing a novel mRNA vaccine against SARS-CoV-2: An immunoinformatics approach

SARS-CoV-2 is the deadly virus behind COVID-19, the disease that went on to ravage the world and caused the biggest pandemic 21st century has witnessed so far. On the face of ongoing death and destruction, the urgent need for the discovery of a vaccine against the virus is paramount. This study resorted to the emerging discipline of immunoinformatics in order to design a multi-epitope mRNA vaccine against the spike glycoprotein of SARS-CoV-2. Various immunoinformatics tools were utilized to predict T and B lymphocyte epitopes. The epitopes were channeled through a filtering pipeline comprised of antigenicity, toxicity, allergenicity, and cytokine inducibility evaluation with the goal of selecting epitopes capable of generating both T and B cell-mediated immune responses. Molecular docking simulation between the epitopes and their corresponding MHC molecules was carried out. 13 epitopes, a highly immunogenic adjuvant, elements for proper sub-cellular trafficking, a secretion booster, and appropriate linkers were combined for constructing the vaccine. The vaccine was found to be antigenic, almost neutral at physiological pH, non-toxic, non-allergenic, capable of generating a robust immune response and had a decent worldwide population coverage. Based on these parameters, this design can be considered a promising choice for a vaccine against SARS-CoV-2.

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SARS-CoV-2, the causative agent for COVID-19, has caused the biggest pandemic 21st century has witnessed so far.

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Here, immunoinformatics was used for designing a muti-epitope mRNA vaccine against the spike glycoprotein of SARS-CoV-2.

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Through stringent selection of T and B cell epitopes and other necessary elements, a vaccine was constructed in silico.

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Proposed mechanism of its synthesis, delivery and action has also been presented.

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The vaccine was found to be immunogenic, almost neutral, non-toxic, non-allergenic and has a decent worldwide coverage.

Prediction of Epitope-Based Peptide Vaccine Against the Chikungunya Virus by Immuno-informatics Approach

BACKGROUND

Chikungunya is an arthropod-borne viral disease characterized by abrupt onset of fever frequently accompanied by joint pain, which has been identified in over 60 countries in Africa, the Americas, Asia, and Europe.

METHODS

Regardless of the availability of molecular knowledge of this virus, no definite vaccine or other remedial agents have been developed yet. In the present study, a combination of B-cell and T-cell epitope predictions, followed by molecular docking simulation approach has been carried out to design a potential epitope-based peptide vaccine, which can trigger a critical immune response against the viral infections.

RESULTS

A total of 52 sequences of E1 glycoprotein from the previously reported isolates of Chikungunya outbreaks were retrieved and examined through in silico methods to identify a potential B-cell and T-cell epitope. From the two separate epitope prediction servers, five potential B-cell epitopes were selected, among them "NTQLSEAHVEKS" was found highly conserved across strains and manifests high antigenicity with surface accessibility, flexibility, and hydrophilicity. Similarly, two highly conserved, non-allergenic, non-cytotoxic putative T-cell epitopes having maximum population coverage were screened to bind with the HLA-C 12*03 molecule. Molecular docking simulation revealed potential T-cell based epitope "KTEFASAYR" as a vaccine candidate for this virus.

CONCLUSION

A combination of these B-cell and T-cell epitope-based vaccine can open up a new skyline with broader therapeutic application against Chikungunya virus with further experimental and clinical investigation.

Extensive immunoinformatics study for the prediction of novel peptide-based epitope vaccine with docking confirmation against envelope protein of Chikungunya virus: a computational biology approach

Chikungunya virus (CHIKV) instigating Chikungunya fever is a global infective menace resulting in high fever, weakened joint-muscle pain, and brain inflammation. Inaccessibility and unavailability of effective drugs have led us to an uncertain arena when it comes to providing proper medical treatment to the affected people. In this study, authentic encroachment has been made concerning the peptide-based epitope vaccine designing against CHIKV. A Proteome-wide search was performed to locate a conserved portion among the accessible viral outer membrane proteins which showcase a remarkable immune response using specific immunoinformatics and docking simulation tools. Primarily, the most probable immunogenic envelope glycoproteins E1 and E2 were identified from the UniProt database depending on their antigenicity scores. Subsequently, we selected two distinctive sequences "SEDVYANTQLVLQRP" and "IMLLYPDHPTLLSYR" in both E1 and E2 glycoproteins respectively. These two sequences identified as the most potent T and B cell epitope-based peptides as they interacted with 6 and 7 HLA-I and 5 HLA-II molecules with an extremely low IC50 score that was verified by molecular docking. Moreover, the sequences possess no allergenicity and are certainly located outside the transmembrane region. In addition, the sequences exhibited 88.46% and 100.00% Conservancy, covering high population coverage of 89.49% to 94.74% and 60.51% to 88.87% respectively in endemic countries. The identified peptide SEDVYANTQLVLQRP and IMLLYPDHPTLLSYR can be utilized next for the development of peptide-based epitope vaccine contrary to CHIKV, so further documentations and experimentations like Antigen testing, Antigen production, Clinical trials are needed to prove the validity of it. Communicated by Ramaswamy H. Sarma.

Immunoinformatic Approaches for Vaccine Designing Against Viral Infections

Vaccines have become a cost-effective method for prevention or treatment of viral infections. Conventional methods to design a vaccine candidate is a laborious process requiring time and economy. Many approaches have been made to reduce the times and economy of vaccine development. In this regard, immunoinformatic approach is supposed to bring a revolution in vaccine development. This chapter provides an overview of immunoinformatics and its application in in silico vaccine design and development strategies in humans against viral diseases with the help of available databases and tools.

Exploring T & B-cell epitopes and designing multi-epitope subunit vaccine targeting integration step of HIV-1 lifecycle using immunoinformatics approach

Till now, AIDS, caused by the human immunodeficiency virus (HIV) is still a severe health problem worldwide. It weakens the immune system by targeting the T-helper cells. Specifically, the severity of the pandemic HIV-1 makes the emergence of an enduring effective vaccine against HIV-1. Therefore, we have applied a series of immunoinformatics approaches to the four conserved domains of HIV-1 integrase (IN) proteins to design an effective multi-epitope based subunit vaccine which might induce a competent immunity against HIV-1. Therefore, we have selected three peptide fragments that contained all overlapping epitopes (35 CD4⁺, 8 CD8⁺ T-cell epitopes, and 3 B-cell epitopes) where the epitopes had a high conservancy score. The cumulative population coverage for combined CD8⁺ and CD4⁺ T-cell epitopes and their respective HLA-alleles were found as 98.03% in the world which is also followed by East Asia (96.24%), South Asia (96.31%), North Africa (96.14%), North America (98.99%), and Europe (98.80%). The proposed vaccine composed by an adjuvant (β-defensin) at the N-terminal site of the vaccine constructs and three peptide fragments where the adjuvant was fused by EAAAK linker and the peptide fragments were fused by GPGPG linker. The designed final vaccine construct (length: 159 amino acid) was found to be antigenic and non-allergic, which indicates its safety. The vaccine construct was found as good antigenic, stable, higher thermostable, and hydrophilic in nature. The codon adaptation and in silico cloning ensured the high expression rate of the vaccine constructs in E. coli K12 with CAI value of 1.0. Finally, the binding affinity of the vaccine constructs with the immune receptor TLR3 was confirmed by the lowest energy score of -1026.8 evaluated by molecular docking. However, the proposed in silico vaccine construct needs experimental validation for assuring the safety and immunogenicity profile which will ensure an active immunity against HIV-1.

Epitope-Based Vaccine Designing of Nocardia asteroides Targeting the Virulence Factor Mce-Family Protein by Immunoinformatics Approach

Nocardia asteroides is the main causative agent responsible for nocardiosis disease in immunocompromised patient viz. Acquired Immunodeficiency Syndrome (AIDS), malignancy, diabetic, organ recipient and genetic disorders. The virulence factor and outer membrane protein pertains immense contribution towards the designing of epitopic vaccine and limiting the robust outbreak of diseases. While epitopic based vaccine element carrying B and T cell epitope along with adjuvant is highly immunoprophylactic in nature. Present research equips immunoinformatics to figure out the suitable epitopes for effective vaccine designing. The selected epitopes VLGSSVQTA, VNIELKPEF and VVPSNLFAV amino acids sequence are identified by HLA-DRB alleles of both MHC class (MHC-I and II) molecules. Simultaneously, these also accessible to B-cell, confirmed through the ABCPred server. Antigenic property expression is validated by the Vaxijen antigenic prediction web portal. Molecular docking between the epitopes and T cell receptor delta chain authenticate the accurate interaction between epitope and receptor with significantly low binding energy. Easy access of epitopes to immune system also be concluded as transmembrane nature of the protein verified by using of TMHMM server. Appropriate structural identity of the virulence factor Mce-family protein generated through Phyre2 server and subsequently validated by ProSA and PROCHECK program suite. The structural configuration of theses epitopes also shaped using DISTILL web server. Both the structure of epitopes and protein will contribute a significant step in designing of epitopic vaccine against N. asteroides. Therefore, such immunoinformatics based computational drive definitely provides a conspicuous impel towards the development of epitopic vaccine as a promising remedy of nocardiosis.

Epitope Prediction by Novel Immunoinformatics Approach: A State-of-the-art Review

Immunoinformatics is a science that helps to create significant immunological information using bioinformatics softwares and applications. One of the most important applications of immunoinformatics is the prediction of a variety of specific epitopes for B cell recognition and T cell through MHC class I and II molecules. This method reduces costs and time compared to laboratory tests. In this state-of-the-art review, we review about 50 papers to find the latest and most used immunoinformatic tools as well as their applications for predicting the viral, bacterial and tumoral structural and linear epitopes of B and T cells. In the clinic, the main application of prediction of epitopes is for designing peptide-based vaccines. Peptide-based vaccines are a considerably potential alternative to low-cost vaccines that may reduce the risks related to the production of common vaccines.

A common conserved peptide harboring predicted T and B cell epitopes in domain III of envelope protein of Japanese Encephalitis Virus and West Nile Virus for potential use in epitope based vaccines

Japanese encephalitis virus (JEV) and West Nile virus (WNV) are two major mosquito borne flaviviruses belonging to same serocomplex. JEV is transmitted by Culex mosquitoes and the reservoir host for the virus is pigs and/or water birds. WNV is also transmitted by Culex mosquitoes and reservoir host in this case is birds. It can also be transmitted through contact with other infected animals, their blood, or other tissues. The envelope protein of these viruses is the major source of epitopes and provides protective immunity. Bioinformatics tools were used to identify conserved epitopes in the envelope protein of these viruses. A conserved peptide "TPVGRLVTVNPFV" present in both the viruses containing predicted T and B cell epitopes was found. The model of one of the predicted epitope was generated and upon docking it bound in the groove of HLA-A0201 Class I MHC molecule. Further, it was amenable to proteasomal cleavage enhancing its chances of processing by cytosolic pathway. The peptide was found to be non toxic, non allergenic and stable in mammalian cells based on database search. The population coverage was pan world and nearly 70% identity of the peptide was found in the Zika virus envelope protein. The peptide was located in the domain III of envelope protein which is the exposed domain therefore B cell receptors may recognize this peptide easily. The conserved peptide containing T and B cell epitopes can have future application for designing epitope based vaccines for both JEV and WNV.

Conserved B and T cell epitopes prediction of ebola virus glycoprotein for vaccine development: An immuno-informatics approach

Ebola virus (EBOV), a non-segmented single-stranded RNA virus, is often-most transmitted through body fluids like sweat, tears, saliva, and nasal secretions. Till date, there is no licensed vaccine of EBOV is available in the market; however, the world is increasingly vulnerable to this emerging threat. Hence, it is the need of time to develop a vaccine for EBOV to hinder its dissemination. The current study has been designed for identification and characterization of the potential B and T-cell epitopes using the Immuno-informatics tools, and it helped in finding the potent vaccine candidates against EBOV. Prediction, antigenicity and allergenicity testing of predicted B and T cells' epitopes was done as well to identify their potential as a vaccine candidate and to measure their safety level respectively. Among B-cell epitopes "WIPAGIGVTGVIIA" showed a high antigenicity score and it would play an important role in evoking the immune response. In T-cell epitopes, peptides "AIGLAWIPY" and "IRGFPRCRY" presented high antigenicity score, which binds to MHC class-I and MHC class-II alleles respectively. All predicted epitopes were analyzed and compared with already reported peptides carefully. Comparatively, Peptides predicted in the present study showed more immunogenicity score than already reported peptides, used as positive control, and are more immunogenic as compared to them. Peptides reported in the present study do not target only Zaire EBOV (ZEBOV), as in previous studies, but also other species, i.e. Tai Forest EBOV (TAFV), Sudan EBOV (SUDV), Bundibugyo EBOV (BDBV), and Reston EBOV (RESTV) and would bring the promising results as potent vaccine candidates.

Epitope-based immunoinformatics approach on RNA-dependent RNA polymerase (RdRp) protein complex of Nipah virus (NiV)

Persistent outbreaks of Nipah virus (NiV) with severe case fatality throw a major challenge on researchers to develop a drug or vaccine to combat the disease. With little knowledge of its molecular mechanisms, we utilized the proteome data of NiV to evaluate the potency of three major proteins (phosphoprotein, polymerase, and nucleocapsid protein) in the RNA-dependent RNA polymerase complex to count as a possible candidate for epitope-based vaccine design. Profound computational analysis was used on the above proteins individually to explore the T-cell immune properties like antigenicity, immunogenicity, binding to major histocompatibility complex class I and class II alleles, conservancy, toxicity, and population coverage. Based on these predictions the peptide 'ELRSELIGY' of phosphoprotein and 'YPLLWSFAM' of nulceocapsid protein were identified as the best-predicted T-cell epitopes and molecular docking with human leukocyte antigen-C (HLA-C*12:03) molecule was effectuated followed by validation with molecular dynamics simulation. The B-cell epitope predictions suggest that the sequence positions 421 to 471 in phosphoprotein, 606 to 640 in polymerase and 496 to 517 in nucleocapsid protein are the best-predicted regions for B-cell immune response. However, the further experimental circumstance is required to test and validate the efficacy of the subunit peptide for potential candidacy against NiV.

In silico Designed Ebola Virus T-Cell Multi-Epitope DNA Vaccine Constructions Are Immunogenic in Mice

Background: The lack of effective vaccines against Ebola virus initiates a search for new approaches to overcoming this problem. The aim of the study was to design artificial polyepitope T-cell immunogens⁻⁻candidate DNA vaccines against Ebola virus and to evaluate their capacity to induce a specific immune response in a laboratory animal model. Method: Design of two artificial polyepitope T-cell immunogens, one of which (EV.CTL) includes cytotoxic and the other (EV.Th)⁻⁻T-helper epitopes of Ebola virus proteins was carried out using original TEpredict/PolyCTLDesigner software. Synthesized genes were cloned in pcDNA3.1 plasmid vector. Target gene expression was estimated by synthesis of specific mRNAs and proteins in cells transfected with recombinant plasmids. Immunogenicity of obtained DNA vaccine constructs was evaluated according to their capacity to induce T-cell response in BALB/c mice using IFNγ ELISpot and ICS. Results: We show that recombinant plasmids pEV.CTL and pEV.Th encoding artificial antigens provide synthesis of corresponding mRNAs and proteins in transfected cells, as well as induce specific responses both to CD4+ and CD8+ T-lymphocytes in immunized animals. Conclusions: The obtained recombinant plasmids can be regarded as promising DNA vaccine candidates in future studies of their capacity to induce cytotoxic and protective responses against Ebola virus.

Immune aging in diabetes and its implications in wound healing

Immune systems have evolved to recognize and eliminate pathogens and damaged cells. In humans, it is estimated to recognize 109 epitopes and natural selection ensures that clonally expanded cells replace unstimulated cells and overall immune cell numbers remain stationary. But, with age, it faces continuous repertoire restriction and concomitant accumulation of primed cells. Changes shaping the aging immune system have bitter consequences because, as inflammatory responses gain intensity and duration, tissue-damaging immunity and inflammatory disease arise. During inflammation, the glycolytic flux cannot cope with increasing ATP demands, limiting the immune response's extent. In diabetes, higher glucose availability stretches the glycolytic limit, dysregulating proteostasis and increasing T-cell expansion. Long-term hyperglycemia exerts an accumulating effect, leading to higher inflammatory cytokine levels and increased cytotoxic mediator secretion upon infection, a phenomenon known as diabetic chronic inflammation. Here we review the etiology of diabetic chronic inflammation and its consequences on wound healing.

Conserved epitopes in variants of amastin protein of Trypanosoma cruzi for vaccine design: A bioinformatics approach

Chagas disease caused by protozoan parasite Trypanosoma cruzi is endemic disease in South and Central American countries but due to migrating human populations it has shown emergence in Europe, North America and Australia. With only two drugs, benznidazole and nifurtimox for its treatment there is need for newer therapies. In the current study, we have tried to analyse the potential of amastin, a major surface protein as a vaccine target using bioinformatics tools. Using 282 variants of this protein available in NCBI protein database we have found out five conserved potential T_c cell and two T_H cell epitopes. These epitopes are conserved in more than 90% of the cohort of sequences used in the study. The epitopes showed binding to the peptide binding cleft of HLA-A02 and HLA-DR molecules. With coverage of pan world populations and being non-toxic and non-allergic these epitopes could be used for future vaccine applications.

An Immunopharmacoinformatics Approach in Development of Vaccine and Drug Candidates for West Nile Virus

An outbreak of West Nile Virus (WNV) like the recent Ebola can be more epidemic and fatal to public health throughout the world. WNV possesses utmost threat as no vaccine or drug is currently available for its treatment except mosquito control. The current study applied the combined approach of immunoinformatics and pharmacoinformatics to design potential epitope-based vaccines and drug candidates against WNV. By analyzing the whole proteome of 2994 proteins, the WNV envelope glycoprotein was selected as a therapeutic target based on its highest antigenicity. After proper assessment “KSFLVHREW” and “ITPSAPSYT” were found to be the most potential T and B-cell epitopes, respectively. Besides, we have designed and validated four novel drugs from a known WNV inhibitor, AP30451 by adopting computational approaches. Toxicity assessment and drug score confirmed the effectiveness of these drug candidates. This in silico research might greatly facilitate the wet lab experiments to develop vaccine and drug against WNV.

Peptide Vaccines: New Trends for Avoiding the Autoimmune Response

Background:

Several marketed antiviral vaccines (such as that against hepatitis virus A and/or B, influenza virus, human papillomavirus, yellow fever virus, measles, rubella and mumps viruses) may elicit various autoimmune reactions.

Results:

The cause of autoimmune response due to vaccination may be: 1. the adjuvant which is regularly added to the vaccine (especially in the case of various oil substrates), 2. the specific viral component itself (a protein or glycoprotein potentially possessing cross-reactive epitopes) and/or 3. contamination of the vaccine with traces of non-viral proteins mostly cellular in origin. Believing that peptide vaccines might represent an optimal solution for avoiding the above-mentioned problems, we discuss the principles of rational design of a typical peptide vaccine which should contain oligopeptides coming either from the selected structural virion components (i.e.capsid proteins and/or envelop glycoproteins or both) or from the virus-coded non-structural polypeptides. The latter should be equally immunogenic as the structural virus proteins. Describing the feasibility of identification and design of immunogenic epitopes, our paper also deals with possible problems of peptide vaccine manufacturing. The presented data are in part based on the experience of our own, in part, they are coming from the results published by others.

Conclusion:

Any peptide vaccine should be able to elicit relevant and specific antibody formation, as well as an efficient cell-mediated immune response. Consequently, the properly designed peptide vaccine is expected to consist of carefully selected viral peptides, which should stimulate the receptors of helper T/CD4 cells as well as of cytotoxic (T/CD8) lymphocytes.

Pathway based therapeutic targets identification and development of an interactive database CampyNIBase of Campylobacter jejuni RM1221 through non-redundant protein dataset

The bacterial species Campylobacter jejuni RM1221 (CjR) is the primary cause of campylobacteriosis which poses a global threat for human health. Over the years the efficacy of antibiotic treatment is becoming more fruitless due to the development of multiple drug resistant strains. Therefore, identification of new drug targets is a valuable tool for the development of new treatments for affected patients and can be obtained by targeting essential protein(s) of CjR. We conducted this in silico study in order to identify therapeutic targets by subtractive CjR proteome analysis. The most important proteins of the CjR proteome, which includes chokepoint enzymes, plasmid, virulence and antibiotic resistant proteins were annotated and subjected to subtractive analyses to filter out the CjR essential proteins from duplicate or human homologous proteins. Through the subtractive and characterization analysis we have identified 38 eligible therapeutic targets including 1 potential vaccine target. Also, 12 potential targets were found in interactive network, 5 targets to be dealt with FDA approved drugs and one pathway as potential pathway based drug target. In addition, a comprehensive database 'CampyNIBase' has also been developed. Besides the results of this study, the database is enriched with other information such as 3D models of the identified targets, experimental structures and Expressed Sequence Tag (EST) sequences. This study, including the database might be exploited for future research and the identification of effective therapeutics against campylobacteriosis. URL: (http://nib.portal.gov.bd/site/page/4516e965-8935-4129-8c3f-df95e754c562#Banner).

In Silico Designed Axl Receptor Blocking Drug Candidates Against Zika Virus Infection

After a large outbreak in Brazil, novel drugs against Zika virus became extremely necessary. Evaluation of virus-based pharmacological strategies concerning essential host factors brought us to the idea that targeting the Axl receptor by blocking its dimerization function could be critical for virus entry. Starting from experimentally validated compounds, such as RU-301, RU-302, warfarin, and R428, we identified a novel compound 2' (R428 derivative) to be the most potent for this task amongst a number of alternative compounds and leads. The improved affinity of compound 2' was confirmed by molecular docking as well as molecular dynamics simulation techniques using implicit solvation models. The current study summarizes a new possibility for inhibition of the Axl function as a potential target for future antiviral therapies.

Mapping HLA-A2, -A3 and -B7 supertype-restricted T-cell epitopes in the ebolavirus proteome

Background

Ebolavirus (EBOV) is responsible for one of the most fatal diseases encountered by mankind. Cellular T-cell responses have been implicated to be important in providing protection against the virus. Antigenic variation can result in viral escape from immune recognition. Mapping targets of immune responses among the sequence of viral proteins is, thus, an important first step towards understanding the immune responses to viral variants and can aid in the identification of vaccine targets. Herein, we performed a large-scale, proteome-wide mapping and diversity analyses of putative HLA supertype-restricted T-cell epitopes of Zaire ebolavirus (ZEBOV), the most pathogenic species among the EBOV family.

Methods

All publicly available ZEBOV sequences (14,098) for each of the nine viral proteins were retrieved, removed of irrelevant and duplicate sequences, and aligned. The overall proteome diversity of the non-redundant sequences was studied by use of Shannon’s entropy. The sequences were predicted, by use of the NetCTLpan server, for HLA-A2, -A3, and -B7 supertype-restricted epitopes, which are relevant to African and other ethnicities and provide for large (~86%) population coverage. The predicted epitopes were mapped to the alignment of each protein for analyses of antigenic sequence diversity and relevance to structure and function. The putative epitopes were validated by comparison with experimentally confirmed epitopes.

Results & discussion

ZEBOV proteome was generally conserved, with an average entropy of 0.16. The 185 HLA supertype-restricted T-cell epitopes predicted (82 (A2), 37 (A3) and 66 (B7)) mapped to 125 alignment positions and covered ~24% of the proteome length. Many of the epitopes showed a propensity to co-localize at select positions of the alignment. Thirty (30) of the mapped positions were completely conserved and may be attractive for vaccine design. The remaining (95) positions had one or more epitopes, with or without non-epitope variants. A significant number (24) of the putative epitopes matched reported experimentally validated HLA ligands/T-cell epitopes of A2, A3 and/or B7 supertype representative allele restrictions. The epitopes generally corresponded to functional motifs/domains and there was no correlation to localization on the protein 3D structure. These data and the epitope map provide important insights into the interaction between EBOV and the host immune system.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4328-8) contains supplementary material, which is available to authorized users.

Discovery of T-cell Driven Subunit Vaccines from Zika Virus Genome: An Immunoinformatics Approach

The recent outbreaks of Zika virus and the absence of a specific therapy have necessitated to identify T-cell-stimulating antigenic peptides as potential subunit vaccine candidates. The translated ssRNA (+) genome of Zika virus was explored in EMBOSS antigenic and VaxiJen to predict 63 peptides as potential antigens. Three MHC-II binding peptide prediction tools, viz. NetMHCIIpan, PREDIVAC and immune epitope database (IEDB) were employed in consensus on 63 antigenic peptides to propose 14 T-helper cell epitopes. Similarly, analysis on 63 antigenic peptides through NetMHC, NetCTL and IEDB MHC-I binding peptide prediction tool led to identification of 14 CTL epitopes. Seven T-cell epitopes, C:44-66, M:135-149, NS2A:124-144, NS3:421-453, NS3:540-554, NS4B:90-134 and NS4B:171-188, are observed to share overlapping MHC-I and MHC-II binding motifs and hence, are being proposed to constitute minimum T-cell antigens to elicit protective T-cell immune response against Zika. Three of them, C:44-66, NS3:421-453 and NS3:540-554 are identified to be conserved across all the selected strains of Zika virus. Moreover, the 21 T-cell epitopes are non-self to humans and exhibited good coverage in variable populations of 14 geographical locations. Therefore, 21 T-cell epitopes are proposed as potential subunit vaccines against Zika virus.

In Silico Analysis of Epitope-Based Vaccine Candidates against Hepatitis B Virus Polymerase Protein

Hepatitis B virus (HBV) infection has persisted as a major public health problem due to the lack of an effective treatment for those chronically infected. Therapeutic vaccination holds promise, and targeting HBV polymerase is pivotal for viral eradication. In this research, a computational approach was employed to predict suitable HBV polymerase targeting multi-peptides for vaccine candidate selection. We then performed in-depth computational analysis to evaluate the predicted epitopes’ immunogenicity, conservation, population coverage, and toxicity. Lastly, molecular docking and MHC-peptide complex stabilization assay were utilized to determine the binding energy and affinity of epitopes to the HLA-A0201 molecule. Criteria-based analysis provided four predicted epitopes, RVTGGVFLV, VSIPWTHKV, YMDDVVLGA and HLYSHPIIL. Assay results indicated the lowest binding energy and high affinity to the HLA-A0201 molecule for epitopes VSIPWTHKV and YMDDVVLGA and epitopes RVTGGVFLV and VSIPWTHKV, respectively. Regions 307 to 320 and 377 to 387 were considered to have the highest probability to be involved in B cell epitopes. The T cell and B cell epitopes identified in this study are promising targets for an epitope-focused, peptide-based HBV vaccine, and provide insight into HBV-induced immune response.

In silico-based vaccine design against Ebola virus glycoprotein

Ebola virus (EBOV) is one of the lethal viruses, causing more than 24 epidemic outbreaks to date. Despite having available molecular knowledge of this virus, no definite vaccine or other remedial agents have been developed yet for the management and avoidance of EBOV infections in humans. Disclosing this, the present study described an epitope-based peptide vaccine against EBOV, using a combination of B-cell and T-cell epitope predictions, followed by molecular docking and molecular dynamics simulation approach. Here, protein sequences of all glycoproteins of EBOV were collected and examined via in silico methods to determine the most immunogenic protein. From the identified antigenic protein, the peptide region ranging from 186 to 220 and the sequence HKEGAFFLY from the positions of 154-162 were considered the most potential B-cell and T-cell epitopes, correspondingly. Moreover, this peptide (HKEGAFFLY) interacted with HLA-A*32:15 with the highest binding energy and stability, and also a good conservancy of 83.85% with maximum population coverage. The results imply that the designed epitopes could manifest vigorous enduring defensive immunity against EBOV.

A Perspective on the Development of Plant-Made Vaccines in the Fight against Ebola Virus

The Ebola virus (EBOV) epidemic indicated a great need for prophylactic and therapeutic strategies. The use of plants for the production of biopharmaceuticals is a concept being adopted by the pharmaceutical industry, with an enzyme for human use currently commercialized since 2012 and some plant-based vaccines close to being commercialized. Although plant-based antibodies against EBOV are under clinical evaluation, the development of plant-based vaccines against EBOV essentially remains an unexplored area. The current technologies for the production of plant-based vaccines include stable nuclear expression, transient expression mediated by viral vectors, and chloroplast expression. Specific perspectives on how these technologies can be applied for developing anti-EBOV vaccines are provided, including possibilities for the design of immunogens as well as the potential of the distinct expression modalities to produce the most relevant EBOV antigens in plants considering yields, posttranslational modifications, production time, and downstream processing.

Finding Potential Therapeutic Targets against Shigella flexneri through Proteome Exploration

Background:Shigella flexneri is a gram negative bacteria that causes the infectious disease “shigellosis.” S. flexneri is responsible for developing diarrhea, fever, and stomach cramps in human. Antibiotics are mostly given to patients infected with shigella. Resistance to antibiotics can hinder its treatment significantly. Upon identification of essential therapeutic targets, vaccine and drug could be effective therapy for the treatment of shigellosis.

Methods: The study was designed for the identification and qualitative characterization for potential drug targets from S. flexneri by using the subtractive proteome analysis. A set of computational tools were used to identify essential proteins those are required for the survival of S. flexneri. Total proteome (13,503 proteins) of S. flexneri was retrieved from NCBI and further analyzed by subtractive channel analysis. After identification of the metabolic proteins we have also performed its qualitative characterization to pave the way for the identification of promising drug targets.

Results: Subtractive analysis revealed that a list of 53 targets of S. flexneri were human non-homologous essential metabolic proteins that might be used for potential drug targets. We have also found that 11 drug targets are involved in unique pathway. Most of these proteins are cytoplasmic, can be used as broad spectrum drug targets, can interact with other proteins and show the druggable properties. The functionality and drug binding site analysis suggest a promising effective way to design the new drugs against S. flexneri.

Conclusion: Among the 53 therapeutic targets identified through this study, 13 were found highly potential as drug targets based on their physicochemical properties whilst only one was found as vaccine target against S. flexneri. The outcome might also be used as module as well as circuit design in systems biology.