A novel strategy of epitope design in Neisseria gonorrhoeae

Reverse vaccinology approaches to introduce promising immunogenic and drug targets against antibiotic-resistant Neisseria gonorrhoeae: Thinking outside the box in current prevention and treatment

Gonorrhea is an urgent antimicrobial resistance threat and its therapeutic options are continuously getting restricted. Moreover, no vaccine has been approved against it so far. Hence, the present study aimed to introduce novel immunogenic and drug targets against antibiotic-resistant Neisseria gonorrhoeae strains. In the first step, the core proteins of 79 complete genomes of N. gonorrhoeae were retrieved. Next, the surface-exposed proteins were evaluated from different aspects such as antigenicity, allergenicity, conservancy, and B-cell and T-cell epitopes to introduce promising immunogenic candidates. Then, the interactions with human Toll-like receptors (TLR-1, 2, and 4), and immunoreactivity to elicit humoral and cellular immune responses were simulated. On the other hand, to identify novel broad-spectrum drug targets, the cytoplasmic and essential proteins were detected. Then, the N. gonorrhoeae metabolome-specific proteins were compared to the drug targets of the DrugBank, and novel drug targets were retrieved. Finally, the protein data bank (PDB) file availability and prevalence among the ESKAPE group and common sexually transmitted infection (STI) agents were assessed. Our analyses resulted in the recognition of ten novel and putative immunogenic targets including murein transglycosylase A, PBP1A, Opa, NlpD, Azurin, MtrE, RmpM, LptD, NspA, and TamA. Moreover, four potential and broad-spectrum drug targets were identified including UMP kinase, GlyQ, HU family DNA-binding protein, and IF-1. Some of the shortlisted immunogenic and drug targets have confirmed roles in adhesion, immune evasion, and antibiotic resistance that can induce bactericidal antibodies. Other immunogenic and drug targets might be associated with the virulence of N. gonorrhoeae as well. Thus, further experimental studies and site-directed mutations are recommended to investigate the role of potential vaccine and drug targets in the pathogenesis of N. gonorrhoeae.

Immunoinformatics Vaccine Design for Zika Virus

Zika virus (ZIKV) is an emerging virus from the Flaviviridae family and Flavivirus genus that has caused important outbreaks around the world. ZIKV infection is associated with severe neuropathology in newborns and adults. Until now, there is no licensed vaccine available for ZIKV infection. Therefore, the development of a safe and effective vaccine against ZIKV is an urgent need. Recently, we designed an in silico multi-epitope vaccine for ZIKV based on immunoinformatics tools. To construct this in silico ZIKV vaccine, we used a consensus sequence generated from ZIKV sequences available in databank. Then, we selected CD4+ and CD8+ T cell epitopes from all ZIKV proteins based on the binding prediction to class II and class I human leukocyte antigen (HLA) molecules, promiscuity, and immunogenicity. ZIKV Envelope protein domain III (EDIII) was added to the construct and B cell epitopes were identified. Adjuvants were associated to increase immunogenicity. Distinct linkers were used for connecting the CD4+ and CD8+ T cell epitopes, EDIII, and adjuvants. Several analyses, such as antigenicity, population coverage, allergenicity, autoimmunity, and secondary and tertiary structures of the vaccine, were evaluated using various immunoinformatics tools and online web servers. In this chapter, we present the protocols with the rationale and detailed steps needed for this in silico multi-epitope ZIKV vaccine design.

Immunoinformatic-guided designing of multi-epitope vaccine construct against Brucella Suis 1300

Brucella suis mediates the transmission of brucellosis in humans and animals and a significant facultative zoonotic pathogen found in livestock. It has the capacity to survive and multiply in a phagocytic environment and to acquire resistance under hostile conditions thus becoming a threat globally. Antibiotic resistance is posing a substantial public health threat, hence there is an unmet and urgent clinical need for immune-based non-antibiotic methods to treat brucellosis. Hence, we aimed to explore the whole proteome of Brucella suis to predict antigenic proteins as a vaccine target and designed a novel chimeric vaccine (multi-epitope vaccine) through subtractive genomics-based reverse vaccinology approaches. The applied subsequent hierarchical shortlisting resulted in the identification of Multidrug efflux Resistance-nodulation-division (RND) transporter outer membrane subunit (gene BepC) that may act as a potential vaccine target. T-cell and B-cell epitopes have been predicted from target proteins using a number of immunoinformatic methods. Six MHC I, ten MHC II, and four B-cell epitopes were used to create a 324-amino-acid MEV construct, which was coupled with appropriate linkers and adjuvant. To boost the immunological response to the vaccine, the vaccine was combined with the TLR4 agonist HBHA protein. The MEV structure predicted was found to be highly antigenic, non-toxic, non-allergenic, flexible, stable, and soluble. To confirm the interactions with the receptors, a molecular docking simulation of the MEV was done using the human TLR4 (toll-like receptor 4) and HLAs. The stability and binding of the MEV-docked complexes with TLR4 were assessed using molecular dynamics (MD) simulation. Finally, MEV was reverse translated, its cDNA structure was evaluated, and then, in silico cloning into an E. coli expression host was conducted to promote maximum vaccine protein production with appropriate post-translational modifications. These comprehensive computer calculations backed up the efficacy of the suggested MEV in protecting against B. suis infections. However, more experimental validations are needed to adequately assess the vaccine candidate's potential. HIGHLIGHTS: • Subtractive genomic analysis and reverse vaccinology for the prioritization of novel vaccine target • Examination of chimeric vaccine in terms of allergenicity, antigenicity, MHC I, II binding efficacy, and structural-based studies • Molecular docking simulation method to rank based vaccine candidate and understand their binding modes.

Immunoinformatic design of a putative multi-epitope vaccine candidate against Trypanosoma brucei gambiense

Human African trypanosomiasis (HAT) is a neglected tropical disease that is caused by flagellated parasites of the genus Trypanosoma. HAT imposes a significant socio-economic burden on many countries in sub-Saharan Africa and its control is hampered by several drawbacks ranging from the ineffectiveness of drugs, complex dosing regimens, drug resistance, and lack of a vaccine. Despite more than a century of research and investigations, the development of a vaccine to tackle HAT is still challenging due to the complex biology of the pathogens. Advancements in computational modeling coupled with the availability of an unprecedented amount of omics data from different organisms have allowed the design of new generation vaccines that offer better antigenicity and safety profile. One of such new generation approaches is a multi-epitope vaccine (MEV) designed from a collection of antigenic peptides. A MEV can stimulate both cellular and humoral immune responses as well as avoiding possible allergenic reactions. Herein, we take advantage of this approach to design a MEV from conserved hypothetical plasma membrane proteins of Trypanosoma brucei gambiense, the trypanosome subspecies that is responsible for the west and central African forms of HAT. The designed MEV is 402 amino acids long (41.5 kDa). It is predicted to be antigenic, non-toxic, to assume a stable 3D conformation, and to interact with a key immune receptor. In addition, immune simulation foresaw adequate immune stimulation by the putative antigen and a lasting memory. Therefore, the designed chimeric vaccine represents a potential candidate that could be used to target HAT.

Identification of vaccine and drug targets in Shigella dysenteriae sd197 using reverse vaccinology approach

Shigellosis is characterized as diarrheal disease that causes a high mortality rate especially in children, elderly and immunocompromised patients. More recently, the World Health Organization advised safe vaccine designing against shigellosis due to the emergence of Shigella dysenteriae resistant strains. Therefore, the aim of this study is to identify novel drug targets as well as the design of the potential vaccine candidates and chimeric vaccine models against Shigella dysenteriae. A computational based Reverse Vaccinology along with subtractive genomics analysis is one of the robust approaches used for the prioritization of drug targets and vaccine candidates through direct screening of genome sequence assemblies. Herein, a successfully designed peptide-based novel highly antigenic chimeric vaccine candidate against Shigella dysenteriae sd197 strain is proposed. The study resulted in six epitopes from outer membrane WP_000188255.1 (Fe (3+) dicitrate transport protein FecA) that ultimately leads to the construction of twelve vaccine models. Moreover, V9 construct was found to be highly immunogenic, non-toxic, non-allergenic, highly antigenic, and most stable in terms of molecular docking and simulation studies against six HLAs and TLRS/MD complex. So far, this protein and multiepitope have never been characterized as vaccine targets against Shigella dysenteriae. The current study proposed that V9 could be a significant vaccine candidate against shigellosis and to ascertain that further experiments may be applied by the scientific community focused on shigellosis.

In Silico Modeling as a Perspective in Developing Potential Vaccine Candidates and Therapeutics for COVID-19

The potential of computational models to identify new therapeutics and repurpose existing drugs has gained significance in recent times. The current ‘COVID-19’ pandemic caused by the new SARS CoV2 virus has affected over 200 million people and caused over 4 million deaths. The enormity and the consequences of this viral infection have fueled the research community to identify drugs or vaccines through a relatively expeditious process. The availability of high-throughput datasets has cultivated new strategies for drug development and can provide the foundation towards effective therapy options. Molecular modeling methods using structure-based or computer-aided virtual screening can potentially be employed as research guides to identify novel antiviral agents. This review focuses on in-silico modeling of the potential therapeutic candidates against SARS CoVs, in addition to strategies for vaccine design. Here, we particularly focus on the recently published SARS CoV main protease (Mpro) active site, the RNA-dependent RNA polymerase (RdRp) of SARS CoV2, and the spike S-protein as potential targets for vaccine development. This review can offer future perspectives for further research and the development of COVID-19 therapies via the design of new drug candidates and multi-epitopic vaccines and through the repurposing of either approved drugs or drugs under clinical trial.

Identification and Design of a Next-Generation Multi Epitopes Bases Peptide Vaccine Candidate Against Prostate Cancer: An In Silico Approach

Prostate cancer (PCa) is the second most diagnosed cancer in men and ranked fifth in overall cancer diagnosis. During the past decades, it has arisen as a significant life-threatening disease in men at an older age. At the early onset of illness when it is in localized form, radiation and surgical treatments are applied against this disease. In case of adverse situations androgen deprivation therapy, chemotherapy, hormonal therapy, etc. are widely used as a therapeutic element. However, studies found the occurrences of several side effects after applying these therapies. In current work, several immunoinformatic techniques were applied to formulate a multi-epitopic vaccine from the overexpressed antigenic proteins of PCa. A total of 13 epitopes were identified from the five prostatic antigenic proteins (PSA, PSMA, PSCA, STEAP, and PAP), after validation with several in silico tools. These epitopes were fused to form a vaccine element by (GGGGS)3 peptide linker. Afterward, 5, 6-dimethylxanthenone-4-acetic acid (DMXAA) was used as an adjuvant to initiate and induce STING-mediated cytotoxic cascade. In addition, molecular docking was performed between the vaccine element and HLA class I antigen with the low ACE value of -251 kcal/mol which showed a significant binding. Molecular simulation using normal mode analysis (NMA) illustrated the docking complex as a stable one. Therefore, this observation strongly indicated that our multi epitopes bases peptide vaccine molecule will be an effective candidate for the treatment of the PCa.

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.

Contriving Multi-Epitope Subunit of Vaccine for COVID-19: Immunoinformatics Approaches

COVID-19 has recently become the most serious threat to public health, and its prevalence has been increasing at an alarming rate. The incubation period for the virus is ~1-14 days and all age groups may be susceptible to a fatality rate of about 5.9%. COVID-19 is caused by a novel single-stranded, positive (+) sense RNA beta coronavirus. The development of a vaccine for SARS-CoV-2 is an urgent need worldwide. Immunoinformatics approaches are both cost-effective and convenient, as in silico predictions can reduce the number of experiments needed. In this study, with the aid of immunoinformatics tools, we tried to design a multi-epitope vaccine that can be used for the prevention and treatment of COVID-19. The epitopes were computed by using B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL) base on the proteins of SARS-CoV-2. A vaccine was devised by fusing together the B cell, HTL, and CTL epitopes with linkers. To enhance the immunogenicity, the β-defensin (45 mer) amino acid sequence, and pan-HLA DR binding epitopes (13aa) were adjoined to the N-terminal of the vaccine with the help of the EAAAK linker. To enable the intracellular delivery of the modeled vaccine, a TAT sequence (11aa) was appended to C-terminal. Linkers play vital roles in producing an extended conformation (flexibility), protein folding, and separation of functional domains, and therefore, make the protein structure more stable. The secondary and three-dimensional (3D) structure of the final vaccine was then predicted. Furthermore, the complex between the final vaccine and immune receptors (toll-like receptor-3 (TLR-3), major histocompatibility complex (MHC-I), and MHC-II) were evaluated by molecular docking. Lastly, to confirm the expression of the designed vaccine, the mRNA of the vaccine was enhanced with the aid of the Java Codon Adaptation Tool, and the secondary structure was generated from Mfold. Then we performed in silico cloning. The final vaccine requires experimental validation to determine its safety and efficacy in controlling SARS-CoV-2 infections.

A systematic strategy for the investigation of vaccines and drugs targeting bacteria

Infectious and epidemic diseases induced by bacteria have historically caused great distress to people, and have even resulted in a large number of deaths worldwide. At present, many researchers are working on the discovery of viable drug and vaccine targets for bacteria through multiple methods, including the analyses of comparative subtractive genome, core genome, replication-related proteins, transcriptomics and riboswitches, which plays a significant part in the treatment of infectious and pandemic diseases. The 3D structures of the desired target proteins, drugs and epitopes can be predicted and modeled through target analysis. Meanwhile, molecular dynamics (MD) analysis of the constructed drug/epitope-protein complexes is an important standard for testing the suitability of these screened drugs and vaccines. Currently, target discovery, target analysis and MD analysis are integrated into a systematic set of drug and vaccine analysis strategy for bacteria. We hope that this comprehensive strategy will help in the design of high-performance vaccines and drugs.

Multi-epitope based vaccine against yellow fever virus applying immunoinformatics approaches

Yellow fever disease is considered a re-emerging major health issue which has caused recent outbreaks with a high number of deaths. Tropical countries, mainly African and South American, are the most affected by Yellow fever outbreaks. Despite the availability of an attenuated vaccine, its use is limited for some groups such as pregnant and nursing women, immunocompromised and immunosuppressed patients, elderly people >65 years, infants <6 months and patients with biological disorders like thymus disorders. In order to achieve new preventive measures, we applied immunoinformatics approaches to develop a multi-epitope-based subunit vaccine for Yellow fever virus. Different epitopes, related to humoral and cell-mediated immunity, were predicted for complete polyproteins of two Yellow fever strains (Asibi and 17 D vaccine). Those epitopes common for both strains were mapped into a set of 137 sequences of Yellow fever virus, including 77 sequences from a recent outbreak at the state of Minas Gerais, southeast Brazil. Therefore, the present work uses robust bioinformatics approaches for the identification of a multi-epitope vaccine against the Yellow fever virus. Our results indicate that the identified multi-epitope vaccine might stimulate humoral and cellular immune responses and could be a potential vaccine candidate against Yellow fever virus infection. Hence, it should be subjected to further experimental validations. Communicated by Ramaswamy H. Sarma.

Immunoinformatics design of a novel multi-epitope peptide vaccine to combat multi-drug resistant infections caused by Vibrio vulnificus

Multi-drug resistant Vibrio vulnificus is a Gram-negative bacillus responsible for diseases, such as: sepsis, septicemia, gastroenteritis, and fatal necrotizing fasciitis in humans. The treatment and prevention of V. vulnificus infections are challenging because of resistance to antibiotics and the non-availability of a licensed vaccine. Considering this, an in-silico based approach comprising subtractive proteomics, immunoinformatics, molecular docking, and dynamics simulation studies is applied herein to identify potential epitope vaccine candidates for the mentioned pathogen. Two potential vaccine candidates: vibC and flgL are filtered based on essentiality, outer membrane localization, virulence, antigenic, pathway mapping, and cellular protein-protein network analysis. Using immunoinformatic tools, 9-mer B-cell derived T-cell antigenic epitopes are predicted for the said shortlisted two proteins that are demonstrating excellent affinity for predominant HLA allele (DRB1*0101) in human population. Screened peptides are used further in multi-epitope peptide designing and linked to an adjuvant to enhance the immunogenic properties of the designed construct. Furthermore, the construct was docked blindly to TLR4 immune receptor, and analyzed in conformational dynamics simulation to decipher the complex affinity and understand time dependent behavior, respectively. We expect this designed in silico construct to be useful for vaccinologists to evaluate its immune protective efficacy in in vivo animal models.

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.

Contriving multiepitope subunit vaccine by exploiting structural and nonstructural viral proteins to prevent Epstein-Barr virus-associated malignancy

Cancer is one of the common lifestyle diseases and is considered to be the leading cause of death worldwide. Epstein-Barr virus (EBV)-infected individuals remain asymptomatic; but under certain stress conditions, EBV may lead to the development of cancers such as Burkitt's and Hodgkin's lymphoma and nasopharyngeal carcinoma. EBV-associated cancers result in a large number of deaths in Asian and African population, and no effective cure has still been developed. We, therefore, tried to devise a subunit vaccine with the help of immunoinformatic approaches that can be used for the prevention of EBV-associated malignancies. The epitopes were predicted through B-cell, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL) from the different oncogenic proteins of EBV. A vaccine was designed by combining the B-cell and T-cell (HTL and CTL) epitopes through linkers, and for the enhancement of immunogenicity, an adjuvant was added at the N-terminal. Further, homology modeling was performed to generate the 3D structure of the designed vaccine. Moreover, molecular docking was performed between the designed vaccine and immune receptor (TLR-3) to determine the interaction between the final vaccine construct and the immune receptor complex. In addition, molecular dynamics was performed to analyze the stable interactions between the ligand final vaccine model and receptor TLR-3 molecule. Lastly, to check the expression of our vaccine construct, we performed in silico cloning. This study needed experimental validation to ensure its effectiveness and potency to control malignancy.

Subtractive proteomics to identify novel drug targets and reverse vaccinology for the development of chimeric vaccine against Acinetobacter baumannii

The emergence of drug-resistant Acinetobacter baumannii is the global health problem associated with high mortality and morbidity. Therefore it is high time to find a suitable therapeutics for this pathogen. In the present study, subtractive proteomics along with reverse vaccinology approaches were used to predict suitable therapeutics against A. baumannii. Using subtractive proteomics, we have identified promiscuous antigenic membrane proteins that contain the virulence factors, resistance factors and essentiality factor for this pathogenic bacteria. Selected promiscuous targeted membrane proteins were used for the design of chimeric-subunit vaccine with the help of reverse vaccinology. Available best tools and servers were used for the identification of MHC class I, II and B cell epitopes. All selected epitopes were further shortlisted computationally to know their immunogenicity, antigenicity, allergenicity, conservancy and toxicity potentials. Immunogenic predicted promiscuous peptides used for the development of chimeric subunit vaccine with immune-modulating adjuvants, linkers, and PADRE (Pan HLA-DR epitopes) amino acid sequence. Designed vaccine construct V4 also interact with the MHC, and TLR4/MD2 complex as confirm by docking and molecular dynamics simulation studies. Therefore designed vaccine construct V4 can be developed to control the host-pathogen interaction or infection caused by A. baumannii.

A novel approach of virulome based reverse vaccinology for exploring and validating peptide-based vaccine candidates against the most troublesome nosocomial pathogen: Acinetobacter baumannii

Acinetobacter baumannii is one of the major cause of nosocomial infections around the globe. The emergence of hyper-virulent strains of the pathogen greatly narrows down therapeutic options for patients infected with this red alert superbug. Development of a peptide-based vaccine can offers an alternative, attractive, and cost-effective remedy for multidrug-resistant A. baumannii associated complications. Herein, we introduced a novel virulome based Reverse Vaccinology for screening peptide based vaccine candidates against A. baumannii and its validation using a negative control. The pipeline screened "FYLNDQPVS" of polysaccharide export outer membrane protein (EpsA) and "LQNNTRRMK" of chaperone-usher pathway protein B (CsuB) as broad-spectrum peptides for induction of targeted immune responses. The 9-mer epitope of both proteins was rendered virulent, antigenic, non-allergen, and highly conserved among thirty-four completely annotated strains. Interactome examination unravels peptides protein direct and indirect interactions with biological significant pathways, essential for A. baumannii pathogenesis and survival. Protein-peptide docking aids in addition by unveiling deep binding of the epitopes in the active site of the most prevalent binding allele in the human population-the DRB1*0101. Both the proteins till to date are not characterized for immunoprotective efficacy and desirable to be deciphered experimentally. The designed series of in silico filters rejected few recently reported peptide and non-peptide vaccine targets and has delivered outcomes, which we believe will enrich the existing knowledge of vaccinology against this life-threatening human pathogen.

In silico prediction of cancer immunogens: current state of the art

Cancer kills 8 million annually worldwide. Although survival rates in prevalent cancers continue to increase, many cancers have no effective treatment, prompting the search for new and improved protocols. Immunotherapy is a new and exciting addition to the anti-cancer arsenal. The successful and accurate identification of aberrant host proteins acting as antigens for vaccination and immunotherapy is a key aspiration for both experimental and computational research. Here we describe key elements of in silico prediction, including databases of cancer antigens and bleeding-edge methodology for their prediction. We also highlight the role dendritic cell vaccines can play and how they can act as delivery mechanisms for epitope ensemble vaccines. Immunoinformatics can help streamline the discovery and utility of Cancer Immunogens.

Excavating chikungunya genome to design B and T cell multi-epitope subunit vaccine using comprehensive immunoinformatics approach to control chikungunya infection

Chikungunya infection has been a cause of countless deaths worldwide. Due to lack of permanent treatment and prevention of this disease, the mortality rate remains very high. Therefore, we followed an immunoinformatics approach for the development of multi-epitope subunit vaccine which is able to elucidate humoral, cell-mediated and innate immune responses inside the host body. Both structural and non-structural proteins of chikungunya virus were utilized for prediction of B-cell and T-cell binding epitopes along with interferon-γ (IFN-γ) inducing epitopes. The vaccine construct is composed of β-defensin as an adjuvant at the N-terminal followed by Cytotoxic T-Lymphocytes (CTL) and Helper T-Lymphocyte (HTL) epitopes. The same vaccine construct was also utilized for the prediction of B-cell binding epitopes and IFN-γ inducing epitopes. This was followed by the 3D model generation, refinement and validation of the vaccine construct. Later on, the interaction of modeled vaccine with the innate immune receptor (TLR-3) was explored by performing molecular docking and molecular dynamics simulation studies. Also to check the efficiency of expression of this vaccine construct in an expression vector, in silico cloning was performed at the final stage of vaccine development. Further, designed multi-epitope subunit vaccine necessitates experimental and clinical investigation to develop as an immunogenic vaccine candidate.

In silico prediction of monovalent and chimeric tetravalent vaccines for prevention and treatment of dengue fever

Reverse vaccinology method was used to predict the monovalent peptide vaccine candidate to produce antibodies for therapeutic purpose and to predict tetravalent vaccine candidate to act as a common vaccine to cover all the fever dengue virus serotypes. Envelope (E)-proteins of DENV-1-4 serotypes were used for vaccine prediction using NCBI, Uniprot/Swissprot, Swiss-prot viewer, VaxiJen V2.0, TMHMM, BCPREDS, Propred-1, Propred and MHC Pred,. E-proteins of DENV-1-4 serotypes were identified as antigen from which T cell epitopes, through B cell epitopes, were predicted to act as peptide vaccine candidates. Each selected T cell epitope of E-protein was confirmed to act as vaccine and to induce complementary antibody against particular serotype of dengue virus. Chimeric tetravalent vaccine was formed by the conjugation of four vaccines, each from four dengue serotypes to act as a common vaccine candidate for all the four dengue serotypes. It can be justifiably concluded that the monovalent 9-mer T cell epitope for each DENV serotypes can be used to produce specific antibody agaomst dengue virus and a chimeric common tetravalent vaccine candidate to yield a comparative vaccine to cover any of the four dengue virus serotype. This vaccine is expected to act as highly immunogenic against preventing dengue fever.

Identification of potential antigens from non-classically secreted proteins and designing novel multitope peptide vaccine candidate against Brucella melitensis through reverse vaccinology and immunoinformatics approach

Brucella melitensis is an intracellular pathogen resides in the professional and non-professional phagocytes of the host, causing zoonotic disease brucellosis. The stealthy nature of the Brucella makes it's highly pathogenic, and it is hard to eliminate the bacteria completely from the infected host. Hitherto, no licensed vaccines are available for human brucellosis. In this study, we identified potential antigens for vaccine development from non-classically secreted proteins through reverse vaccinology approach. Based on the systemic screening of non-classically secreted proteins of B. melitensis 16M, we identified nine proteins as potential vaccine candidates. Among these, Omp31 and Omp22 are known immunogens, and its role in the virulence of Brucella is known. Roles of other proteins in the pathogenesis are yet to be studied. From the nine proteins, we identified six novel antigenic epitopes that can elicit both B-cell and T-cell immune responses. Among the nine proteins, the epitopes were predicted from Omp31 immunogenic protein precursor, Omp22 protein precursor, extracellular serine protease, hypothetical membrane-associated protein, iron-regulated outer membrane protein FrpB. Further, we designed a multitope vaccine using Omp31 immunogenic protein precursor, Omp22 protein precursor, extra cellular serine protease, iron-regulated outer membrane protein FrpB, hypothetical membrane-associated protein, and LPS-assembly protein LptD and polysaccharide export protein identified in the previous study. Epitopes were joined using amino acid linkers such as EAAAK and GPGPG. Cholera toxin subunit B, the nontoxic part of cholera toxin, was used as an adjuvant and it was linked to the N-terminal of the multitope vaccine candidate. The designed vaccine candidate was modeled, validated and the physicochemical properties were analyzed. Results revealed that the vaccine candidate is soluble, stable, non-allergenic, antigenic and 87% of residues of the designed vaccine candidate is located in the favored region. In conclusion, the computational analysis showed that the newly designed multitope protein could be used to develop a promising vaccine for human brucellosis.

Exploring dengue genome to construct a multi-epitope based subunit vaccine by utilizing immunoinformatics approach to battle against dengue infection

Dengue is considered as a major health issue which causes a number of deaths worldwide each year; tropical countries are majorly affected by dengue outbreaks. It is considered as life threatening issue because, since many decades not a single effective approach for treatment and prevention of dengue has been developed. Therefore, to find new preventive measure, we used immunoinformatics approaches to develop a multi-epitope based subunit vaccine for dengue which can generate various immune responses inside the host. Different B-cell, TC cell, and TH cell binding epitopes were predicted for structural and non-structural proteins of dengue virus. Final vaccine constructs consisting of TC and TH cell epitopes and an adjuvant (β-defensin) at N-terminal of the construct. Presence of B-cell and IFN-γ inducing epitopes confirms the humoral and cell mediated immune response developed by designed vaccine. Designed vaccine was not found allergic and was potentially antigenic in nature. Modeling of tertiary structure and the refined model was used for molecular docking with TLR-3 (immune receptor). Molecular docking and dynamics simulation confirms the microscopic interactions between ligand and receptor. In silico cloning approach was used to ensure the expression and translation efficiency of vaccine within an expression vector.

In silico structure analysis and epitope prediction of E3 CR1-beta protein of Human Adenovirus E for vaccine design

BACKGROUND

Human Adenoviruses are divided into 7 species of Human Adenovirus A to G based on DNA genome homology. The Human Adenovirus E (HAdVs-E) genome is a linear, double-stranded DNA containing 38 protein-coding genes. Wild-type adenoviruses type E, are linked to a number of slight illnesses. The most important part of HAdVs-E is E3 CR1-beta protein which controls the host immune response and viral attachment.

METHOD

We use numerous bio-informatics and immuno-informatics implements comprising sequence and construction tools for construction of 3D model and epitope prediction for HAdVs-E.

RESULTS

The 3D structure of E3 CR1-beta protein was generated and total of ten antigenic B cell epitopes, 6 MHC class I and 11 MHC class II binding peptides were predicted.

CONCLUSION

The study was carried out to predict antigenic determinants/epitopes of the E3 CR1-beta protein of Human Adenovirus E along with the 3D protein modeling. The study revealed potential T-cell and B-cell epitopes that can raise the desired immune response against E3 CR1-beta protein and useful in developing effective vaccines against HAdVs-E.

In-silico Hierarchical Approach for the Identification of Potential Universal Vaccine Candidates (PUVCs) from Neisseria gonorrhoeae

OBJECTIVES

Resistance to the currently recommended extended-spectrum cephalosporins, which is used to treat Gonorrhea, is increasing continuously and leading to a threat of untreatable infection. It is, therefore, becoming extremely essential to search for new therapeutic strategies to control Gonorrhea. Vaccination may be considered as an effective control measure to control this disease, which is caused by Neisseria gonorrhoeae.

METHODS

In-silico hierarchical approach was used to help identify candidate proteins of N. gonorrhoeae that might contribute significantly in vaccine research. In contrast to the conventional vaccine research which requires at least 10-12 years, the present approach would reduce the time period drastically and help to identify Potential Universal Vaccine Candidates (PUVCs). These proteins were further analyzed for the presence of T-cell and linear B-cell epitopes, by using HLAPred and ABCpred servers respectively, in order to facilitate the identification of Multi Epitope Peptide Vaccine Constructs.

RESULTS

We have identified 23 non-host candidate proteins, using the proteomic information of four sequenced strains of N. gonorrhoeae namely FA 1090, TCDC_NG08107, NCCP11945 and MS11 and labeled them as PUVCs. Since all these identified 23 PUVCs contained both T cell and B cell epitopes, these have been further reiterated as PUVCs which could be used as promising leads for vaccine development.

CONCLUSIONS

This hierarchical approach is the first comprehensive study to identify potential vaccine candidates which once utilized for vaccine development would surely serve as promising tools for effective control of Gonorrhea.

Implications from predicted B-cell and T-cell epitopes of Plasmodium falciparum merozoite proteins EBA175-RII and Rh5

The leading circumsporozoite protein (CSP) based malaria vaccine, RTS,S, though promising, has shown limited efficacy in field studies. There is therefore, still a need to identify other malaria vaccine targets. Merozoite antigens are potential vaccine candidates, since naturally acquired antibodies generated against them inhibit erythrocyte invasion and in some cases result in the clinical protection from disease. We thus used in silico tools (BCPreds, NetMHCcons and NetMHCIIpan 3.0) to predict B-cell epitopes (BCEs) and T-cell epitopes (TCEs) in two merozoite invasion proteins, EBA175-RII and Rh5. Initially, we validated these tools using CSP to determine whether the algorithms could predict the epitopes in the RTS,S vaccine. In EBA175-RII, we prioritised three BCEs 15REKRKGMKWDCKKKNDRSNY34, 420SNRKLVGKINTNSNYVHRNKQ440 and 528WISKKKEEYNKQAKQYQEYQ547, a CD8+ epitope 553KMYSEFKSI561 and a CD4+ epitope 440QNDKLFRDEWWK VIKKD456. Three Rh5 epitopes were prioritised, a BCE 344SCYNNNFCNTNGIRYHYDEY363, a CD8+ epitope 198STYGKCIAV206 and a Rh5 CD4+ epitope 180TFLDYYKHLSYNSIYHKSSTY200. All these epitopes are in the region involved in the proteins' interaction with their erythrocyte receptors, thus enabling erythrocyte invasion. Therefore, upon validation of their immunogenicity, by ELISA using serum from a malaria endemic population, antibodies to these epitopes may inhibit erythrocyte invasion. All the epitopes we predicted in EBA175-RII and Rh5 are novel. We also identified polymorphic epitopes that may escape host immunity, as some variants were not predicted as epitopes, suggesting that they may not be immunogenic regions. We present a set of epitopes that following in vitro validation provide a set of molecules to screen as potential vaccine candidates.

Novel Vaccine Candidates against Brucella melitensis Identified through Reverse Vaccinology Approach

Global health therapeutics is a rapidly emerging facet of postgenomics medicine. In this connection, Brucella melitensis is an intracellular bacterium that causes the zoonotic infectious disease, brucellosis. Presently, no licensed vaccines are available for human brucellosis. Here, we report the identification of potential vaccine candidates against B. melitensis using a reverse vaccinology approach. Based on a systematic screening of exoproteome and secretome of B. melitensis 16 M, we identified eight proteins as potential vaccine candidates, including LPS-assembly protein LptD, a polysaccharide export protein, a cell surface protein, heme transporter BhuA, flagellin FliC, 7-alpha-hydroxysteroid dehydrogenase, immunoglobulin-binding protein EIBE, and hemagglutinin. Among these, the roles of BhuA and hemagglutinin in the virulence of Brucella are essential to establish infection. Roles of other proteins in the virulence are yet to be studied. Prediction of protein-protein interactions revealed that these proteins can interact with other proteins involved in virulence, secretion system, metabolism, and transport. From these eight potential vaccine candidates, we predicted three surface exposed novel antigenic epitopes that can induce both B-cell and T-cell immune responses. These peptides can be used for the development of either exclusive peptide vaccines or multi-component vaccines against human brucellosis. Reverse vaccinology is an important strategy for discovery of novel global health therapeutics.

Identification of putative vaccine candidates against Helicobacter pylori exploiting exoproteome and secretome: a reverse vaccinology based approach

Helicobacter pylori (H. pylori) is an important pathogen associated with diverse gastric disorders ranging from peptic ulcer to malignancy. It has also been recognized by the World Health Organization (WHO) as class I carcinogen. Conventional treatment regimens for H. pylori seem to be ineffective, possibly due to antibiotic resistance mechanisms acquired by the pathogen. In this study we have successfully employed a reverse vaccinology approach to predict the potential vaccine candidates against H. pylori. The predicted potential vaccine candidates include vacA, babA, sabA, fecA and omp16. Host-pathogen interactions analysis elaborated their direct or indirect role in the specific signaling pathways including epithelial cell polarity, metabolism, secretion system and transport. Furthermore, surface-exposed antigenic epitopes were predicted and analyzed for conservation among 39 complete genomes of H. pylori (Genbank) for all the candidate proteins. These epitopes may serve as a base for the development of broad spectrum peptide or multi-component vaccines against H. pylori. We also believe that the proposed pipeline can be extended to other pathogens and for the identification of novel candidates for the development of effective vaccines.

Genome informatics and vaccine targets in Corynebacterium urealyticum using two whole genomes, comparative genomics, and reverse vaccinology

BACKGROUND

Corynebacterium urealyticum is an opportunistic pathogen that normally lives on skin and mucous membranes in humans. This high Gram-positive bacteria can cause acute or encrusted cystitis, encrusted pyelitis, and pyelonephritis in immunocompromised patients. The bacteria is multi-drug resistant, and knowledge about the genes that contribute to its virulence is very limited. Two complete genome sequences were used in this comparative genomic study: C. urealyticum DSM 7109 and C. urealyticum DSM 7111.

RESULTS

We used comparative genomics strategies to compare the two strains, DSM 7109 and DSM 7111, and to analyze their metabolic pathways, genome plasticity, and to predict putative antigenic targets. The genomes of these two strains together encode 2,115 non-redundant coding sequences, 1,823 of which are common to both genomes. We identified 188 strain-specific genes in DSM 7109 and 104 strain-specific genes in DSM 7111. The high number of strain-specific genes may be a result of horizontal gene transfer triggered by the large number of transposons in the genomes of these two strains. Screening for virulence factors revealed the presence of the spaDEF operon that encodes pili forming proteins. Therefore, spaDEF may play a pivotal role in facilitating the adhesion of the pathogen to the host tissue. Application of the reverse vaccinology method revealed 19 putative antigenic proteins that may be used in future studies as candidate drug or vaccine targets.

CONCLUSIONS

The genome features and the presence of virulence factors in genomic islands in the two strains of C. urealyticum provide insights in the lifestyle of this opportunistic pathogen and may be useful in developing future therapeutic strategies.

Emerging Vaccine Technologies

Vaccination has proven to be an invaluable means of preventing infectious diseases by reducing both incidence of disease and mortality. However, vaccines have not been effectively developed for many diseases including HIV-1, hepatitis C virus (HCV), tuberculosis and malaria, among others. The emergence of new technologies with a growing understanding of host-pathogen interactions and immunity may lead to efficacious vaccines against pathogens, previously thought impossible.

Designing vaccines for the twenty-first century society

The history of vaccination clearly demonstrates that vaccines have been highly successful in preventing infectious diseases, reducing significantly the incidence of childhood diseases and mortality. However, many infections are still not preventable with the currently available vaccines and they represent a major cause of mortality worldwide. In the twenty-first century, the innovation brought by novel technologies in antigen discovery and formulation together with a deeper knowledge of the human immune responses are paving the way for the development of new vaccines. Final goal will be to rationally design effective vaccines where conventional approaches have failed.

Model for vaccine design by prediction of B-epitopes of IEDB given perturbations in peptide sequence, in vivo process, experimental techniques, and source or host organisms

Perturbation methods add variation terms to a known experimental solution of one problem to approach a solution for a related problem without known exact solution. One problem of this type in immunology is the prediction of the possible action of epitope of one peptide after a perturbation or variation in the structure of a known peptide and/or other boundary conditions (host organism, biological process, and experimental assay). However, to the best of our knowledge, there are no reports of general-purpose perturbation models to solve this problem. In a recent work, we introduced a new quantitative structure-property relationship theory for the study of perturbations in complex biomolecular systems. In this work, we developed the first model able to classify more than 200,000 cases of perturbations with accuracy, sensitivity, and specificity >90% both in training and validation series. The perturbations include structural changes in >50000 peptides determined in experimental assays with boundary conditions involving >500 source organisms, >50 host organisms, >10 biological process, and >30 experimental techniques. The model may be useful for the prediction of new epitopes or the optimization of known peptides towards computational vaccine design.

Exoproteome and secretome derived broad spectrum novel drug and vaccine candidates in Vibrio cholerae targeted by Piper betel derived compounds

Vibrio cholerae is the causal organism of the cholera epidemic, which is mostly prevalent in developing and underdeveloped countries. However, incidences of cholera in developed countries are also alarming. Because of the emergence of new drug-resistant strains, even though several generic drugs and vaccines have been developed over time, Vibrio infections remain a global health problem that appeals for the development of novel drugs and vaccines against the pathogen. Here, applying comparative proteomic and reverse vaccinology approaches to the exoproteome and secretome of the pathogen, we have identified three candidate targets (ompU, uppP and yajC) for most of the pathogenic Vibrio strains. Two targets (uppP and yajC) are novel to Vibrio, and two targets (uppP and ompU) can be used to develop both drugs and vaccines (dual targets) against broad spectrum Vibrio serotypes. Using our novel computational approach, we have identified three peptide vaccine candidates that have high potential to induce both B- and T-cell-mediated immune responses from our identified two dual targets. These two targets were modeled and subjected to virtual screening against natural compounds derived from Piper betel. Seven compounds were identified first time from Piper betel to be highly effective to render the function of these targets to identify them as emerging potential drugs against Vibrio. Our preliminary validation suggests that these identified peptide vaccines and betel compounds are highly effective against Vibrio cholerae. Currently we are exhaustively validating these targets, candidate peptide vaccines, and betel derived lead compounds against a number of Vibrio species.

Immunoinformatic evaluation of multiple epitope ensembles as vaccine candidates: E coli 536

Epitope prediction is becoming a key tool for vaccine discovery. Prospective analysis of bacterial and viral genomes can identify antigenic epitopes encoded within individual genes that may act as effective vaccines against specific pathogens. Since B-cell epitope prediction remains unreliable, we concentrate on T-cell epitopes, peptides which bind with high affinity to Major Histacompatibility Complexes (MHC). In this report, we evaluate the veracity of identified T-cell epitope ensembles, as generated by a cascade of predictive algorithms (SignalP, Vaxijen, MHCPred, IDEB, EpiJen), as a candidate vaccine against the model pathogen uropathogenic gram negative bacteria Escherichia coli (E-coli) strain 536 (O6:K15:H31). An immunoinformatic approach was used to identify 23 epitopes within the E-coli proteome. These epitopes constitute the most promiscuous antigenic sequences that bind across more than one HLA allele with high affinity (IC50 < 50nM). The reliability of software programmes used, polymorphic nature of genes encoding MHC and what this means for population coverage of this potential vaccine are discussed.

Structure-based vaccines provide protection in a mouse model of ehrlichiosis

BACKGROUND

Recent advances in bioinformatics have made it possible to predict the B cell and T cell epitopes of antigenic proteins. This has led to design of peptide based vaccines that are more specific, safe, and easy to produce. The obligately intracellular gram negative bacteria Ehrlichia cause ehrlichioses in humans and animals. As yet there are no vaccines to protect against Ehrlichia infection.

METHODOLOGY/PRINCIPAL FINDINGS

We applied the principle of structural vaccinology to design peptides to the epitopes of Ehrlichia muris outer membrane P28-19 (OMP-1/P28) and Ehrlichia Heat shock protein 60 (Hsp60/GroEL) antigenic proteins. Both P28-19 and Ehrlichia Hsp60 peptides reacted with polyclonal antibodies against E. canis and E. chaffeensis and could be used as a diagnostic tool for ehrlichiosis. In addition, we demonstrated that mice vaccinated with Ehrlichia P28-19 and Hsp60 peptides and later challenged with E. muris were protected against the pathogen.

CONCLUSIONS/SIGNIFICANCE

Our results demonstrate the power of structural vaccines and could be a new strategy in the development of vaccines to provide protection against pathogenic microorganisms.