scholarly journals Designing of multiepitope-based vaccine against Leptospirosis using Immuno-Informatics approaches

2021 ◽  
Author(s):  
Mohd Abdullah ◽  
Mohammad Kadivella ◽  
Rolee Sharma ◽  
Syed M. Faisal ◽  
Sarwar Azam
Keyword(s):  
T Cell ◽  
B Cell ◽  
Cellular Localization ◽  
Tertiary Structure ◽  
Vaccine Candidate ◽  
Surface Proteins ◽  
World Population ◽  
T Cell Epitopes ◽  
Universal Vaccine ◽  
Vaccine Candidates

AbstractLeptospira is a zoonotic pathogen causing significant morbidity and mortality both in animals and humans. Although several surface proteins have been identified as vaccine candidate, they failed to induce sterilizing immunity and cross protection against different serovars. Thus, identification of highly immunogenic antigens that are conserved among pathogenic serovars would be first step towards development of universal vaccine for Leptospirosis. Here we used reverse vaccinology pipeline to screen core genome of pathogenic Leptospira spp.in order to identify suitable vaccine candidates. Based on properties like sub cellular localization, adhesin, homology to human proteins, antigenicity and allergenicity, 18 antigenic proteins were identified and were further investigated for immunological properties. Based on immunogenicity, Protegenicity, Antigenicity, B-cell and promiscuous T-cell epitopes, 6 Potential Vaccine Candidates (PVCs) were finally selected which covered most of the affected world population. For designing a Multi-Epitope Vaccine (MEV), 6 B-cell and 6 promiscuous MHC-I and MHC-II epitopes from each candidate were clustered with linkers in between and stitched along with a TLR4 adjuvant (APPHALS) at the N-terminal to form a construct of 361 amino acids. The physiochemical properties, secondary and tertiary structure analysis revealed that MEV was highly stable. Molecular docking analysis revealed the deep binding interactions of the MEV construct within the grooves of human TLR4 (4G8A). In-silico codon optimization and cloning of the vaccine construct assured good expression. Further, immune simulations have shown that MEV could induce strong and diverse B and T cell responses. Taken together our results indicate that the designed MEV could be a promising subunit vaccine candidate against Leptospirosis, however it requires experimental validation.

scholarly journals Computational assembly of a human Cytomegalovirus vaccine upon experimental epitope legacy

2019 ◽  
Vol 20 (S6) ◽  
Author(s):  
Monica J. Quinzo ◽  
Esther M. Lafuente ◽  
Pilar Zuluaga ◽  
Darren R. Flower ◽  
Pedro A. Reche
Keyword(s):  
T Cell ◽  
B Cell ◽  
Human Cytomegalovirus ◽  
Cd4 T Cell ◽  
World Population ◽  
T Cell Epitopes ◽  
Cell Component ◽  
Universal Vaccine ◽  
Cell Responses ◽  
Immunosuppressed Patients

Abstract Background Human Cytomegalovirus (HCMV) is a ubiquitous herpesvirus affecting approximately 90% of the world population. HCMV causes disease in immunologically naive and immunosuppressed patients. The prevention, diagnosis and therapy of HCMV infection are thus crucial to public health. The availability of effective prophylactic and therapeutic treatments remain a significant challenge and no vaccine is currently available. Here, we sought to define an epitope-based vaccine against HCMV, eliciting B and T cell responses, from experimentally defined HCMV-specific epitopes. Results We selected 398 and 790 experimentally validated HCMV-specific B and T cell epitopes, respectively, from available epitope resources and apply a knowledge-based approach in combination with immunoinformatic predictions to ensemble a universal vaccine against HCMV. The T cell component consists of 6 CD8 and 6 CD4 T cell epitopes that are conserved among HCMV strains. All CD8 T cell epitopes were reported to induce cytotoxic activity, are derived from early expressed genes and are predicted to provide population protection coverage over 97%. The CD4 T cell epitopes are derived from HCMV structural proteins and provide a population protection coverage over 92%. The B cell component consists of just 3 B cell epitopes from the ectodomain of glycoproteins L and H that are highly flexible and exposed to the solvent. Conclusions We have defined a multiantigenic epitope vaccine ensemble against the HCMV that should elicit T and B cell responses in the entire population. Importantly, although we arrived to this epitope ensemble with the help of computational predictions, the actual epitopes are not predicted but are known to be immunogenic.

scholarly journals Immunoinformatic Approach for the identification of T Cell and B Cell Epitopes in the Surface Glycoprotein and Designing a Potent Multiepitope Vaccine Construct Against SARS-CoV-2 including the new UK variant

2021 ◽  
Author(s):  
Kaveri Krishnasamy ◽  
Gracy Fathima Selvaraj ◽  
Kiruba Ramesh ◽  
Padmaoriya Padmanabhan ◽  
Vidya Gopalan ◽  
...  
Keyword(s):  
T Cell ◽  
Immune Responses ◽  
B Cell ◽  
T Lymphocyte ◽  
Vaccine Candidate ◽  
Surface Glycoprotein ◽  
T Cell Epitopes ◽  
B Cell Epitopes ◽  
New Variant

The emergence of a novel coronavirus in China in late 2019 has turned into a SARS-CoV-2 pandemic affecting several millions of people worldwide in a short span of time with high fatality. The crisis is further aggravated by the emergence and evolution of new variant SARS-CoV-2 strains in UK during December, 2020 followed by their transmission to other countries. A major concern is that prophylaxis and therapeutics are not available yet to control and prevent the virus which is spreading at an alarming rate, though several vaccine trials are in the final stage. As vaccines are developed through various strategies, their immunogenic potential may drastically vary and thus pose several challenges in offering both arms of immunity such as humoral and cell-mediated immune responses against the virus. In this study, we adopted an immunoinformatics-aided identification of B cell and T cell epitopes in the Spike protein, which is a surface glycoprotein of SARS-CoV-2, for developing a new Multiepitope vaccine construct (MEVC). MEVC has 575 amino acids and comprises adjuvants and various cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes that possess the highest affinity for the respective HLA alleles, assembled and joined by linkers. The computational data suggest that the MEVC is non-toxic, non-allergenic and thermostable with the capability to elicit both humoral and cell-mediated immune responses. The population coverage of various countries affected by COVID-19 with respect to the selected B and T cell epitopes in MEVC was also investigated. Subsequently, the biological activity of MEVC was assessed by bioinformatic tools using the interaction between the vaccine candidate and the innate immune system receptors TLR3 and TLR4. The epitopes of the construct were analyzed with that of the strains belonging to various clades including the new variant UK strain having multiple unique mutations in S protein. Due to the advantageous features, the MEVC can be tested in vitro for more practical validation and the study offers immense scope for developing a potential vaccine candidate against SARS-CoV-2 in view of the public health emergency associated with COVID-19 disease caused by SARS-CoV-2.

scholarly journals Strategies for vaccine design for corona virus using Immunoinformatics techniques

2020 ◽  
Author(s):  
Anamika Basu ◽  
Anasua Sarkar ◽  
Ujjwal Maulik
Keyword(s):  
T Cell ◽  
B Cell ◽  
Nonstructural Protein ◽  
Alpha Helix ◽  
Peptide Sequence ◽  
Phylogenetic Study ◽  
World Population ◽  
T Cell Epitopes ◽  
Kcal Mole ◽  
Mhc I

ABSTRACTThe cutting-edge technology vaccinomics is the combination of two topics immunogenetics and immunogenomics with the knowledge of systems biology and immune profiling for designing vaccine against infectious disease. In our present study, an epitope-based peptide vaccine against nonstructural protein 4 of beta coronavirus, using a combination of B cell and T cell epitope predictions, followed by molecular docking methods are performed. Here, protein sequences of homologous nonstructural protein 4 of beta coronavirus are collected and conserved regions present in them are investigated via phylogenetic study to determine the most immunogenic part of protein. From the identified region of the target protein, the peptide sequence IRNTTNPSAR from the region ranging from 38-47 and the sequence PTDTYTSVYLGKFRG from the positions of 76-90 are considered as the most potential B cell and T cell epitopes respectively. Furthermore, this predicted T cell epitopes PTDTYTSVY and PTDTYTSVYLGKFRG interacted with MHC allelic proteins HLA-A*01:01 and HLA-DRB5*01:01 respectively with the low IC50 values. These epitopes are perfectly fitted into the epitope binding grooves of alpha helix of MHC I molecule and MHC II molecule with binding energy scores −725.0 Kcal/mole and −786.0 Kcal/mole respectively, showing stability in MHC molecules binding. This MHC restricted epitope PTDTYTSVY also showed a good conservancy of 50.16% in world population coverage. This MHC I HLA-A*01:01 allele is present among 58.87% of Chinese population also. Therefore, the epitopes IRNTTNPSAR and PTDTYTSVYLGKFRG may be considered as potential peptides for peptide-based vaccine for coronavirus after further experimental study.

scholarly journals Computational perspectives revealed prospective vaccine candidates from five structural proteins of novel SARS corona virus 2019 (SARS-CoV-2)

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9855
Author(s):  
Rajesh Anand ◽  
Subham Biswal ◽  
Renu Bhatt ◽  
Bhupendra N. Tiwary
Keyword(s):  
T Cell ◽  
B Cell ◽  
Structural Proteins ◽  
T Cell Epitopes ◽  
Population Coverage ◽  
B Cell Epitopes ◽  
Vaccine Candidates ◽  
Conformational Epitopes ◽  
Potential Vaccine ◽  
Linear B

Background The present pandemic COVID-19 is caused by SARS-CoV-2, a single-stranded positive-sense RNA virus from the Coronaviridae family. Due to a lack of antiviral drugs, vaccines against the virus are urgently required. Methods In this study, validated computational approaches were used to identify peptide-based epitopes from six structural proteins having antigenic properties. The Net-CTL 1.2 tool was used for the prediction of CD8+ T-cell epitopes, while the robust tools Bepi-Pred 2 and LBtope was employed for the identification of linear B-cell epitopes. Docking studies of the identified epitopes were performed using HADDOCK 2.4 and the structures were visualized by Discovery Studio and LigPlot+. Antigenicity, immunogenicity, conservancy, population coverage and allergenicity of the predicted epitopes were determined by the bioinformatics tools like VaxiJen v2.0 server, the Immune Epitope Database tools and AllerTOP v.2.0, AllergenFP 1.0 and ElliPro. Results The predicted T cell and linear B-cell epitopes were considered as prime vaccine targets in case they passed the requisite parameters like antigenicity, immunogenicity, conservancy, non-allergenicity and broad range of population coverage. Among the predicted CD8+ T cell epitopes, potential vaccine targets from surface glycoprotein were; YQPYRVVVL, PYRVVVLSF, GVYFASTEK, QLTPTWRVY, and those from ORF3a protein were LKKRWQLAL, HVTFFIYNK. Similarly, RFLYIIKLI, LTWICLLQF from membrane protein and three epitopes viz; SPRWYFYYL, TWLTYTGAI, KTFPPTEPK from nucleocapsid phosphoprotein were the superior vaccine targets observed in our study. The negative values of HADDOCK and Z scores obtained for the best cluster indicated the potential of the epitopes as suitable vaccine candidates. Analysis of the 3D and 2D interaction diagrams of best cluster produced by HADDOCK 2.4 displayed the binding interaction of leading T cell epitopes within the MHC-1 peptide binding clefts. On the other hand, among linear B cell epitopes the majority of potential vaccine targets were from nucleocapsid protein, viz; 59−HGKEDLKFPRGQGVPINTNSSPDDQIGYYRRATRRIRGGDGKMKDLS−105, 227−LNQLE SKMSGKGQQQQGQTVTKKSAAEASKKPRQKRTATK−266, 3−DNGPQNQRNAPRITFGGP−20, 29−GERSGARSKQRRPQGL−45. Two other prime vaccine targets, 370−NSASFSTFKCYGVSPTKLNDLCFTNV−395 and 260−AGAAAYYVGYLQPRT−274 were identified in the spike protein. The potential B-cell conformational epitopes were predicted on the basis of a higher protrusion index indicating greater solvent accessibility. These conformational epitopes were of various lengths and belonged to spike, ORF3a, membrane and nucleocapsid proteins. Conclusions Taken together, eleven T cell epitopes, seven B cell linear epitopes and ten B cell conformational epitopes were identified from five structural proteins of SARS-CoV-2 using advanced computational tools. These potential vaccine candidates may provide important timely directives for an effective vaccine against SARS-CoV-2.

scholarly journals A Bioinformatics Approach for the Prediction of Immunogenic Properties and Structure of the SARS-COV-2 B.1.617.1 Variant Spike Protein

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Vijay Kumar Srivastava ◽  
Sanket Kaushik ◽  
Gazal Bhargava ◽  
Ajay Jain ◽  
Juhi Saxena ◽  
...  
Keyword(s):  
Amino Acid ◽  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Tertiary Structure ◽  
In Silico Analysis ◽  
Respiratory Illness ◽  
T Cell Epitopes ◽  
S Protein ◽  
Immunogenic Properties

Background. B.1.617.1, a variant of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causing respiratory illness is responsible for the second wave of COVID-19 and associated with a high incidence of infectivity and mortality. To mitigate the B.1.617.1 variant of SARS-CoV-2, deciphering the protein structure and immunological responses by employing bioinformatics tools for data mining and analysis is pivotal. Objectives. Here, an in silico approach was employed for deciphering the structure and immune function of the subunit of spike (S) protein of SARS-CoV-2 B.1.617.1 variant. Methods. The partial amino acid sequence of SARS-CoV-2 B.1.617.1 variant S protein was analyzed, and its putative secondary and tertiary structure was predicted. Immunogenic analyses including B- and T-cell epitopes, interferon-gamma (IFN-γ) response, chemokine, and protective antigens for SARS-CoV 2 S proteins were predicted using appropriate tools. Results. B.1.617.1 variant S protein sequence was found to be highly stable and amphipathic. ABCpred and CTLpred analyses led to the identification of two potential antigenic B cell and T cell epitopes with starting amino acid positions at 60 and 82 (for B cell epitopes) and 54 and 98 (for T cell epitopes) having prediction scores > 0.8 . Further, RAMPAGE tool was used for determining the allowed and disallowed regions of the three-dimensional predicted structure of SARS-CoV-2 B.1.617.1 variant S protein. Conclusion. Together, the in silico analysis revealed the predicted structure of partial S protein, immunogenic properties, and possible regions for S protein of SARS-CoV-2 and provides a valuable prelude for engineering the targeted vaccine or drug against B.1.617.1 variant of SARS-CoV-2.

In Silico Vaccine Designing Targeting the Virulence Factors of mce Operons of Mycobacterium avium subsp. Paratuberculosis

2020 ◽  
Vol 17 ◽  
Author(s):  
Taruna Mohinani ◽  
Aditya Saxena ◽  
Shoor Vir Singh
Keyword(s):  
T Cell ◽  
B Cell ◽  
Mycobacterium Avium ◽  
Cellular Localization ◽  
Cell Epitope ◽  
Economic Losses ◽  
Effective Vaccine ◽  
T Cell Epitopes ◽  
Domestic Livestock ◽  
Mce Operons

Background: Mycobacterium avium sp. paratuberculosis (MAP) causes Paratuberculosis (pTB) in domestic livestock and has also been associated with auto-immune disorders in humans. Infection leads to huge economic losses to the farmers associated with livestock production system worldwide. Currently, search to find proteins with potential to develop as vaccine candidates against MAP are underway. Objective: In this study, we aimed to explore the immunogenicity of the proteins of mammalian cell entry (mce) operons of MAP using computational tools. Method: Genes of mce operons of MAP strain K10 were selected and their orthologs identification was done using VFanalyzer tool. Mce proteins encoded by these operons were analyzed for their antigenicity and sub-cellular localization. Three dimensional structures for Mce proteins were predicted using Phyre2. B cell and T cell epitope analysis was done using methods available at Immune Epitope Database and Analysis Resource. Selection analysis of mce genes was also done. Results: Eight Mce proteins were predicted with B cell and T cell epitopes. Some of them were reported with overlapping B cell and T cell epitopes. We found positively selected sites within some predicted epitopes that indicated some kind of selection pressure by immune system on these protein regions. Some predicted epitopes also had similarity with experimentally identified epitopes of Mce proteins of M. tuberculosis which further strengthened the immunogenic role of Mce proteins. Conclusion: Our findings may potentially assist in the development of effective vaccine against the incurable infection due to MAP bacilli in the domestic livestock species.

Prediction of Prophylactic Peptide Vaccine Candidates for Human Papillomavirus (HPV): An Immunoinformatics and Reverse Vaccinology Approach

2020 ◽  
Vol 17 ◽  
Author(s):  
Mehreen Ismail ◽  
Zureesha Sajid ◽  
Amjad Ali ◽  
Xiaogang Wu ◽  
Syed Aun Muhammad ◽  
...  
Keyword(s):  
T Cells ◽  
Human Papillomavirus ◽  
T Cell ◽  
Binding Affinity ◽  
Cd8 T Cells ◽  
Reverse Vaccinology ◽  
Host Immune System ◽  
T Cell Epitopes ◽  
Multiple Alleles ◽  
Vaccine Candidates

Background: Human Papillomavirus (HPV) is responsible for substantial morbidity and mortality worldwide. We predicted immunogenic promiscuous monovalent and polyvalent T-cell epitopes from the polyprotein of the Human Papillomavirus (HPV) using a range of bioinformatics tools and servers. Methods: We used immunoinformatics and reverse vaccinology-based approaches to design prophylactic peptides by antigenicity analysis, Tcell epitopes prediction, proteasomal and conservancy evaluation, host-pathogen protein interactions, and in silico binding affinity analysis. Results: We found two early proteins (E2 and E6) and two late proteins (L1 and L2) of HPV as potential vaccine candidates. Of these proteins (E2, E6, L1 & L2), 2-epitopes of each candidate protein for multiple alleles of MHC class I and II bearing significant binding affinity (>-6.0 kcal/mole). These potential epitopes for CD4+ and CD8+ T-cells were also linked to design polyvalent construct using GPGPG linkers. Cholera toxin B and mycobacterial heparin-binding hemagglutinin adjuvant with a molecular weight of 12.5 and 18.5 kDa were used for epitopes of CD4+ and CD8+ T-cells respectively. The molecular docking indicated the optimum binding affinity of HPV peptides with MHC molecules. This interaction showed that our predicted vaccine candidates are suitable to trigger the host immune system to prevent HPV infections. Conclusion: The predicted conserved T-cell epitopes would contribute to the imminent design of HPV vaccine candidates, which will be able to induce a broad range of immune-responses in a heterogeneous HLA population.

Immuno-informatics-based identification of novel potential B cell and T cell epitopes to fight Zika virus infections

2020 ◽  
Vol 20 ◽  
Author(s):  
Wahiba Ezzemani ◽  
Marc P. Windisch ◽  
Anass Kettani ◽  
Haya Altawalah ◽  
Jalal Nourlil ◽  
...  
Keyword(s):  
Major Histocompatibility Complex ◽  
T Cell ◽  
Major Histocompatibility Complex Class ◽  
B Cell ◽  
Zika Virus ◽  
T Cell Epitopes ◽  
Complex Class ◽  
Major Histocompatibility ◽  
Virus Infections ◽  
Histocompatibility Complex

Background: Globally, the recent outbreak of Zika virus (ZIKV) in Brazil, Asia Pacific, and other countries highlighted the unmet medical needs. Currently, there are neither effective vaccines nor therapeutics available to prevent or treat ZIKV infection. Objective: In this study, we aimed to design an epitope-based vaccine for ZIKV using an in silico approach to predict and analyze B- and T-cell epitopes. Methods: The prediction of the most antigenic epitopes has targeted the capsid and the envelope proteins as well as nonstructural proteins NS5 and NS3 using immune-informatics tools PROTPARAM, CFSSP, PSIPRED, and Vaxijen v2.0. B and T-cell epitopes were predicted using ABCpred, IEDB, TepiTool, and their toxicity were evaluated using ToxinPred. The 3-dimensional epitope structures were generated by PEP-FOLD. Energy minimization was performed using Swiss-Pdb Viewer, and molecular docking was conducted using PatchDock and FireDock server. Results: As a result, we predicted 307 epitopes of MHCI (major histocompatibility complex class I) and 102 epitopes of MHCII (major histocompatibility complex class II). Based on immunogenicity and antigenicity scores, we identified the four most antigenic MHC I epitopes: MVLAILAFLR (HLA-A*68 :01), ETLHGTVTV (HLA-A*68 :02), DENHPYRTW (HLA-B*44 :02),QEGVFHTMW (HLA-B*44 :03) and TASGRVIEEW (HLA-B*58:01), and MHC II epitopes: IIKKFKKDLAAMLRI (HLA-DRB3*02 :02), ENSKMMLELDPPFGD (HLA-DRB3*01:01), HAETWFFDENHPYRT (HLA-DRB3*01:01), TDGVYRVMTRRLLGS (HLA-DRB1*11 :01), and DGCWYGMEIRPRKEP (HLA-DRB5*01:01). Conclusion : This study provides novel potential B cell and T cell epitopes to fight Zika virus infections and may prompt further development of vaccines against ZIKV and other emerging infectious diseases. However, further investigations for protective immune response by in vitro and in vivo studies to ratify the immunogenicity, safety of the predicted structure, and ultimately the vaccine properties to prevent ZIKV infections are warranted.

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