scholarly journals Immuno-informatics design of a multimeric epitope peptide based vaccine targeting SARS-CoV-2 spike glycoprotein

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248061
Author(s):  
Onyeka S. Chukwudozie ◽  
Clive M. Gray ◽  
Tawakalt A. Fagbayi ◽  
Rebecca C. Chukwuanukwu ◽  
Victor O. Oyebanji ◽  
...  
Keyword(s):  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Peptide Vaccine ◽  
Spike Protein ◽  
Cell Mediated Immunity ◽  
Epitope Peptide ◽  
Mhc I ◽  
B Cell Epitopes ◽  
Antibody Recognition

Developing an efficacious vaccine for SARS-CoV-2 infection is critical to stemming COVID-19 fatalities and providing the global community with immune protection. We have used a bioinformatic approach to aid in designing an epitope peptide-based vaccine against the spike protein of the virus. Five antigenic B cell epitopes with viable antigenicity and a total of 27 discontinuous B cell epitopes were mapped out structurally in the spike protein for antibody recognition. We identified eight CD8+ T cell 9-mers and 12 CD4+ T cell 14-15-mer as promising candidate epitopes putatively restricted by a large number of MHC I and II alleles, respectively. We used this information to construct an in silico chimeric peptide vaccine whose translational rate was highly expressed when cloned in pET28a (+) vector. With our In silico test, the vaccine construct was predicted to elicit high antigenicity and cell-mediated immunity when given as a homologous prime-boost, triggering of toll-like receptor 5 by the adjuvant linker. The vaccine was also characterized by an increase in IgM and IgG and an array of Th1 and Th2 cytokines. Upon in silico challenge with SARS-CoV-2, there was a decrease in antigen levels using our immune simulations. We, therefore, propose that potential vaccine designs consider this approach.

scholarly journals Immuno-informatics Design of a Multimeric Epitope Peptide Based Vaccine Targeting SARS-CoV-2 Spike Glycoprotein

2020 ◽  
Author(s):  
Onyeka S. Chukwudozie ◽  
Clive M. Gray ◽  
Tawakalt A. Fagbayi ◽  
Rebecca C. Chukwuanukwu ◽  
Victor O. Oyebanji ◽  
...  
Keyword(s):  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Peptide Vaccine ◽  
Spike Protein ◽  
Cell Mediated Immunity ◽  
Epitope Peptide ◽  
Mhc I ◽  
B Cell Epitopes ◽  
Antibody Recognition

ABSTRACTDeveloping an efficacious vaccine to SARS-CoV-2 infection is critical to stem COVID-19 fatalities and providing the global community with immune protection. We have used a bioinformatic approach to aid in the design of an epitope peptide-based vaccine against the spike protein of the virus. Five antigenic B cell epitopes with viable antigenicity and a total of 27 discontinuous B cell epitopes were mapped out structurally in the spike protein for antibody recognition. We identified eight CD8+ T cell 9-mers along with 12 CD4+ T cell 14-15-mer as promising candidate epitopes putatively restricted by a large number of MHC-I and II alleles respectively. We used this information to construct an in silico chimeric peptide vaccine whose translational rate was highly expressed when cloned in pET28a (+) vector. The vaccine construct was predicted to elicit high antigenicity and cell-mediated immunity when given as a homologous prime-boost, with triggering of toll-like receptor 5 by the adjuvant linker. The vaccine was characterized by an increase in IgM and IgG and an array of Th1 and Th2 cytokines. Upon in silico challenge with SARS-CoV-2, there was a decrease in antigen levels using our immune simulations. We therefore propose that potential vaccine designs consider this approach.

scholarly journals A Computational Assay to Design an Epitope-Based Peptide Vaccine against Saint Louis Encephalitis Virus

2013 ◽  
Vol 7 ◽  
pp. BBI.S13402 ◽  
Author(s):  
Anayet Hasan ◽  
Mehjabeen Hossain ◽  
Jibran Alam
Keyword(s):  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Peptide Vaccine ◽  
Encephalitis Virus ◽  
Peptide Sequence ◽  
Cell Mediated Immunity ◽  
Protein Database ◽  
Saint Louis ◽  
Saint Louis Encephalitis

Saint Louis encephalitis virus, a member of the flaviviridae subgroup, is a culex mosquito-borne pathogen. Despite severe epidemic outbreaks on several occasions, not much progress has been made with regard to an epitope-based vaccine designed for Saint Louis encephalitis virus. The envelope proteins were collected from a protein database and analyzed with an in silico tool to identify the most immunogenic protein. The protein was then verified through several parameters to predict the T-cell and B-cell epitopes. Both T-cell and B-cell immunity were assessed to determine that the protein can induce humoral as well as cell-mediated immunity. The peptide sequence from 330–336 amino acids and the sequence REYCYEATL from the position 57 were found as the most potential B-cell and T-cell epitopes, respectively. Furthermore, as an RNA virus, one important thing was to establish the epitope as a conserved one; this was also done by in silico tools, showing 63.51% conservancy. The epitope was further tested for binding against the HLA molecule by computational docking techniques to verify the binding cleft epitope interaction. However, this is a preliminary study of designing an epitope-based peptide vaccine against Saint Louis encephalitis virus; the results awaits validation by in vitro and in vivo experiments.

scholarly journals An Integrated In-Silico Approach to Develop Epitope-Based Peptide Vaccine against SARS-CoV-2

2020 ◽  
Author(s):  
Prekshi Garg ◽  
Neha Srivastava ◽  
Prachi Srivastava
Keyword(s):  
T Cell ◽  
B Cell ◽  
In Silico ◽  
3D Structure ◽  
Peptide Vaccine ◽  
Cell Epitope ◽  
Peptide Sequence ◽  
T Cell Epitopes ◽  
Mhc I ◽  
In Silico Study

SARS-CoV-2 has been the talk of the town ever since the beginning of 2020. The pandemic has brought the complete world on a halt. Every country is trying all possible steps to combat the disease ranging from shutting the complete economy of the country to repurposing of drugs and vaccine development. The rapid data analysis and widespread tools, software and databases have made bioinformatics capable of giving new insights to the researchers to deal with the current scenario more efficiently. Vaccinomics, the new emerging field of bioinformatics uses concepts of immunogenetics and immunogenomics with in silico tools to give promising results for wet lab experiments. This approach is highly validated for the designing and development of potent vaccines. The present in-silico study was attempted to identify peptide fragments from spike surface glycoprotein that can be efficiently used for the designing and development of epitope-based vaccine designing approach. Both B-cell and T-cell epitopes are predicted using integrated computational tools. VaxiJen server was used for prediction of protective antigenicity of the protein. NetCTL was studied for analyzing most potent T cell epitopes and its subsequent MHC-I interaction through tools provided by IEDB. 3D structure prediction of peptides and MHC-I alleles (HLA-C*03:03) was further done to carry out docking studies using AutoDock4.0. Various tools from IEDB were used to predict B-cell epitopes on the basis of different essential parameters like surface accessibility, beta turns and many more. Based on results interpretation, the peptide sequence from 1138-1145 amino acid and sequence WTAGAAAYY and YDPLQPEL were obtained as a potential B-cell epitope and T-cell epitope respectively. This in-silico study will help us to identify novel epitope-based peptide vaccine target in spike protein of SARS-CoV-2. Further, in-vitro and in-vivo study needed to validate the findings.

An Integrated In-Silico Approach to Develop Epitope-Based Peptide Vaccine against SARS-CoV-2

Coronaviruses ◽  
2021 ◽  
Vol 02 ◽  
Author(s):  
Prekshi Garg ◽  
Neha Srivastava ◽  
Prachi Srivastava
Keyword(s):  
Amino Acid ◽  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Peptide Vaccine ◽  
Cell Epitope ◽  
Peptide Sequence ◽  
T Cell Epitopes ◽  
Mhc I ◽  
In Silico Study

Background: SARS-CoV-2 has been the talk of the town ever since the beginning of 2020. Every country is trying all possible steps to combat the disease ranging from shutting the complete economy of the country to the repurposing of drugs and vaccine development. The rapid data analysis and widespread tools have made bioinformatics capable of giving new insights to deal with the current scenario more efficiently through an emerging field, Vaccinomics. Objective: The present in-silico study was attempted to identify peptide fragments from spike surface glycoprotein of SARS-CoV-2 that can be efficiently used for the development of an epitope-based vaccine designing approach. Methodology: The epitopes of B and T-cell are predicted using integrated computational tools. VaxiJen server, NetCTL, and IEDB tools were used to study, analyze, and predict potent T-cell epitopes, its subsequent MHC-I interactions, and B-cell epitopes. The 3D structure prediction of peptides and MHC-I alleles (HLA-C*03:03) was further done using AutoDock4.0. Result: Based on result interpretation, the peptide sequence from 1138-1145 amino acid and sequence WTAGAAAYY and YDPLQPEL were obtained as potential B-cell and T-cell epitopes respectively. Conclusion: The peptide sequence WTAGAAAYY and the amino acid sequence from 1138-1145 of the spike protein of SARS-CoV-2 can be used as a probable B-cell epitope candidate. Also, the amino acid sequence YDPLQPEL can be used as a potent T-cell epitope. This in-silico study will help us to identify novel epitope-based peptide vaccine targets in the spike protein of SARS-CoV-2. Further, the in-vitro and in-vivo study needed to validate the findings.

scholarly journals Potential T-cell and B-cell Epitopes of 2019-nCoV

2020 ◽  
Author(s):  
Ethan Fast ◽  
Russ B. Altman ◽  
Binbin Chen
Keyword(s):  
Experimental Data ◽  
T Cell ◽  
B Cell ◽  
Antigen Presentation ◽  
Spike Protein ◽  
Receptor Binding Domain ◽  
Computational Pipeline ◽  
Mhc I ◽  
B Cell Epitopes ◽  
Protein Receptor

As of early March, 2019-nCoV has infected more than one hundred thousand people and claimed thousands of lives. 2019-nCoV is a novel form of coronavirus that causes COVID-19 and has high similarity with SARS-CoV. No approved vaccine yet exists for any form of coronavirus. Here we use computational tools from structural biology and machine learning to identify 2019-nCoV T-cell and B-cell epitopes based on viral protein antigen presentation and antibody binding properties. These epitopes can be used to develop more effective vaccines and identify neutralizing antibodies. We identified 405 viral peptides with good antigen presentation scores for both human MHC-I and MHC-II alleles, and two potential neutralizing B-cell epitopes near the 2019-nCoV spike protein receptor binding domain (440-460 and 494-506). Analyzing mutation profiles of 68 viral genomes from four continents, we identified 96 coding-change mutations. These mutations are more likely to occur in regions with good MHC-I presentation scores (p=0.02). No mutations are present near the spike protein receptor binding domain. Based on these findings, the spike protein is likely immunogenic and a potential vaccine candidate. We validated our computational pipeline with SARS-CoV experimental data.Significance StatementThe novel coronavirus 2019-nCoV has affected more than 100 countries and continues to spread. There is an immediate need for effective vaccines that contain antigens which trigger responses from human T-cells and B-cells (known as epitopes). Here we identify potential T-cell epitopes through an analysis of human antigen presentation, as well as B-cell epitopes through an analysis of protein structure. We identify a list of top candidates, including an epitope located on 2019-nCoV spike protein that potentially triggers both T-cell and B-cell responses. Analyzing 68 samples, we observe that viral mutations are more likely to happen in regions with strong antigen presentation, a potential form of immune evasion. Our computational pipeline is validated with experimental data from SARS-CoV.

In silico prediction of T‐cell and B‐cell epitopes of human papillomavirus type 16 L1 protein

2021 ◽  
Author(s):  
Shahab Mahmoudvand ◽  
Somayeh Shokri ◽  
Manoochehr Makvandi ◽  
Reza Taherkhani ◽  
Mohammad Rashno ◽  
...  
Keyword(s):  
Human Papillomavirus ◽  
T Cell ◽  
B Cell ◽  
In Silico ◽  
In Silico Prediction ◽  
B Cell Epitopes ◽  
Human Papillomavirus Type 16 ◽  
L1 Protein

scholarly journals Epitope‐based peptide vaccine design and target site depiction against Middle East Respiratory Syndrome Coronavirus: an immune-informatics study

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Muhammad Tahir ul Qamar ◽  
Saman Saleem ◽  
Usman Ali Ashfaq ◽  
Amna Bari ◽  
Farooq Anwar ◽  
...  
Keyword(s):  
T Cell ◽  
Middle East ◽  
B Cell ◽  
Mhc Class Ii ◽  
Peptide Vaccine ◽  
Middle East Respiratory Syndrome ◽  
T Cell Epitopes ◽  
Resistance Response ◽  
B Cell Epitopes ◽  
S Protein

Abstract Background Middle East Respiratory Syndrome Coronavirus (MERS-COV) is the main cause of lung and kidney infections in developing countries such as Saudi Arabia and South Korea. This infectious single-stranded, positive (+) sense RNA virus enters the host by binding to dipeptidyl-peptide receptors. Since no vaccine is yet available for MERS-COV, rapid case identification, isolation, and infection prevention strategies must be used to combat the spreading of MERS-COV infection. Additionally, there is a desperate need for vaccines and antiviral strategies. Methods The present study used immuno-informatics and computational approaches to identify conserved B- and T cell epitopes for the MERS-COV spike (S) protein that may perform a significant role in eliciting the resistance response to MERS-COV infection. Results Many conserved cytotoxic T-lymphocyte epitopes and discontinuous and linear B-cell epitopes were predicted for the MERS-COV S protein, and their antigenicity and interactions with the human leukocyte antigen (HLA) B7 allele were estimated. Among B-cell epitopes, QLQMGFGITVQYGT displayed the highest antigenicity-score, and was immensely immunogenic. Among T-cell epitopes, MHC class-I peptide YKLQPLTFL and MHC class-II peptide YCILEPRSG were identified as highly antigenic. Furthermore, docking analyses revealed that the predicted peptides engaged in strong bonding with the HLA-B7 allele. Conclusion The present study identified several MERS-COV S protein epitopes that are conserved among various isolates from different countries. The putative antigenic epitopes may prove effective as novel vaccines for eradication and combating of MERS-COV infection.

scholarly journals Molecular cloning, expression, purification and in silico epitope prediction of cobalamin-independent methionine synthase (Mor a 2), as a novel allergen from Morus alba pollen

2021 ◽  
Author(s):  
Yunus AKSÜT
Keyword(s):  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Allergic Diseases ◽  
Structural Features ◽  
Morus Alba ◽  
Methionine Synthase ◽  
Antigenic Peptides ◽  
T Cell Epitopes ◽  
B Cell Epitopes

IntroductionMorus alba (white mulberry) pollen is an aero-allergen source that can trigger allergic diseases. Cobalamin-independent methionine synthase (MetE) in M. alba pollen has been proved to be one of the major allergens for some patients living in Istanbul (Turkey). The aim of the present study was the recombinant production and identification of MetE (Mor a 2), a novel allergen from M. alba pollen. The IgE binding reactivity of rMor a 2 produced for the first time was evaluated and some structural features were investigated by in silico methods to better understand its immunogenicity.Material and methodsThe gene encoding Mor a 2 was cloned in fission yeast, Schizosaccharomyces pombe ura4-D18h- strain, using pSLF1073 vector. This is the first report of the production of recombinant pollen allergen in S. pombe. After the purification, immunoreactivity of rMor a 2 was confirmed by immunoblotting using sera of patient allergic to M. alba pollen. Besides, B-cell epitopes of rMor a 2 were predicted using various bioinformatic tools, namely Bioinformatics Predicted Antigenic Peptides, BepiPred 2.0 and Immune Epitope Database whereas T-cell epitopes were estimated using NetMHCIIpan-3.2 and NetMHCII 2.3 servers.ResultsThe immunoblotting analysis yielded 11 of 11 positive reactions to rMor a 2. In silico predictions exerted seven B-cell epitopes (22-33, 384-394, 407-423, 547-553, 571-577, 671-678, 736-741) and seven T-cell epitopes (54-62, 161-170, 197-205, 347-358, 622-630, 657-665, 756-764).ConclusionsThese findings may help the use of rMor a 2 in the diagnosis and treatment of allergic diseases associated with M. alba and/or MetE.

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