Prediction of B-cell and T-cell epitopes in the spike glycoprotein of SARS-CoV-2 in Bangladesh: An in-silico approach

2020 ◽  
Vol 3 (4) ◽  
pp. 49
Author(s):  
Mehedi Hasan ◽  
Md Shihab ◽  
Mohammad Islam
Keyword(s):  
T Cell ◽  
B Cell ◽  
In Silico ◽  
T Cell Epitopes ◽  
Spike Glycoprotein

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.

scholarly journals Using Immunoinformatics to Design a mRNA Vaccine against the Spike Glycoprotein of SARS-CoV-2

2021 ◽  
Vol 26 (5) ◽  
pp. 2901-2915
Author(s):  
SHEREEN F. ELKHOLY ◽  
Keyword(s):  
T Cell ◽  
B Cell ◽  
T Lymphocyte ◽  
Cell Epitope ◽  
T Cell Epitopes ◽  
Spike Glycoprotein ◽  
Ifn Gamma ◽  
Robust Immune Response ◽  
B Cell Epitope ◽  
Public Health Challenge

The rapid outbreak of the new coronavirus SARS-COV-2 has created a major public health challenge. Immunoinformatics tools had a clear effect in tracking the genetic sequence of the virus and monitoring mutations and design vaccines that are effective enough to produce antibodies. In our study, we resorted to the emerging discipline of immunoinformatics in order to design a multi-epitope mRNA vaccine against the spike glycoprotein of SARS-CoV-2. We screened the B cell and T cell epitopes of the Spike glycoprotein. we used ABC pred server to predict B cell epitope in the spike glycoprotein sequence and we used NetMHC-4.1 server to predict the T-cell epitope. Then we selected the B cell and T cell epitopes that fulfilled the antigenicity, non-toxicity, non-allergenicity, induction of both IL4 and IFN gamma. Finally, we designed multi-epitope mRNA Vaccine construct by linking 6 B lymphocytes epitopes (BL) with 6 cytotoxic T lymphocytes epitopes (CTL) together with helper T lymphocyte (HTL) epitope up-streamed by 5’ cap and down-streamed by poly A tail. The vaccine was found to be antigenic, non-toxic, non-allergenic, capable of generating a robust immune response. Based on these parameters, this design can be considered a promising choice for a vaccine against SARS-CoV-2.

In silico identification of immunodominant B-cell and T-cell epitopes of non-structural proteins of Usutu Virus

2018 ◽  
Vol 125 ◽  
pp. 129-143 ◽  
Author(s):  
Rohit Satyam ◽  
Essam Mohammed Janahi ◽  
Tulika Bhardwaj ◽  
Pallavi Somvanshi ◽  
Shafiul Haque ◽  
...  
Keyword(s):  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Structural Proteins ◽  
T Cell Epitopes ◽  
Usutu Virus ◽  
In Silico Identification

scholarly journals Attenuated Subcomponent Vaccine Design Targeting the SARS-CoV-2 Nucleocapsid Phosphoprotein RNA Binding Domain: In Silico Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Onyeka S. Chukwudozie ◽  
Rebecca C. Chukwuanukwu ◽  
Onyekachi O. Iroanya ◽  
Daniel M. Eze ◽  
Vincent C. Duru ◽  
...  
Keyword(s):  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Rna Binding ◽  
Peptide Vaccine ◽  
In Silico Analysis ◽  
Dynamics Simulation ◽  
Effective Vaccine ◽  
Translation Efficiency ◽  
T Cell Epitopes

The novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has previously never been identified with humans, thereby creating devastation in public health. The need for an effective vaccine to curb this pandemic cannot be overemphasized. In view of this, we designed a subcomponent antigenic peptide vaccine targeting the N-terminal (NT) and C-terminal (CT) RNA binding domains of the nucleocapsid protein that aid in viral replication. Promising antigenic B cell and T cell epitopes were predicted using computational pipelines. The peptides “RIRGGDGKMKDL” and “AFGRRGPEQTQGNFG” were the B cell linear epitopes with good antigenic index and nonallergenic property. Two CD8+ and Three CD4+ T cell epitopes were also selected considering their safe immunogenic profiling such as allergenicity, antigen level conservancy, antigenicity, peptide toxicity, and putative restrictions to a number of MHC-I and MHC-II alleles. With these selected epitopes, a nonallergenic chimeric peptide vaccine incapable of inducing a type II hypersensitivity reaction was constructed. The molecular interaction between the Toll-like receptor-5 (TLR5) which was triggered by the vaccine was analyzed by molecular docking and scrutinized using dynamics simulation. Finally, in silico cloning was performed to ensure the expression and translation efficiency of the vaccine, utilizing the pET-28a vector. This research, therefore, provides a guide for experimental investigation and validation.

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.

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

2021 ◽  
Vol 22 ◽  
Author(s):  
Taruna Mohinani ◽  
Aditya Saxena ◽  
Shoor Vir Singh
Keyword(s):  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Three Dimensional ◽  
Cell Epitope ◽  
Buruli Ulcer ◽  
Mycobacterium Ulcerans ◽  
T Cell Epitopes ◽  
Virulence Proteins ◽  
Vaccine Potential

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

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 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.

scholarly journals Designing of epitope-based vaccine from the conserved region of spike glycoprotein of SARS-CoV-2

2020 ◽  
Author(s):  
Vidhu Agarwal ◽  
Pritish Varadwaj ◽  
Akhilesh Tiwari
Keyword(s):  
T Cell ◽  
B Cell ◽  
Cell Epitope ◽  
Morbidity Rate ◽  
High Morbidity ◽  
T Cell Epitope ◽  
T Cell Epitopes ◽  
Spike Glycoprotein ◽  
Mhc I ◽  
High Morbidity Rate

AbstractThe emergence of COVID-19 as a pandemic with a high morbidity rate is posing serious global concern. There is an urgent need to design a suitable therapy or vaccine that could fight against SARS-CoV-2 infection. As spike glycoprotein of SARS-CoV-2 plays a crucial role in receptor binding and membrane fusion inside the host, it could be a suitable target for designing of an epitope-based vaccine. SARS-CoV-2 is an RNA virus and thus has a property to mutate. So, a conserved peptide region of spike glycoprotein was used for predicting suitable B cell and T cell epitopes. 4 T cell epitopes were selected based on stability, antigenicity, allergenicity and toxicity. Further, MHC-I were found from the immune database that could best interact with the selected epitopes. Population coverage analysis was also done to check the presence of identified MHC-I, in the human population of the affected countries. The T cell epitope that binds with the respective MHC-I with highest affinity was chosen. Molecular dynamic simulation results show that the epitope is well selected. This is an in-silico based study that predicts a novel T cell epitope from the conserved spike glycoprotein that could act as a target for designing of the epitope-based vaccine. Further, B cell epitopes have also been found but the main work focuses on T cell epitope as the immunity generated by it is long lasting as compared to B cell epitope.

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