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 Attenuated Subcomponent Vaccine Design Targeting the SARS-CoV-2 Nucleocapsid Phosphoprotein RNA Binding Domain: In silico analysis

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

ABSTRACTThe 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, therefore, designed a subcomponent antigenic peptide vaccine targeting the N-terminal (NT) and C-terminal (CT) RNA binding domains of nucleocapsid protein that aid in viral replication. Promising antigenic B-cells 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 non-allergenic 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 II alleles. With these selected epitopes, a non-allergenic 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 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.

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 In Silico Identification of Novel B Cell and T Cell Epitopes of Wuhan Coronavirus (2019-nCoV) for Effective Multi Epitope-Based Peptide Vaccine Production

2020 ◽  
Author(s):  
Muhammad Asif Rasheed ◽  
Sohail Raza ◽  
Ali Zohaib ◽  
Tahir Yaqub ◽  
Masood Rabbani ◽  
...  
Keyword(s):  
T Cell ◽  
B Cell ◽  
Vaccine Development ◽  
Peptide Vaccine ◽  
Surface Glycoprotein ◽  
World Health ◽  
Effective Vaccine ◽  
Computer Assisted ◽  
T Cell Epitopes ◽  
Epitope Peptide

During December 2019, a novel coronavirus named as 2019-nCoV, has emerged in Wuhan, China. The human to human transmission of this virus has also been established. Untill now the virus has infected more than seven thousand people and has spread to fifteen countries. The World Health Organization (WHO) has declared 2019-nCoV as global health emergency due to its outburst well beyond China. There is need to develop some vaccines or therapeutics to control or prevent 2019-nCoV infections. The bottleneck with current conventional approaches is that these require longer time for vaccine development. However, computer assisted approaches help us to produce effective vaccine in short time compared with conventional methods. In this study, bioinformatics analysis was used to predict B cell and T cell epitopes of surface glycoprotein of 2019-nCoV that could be suitable to trigger significant immune response. The sequence of surface glycoprotein was collected from the database and analyzed to identify the immunogenic epitope. Both B cell and T cell epitopes were analyzed so the predicted epitopes can stimulate both cellular and humoral immune responses. We predicted 13 B cell and 05 T cell epitopes that later on were joined with GPGPG linker to make a single peptide. This computational approach to design a multi epitope peptide vaccine against emerging 2019-nCoV allows us to find novel immunogenic epitopes against the antigen targets of surface 2019-nCoV surface glycoprotein. This multi epitope peptide vaccine may prove effective to combat 2019-nCoV infections.

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 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 In silico analysis and modeling of putative T cell epitopes for vaccine design of Toscana virus

3 Biotech ◽  
2014 ◽  
Vol 5 (4) ◽  
pp. 497-503 ◽  
Author(s):  
Amisha Jain ◽  
Pranav Tripathi ◽  
Aniket Shrotriya ◽  
Ritu Chaudhary ◽  
Ajeet Singh
Keyword(s):  
T Cell ◽  
In Silico ◽  
In Silico Analysis ◽  
Vaccine Design ◽  
T Cell Epitopes ◽  
Toscana Virus ◽  
Silico Analysis

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.

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