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

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.

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

10.1101/2020.07.30.228221 ◽

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

PLoS ONE ◽

10.1371/journal.pone.0248061 ◽

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.

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

10.20944/preprints202005.0401.v1 ◽

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.

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

Coronaviruses ◽

10.2174/2666796702666210208142945 ◽

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.

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

Journal of Immunology Research ◽

10.1155/2020/2837670 ◽

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.

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In silico screening of antigenic B-cell derived T-cell epitopes and designing of a multi-epitope peptide vaccine for Acinetobacter nosocomialis

Journal of Molecular Graphics and Modelling ◽

10.1016/j.jmgm.2019.107477 ◽

2020 ◽

Vol 94 ◽

pp. 107477 ◽

Cited By ~ 2

Author(s):

Rida Sajjad ◽

Sajjad Ahmad ◽

Syed Sikander Azam

Keyword(s):

T Cell ◽

B Cell ◽

In Silico ◽

Peptide Vaccine ◽

T Cell Epitopes ◽

Epitope Peptide ◽

In Silico Screening

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In Silico Modeling and Immunoinformatics Probing Disclose the Epitope Based PeptideVaccine Against Zika Virus Envelope Glycoprotein

Indian Journal of Pharmaceutical and Biological Research ◽

10.30750/ijpbr.2.4.10 ◽

2014 ◽

Vol 2 (04) ◽

pp. 44-57 ◽

Cited By ~ 15

Author(s):

Daga Dadjo Florian ◽

Mohammad Mahfuz Ali Khan Shawan ◽

Hafij Al Mahmud ◽

Md. Mahmudul Hasan ◽

Afroza Parvin ◽

...

Keyword(s):

Amino Acids ◽

Immune Response ◽

T Cell ◽

B Cell ◽

Zika Virus ◽

Envelope Glycoprotein ◽

Peptide Vaccine ◽

Cd8 T Cell ◽

Peptide Sequence ◽

Conformational Epitopes

Zika virus (ZIKV) is an aedes mosquito borne pathogen belonging to the member of flaviviridae subgroup is the causative agent of an emerging disease called Zika fever, known as a benign infection usually presenting as influenza like illness with cutaneous rash. Due to recent epidemic outbreaks it is realized as a major health risk which need enhanced surveillance, but no attempt has been made to design an epitope based peptide vaccine against Zika virus. Viral envelope proteins are derived from host cell membrane proteins with some viral glycoproteins and are used to cover their protective protein capsid, help the viruses to enter host cells and help them to avoid the host immune response. In this study, amino acid sequence of ZIKV envelope glycoprotein was obtained from a protein database and examined with in silico approaches to determine the most immunogenic epitopes for B cell and T cell which could induce humoral as well as cell mediated immune response. Both the linear and conformational epitopes for B cell were predicted by immunoinformatics tools housed in IEDB resources. The peptide sequence DAHAKRQTVVVLGSQEGAV from position 121 and peptide sequence from 117-137 amino acids were predicted as most potential B cell linear and conformational epitopes respectively. Epitopes for CD4+ and CD8+ T cell were also predicted by using tools within IEDB resource and peptide sequence MMLELDPPF from position 250-258 amino acids was predicted as most immunogenic CD8+ T cell epitope with immune response evoking ability prediction score (I pMHC) of 0.09139 and conservancy of 52.17%. The innate immune response for ZIKV envelope glycoprotein was determined by interferon (IFN)-gamma effectuation and mimicking capacity by immunoinformatics and molecular docking study respectively. However, this is an introductory approach to design an epitope based peptide vaccine against Zika virus; we hope this model will be very much helpful in designing and predicting novel vaccine candidate.

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