scholarly journals Translationally Controlled Tumor ProteinTCTPas Peptide Vaccine againstSchistosoma japonicum: an Immunoinformatics Approach

2018 ◽  
Author(s):  
Rayan A Abdalrahman ◽  
Shima S Ahmed ◽  
Mahmoud A Elnaeem ◽  
Marwa S Mohammed ◽  
Nawraz M Jammie ◽  
...  
Keyword(s):  
T Cell ◽  
B Cell ◽  
Schistosoma Japonicum ◽  
Peptide Vaccine ◽  
Cell Epitope ◽  
In Vivo Studies ◽  
Effective Vaccine ◽  
Good Prediction ◽  
Mhc I ◽  
Major Health Problem

AbstractSchistosoma japonicum is the most pathogenic causative form of schistosomiasis that causes a major health problem in its endemic countries. Until now, praziquantel is the only drug used to treat Schistosomiasis, but it does not prevent re-infection. So, repetition of the treatment is needed. Moreover, there is no effective vaccine against S. japonicum. Therefore, an urgent need for the development of vaccines is mandatory. This study aimed to analyze an immunogenic protein, Transitionally Controlled Tumor Protein (TCTP) using an immunoinformatics approach to design a universal peptide vaccine against Schistosoma japonicum. A set of 22 of TCTP sequences were retrieved from NCBI database. Conservancy of these sequences was tested and then conserved B cell and T cell epitopes were predicted using different tools available in IEBD. Epitopes having high scores in both B and T cell predicting tools were proposed. An epitope129YEHYI133was predicted as a most promising epitope with good prediction scores in surface accessibility and antigenicity. Besides that, epitopes129YEHYIGESM137and92YLKAIKERL100were predicted as the most promising epitopes concerning their binding to MHC I and MHC II allele respectively. The study revealed that our predicted epitopes could be used to develop an efficacious vaccine against Schistosoma japonicum in the future especially epitope YEHYIGESM as it is shared between MHC I and II alleles and overlapped with the most promising B cell epitope. Both in vitro and in vivo studies is recommended to confirm the efficacy of YEHYIGESM as a peptide vaccine.

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 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.

Prediction of Epitope-Based Peptide Vaccine Against the Chikungunya Virus by Immuno-informatics Approach

2020 ◽  
Vol 21 (4) ◽  
pp. 325-340 ◽  
Author(s):  
Saeed Anwar ◽  
Jarin T. Mourosi ◽  
Md. Fahim Khan ◽  
Mohammad J. Hosen
Keyword(s):  
Molecular Docking ◽  
T Cell ◽  
B Cell ◽  
Chikungunya Virus ◽  
Clinical Investigation ◽  
Peptide Vaccine ◽  
Cell Epitope ◽  
Docking Simulation ◽  
T Cell Epitope ◽  
Molecular Docking Simulation

Background: Chikungunya is an arthropod-borne viral disease characterized by abrupt onset of fever frequently accompanied by joint pain, which has been identified in over 60 countries in Africa, the Americas, Asia, and Europe. Methods: Regardless of the availability of molecular knowledge of this virus, no definite vaccine or other remedial agents have been developed yet. In the present study, a combination of B-cell and T-cell epitope predictions, followed by molecular docking simulation approach has been carried out to design a potential epitope-based peptide vaccine, which can trigger a critical immune response against the viral infections. Results: A total of 52 sequences of E1 glycoprotein from the previously reported isolates of Chikungunya outbreaks were retrieved and examined through in silico methods to identify a potential B-cell and T-cell epitope. From the two separate epitope prediction servers, five potential B-cell epitopes were selected, among them “NTQLSEAHVEKS” was found highly conserved across strains and manifests high antigenicity with surface accessibility, flexibility, and hydrophilicity. Similarly, two highly conserved, non-allergenic, non-cytotoxic putative T-cell epitopes having maximum population coverage were screened to bind with the HLA-C 12*03 molecule. Molecular docking simulation revealed potential T-cell based epitope “KTEFASAYR” as a vaccine candidate for this virus. Conclusion: A combination of these B-cell and T-cell epitope-based vaccine can open up a new skyline with broader therapeutic application against Chikungunya virus with further experimental and clinical investigation.

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 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 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 Epitope - based peptide vaccine against glycoprotein G of Nipah henipavirus using immunoinformatics approaches

2019 ◽  
Author(s):  
Arwa A. Mohammed ◽  
Shaza W. Shantier ◽  
Mujahed I. Mustafa ◽  
Hind K. Osman ◽  
Hashim E. Elmansi ◽  
...  
Keyword(s):  
B Cell ◽  
Binding Affinity ◽  
Mhc Class Ii ◽  
Peptide Vaccine ◽  
Cell Epitope ◽  
Case Fatality ◽  
Mhc I ◽  
Strong Binding ◽  
Glycoprotein G

AbstractBackgroundNipah virus (NiV) is a member of the genus Henipavirus of the family Paramyxoviridae, characterized by high pathogenicity and endemic in South Asia, first emerged in Malaysia in 1998. The case-fatality varies from 40% to 70% depending on the severity of the disease and on the availability of adequate healthcare facilities. At present no antiviral drugs are available for NiV disease and the treatment is just supportive. Clinical presentation ranges from asymptomatic infection to fatal encephalitis. Bats are the main reservoir for this virus, which can cause disease in humans and animals. The last investigated NiV outbreak has occurred in May 2018 in Kerala.ObjectiveThis study aims to predict effective epitope-based vaccine against glycoprotein G of Nipah henipavirus using immunoinformatics approaches.Methods and MaterialsGlycoprotein G of Nipah henipavirus sequence was retrieved from NCBI. Different prediction tools were used to analyze the nominee’s epitopes in BepiPred-2.0: Sequential B-Cell Epitope Predictor for B-cell, T-cell MHC class II & I. Then the proposed peptides were docked using Autodock 4.0 software program.Results and ConclusionsPeptide TVYHCSAVY shows a very strong binding affinity to MHC I alleles while FLIDRINWI shows a very strong binding affinity to MHC II and MHC I alleles. This indicates a strong potential to formulate a new vaccine, especially with the peptide FLIDRINWI that is likely to be the first proposed epitope-based vaccine against glycoprotein G of Nipah henipavirus. This study recommends an in-vivo assessment for the most promising peptides especially FLIDRINWI.

scholarly journals Multi-epitope Based Peptide Vaccine Design Using Three Structural Proteins (S, E, and M) of SARS-CoV-2: An In Silico Approach

2020 ◽  
Author(s):  
Arpita Singha Roy ◽  
Mahafujul Islam Quadery Tonmoy ◽  
Atqiya Fariha ◽  
Ithmam Hami ◽  
Ibrahim Khalil Afif ◽  
...  
Keyword(s):  
T Cell ◽  
B Cell ◽  
Peptide Vaccine ◽  
Evolutionary Relationship ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Vaccine Design ◽  
Structural Proteins ◽  
T Cell Epitopes ◽  
Novel Coronavirus

AbstractSevere Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the novel coronavirus responsible for the ongoing pandemic of coronavirus disease (COVID-19). No sustainable treatment option is available so far to tackle such a public health threat. Therefore, designing a suitable vaccine to overcome this hurdle asks for immediate attention. In this study, we targeted for a design of multi-epitope based vaccine using immunoinformatics tools. We considered the structural proteins S, E and, M of SARS-CoV-2, since they facilitate the infection of the virus into host cell and using different bioinformatics tools and servers, we predicted multiple B-cell and T-cell epitopes having potential for the required vaccine design. Phylogenetic analysis provided insight on ancestral molecular changes and molecular evolutionary relationship of S, E, and M proteins. Based on the antigenicity and surface accessibility of these proteins, eight epitopes were selected by various B cell and T cell epitope prediction tools. Molecular docking was executed to interpret the binding interactions of these epitopes and three potential epitopes WTAGAAAYY, YVYSRVKNL, and GTITVEELK were selected for their noticeable higher binding affinity scores −9.1, −7.4, and −7.0 kcal/mol, respectively. Targeted epitopes had 91.09% population coverage worldwide. In summary, we identified three epitopes having the most significant properties of designing the peptide-based vaccine against SARS-CoV-2.

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