scholarly journals In silico-guided sequence modifications of K-ras epitopes improve immunological outcome against G12V and G13D mutant KRAS antigens

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5056 ◽  
Author(s):  
Allan Wee Ren Ng ◽  
Pei Jun Tan ◽  
Winfrey Pui Yee Hoo ◽  
Dek Shen Liew ◽  
Michelle Yee Mun Teo ◽  
...  
Keyword(s):  
B Cell ◽  
In Silico ◽  
Secondary Structure Prediction ◽  
Cell Epitope ◽  
Peptide Sequence ◽  
Single Amino Acid ◽  
Peptide Vaccines ◽  
Exon 2 ◽  
B Cell Epitopes

Background Somatic point substitution mutations in the KRAS proto-oncogene primarily affect codons 12/13 where glycine is converted into other amino acids, and are highly prevalent in pancreatic, colorectal, and non-small cell lung cancers. These cohorts are non-responsive to anti-EGFR treatments, and are left with non-specific chemotherapy regimens as their sole treatment options. In the past, the development of peptide vaccines for cancer treatment was reported to have poor AT properties when inducing immune responses. Utilization of bioinformatics tools have since become an interesting approach in improving the design of peptide vaccines based on T- and B-cell epitope predictions. Methods In this study, the region spanning exon 2 from the 4th to 18th codon within the peptide sequence of wtKRAS was chosen for sequence manipulation. Mutated G12V and G13D K-ras controls were generated in silico, along with additional single amino acid substitutions flanking the original codon 12/13 mutations. IEDB was used for assessing human and mouse MHC class I/II epitope predictions, as well as linear B-cell epitopes predictions, while RNA secondary structure prediction was performed via CENTROIDFOLD. A scoring and ranking system was established in order to shortlist top mimotopes whereby normalized and reducing weighted scores were assigned to peptide sequences based on seven immunological parameters. Among the top 20 ranked peptide sequences, peptides of three mimotopes were synthesized and subjected to in vitro and in vivo immunoassays. Mice PBMCs were treated in vitro and subjected to cytokine assessment using CBA assay. Thereafter, mice were immunized and sera were subjected to IgG-based ELISA. Results In silico immunogenicity prediction using IEDB tools shortlisted one G12V mimotope (68-V) and two G13D mimotopes (164-D, 224-D) from a total of 1,680 candidates. Shortlisted mimotopes were predicted to promote high MHC-II and -I affinities with optimized B-cell epitopes. CBA assay indicated that: 224-D induced secretions of IL-4, IL-5, IL-10, IL-12p70, and IL-21; 164-D triggered IL-10 and TNF-α; while 68-V showed no immunological responses. Specific-IgG sera titers against mutated K-ras antigens from 164-D immunized Balb/c mice were also elevated post first and second boosters compared to wild-type and G12/G13 controls. Discussion In silico-guided predictions of mutated K-ras T- and B-cell epitopes were successful in identifying two immunogens with high predictive scores, Th-bias cytokine induction and IgG-specific stimulation. Developments of such immunogens are potentially useful for future immunotherapeutic and diagnostic applications against KRAS(+) malignancies, monoclonal antibody production, and various other research and development initiatives.

scholarly journals Design of a candidate multi-epitope vaccine against SARS-CoV-2 using reverse vaccinology approach

2021 ◽  
Author(s):  
Amir Atapour ◽  
Ali Golestan
Keyword(s):  
B Cell ◽  
In Silico ◽  
Peptide Sequence ◽  
Epitope Vaccine ◽  
B Cell Epitopes ◽  
S Protein ◽  
Global Epidemic ◽  
In Vivo Experiments

Abstract Coronavirus 2019 (COVID-19) infection as a global epidemic that is spreading dramatically day to day. Currently, many efforts have been made against COVID-19 through the designing or developing of specific vaccine or drug, worldwide. In this study, we used the bioinformatics approach to design an effective multi-epitope vaccine against COVID-19 based on Spike (S) protein. Here, we employed in silico tools to identify potential T and B cell epitopes from S protein that have the ability to induce cellular and humoral immunity. Then, the peptide sequence of potential T, B cell epitopes and flagellin (as adjuvant molecule) were joined together by suitable linkers to construct of candidate multi-epitope vaccine (MEV). Subsequently, immunological and structural evaluations such as antigenicity, allergenicity, 3D modeling, molecular docking, fast flexibility simulations as well as in silico cloning were performed. Immunological and structural computational data showed that designed MEV potentially has proper capacity for inducing of cellular and humoral immune responses against COVID-19. Based on the preliminary results, in vitro and in vivo experiments are required for validation in the future.

scholarly journals Designing A Candidate Multi-Epitope Vaccine Against SARS-CoV-2 Using Reverse Vaccinology Approach

2021 ◽  
Author(s):  
Amir Atapour ◽  
Ali Golestan
Keyword(s):  
Molecular Docking ◽  
B Cell ◽  
In Silico ◽  
Md Simulation ◽  
Peptide Sequence ◽  
Reverse Vaccinology ◽  
Effective Vaccine ◽  
Epitope Vaccine ◽  
B Cell Epitopes

Abstract Coronavirus 2019 (COVID-19) infection is a global epidemic that is spreading dramatically from day today. Currently, many efforts have been made against COVID-19 through the designing or developing of specific vaccines or drugs, worldwide. Unfortunately, to date, it has not been successful. Therefore, an effective vaccine against COVID-19 is mandatory. In this study, we used the bioinformatics approach to design an effective multi-epitope vaccine against COVID-19 based on Spike protein. Here, we implemented in silico tools to identify potential T and B cell epitopes that can induce cellular and humoral immunity. Then, the peptide sequence of potential T, B cell epitopes, and flagellin (as an adjuvant molecule) was joined together by suitable linkers to construct of candidate multi-epitope vaccine (MEV). Subsequently, immunological and structural evaluations such as antigenicity, 3D modeling, etc. were performed. In the following, molecular docking of vaccine constructs with Toll-Like Receptors 5 (TLR5), Molecular Dynamics (MD) simulation as well as in silico cloning were carried out. Immunological and structural computational data showed that designed MEV potentially has proper capacity for inducing cellular and humoral immune responses against COVID-19. Based on the preliminary results, in vitro and in vivo experiments are required for validation in the future. Keywords: COVID-19, Vaccine, Reverse Vaccinology, Multi-epitope, Molecular docking, MD Simulation.

scholarly journals An Introduction to B-Cell Epitope Mapping and In Silico Epitope Prediction

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Lenka Potocnakova ◽  
Mangesh Bhide ◽  
Lucia Borszekova Pulzova
Keyword(s):  
B Cell ◽  
In Silico ◽  
Epitope Mapping ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Diagnostic Tools ◽  
Accurate Identification ◽  
B Cell Epitopes ◽  
Epitope Identification ◽  
B Cell Epitope

Identification of B-cell epitopes is a fundamental step for development of epitope-based vaccines, therapeutic antibodies, and diagnostic tools. Epitope-based antibodies are currently the most promising class of biopharmaceuticals. In the last decade, in-depth in silico analysis and categorization of the experimentally identified epitopes stimulated development of algorithms for epitope prediction. Recently, various in silico tools are employed in attempts to predict B-cell epitopes based on sequence and/or structural data. The main objective of epitope identification is to replace an antigen in the immunization, antibody production, and serodiagnosis. The accurate identification of B-cell epitopes still presents major challenges for immunologists. Advances in B-cell epitope mapping and computational prediction have yielded molecular insights into the process of biorecognition and formation of antigen-antibody complex, which may help to localize B-cell epitopes more precisely. In this paper, we have comprehensively reviewed state-of-the-art experimental methods for B-cell epitope identification, existing databases for epitopes, and novel in silico resources and prediction tools available online. We have also elaborated new trends in the antibody-based epitope prediction. The aim of this review is to assist researchers in identification of B-cell epitopes.

scholarly journals Use of a Novel Peptide Welding Technology Platform for the Development of B- and T-Cell Epitope-Based Vaccines

Vaccines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 526
Author(s):  
Francesco Nicoli ◽  
Salvatore Pacifico ◽  
Eleonora Gallerani ◽  
Erika Marzola ◽  
Valentina Albanese ◽  
...  
Keyword(s):  
T Cell ◽  
B Cell ◽  
Cell Epitope ◽  
Subcutaneous Administration ◽  
T Cell Epitopes ◽  
Peptide Vaccines ◽  
Peptide Epitope ◽  
Welding Technology

Peptide vaccines incorporating B- and T-cell epitopes have shown promise in the context of various cancers and infections. These vaccines are relatively simple to manufacture, but more immunogenic formulations are considered a priority. We developed tetrabranched derivatives for this purpose based on a novel peptide welding technology (PWT). PWTs provide molecular scaffolds for the efficient synthesis of ultrapure peptide dendrimers, which allow the delivery of multiple ligands within a single macromolecular structure. Peptide vaccines incorporating T-cell epitopes derived from melanoma and B-cell epitopes derived from human immunodeficiency virus, synthesized using this approach, elicited primary immune responses in vitro and in vivo. Subcutaneous administration of the B-cell epitope-based vaccines also elicited more potent humoral responses than subcutaneous administration of the corresponding peptides alone. Highly immunogenic peptide epitope-based vaccines can therefore be generated quickly and easily using a novel PWT.

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.

Advances in In-silico B-cell Epitope Prediction

2019 ◽  
Vol 19 (2) ◽  
pp. 105-115 ◽  
Author(s):  
Pingping Sun ◽  
Sijia Guo ◽  
Jiahang Sun ◽  
Liming Tan ◽  
Chang Lu ◽  
...  
Keyword(s):  
B Cell ◽  
In Silico ◽  
Vaccine Development ◽  
Cell Epitope ◽  
Disease Diagnosis ◽  
Diagnostic Tools ◽  
Accurate Identification ◽  
B Cell Epitopes ◽  
B Cell Epitope ◽  
In Silico Methods

Identification of B-cell epitopes in target antigens is one of the most crucial steps for epitopebased vaccine development, immunodiagnostic tests, antibody production, and disease diagnosis and therapy. Experimental methods for B-cell epitope mapping are time consuming, costly and labor intensive; in the meantime, various in-silico methods are proposed to predict both linear and conformational B-cell epitopes. The accurate identification of B-cell epitopes presents major challenges for immunoinformaticians. In this paper, we have comprehensively reviewed in-silico methods for B-cell epitope identification. The aim of this review is to stimulate the development of better tools which could improve the identification of B-cell epitopes, and further for the development of therapeutic antibodies and diagnostic tools.

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.

In silico prediction and in vitro identification of bluetongue virus 4 VP5 protein B-cell epitopes

2013 ◽  
Vol 98 (7) ◽  
pp. 3033-3047 ◽  
Author(s):  
L. Sun ◽  
E. C. Sun ◽  
T. Yang ◽  
Q. Y. Xu ◽  
Y. F. Feng ◽  
...  
Keyword(s):  
B Cell ◽  
In Silico ◽  
Bluetongue Virus ◽  
In Silico Prediction ◽  
B Cell Epitopes ◽  
Protein B

scholarly journals Prediction of B-cell epitope by in silico analysis of Mycobacterium tuberculosis Ag85B antigen

2020 ◽  
pp. 101-109
Author(s):  
Nihayatul Karimah ◽  
Sabar Pambudi
Keyword(s):  
Mycobacterium Tuberculosis ◽  
B Cell ◽  
In Silico ◽  
Cell Epitope ◽  
Docking Simulation ◽  
In Silico Analysis ◽  
Protein Biomarkers ◽  
B Cell Epitopes ◽  
Good Target ◽  
Silico Analysis

Mycobacterium tuberculosis (Mtb) is a causative pathogen of tuberculosis (TB) that emerges as one of the deadliest communicable diseases in Indonesia. The quest for protein biomarkers for TB has been conducted in order to develop a TB diagnostic kit and a TB vaccine. One of the abundant biomarkers in the TB infected human serum is the Ag85B antigen. In this study, we employed immunoinformatic prediction tools such as Ellipro and VaxiJen to predict the B-cell epitopes of Ag85B wildtype and multidrug resistance type (mutant). We then performed molecular docking simulation to evaluate the predicted epitopes using HADDOCK. The screening of both continuous and discontinuous B-cell epitopes using criteria-based analysis resulted in the eight linear epitopes and two conformational epitopes in Ag85B with high antigenicity. The in silico analysis showed no major differences between Ag85B wildtype and Ag85B mutant, implying Ag85B a good target for TB vaccine candidates but not for a specific biomarker that differentiates wild-type and mutant TB.

scholarly journals Computational Approach for Predicting Common Epitopes in the VP1 Structural Protein of Enterovirus Serotypes EV-D68, EV-D70, and EV-A71

2021 ◽  
Author(s):  
Rihabe Boussettine ◽  
Yassine Kasmi ◽  
Najwa Hassou ◽  
Hlima Bessi ◽  
Moulay Mustapha Ennaji
Keyword(s):  
T Cell ◽  
B Cell ◽  
Cell Epitope ◽  
Human Enterovirus ◽  
T Cell Epitopes ◽  
Structural Protein ◽  
B Cell Epitopes ◽  
Study Results ◽  
Enterovirus Serotypes

The three human Enterovirus serotypes D-68, D-70, and A-71, are common pathogens that are transmitted by fecal-oral and aerosol routes. These positive RNA viruses were known to exhibit high levels of genetic diversity and variability. Currently, no vaccines are available to protect humans from these three serotypes. Therefore, efforts are needed for the development of a vaccine directed against heterologous viruses. In our study, an immunoinformatics approach is used to identify T- and B-cell epitopes that may help for the generation of a universal vaccine against EV-D70, EV-A71, and EV-D68. B and T cell epitopes were selected based on their length. As a result, 5 B cell epitopes and 18 T cell epitopes were predicted. Our B cell epitope prediction results showed that there are a number of linear regions. Position 150-170 was found to be the most immunogenic for the different strains. Regarding the epitopes of the T lymphocytes, the result of the interactions shows that 95% of the predicted epitopes are common between the 3 sequences and the 5 methods used. These results demonstrate the great immunogenic potential of these sequences and their capacities to trigger immune reactions in people with different HLA alleles. The “VFYDGFAGF” epitope is the most important and most immunogenic for triggering an immune response. Our study results allowed us to identify epitopes to be used in the development of cross-protection vaccines against the three Enterovirus serotypes. However, in vivo and in vitro studies are needed to assess the potential of the epitopes predicted by our study.

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