scholarly journals B Cell Epitopes of Four Fimbriae Antigens of Klebsiella pneumoniae: A Comprehensive In Silico Study for Vaccine Development

2020 ◽  
Author(s):  
Fatemeh Nemati Zargaran ◽  
Alisha Akya ◽  
Shahab Rezaeian ◽  
Keyghobad Ghadiri ◽  
Roya Chegene Lorestani ◽  
...  
Keyword(s):  
Klebsiella Pneumoniae ◽  
B Cell ◽  
In Silico ◽  
Vaccine Development ◽  
B Cell Epitopes ◽  
In Silico Study

scholarly journals In silico study to predict promiscuous T cell and B cell-epitopes derived from the vaccine candidate antigens of Plasmodium vivax binding to MHC class-II alleles

2022 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Umar Farooq ◽  
Nazam Khan ◽  
MonaN Bin-Mwena ◽  
MashaelW Alruways ◽  
Noor MotairM Allehyani ◽  
...  
Keyword(s):  
T Cell ◽  
B Cell ◽  
Plasmodium Vivax ◽  
Mhc Class Ii ◽  
In Silico ◽  
Vaccine Candidate ◽  
Class Ii ◽  
B Cell Epitopes ◽  
In Silico Study ◽  
Mhc Class Ii Alleles

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.

In silico prediction of T‐cell and B‐cell epitopes of human papillomavirus type 16 L1 protein

2021 ◽  
Author(s):  
Shahab Mahmoudvand ◽  
Somayeh Shokri ◽  
Manoochehr Makvandi ◽  
Reza Taherkhani ◽  
Mohammad Rashno ◽  
...  
Keyword(s):  
Human Papillomavirus ◽  
T Cell ◽  
B Cell ◽  
In Silico ◽  
In Silico Prediction ◽  
B Cell Epitopes ◽  
Human Papillomavirus Type 16 ◽  
L1 Protein

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 Serodiagnosis of tuberculosis using nine in silico predicted B-cell epitopes peptides derived from Mycobacterium tuberculosis proteins

2010 ◽  
Vol 14 ◽  
pp. e354
Author(s):  
L. Baassii ◽  
K. Sadki ◽  
F. Seghrouchni ◽  
S. Contini ◽  
W. Cherki ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
B Cell ◽  
In Silico ◽  
B Cell Epitopes

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.

scholarly journals In silico prediction of B cell epitopes of the hemolysis-associated protein 1 for vaccine design against leptospirosis

2020 ◽  
Vol 1 (1) ◽  
pp. 32-37
Author(s):  
Sakineh Poorhosein Fookolaee ◽  
Somayyeh Talebishelimaki ◽  
Mohammad Taha Saadati Rad ◽  
Mostafa Akbarian Rokni
Keyword(s):  
B Cell ◽  
In Silico ◽  
Vaccine Design ◽  
In Silico Prediction ◽  
B Cell Epitopes

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 In-silico Design of Multi-epitope Vaccine against Nipah Virus using Immunoinformatics Approach

2021 ◽  
Vol 15 (1) ◽  
pp. 212-231
Author(s):  
Suraj Raju ◽  
Debasish Sahoo ◽  
Vikas Kumar Bhari
Keyword(s):  
T Cell ◽  
B Cell ◽  
In Silico ◽  
Vaccine Development ◽  
Homology Modelling ◽  
Nipah Virus ◽  
Docking Simulation ◽  
Dynamics Simulation ◽  
Cytotoxic T Cell ◽  
Viral Spread

Nipah virus is a pleomorphic virus that causes high mortality with unpredictable outbreaks. The virus also shows high zoonotic potential with long term neurological damage after recovery further adding to the disease burden. An in-silico epitope-based vaccine offers a promising solution to supplement wider efforts to control the viral spread. This is achieved through immunoinformatics approach using a plethora of servers available. We derived cytotoxic T-cell, T-Helper, B-cell and IFN-γ targeting epitopes from surface glycoprotein G. Cytotoxic T-cell specific epitopes, HLA-B*4402, chimeric multiepitope vaccine structures were prepared using homology modelling method. The structures were validated using various methods and docking simulation was performed between epitopes and HLA-B*4402. Similarly, the vaccine construct was docked to Toll like receptor-4 and a molecular dynamics simulation was performed to assess stability of interaction. Both the docking simulations showed stable interactions with their respective receptors. Immune-simulation was carried out to validate the efficacy of vaccine candidate which showed elevated levels of antibodies such as IgM and IgG due to increase in active B cell population. Both in-vitro and in-vivo serological analysis is required for confirmation of vaccine potency. To facilitate this effort, codon optimization was undertaken to remove existing codon bias. The optimized gene sequence was cloned into the PUC19 vector to express in Escherichia coli K12 strain. Additionally, a poly histidine (6xHis) tag was added at the C-terminal end to ease the purification step. The immune-informatics approach hopes to accelerate vaccine development process to reduce the risk of attenuation while increasing the success rates of pre-clinical trials.

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