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.

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.

scholarly journals Data curation to improve the pattern recognition performance of B-cell epitope prediction by support vector machine

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Li Cen Lim ◽  
Yee Ying Lim ◽  
Yee Siew Choong
Keyword(s):  
Pattern Recognition ◽  
Support Vector Machine ◽  
B Cell ◽  
Recognition Performance ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Support Vector ◽  
B Cell Epitopes ◽  
Prediction Module ◽  
B Cell Epitope

Abstract B-cell epitope will be recognized and attached to the surface of receptors in B-lymphocytes to trigger immune response, thus are the vital elements in the field of epitope-based vaccine design, antibody production and therapeutic development. However, the experimental approaches in mapping epitopes are time consuming and costly. Computational prediction could offer an unbiased preliminary selection to reduce the number of epitopes for experimental validation. The deposited B-cell epitopes in the databases are those with experimentally determined positive/negative peptides and some are ambiguous resulted from different experimental methods. Prior to the development of B-cell epitope prediction module, the available dataset need to be handled with care. In this work, we first pre-processed the B-cell epitope dataset prior to B-cell epitopes prediction based on pattern recognition using support vector machine (SVM). By using only the absolute epitopes and non-epitopes, the datasets were classified into five categories of pathogen and worked on the 6-mers peptide sequences. The pre-processing of the datasets have improved the B-cell epitope prediction performance up to 99.1 % accuracy and showed significant improvement in cross validation results. It could be useful when incorporated with physicochemical propensity ranking in the future for the development of B-cell epitope prediction module.

scholarly journals Linear and Conformational B Cell Epitope Prediction of the HER 2 ECD-Subdomain III by in silico Methods

2012 ◽  
Vol 13 (7) ◽  
pp. 3053-3059 ◽  
Author(s):  
Manijeh Mahdavi ◽  
Hassan Mohabatkar ◽  
Mehrnaz Keyhanfar ◽  
Abbas Jafarian Dehkordi ◽  
Mohammad Rabbani
Keyword(s):  
B Cell ◽  
In Silico ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
B Cell Epitope ◽  
Her 2 ◽  
In Silico Methods

scholarly journals Immunodominant linear B cell epitopes in the spike and membrane proteins of SARS-CoV-2 identified by immunoinformatics prediction and immunoassay

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kanokporn Polyiam ◽  
Waranyoo Phoolcharoen ◽  
Namphueng Butkhot ◽  
Chanya Srisaowakarn ◽  
Arunee Thitithanyanont ◽  
...  
Keyword(s):  
B Cell ◽  
Cleavage Site ◽  
Vaccine Development ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
E Proteins ◽  
B Cell Epitopes ◽  
C Terminus ◽  
B Cell Epitope ◽  
Linear B

AbstractSARS-CoV-2 continues to infect an ever-expanding number of people, resulting in an increase in the number of deaths globally. With the emergence of new variants, there is a corresponding decrease in the currently available vaccine efficacy, highlighting the need for greater insights into the viral epitope profile for both vaccine design and assessment. In this study, three immunodominant linear B cell epitopes in the SARS-CoV-2 spike receptor-binding domain (RBD) were identified by immunoinformatics prediction, and confirmed by ELISA with sera from Macaca fascicularis vaccinated with a SARS-CoV-2 RBD subunit vaccine. Further immunoinformatics analyses of these three epitopes gave rise to a method of linear B cell epitope prediction and selection. B cell epitopes in the spike (S), membrane (M), and envelope (E) proteins were subsequently predicted and confirmed using convalescent sera from COVID-19 infected patients. Immunodominant epitopes were identified in three regions of the S2 domain, one region at the S1/S2 cleavage site and one region at the C-terminus of the M protein. Epitope mapping revealed that most of the amino acid changes found in variants of concern are located within B cell epitopes in the NTD, RBD, and S1/S2 cleavage site. This work provides insights into B cell epitopes of SARS-CoV-2 as well as immunoinformatics methods for B cell epitope prediction, which will improve and enhance SARS-CoV-2 vaccine development against emergent variants.

scholarly journals Benchmarking B-Cell Epitope Prediction for the Design of Peptide-Based Vaccines: Problems and Prospects

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Salvador Eugenio C. Caoili
Keyword(s):  
B Cell ◽  
Protein Function ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Cross Reactivity ◽  
Sequence Alignments ◽  
B Cell Epitopes ◽  
B Cell Epitope ◽  
Physicochemical Factors ◽  
Structural Differences

To better support the design of peptide-based vaccines, refinement of methods to predict B-cell epitopes necessitates meaningful benchmarking against empirical data on the cross-reactivity of polyclonal antipeptide antibodies with proteins, such that the positive data reflect functionally relevant cross-reactivity (which is consistent with antibody-mediated change in protein function) and the negative data reflect genuine absence of cross-reactivity (rather than apparent absence of cross-reactivity due to artifactual masking of B-cell epitopes in immunoassays). These data are heterogeneous in view of multiple factors that complicate B-cell epitope prediction, notably physicochemical factors that define key structural differences between immunizing peptides and their cognate proteins (e.g., unmatched electrical charges along the peptide-protein sequence alignments). If the data are partitioned with respect to these factors, iterative parallel benchmarking against the resulting subsets of data provides a basis for systematically identifying and addressing the limitations of methods for B-cell epitope prediction as applied to vaccine design.

The Computational Prediction Methods for Linear B-cell Epitopes

2019 ◽  
Vol 14 (3) ◽  
pp. 226-233 ◽  
Author(s):  
Cangzhi Jia ◽  
Hongyan Gong ◽  
Yan Zhu ◽  
Yixia Shi
Keyword(s):  
B Cell ◽  
Structural Information ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Computational Prediction ◽  
Extraction Methods ◽  
B Cell Epitopes ◽  
B Cell Epitope ◽  
Reliable Methods ◽  
Linear B

Background: B-cell epitope prediction is an essential tool for a variety of immunological studies. For identifying such epitopes, several computational predictors have been proposed in the past 10 years. Objective: In this review, we summarized the representative computational approaches developed for the identification of linear B-cell epitopes. </P><P> Methods: We mainly discuss the datasets, feature extraction methods and classification methods used in the previous work. Results: The performance of the existing methods was not very satisfying, and so more effective approaches should be proposed by considering the structural information of proteins. Conclusion: We consider existing challenges and future perspectives for developing reliable methods for predicting linear B-cell epitopes.

scholarly journals Identification of B-Cell Epitopes with Potential to Serologicaly Discrimnate Dengue from Zika Infections

Viruses ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1079 ◽  
Author(s):  
Alice F. Versiani ◽  
Raissa Prado Rocha ◽  
Tiago A. O. Mendes ◽  
Glauco C. Pereira ◽  
Jordana Graziella A. Coelho dos Reis ◽  
...  
Keyword(s):  
Early Diagnosis ◽  
B Cell ◽  
Epitope Mapping ◽  
Cell Epitope ◽  
Elisa Test ◽  
B Cell Epitopes ◽  
Denv Serotypes ◽  
B Cell Epitope ◽  
Human Sera ◽  
Cellulose Membranes

Dengue is currently one of the most important arbovirus infections worldwide. Early diagnosis is important for disease outcome, particularly for those afflicted with the severe forms of infection. The goal of this work was to identify conserved and polymorphic linear B-cell Dengue virus (DENV) epitopes that could be used for diagnostic purposes. To this end, we aligned the predicted viral proteome of the four DENV serotype and performed in silico B-cell epitope mapping. We developed a script in Perl integrating alignment and prediction information to identify potential serotype-specific epitopes. We excluded epitopes that were similarly present in the yellow fever and zika viruses’ proteomes. A total of 15 polymorphic and nine conserved peptides among DENV serotypes were selected. Peptides were spotted on cellulose membranes and tested against sera from rabbits that were monoinfected with each DENV serotype. Although serotype-specific peptides failed to recognize any sera, three conserved peptides were recognized by all anti-dengue sera and were included on an ELISA test employing a well-characterized human sera bank. Of the three peptides, one was able to efficiently identify sera from all four DENV serotypes and to discriminate them from Zika virus positive sera.

scholarly journals Bioinformatics Resources and Tools for Conformational B-Cell Epitope Prediction

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Pingping Sun ◽  
Haixu Ju ◽  
Zhenbang Liu ◽  
Qiao Ning ◽  
Jian Zhang ◽  
...  
Keyword(s):  
B Cell ◽  
High Speed ◽  
Low Cost ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Experimental Methods ◽  
Time Cost ◽  
B Cell Epitopes ◽  
B Cell Epitope ◽  
Humoral Responses

Identification of epitopes which invoke strong humoral responses is an essential issue in the field of immunology. Localizing epitopes by experimental methods is expensive in terms of time, cost, and effort; therefore, computational methods feature for its low cost and high speed was employed to predict B-cell epitopes. In this paper, we review the recent advance of bioinformatics resources and tools in conformational B-cell epitope prediction, including databases, algorithms, web servers, and their applications in solving problems in related areas. To stimulate the development of better tools, some promising directions are also extensively discussed.

scholarly journals Corrigendum: Leishmania infantum Virulence Factor A2 Protein: Linear B-Cell Epitope Mapping and Identification of Three Main Linear B-Cell Epitopes in Vaccinated and Naturally Infected Dogs

2018 ◽  
Vol 9 ◽  
Author(s):  
Monique Paiva Campos ◽  
Fabiano Borges Figueiredo ◽  
Fernanda Nazaré Morgado ◽  
Alinne Rangel dos Santos Renzetti ◽  
Sara Maria Marques de Souza ◽  
...  
Keyword(s):  
B Cell ◽  
Virulence Factor ◽  
Leishmania Infantum ◽  
Epitope Mapping ◽  
Cell Epitope ◽  
B Cell Epitopes ◽  
B Cell Epitope ◽  
Linear B
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