The effect of the sequential order of T- and B-cell epitopes on the immunogenicity and antibody recognition of B-cell epitope

Peptides 1994 ◽  
1995 ◽  
pp. 825-826
Author(s):  
G. Denton ◽  
J. Kajtár ◽  
T. M. Morris ◽  
M. R. Price ◽  
F. Hudecz
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Li Cen Lim ◽  
Yee Ying Lim ◽  
Yee Siew Choong

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.


2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Lenka Potocnakova ◽  
Mangesh Bhide ◽  
Lucia Borszekova Pulzova

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.


2018 ◽  
Vol 49 (4) ◽  
pp. 1600-1614 ◽  
Author(s):  
Shudong He ◽  
Jinlong Zhao ◽  
Walid Elfalleh ◽  
Mohamed Jemaà ◽  
Hanju  Sun ◽  
...  

Background/Aims: The incidence of lectin allergic disease is increasing in recent decades, and definitive treatment is still lacking. Identification of B and T-cell epitopes of allergen will be useful in understanding the allergen antibody responses as well as aiding in the development of new diagnostics and therapy regimens for lectin poisoning. In the current study, we mainly addressed these questions. Methods: Three-dimensional structure of the lectin from black turtle bean (Phaseolus vulgaris L.) was modeled using the structural template of Phytohemagglutinin from P. vulgaris (PHA-E, PDB ID: 3wcs.1.A) with high identity. The B and T-cell epitopes were screened and identified by immunoinformatics and subsequently validated by ELISA, lymphocyte proliferation and cytokine profile analyses. Results: Seven potential B-cell epitopes (B1 to B7) were identified by sequence and structure based methods, while three T-cell epitopes (T1 to T3) were identified by the predictions of binding score and inhibitory concentration. The epitope peptides were synthesized. Significant IgE binding capability was found in B-cell epitopes (B2, B5, B6 and B7) and T2 (a cryptic B-cell epitope). T1 and T2 induced significant lymphoproliferation, and the release of IL-4 and IL-5 cytokine confirmed the validity of T-cell epitope prediction. Abundant hydrophobic amino acids were found in B-cell epitope and T-cell epitope regions by amino acid analysis. Positively charged amino acids, such as His residue, might be more favored for B-cell epitope. Conclusion: The present approach can be applied for the identification of epitopes in novel allergen proteins and thus for designing diagnostics and therapies in lectin allergy.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kanokporn Polyiam ◽  
Waranyoo Phoolcharoen ◽  
Namphueng Butkhot ◽  
Chanya Srisaowakarn ◽  
Arunee Thitithanyanont ◽  
...  

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.


2016 ◽  
Vol 2016 ◽  
pp. 1-7
Author(s):  
Huixin Liu ◽  
Wei Liu ◽  
Xuexia Hou ◽  
Lin Zhang ◽  
Qin Hao ◽  
...  

The 41 kD flagellin of Borrelia burgdorferi (B. burgdorferi) is a major component of periplasmic flagellar filament core and a good candidate for serodiagnosis in early stage of Lyme disease. Here, we chose 89 B. burgdorferi strains in China, amplified the gene encoding the 41 kD flagellin, and compared the sequences. The results showed that genetic diversity presented in the 41 kD flagellin genes of all 89 strains among the four genotypes of B. burgdorferi, especially in the genotype of B. garinii. Some specific mutation sites for each genotype of the 41 kD flagellin genes were found, which could be used for genotyping B. burgdorferi strains in China. Human B-cell epitope analysis showed that thirteen of 15 nonsynonymous mutations occurred in the epitope region of 41 kD flagellin and thirty of 42 B-cell epitopes were altered due to all 13 nonsynonymous mutations in the epitope region, which may affect the function of the antigen. Nonsynonymous mutations and changed human B-cell epitopes exist in 41 kD flagellin of B. burgdorferi sensu lato strains; these changes should be considered in serodiagnosis of Lyme disease.


2006 ◽  
Vol 04 (02) ◽  
pp. 389-402 ◽  
Author(s):  
ELENA SVIRSHCHEVSKAYA ◽  
LUDMILA ALEKSEEVA ◽  
ALEXEI MARCHENKO ◽  
SERGEI BENEVOLENSKII ◽  
VALENTINA M. BERZHEC ◽  
...  

Sub-unit vaccines are synthetic or recombinant peptides representing T- or B-cell epitopes of major protein antigens from a particular pathogen. Epitope selection requires the synthesis of peptides that overlap the protein sequences and screening for the most effective ones. In this study a new method of immunogenic peptide selection based on the analysis of information structure of protein sequences is suggested. The analysis of known B-cell epitope location in the information structure of Aspergillus fumigatus proteins Asp f 2 and Asp f 3 has shown that epitopes are scattered along the sequences of proteins for the exception of sites with Increased Degree Information Coordination (IDIC). Based on these results peptides from different allergens such as Asp f 2, Der p 1, and Fel d 1 were selected and produced in a recombinant form in the context of yeast virus-like particles (VLPs). Immunization of mice with VLPs containing peptides form allergens has induced the production of IgG able to recognize full-length antigens. This result suggests that the analysis of information structure of proteins can be used for the selection of peptides possessing cryptic B-cell epitope activity.


2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Salvador Eugenio C. Caoili

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.


2020 ◽  
Author(s):  
Lin Li ◽  
Zhongpeng Zhao ◽  
Xiaolan Yang ◽  
WenDong Li ◽  
Shaolong Chen ◽  
...  

SARS-CoV-2 unprecedentedly threatens the public health at worldwide level. There is an urgent need to develop an effective vaccine within a highly accelerated time. Here, we present the most comprehensive S-protein-based linear B-cell epitope candidate list by combining epitopes predicted by eight widely-used immune-informatics methods with the epitopes curated from literature published between Feb 6, 2020 and July 10, 2020. We find four top prioritized linear B-cell epitopes in the hotspot regions of S protein can specifically bind with serum antibodies from horse, mouse, and monkey inoculated with different SARS-CoV-2 vaccine candidates or a patient recovering from COVID-19. The four linear B-cell epitopes can induce neutralizing antibodies against both pseudo and live SARS-CoV-2 virus in immunized wild-type BALB/c mice. This study suggests that the four linear B-cell epitopes are potentially important candidates for serological assay or vaccine development.


Author(s):  
Shota Yoshida ◽  
Chikako Ono ◽  
Hiroki Hayashi ◽  
Satoshi Shiraishi ◽  
Kazunori Tomono ◽  
...  

AbstractThe aim of this study is to understand adaptive immunity to SARS-CoV-2 through the analysis of B cell epitope and neutralizing activity in coronavirus disease 2019 (COVID-19) patients. We obtained serum from thirteen COVID-19 patients. Most individuals revealed neutralizing activity against SARS-CoV-2 assessed by a pseudotype virus-neutralizing assay. The antibody production against the spike glycoprotein (S protein) or receptor-binding domain (RBD) of SARS-CoV-2 was elevated, with large individual differences, as assessed by ELISA. In the analysis of the predicted the linear B cell epitopes, two regions (671-690 aa. and 1146-1164 aa.), which were located in S1 and S2 but not in the RBD, were highly reactive with the sera from patients. In the further analysis of the B cell epitope within the S protein by utilizing a B cell epitope array, a hot spot in the N-terminal domain of the S protein but not the RBD was observed in individuals with neutralizing activity. Overall, the analysis of antibody production and B cell epitopes of the S protein from patient serum may provide a novel target for the vaccine development against SARS-CoV-2.


2019 ◽  
Vol 14 (3) ◽  
pp. 226-233 ◽  
Author(s):  
Cangzhi Jia ◽  
Hongyan Gong ◽  
Yan Zhu ◽  
Yixia Shi

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.


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