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Related Experiment Video

Updated: Jun 28, 2026

Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope
08:09

Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope

Published on: March 24, 2017

Recent developments with B-cell epitope identification for predictive studies.

Erwin L Roggen

    Journal of Immunotoxicology
    |October 30, 2008
    PubMed
    Summary
    This summary is machine-generated.

    Predicting B-cell epitopes is crucial for vaccine and drug development. While computational tools show promise, no fully validated method exists for identifying B-cell epitopes on unknown proteins.

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    Published on: August 22, 2019

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    Last Updated: Jun 28, 2026

    Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope
    08:09

    Peptide Scanning-assisted Identification of a Monoclonal Antibody-recognized Linear B-cell Epitope

    Published on: March 24, 2017

    A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
    07:59

    A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

    Published on: March 25, 2014

    Single-cell Screening Method for the Selection and Recovery of Antibodies with Desired Specificities from Enriched Human Memory B Cell Populations
    09:07

    Single-cell Screening Method for the Selection and Recovery of Antibodies with Desired Specificities from Enriched Human Memory B Cell Populations

    Published on: August 22, 2019

    Area of Science:

    • Immunology
    • Bioinformatics
    • Computational Biology

    Background:

    • B-cell epitopes are key targets for antibody recognition and immune responses.
    • Accurate prediction of B-cell epitopes is essential for designing effective vaccines and therapeutics.
    • Current methods for epitope prediction face limitations, especially for antigenically unknown proteins.

    Purpose of the Study:

    • To review and evaluate existing methods for predicting B-cell epitopes on proteins.
    • To highlight the strengths and limitations of various in silico and in vitro approaches.
    • To discuss the challenges in B-cell epitope identification for novel antigens.

    Main Methods:

    • Review of computational methods, including propensity scales, comparative approaches, and motif databases.
    • Analysis of peptide-based technologies and antibody-based tests.
    • Discussion of species-specific differences in B-cell and T-cell epitope recognition.

    Main Results:

    • Physico-chemical and structural scales are useful for predicting linear epitopes.
    • Novel computational tools show potential for identifying conformational epitopes.
    • Comparative methods and data mining can identify similarities in B-cell epitope profiles between related proteins.

    Conclusions:

    • Promising computational tools for B-cell epitope identification have been developed.
    • No validated method currently exists for predicting B-cell epitopes on antigenically unknown proteins.
    • Further validation of computational tools, especially for conformational epitopes, is required.