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Related Concept Videos

Diversity of Antigen Receptors01:28

Diversity of Antigen Receptors

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Antigen receptors are essential components of the immune system crucial in defending the body against foreign invaders. These receptors are present on the surface of B and T cells, enabling them to recognize antigens and mount an appropriate immune response.
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T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
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Related Experiment Video

Updated: Dec 26, 2025

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens
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TCRBuilder: multi-state T-cell receptor structure prediction.

Wing Ki Wong1, Claire Marks1, Jinwoo Leem1

  • 1Department of Statistics, University of Oxford, Oxford OX1 3LB, UK.

Bioinformatics (Oxford, England)
|March 18, 2020
PubMed
Summary
This summary is machine-generated.

TCRBuilder predicts multiple T-cell receptor (TCR) conformations, enabling analysis of TCR polyspecificity. This novel tool models TCR binding site variability, improving predictions beyond current limitations.

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Measuring TCR-pMHC Binding In Situ using a FRET-based Microscopy Assay
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Area of Science:

  • Immunology
  • Structural Biology
  • Computational Biology

Background:

  • T-cell receptors (TCRs) are crucial immune proteins recognizing peptide-MHC complexes.
  • TCRs exhibit lower specificity and affinity than antibodies, with binding sites adopting multiple conformations.
  • This conformational flexibility is key to TCR polyspecificity but is not predicted by current modeling tools.

Purpose of the Study:

  • To develop a novel computational tool for predicting TCR structure and conformational variability.
  • To enable the analysis of structurally driven TCR polyspecificity.

Main Methods:

  • Development of TCRBuilder, a multi-state TCR structure prediction tool.
  • Input: paired αβTCR sequences.
  • Output: models or ensembles representing potential binding site conformations.

Main Results:

  • TCRBuilder successfully predicts ensembles of TCR structures, capturing binding site conformational diversity.
  • This capability allows for the investigation of TCR polyspecificity driven by structural flexibility.
  • Enables analysis previously not possible with existing TCR modeling software.

Conclusions:

  • TCRBuilder addresses a critical gap in TCR modeling by predicting conformational variability.
  • The tool facilitates a deeper understanding of TCR-antigen interactions and polyspecificity.
  • Facilitates structural analysis of TCRs, crucial for immunology and drug discovery.