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Related Concept Videos

Antibody Structure01:10

Antibody Structure

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Overview
Antibodies, also known as immunoglobulins (Ig), are essential players of the adaptive immune system. These antigen-binding proteins are produced by B cells and make up 20 percent of the total blood plasma by weight. In mammals, antibodies fall into five different classes, which each elicits a different biological response upon antigen binding.
The Y-Shaped Structure of Antibodies Consists of Four Polypeptide Chains
Antibodies consist of four polypeptide chains: two identical heavy...
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Conjugated Proteins02:50

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Simple proteins and protein complexes contain only amino acids. In contrast, many other proteins, called conjugated proteins, covalently bond with non-protein moieties.
Nucleoproteins are protein complexes that contain nucleic acids, categorized as deoxyribonucleoproteins (DNPs) or ribonucleoproteins (RNPs) respectively. The nucleosome is a typical example of a DNP where nuclear DNA is associated with histone proteins. The major antigen for the Covid-19 virus SARS-CoV is an RNP that is critical...
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Related Experiment Video

Updated: Oct 10, 2025

Author Spotlight: Advancing Antiviral Strategies Through Novel Immunocapture and Mass Spectrometry Techniques
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Author Spotlight: Advancing Antiviral Strategies Through Novel Immunocapture and Mass Spectrometry Techniques

Published on: January 12, 2024

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Epitope profiling using computational structural modelling demonstrated on coronavirus-binding antibodies.

Sarah A Robinson1, Matthew I J Raybould1, Constantin Schneider1

  • 1Oxford Protein Informatics Group, Department of Statistics, University of Oxford, United Kingdom.

Plos Computational Biology
|December 13, 2021
PubMed
Summary
This summary is machine-generated.

Structural modeling reveals functionally similar antibodies with distinct lineages targeting coronaviruses. This approach identifies greater immune response convergence than sequence-based methods, aiding therapeutic development.

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Area of Science:

  • Immunology
  • Structural Biology
  • Computational Biology

Background:

  • Epitope identification is crucial for antibody function and therapeutic potential.
  • Sequence-based methods can miss antibodies with similar structures but different lineages targeting the same epitope.
  • Functional convergence in immune responses to coronaviruses may be underestimated by sequence-only analyses.

Purpose of the Study:

  • To develop a novel computational method for epitope profiling using structural modeling and clustering.
  • To identify sequence-dissimilar but functionally similar antibodies within the Coronavirus Antibody Database.
  • To demonstrate the utility of structural analytics for uncovering hidden functional convergence in antibody responses.

Main Methods:

  • Development of a computational method for epitope profiling based on structural modeling.
  • Clustering of antibodies based on structural similarity to identify shared epitopes.
  • Analysis of the Coronavirus Antibody Database to find sequence-dissimilar antibodies with similar structures.

Main Results:

  • The novel method accurately identifies functionally similar antibodies across distinct lineages (92% accuracy in binding consistent domains).
  • Sequence-dissimilar antibodies engaging the same epitope were identified, highlighting structural convergence.
  • The approach linked antibodies with diverse genetic backgrounds and specificities, revealing broader immune response patterns.

Conclusions:

  • Structural modeling and clustering provide a powerful approach for epitope profiling.
  • Immune responses to coronaviruses exhibit greater functional convergence than previously recognized.
  • Applying structural analytics to antibody databases enables high-confidence structure-function relationships and discovery of missed functional convergence.