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Antibody Structure01:10

Antibody Structure

60.9K
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...
60.9K
Antibody Structure and Classes01:25

Antibody Structure and Classes

2.5K
Antibodies, also known as immunoglobulins, are produced by B cells in response to foreign substances, such as bacteria and viruses. These proteins are critical for recognizing and neutralizing these substances, protecting the body from potential harm.
The basic structure of an antibody consists of four protein chains: two identical heavy chains and two identical light chains. These chains are held together by disulfide bonds and other non-covalent interactions, forming a Y-shaped structure.
2.5K
Antibody Actions01:26

Antibody Actions

1.2K
Antibodies, or immunoglobulins, are critical players in the immune system's arsenal against invading pathogens. Produced by B cells and plasma cells, their primary role is to detect and bind to specific antigens, molecules found on the surface of pathogens like bacteria or viruses. Beyond antigen recognition, antibodies perform several vital functions that contribute to immune defense.
Neutralization
Antibodies can bind to pathogens, preventing them from infecting host cells. This process...
1.2K
Diversity of Antigen Receptors01:28

Diversity of Antigen Receptors

720
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.
Before encountering any antigen, lymphocytes express these receptors. On B cells, the antigen receptor is a membrane-bound antibody molecule called BCR; on T cells, it is a T cell receptor or TCR. B and T cell receptors are composed of two...
720
Hybridoma Technology01:31

Hybridoma Technology

15.1K
Hybridoma technology is used for the large-scale production of monoclonal antibodies. Monoclonal antibodies bind to only a single antigenic determinant or epitope. Such antibodies are used in research, diagnostics, and disease therapy. The hybridoma technology established in 1975 by Georges Köhler and Cesar Milstein was awarded the Nobel Prize in Medicine in 1984 for revolutionizing research and therapy.
Hybridoma Selection
Commonly used fusion techniques — electroporation,...
15.1K
Affinity and Avidity01:41

Affinity and Avidity

36.5K
Overview
36.5K

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Related Experiment Video

Updated: Aug 12, 2025

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing
08:51

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

Published on: March 15, 2019

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AbLang: an antibody language model for completing antibody sequences.

Tobias H Olsen1, Iain H Moal2, Charlotte M Deane1

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

Bioinformatics Advances
|January 26, 2023
PubMed
Summary

AbLang, a new language model trained on antibody sequences, effectively restores missing amino acids in antibody sequences. This method outperforms existing approaches and is faster than general protein models.

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Area of Science:

  • Immunoinformatics
  • Computational Biology
  • Protein Language Models

Background:

  • General protein language models capture sequence semantics for predictive tasks.
  • Antibody-specific models may offer superior performance for antibody-related challenges, like residue restoration.
  • The Observed Antibody Space (OAS) database provides ample antibody sequence data for training.

Purpose of the Study:

  • Introduce AbLang, a novel language model trained on antibody sequences from the OAS database.
  • Evaluate AbLang's efficacy in restoring missing residues in antibody sequences, a common issue in B-cell receptor sequencing.
  • Compare AbLang's performance against IMGT germlines and the general protein language model ESM-1b.

Main Methods:

  • Trained AbLang on antibody sequences from the Observed Antibody Space (OAS) database.
  • Utilized AbLang to restore missing amino acid residues in antibody sequences.
  • Benchmarked AbLang against IMGT germlines and ESM-1b for residue restoration accuracy and speed.

Main Results:

  • AbLang demonstrates superior performance in restoring missing antibody residues compared to IMGT germlines and ESM-1b.
  • Over 40% of sequences in the OAS database are missing the first 15 amino acids, highlighting the need for residue restoration.
  • AbLang achieves this restoration without requiring knowledge of the antibody's germline and is seven times faster than ESM-1b.

Conclusions:

  • AbLang offers a powerful and efficient solution for restoring missing residues in antibody sequences.
  • The model's ability to perform without germline information and its speed make it a valuable tool for antibody sequence analysis.
  • AbLang is available as a Python package, facilitating its use in the research community.