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Antibody Structure

Antibody Structure

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...

Antibody Structure and Classes

Antibody Structure and Classes

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.

Antigens Involved in Adaptive Immunity

Antigens Involved in Adaptive Immunity

An antigen is any substance the immune system identifies as foreign and potentially harmful to the body, prompting an immune response. Antigens have two functional properties: immunogenicity and reactivity. Immunogenicity is the ability of an antigen to stimulate a specific immune response. At the same time, reactivity describes the antigen's ability to react with the cells and antibodies produced in response to it.
Complete Antigens
Complete antigens possess both immunogenicity and...

Antibody Actions

Antibody Actions

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...

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Related Experiment Video

Updated: Aug 22, 2025

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

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

Published on: March 15, 2019

Information-Driven Antibody-Antigen Modelling with HADDOCK.

Francesco Ambrosetti¹, Zuzana Jandova¹, Alexandre M J J Bonvin²

¹Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Utrecht, The Netherlands.

Methods in Molecular Biology (Clifton, N.J.)

|November 8, 2022

Summary

Computational modeling offers a faster, cost-effective way to understand antibody-antigen interactions. This study presents a HADDOCK protocol for predicting antibody-antigen complex structures, aiding therapeutic antibody design.

Keywords:

Antibody HADDOCK Information-driven docking

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Antigenic Liposomes for Generation of Disease-specific Antibodies

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Last Updated: Aug 22, 2025

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

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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

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Antigenic Liposomes for Generation of Disease-specific Antibodies

Antigenic Liposomes for Generation of Disease-specific Antibodies

Published on: October 25, 2018

Area of Science:

Structural Biology
Computational Biology
Immunology

Background:

Therapeutic antibody use is rapidly expanding, driven by advancements in antibody characterization.
Understanding antibody-antigen interactions is crucial for designing effective therapeutic antibodies.
Experimental methods for structural determination are often costly and time-consuming.

Purpose of the Study:

To present a computational protocol for predicting the 3D structure of antibody-antigen complexes.
To offer a valuable alternative to experimental techniques for characterizing these interactions.
To guide the use of the HADDOCK platform for antibody-antigen complex modeling.

Main Methods:

Utilizing the HADDOCK (High Ambiguity Driven protein-protein Docking) integrative modeling platform.
Identifying critical antibody hypervariable loop residues to guide the docking process.
Employing the HADDOCK 2.4 webserver with strategies tailored to epitope information availability.

Main Results:

A detailed protocol for predicting antibody-antigen complex structures using HADDOCK was established.
The protocol facilitates the characterization of antibody-antigen interactions through computational modeling.
Different docking strategies were outlined based on the available epitope data.

Conclusions:

Computational approaches, specifically HADDOCK, provide an efficient alternative for antibody-antigen complex structure prediction.
This protocol aids in the structural analysis and engineering of therapeutic antibodies.
The method supports diverse scenarios depending on the extent of prior knowledge regarding epitope residues.