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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

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.

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Related Experiment Video

Updated: Jul 3, 2026

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

PIGS: automatic prediction of antibody structures.

Paolo Marcatili¹, Alessandra Rosi, Anna Tramontano

¹Department of Biochemical Sciences and Istituto Pasteur Fondazione Cenci Bolognetti, Sapienza University, P.le A. Moro 5, 00185 Rome, Italy.

Bioinformatics (Oxford, England)

|July 22, 2008

Summary

This study presents a user-friendly web server for predicting immunoglobulin variable domains using a canonical structure model. The tool generates detailed 3D models, aiding antibody research.

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Last Updated: Jul 3, 2026

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

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Published on: March 15, 2019

Optimized Negative Staining: a High-throughput Protocol for Examining Small and Asymmetric Protein Structure by Electron Microscopy

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Area of Science:

* Computational biology and structural bioinformatics.
* Molecular modeling and immunology.

Background:

* Immunoglobulin variable domains are crucial for antibody function.
* Accurate prediction of their 3D structures is essential for antibody engineering and drug design.
* Existing methods may lack flexibility or user-friendliness.

Purpose of the Study:

* To introduce a novel web server for automated prediction of immunoglobulin variable domains.
* To provide a flexible and user-friendly platform for generating 3D models of antibody variable regions.
* To leverage the canonical structure model for enhanced prediction accuracy.

Main Methods:

* Development of a web server implementing the canonical structure model.
* User-selectable strategies for choosing framework and loop templates.
* Automated generation of full 3D models for target immunoglobulin variable domains.

Main Results:

* Successful implementation of a web server for immunoglobulin variable domain prediction.
* The server offers flexibility in template selection for frameworks and loops.
* Outputs complete 3D structural models of variable domains.

Conclusions:

* The developed web server provides an accessible and efficient tool for predicting immunoglobulin variable domain structures.
* Its user-friendly interface and flexible options facilitate its application in antibody research.
* The server contributes to advancing structural bioinformatics in immunology.