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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...

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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

Using Graph-Based Signatures to Guide Rational Antibody Engineering.

David B Ascher^1,2,3,4, Lisa M Kaminskas⁵, Yoochan Myung^1,2,4

¹Structural Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Parkville, VIC, Australia.

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

|November 8, 2022

Summary

This summary is machine-generated.

Rational antibody engineering is enhanced by mCSM, a computational tool. This in silico suite identifies mutation consequences to improve antibody stability, affinity, and specificity for better biotherapeutics.

Keywords:

Antibody engineering Antibody interactions Antibody structure Graph-based signatures Mutation Rational engineering mCSM mCSM-AB mCSM-AB2 mmCSM-AB

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Last Updated: Aug 22, 2025

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Genetic Encoding of a Non-Canonical Amino Acid for the Generation of Antibody-Drug Conjugates Through a Fast Bioorthogonal Reaction

Published on: September 14, 2018

Area of Science:

Biochemistry
Computational Biology
Immunology

Background:

Antibodies are crucial tools in research, diagnostics, and therapy.
Biotherapeutics, particularly antibodies, have revolutionized disease treatment.
Advances in computational methods enable rational protein engineering.

Purpose of the Study:

To describe the application of the mCSM web-based suite for antibody engineering.
To demonstrate how in silico analysis can guide the rational design of antibodies.
To improve antibody stability, affinity, and specificity through computational guidance.

Main Methods:

Utilized the mCSM web-based in silico suite.
Employed graph-based signatures to analyze mutation effects.
Applied computational predictions to guide antibody engineering.

Main Results:

mCSM rapidly identified structural and functional consequences of mutations.
The tool guided rational engineering efforts.
Improvements in antibody stability, affinity, and specificity were achieved.

Conclusions:

The mCSM suite is a valuable tool for rational antibody engineering.
Computational approaches significantly enhance the design of improved antibody therapeutics.
This method offers a pathway to develop antibodies with superior properties.