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Related Experiment Video

Updated: Oct 10, 2025

Laboratory Scale Production and Purification of a Therapeutic Antibody

Laboratory Scale Production and Purification of a Therapeutic Antibody

Published on: January 24, 2017

Deep mutational scanning for therapeutic antibody engineering.

Kyrin R Hanning¹, Mason Minot², Annmaree K Warrender¹

¹Te Huataki Waiora School of Health, University of Waikato, Hamilton 3240, New Zealand.

Trends in Pharmacological Sciences

|December 13, 2021

Summary

This summary is machine-generated.

Deep mutational scanning (DMS) enhances monoclonal antibody (mAb) drug candidates by improving affinity, specificity, and stability. This powerful protein engineering method also aids in epitope mapping and profiling viral escape mutations.

Keywords:

antibodies machine learning mutagenesis protein engineering

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Area of Science:

Biotechnology
Protein Engineering
Immunology

Background:

Monoclonal antibody (mAb) drug candidates require optimization for clinical efficacy.
Protein engineering methods are crucial for enhancing mAb properties.
Deep mutational scanning (DMS) is an emerging technique for protein engineering.

Purpose of the Study:

To summarize the applications and advancements of deep mutational scanning (DMS) in antibody engineering.
To highlight DMS's role in improving mAb biophysical and functional properties.
To showcase DMS's utility in epitope mapping and understanding viral evolution.

Main Methods:

Deep mutational scanning (DMS) involves exhaustive protein mutagenesis.
Functional screening and deep sequencing are integrated with bioinformatics.
Machine learning is combined with DMS for computational antibody engineering.

Main Results:

DMS significantly improves antibody affinity, specificity, and stability.
Novel applications include engineering multi-specific binding properties.
DMS precisely maps antibody-binding epitopes and profiles viral mutational escape (e.g., SARS-CoV-2).

Conclusions:

DMS is a powerful tool for engineering therapeutic antibodies with enhanced properties.
DMS facilitates precise epitope mapping and understanding of viral escape mechanisms.
The integration of DMS with machine learning advances computational antibody design.