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Related Concept Videos

In vitro Mutagenesis01:16

In vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.
In-vitro Mutagenesis01:16

In-vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.

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Related Experiment Video

Updated: May 17, 2026

Directed Evolution Method in Saccharomyces cerevisiae: Mutant Library Creation and Screening
10:50

Directed Evolution Method in Saccharomyces cerevisiae: Mutant Library Creation and Screening

Published on: April 1, 2016

Robust in vitro affinity maturation strategy based on interface-focused high-throughput mutational scanning.

Yasuhiro Fujino1, Risako Fujita, Kouichi Wada

  • 1Advanced Medical Research Department, Mitsubishi Tanabe Pharma Corporation, 3-16-89 Kashima, Osaka 532-8505, Japan. Fujino.Yasuhiro@mb.mt-pharma.co.jp

Biochemical and Biophysical Research Communications
|October 30, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a new protein engineering strategy for improving binding affinity. The method rapidly generates high-affinity protein variants, accelerating the development of therapeutics and biosensors.

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Area of Science:

  • Protein Engineering
  • Biochemistry
  • Molecular Biology

Background:

  • In vitro affinity maturation is crucial for developing protein therapeutics and biosensors.
  • Existing methods can be time-consuming and may not yield optimal results.

Purpose of the Study:

  • To develop a robust and efficient affinity engineering strategy.
  • To create customized combinatorial libraries for rapid protein optimization.

Main Methods:

  • A two-step strategy involving single amino acid substitution identification followed by combination.
  • High-throughput mutational scanning of single substitution libraries.
  • Customized combinatorial library design based on binding-interface.

Main Results:

  • Successfully optimized a model antibody Fab fragment.
  • Generated a diverse panel of high-affinity variants.
  • Achieved a 2110-fold affinity improvement (Kd of 3.45 pM) with 7 substitutions.

Conclusions:

  • The developed strategy facilitates rapid affinity engineering of protein-protein interactions.
  • Context-dependent library design enhances the efficiency of affinity maturation.
  • This method can accelerate the development of novel protein-based tools and therapeutics.