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Updated: Feb 6, 2026
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Modified Yeast-Two-Hybrid System to Identify Proteins Interacting with the Growth Factor Progranulin
Published on: January 17, 2012
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Yeast Two-Hybrid Assay to Identify Interacting Proteins
Aurora Paiano1, Azzurra Margiotta1,2, Maria De Luca1
1Department of Biological and Environmental Sciences and Technologies (DiSTeBA), University of Salento, Lecce, Italy.
Current Protocols in Protein Science
|August 23, 2018
Summary
The yeast two-hybrid system remains a cost-effective and efficient method for studying protein-protein interactions. This technique reliably identifies direct interactions and has evolved into high-throughput systems for proteome-wide analysis.
Area of Science:
- Molecular Biology
- Biochemistry
- Genetics
Background:
- Protein-protein interactions are crucial for cellular functions.
- Identifying these interactions is fundamental to understanding biological processes.
- The yeast two-hybrid system is a widely used genetic method for this purpose.
Purpose of the Study:
- To describe the classical yeast two-hybrid system methodology.
- To highlight its utility in identifying and studying protein-protein interactions.
- To discuss its reliability and evolution into advanced techniques.
Main Methods:
- The article details the general procedure for performing the classical yeast two-hybrid assay.
- This genetic technique involves detecting interactions in yeast cells.
- Variants include high-throughput systems for large-scale interaction mapping.
Main Results:
- The yeast two-hybrid system effectively identifies binary, direct protein-protein interactions.
- Its reliability is comparable to other methods like mass spectrometry.
- Numerous variations have been developed, including proteome-scale applications.
Conclusions:
- The yeast two-hybrid system is a valuable, economical, and time-saving tool for protein interaction research.
- Its established reliability and adaptability continue to drive its use in molecular biology.
- Modern variants enable comprehensive mapping of protein interaction networks.
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