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Related Experiment Video

Updated: Mar 22, 2026

Protein Engineering by Yeast Surface Display

Protein Engineering by Yeast Surface Display

Published on: November 29, 2024

Generating High-Accuracy Peptide-Binding Data in High Throughput with Yeast Surface Display and SORTCERY.

Lothar Luther Reich¹, Sanjib Dutta¹, Amy E Keating²

¹Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Rm 68-622A, Cambridge, MA, 02139, USA.

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

|April 21, 2016

Summary

This summary is machine-generated.

We developed SORTCERY, a method to accurately rank peptide ligand affinities for protein targets. This technique uses fluorescence-activated cell sorting (FACS) and deep sequencing to identify high-affinity binders for drug discovery.

Keywords:

Bcl-2 family Deep sequencing High-throughput assay Protein–protein interaction Yeast surface display

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Area of Science:

Biochemistry
Molecular Biology
Biotechnology

Background:

Protein-protein interactions are crucial in biological processes.
Identifying peptide ligands for protein targets is essential for drug discovery and research.
Current methods for screening and selecting ligands can be laborious and may lack accurate affinity ranking.

Purpose of the Study:

To introduce and validate a novel procedure, SORTCERY, for accurately ranking the affinities of peptide library members for a specific protein target.
To demonstrate the utility of SORTCERY in identifying high-affinity peptide ligands.

Main Methods:

Utilizes a three-step protocol involving fluorescence-activated cell sorting (FACS) to sort yeast-displayed peptide libraries based on target affinity.
Employs deep sequencing of all sorted pools to capture comprehensive data.
Analyzes sequencing data to generate an accurate ranking of peptide ligand affinities.

Main Results:

SORTCERY successfully ranks the affinities of peptide ligands for a target protein with high accuracy.
Demonstrated application in identifying peptide ligands for the anti-apoptotic regulator Bcl-xL.
Provides a robust method for high-throughput screening and selection of protein-binding peptides.

Conclusions:

SORTCERY offers a powerful and accurate approach for quantifying peptide-target affinities.
This method significantly enhances the process of identifying and ranking potential therapeutic or research ligands.
Facilitates advancements in understanding protein-protein interactions and developing targeted therapies.