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Imaging Protein-protein Interactions in vivo

Imaging Protein-protein Interactions in vivo

Published on: October 10, 2010

High-Throughput FRET Affinity Screening Technique (HTFAST) For Cell-Free Expressed Binding Protein Characterization.

Sepehr Hejazi, Kimia Noroozi, Vito Jurasic

Biorxiv : the Preprint Server for Biology

|February 23, 2026

Summary

This summary is machine-generated.

We developed HTFAST, a new method for quickly measuring binding affinity of proteins like nanobodies. This cell-free technique works directly in crude lysates, speeding up the development of new binding proteins.

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Area of Science:

Biotechnology
Protein Engineering
Biophysics

Background:

Cell-free protein synthesis (CFPS) enables rapid engineering of high-affinity binding proteins.
High-throughput characterization of binding affinity is a bottleneck, especially for unpurified proteins from CFPS.
Machine learning guides optimization, necessitating efficient binding validation.

Purpose of the Study:

To develop a high-throughput, quantitative method for binding affinity screening of cell-free expressed proteins.
To enable rapid characterization of binding proteins directly in crude lysates without purification.
To accelerate the development of next-generation binding proteins through streamlined screening.

Main Methods:

Developed High-Throughput FRET Affinity Screening Technique (HTFAST) using Förster resonance energy transfer (FRET).
Utilized fluorescent-protein-fused binders and dye-labeled antigens for real-time equilibrium dissociation constant measurement.
Optimized fluorophore pairs and labeling parameters using the SpyTag003-SpyCatcher003 system.

Main Results:

HTFAST reliably quantified nanomolar binding affinities in crude lysates.
Validated the platform for nanobodies, including a CD4-binding nanobody (Nb457).
Successfully benchmarked SARS-CoV-2 receptor-binding domain sdAbs, ranking their binding strengths.
Demonstrated that both binding partners can be expressed directly in CFPS.

Conclusions:

HTFAST offers a scalable, quantitative, and cell-free-compatible approach for high-throughput affinity screening.
The method is well-suited for Design-Build-Test-Learn (DBTL) campaigns.
Accelerates the development of high-affinity binding proteins for various applications.