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

The rapid engineering of binding proteins is increasingly driven by cell-free, machine-learning-guided optimization. However, high-throughput, quantitative characterization of binding affinity remains a major bottleneck, particularly for proteins expressed in cell-free systems without purification. Here, we present High-Throughput FRET Affinity Screening Technique (HTFAST) for rapid affinity characterization of binders expressed directly in crude E. coli cell-free protein expression reactions. HTFAST leverages Förster resonance energy transfer (FRET) between cell-free expressed fluorescent-protein-fused binders and dye-labeled antigens to enable real-time, quantitative measurement of equilibrium dissociation constants. We systematically optimized fluorophore pairs and labeling parameters using the SpyTag003-SpyCatcher003 model system. HTFAST reliably quantified nanomolar binding affinities in crude lysates for the SpyTag003-SpyCatcher003 model system. It also resolved affinities spanning low-nanomolar to hundreds-of-nanomolar for nanobodies against multiple antigens, including CD4, HER2, and HSA. We further benchmarked HTFAST against a panel of five SARS-CoV-2 RBD nanobodies, demonstrating HTFAST's ability to rank binders targeting the same antigen with affinities correlating strongly with reported BLI/SPR measurements. Finally, we demonstrate that both binding partners can be expressed directly in CFE, further streamlining screening workflows. Overall, HTFAST provides a scalable, quantitative, and cell-free-compatible approach for high-throughput affinity screening, well-suited for DBTL protein engineering campaigns.