Accelerating Protein Design by Scaling Experimental Characterization 🚀 New preprint from David Baker!🚀 1. This preprint introduces a novel workflow called Semi-Automated Protein Production (SAPP) that significantly accelerates the experimental validation of de novo protein designs. SAPP enables rapid, modular, and cost-effective protein production and characterization, allowing for the purification and analysis of hundreds of protein designs per day. 2. The SAPP protocol leverages a standardized cloning approach and optimized purification pipeline to achieve at least a tenfold increase in throughput compared to traditional methods. It reduces the total hands-on time to just 6 hours for end-to-end execution, making it highly efficient for large-scale protein design campaigns. 3. A key innovation is the use of a background-suppressing cassette in the cloning process, which eliminates the need for colony isolation and sequencing, thus bypassing traditional multi-day cloning protocols. This approach ensures that the correct clone is the dominant construct in most cases, with a clonal purity of over 90% in many instances. 4. The authors also developed a scalable demultiplexing protocol (DMX) to further reduce costs. DMX converts DNA oligo pools into sequence-verified clonal constructs, enabling the purification and characterization of over 1000 designs at a cost of $5 per construct. This protocol integrates seamlessly with SAPP and is particularly useful for large design campaigns. 5. The SAPP and DMX protocols have been successfully applied to characterize tens of thousands of de novo designed proteins, including mini-protein binders, enzymes, and large protein assemblies. These workflows are designed to be widely adoptable, making large-scale experimental testing more accessible and affordable. 6. The integration of these protocols with computational protein design methods is expected to drive the development of new protein design models informed by experimental data. This could also enable active learning approaches, where experimental feedback is used to iteratively improve protein designs. 💻Code: github.com/bwicky/SAPP_DMX 📜Paper: biorxiv.org/content/10.1101/… #ProteinDesign #ExperimentalValidation #SAPP #DMX #ComputationalBiology #HighThroughput #CostEffective #ActiveLearning