Affinity Determination by Adaptation of ProTein binders for Microfluidics enables rapid, parallel measurement of binding affinities and dissociation behavior directly from enriched display libraries in under one week, without requiring gene synthesis or hands-on protein purification.
Abstract
Protein-protein interactions underpin most cellular processes, and engineered binders present powerful tools for probing biology and developing novel therapeutics. However, scalable, quantitative characterization of large numbers of candidates remains a major bottleneck. Here we show that ADAPT-M (Affinity Determination by Adaptation of ProTein binders for Microfluidics) enables rapid, parallel measurement of binding affinities and dissociation behavior directly from enriched display libraries in under one week, without requiring gene synthesis or hands-on protein purification. Applied to a computationally designed library targeting the SARS-CoV-2 Omicron BA.1 receptor binding domain, ADAPT-M recovered most highly enriched variants and revealed that many display-enriched binders lacked measurable binding in vitro, highlighting limitations of screening alone. ADAPT-M enabled quantitative characterization of dozens of binders in parallel and selection of lead candidates for structural analysis. Unexpectedly, structural and mutational studies revealed that designed binding interfaces were preserved despite engaging alternative epitopes. By bridging screening and scalable in vitro validation, ADAPT-M accelerates protein binder discovery and supports data-driven protein engineering. ADAPT-M is a workflow combining design and high-throughput experimentation. It overcomes the testing bottleneck and enables rapid quantitative affinity measurements of thousands of designer proteins enriched from yeast surface display libraries.
A protocol for discovering protein‐binding peptides using a very large, target‐agnostic yeast surface display library containing approximately 6.1 × 109 unique clones and providing broad coverage of short peptide sequence space is described.
J. D. Hurley, Andrew C. Kruse· Current Protocols· 0 citations
The Human Bindome is presented, a proteome-scale atlas of high-confidence in silico protein binder candidates that positions the Bindome as a resource of genetically encodable perturbagens for site-specific, modular control of protein function.
Julius Wenckstern, Anna M. Díaz-Rovira, Julia A. Kuhn et al.· bioRxiv· 0 citations
Accurate identification of epitope residues is essential for developing biopharmaceuticals and understanding the mechanisms of immune recognition. However, experimental approaches for residue‐level epitope mapping remain time‐consuming and labor‐intensive, while accurate computational prediction of protein–protein interfaces remains challenging. Here, we present MAXTIA, a high‐throughput kinetic screening platform that integrates cell‐free protein synthesis with high‐throughput surface plasmon resonance and demonstrate its application to alanine scanning‐based functional epitope mapping. This workflow enables the rapid preparation and kinetic characterization of up to 384 protein variants, allowing the identification of functional epitope residues within 3 days while simultaneously providing binding affinity and kinetic parameters (KD, kon, and koff). We applied MAXTIA to map the epitope of the single‐domain antibody (VHH) N1 against the pentraxin domain of neuronal pentraxin‐2 (NP2 PTX). Alanine substitutions that cause substantial affinity losses clustered within a localized region on the AlphaFold3‐predicted NP2 PTX structure, defining a functional epitope site. These residues closely matched the interface observed in the NP2 PTX–VHH N1 crystal structure, validating the accuracy of MAXTIA. Beyond epitope identification, MAXTIA provides a simple and versatile platform for the quantitative analysis of protein–protein interactions, including high‐throughput screening of antibody variants for affinity optimization. This approach should accelerate biopharmaceutical development and facilitate mechanistic studies of molecular recognition.
Kihoon Kim, Ryo Matsunaga, T. Yokoo et al.· Protein Science· 0 citations
This work presents a scalable mammalian cell-display workflow to identify AI-designed minibinders against cancer surface targets and identifies biochemical optimization beyond the binding interface as a critical requirement for translating AI-minibinders into functional applications.
B. Broske, B. McEnroe, S. C. Frechen et al.· Nature Communications· 1 citation
Various strategies to multimerize monomeric targets are explored, thus allowing them to be used as targets in this fragment discovery platform and a particularly effective and convenient strategy is to express a fusion of the POI with FOLDON, a 30-residue, homo-trimeric peptide.
Joel Tong, Isuru M. Jayalath, James V. Parsons et al.· RSC Chemical Biology· 0 citations
“Undruggable” proteins without surface-accessible binding sites pose significant challenges to target-based drug discovery. Innovative approaches are needed to tackle these proteins. One promising strategy is targeting them in their nascent chain form at the ribosome, where they have a different conformation than in the folded form. A systematic approach to screen for such compounds has however been lacking. Here, we present a high-throughput assay to identify small molecules that specifically inhibit a protein of interest in its nascent-chain form. The assay employs a human in vitro transcription/translation system and monitors expression of the protein in real time via fluorescence detection. Specific inhibitors for the nascent chain of interest can then be identified by comparison with a counter screen. The assay was optimized to maximal sensitivity and reaction costs of ∼$0.01 per well, enabling large-scale screens. We validated performance with the reference compound PF846 on the nascent chain of the protein PCSK9. Feasibility for high-throughput screening was demonstrated using a library of 1,760 compounds against the oncogenic KRAS variant A146T and the protein ApoC3, with mean Z′ scores of 0.69 and 0.88, respectively. Sixteen global translation inhibitors were identified in each campaign, while no compounds met the criteria for POI-selective inhibition. The assay thus provides a robust platform for larger-scale screening campaigns.
P. Fischer, Sebastian Hiller· bioRxiv· 0 citations
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