G protein-coupled receptors (GPCRs) are key drug targets, but ligand promiscuity complicates mechanistic studies. We hypothesized that linking GPCR ligands to antibodies could improve specificity and performance. We linked small-molecule GPCR agonists to nanobodies. Such conjugates showed high receptor specificity, potency, and pronounced signaling bias. This approach also facilitates selective targeting of receptor assemblies, offering a path towards logic-gated ligand function.

We developed a fully integrated, end-to-end discovery platform for generating antibodies, nanobodies, and biparatopics with high specificity. This high-throughput system combines antigen engineering, yeast display, next-generation sequencing, antibody production, and characterization, enabling the discovery of diverse binding reagents tailored for various applications. Specifically, in the last 12 months, we generated antibodies against more than 200 targets and are now focusing on generating biparatopic antibodies against multiple human targets.

This talk explores the emerging application of targeted protein degradation to membrane proteins. Unlike conventional inhibitors that block protein function, these new approaches remove the protein entirely, opening new ways to overcome resistance and targeting previously "undruggable" targets. New advances in technologies for degrading cell surface proteins are discussed in the talk. The presentation illustrates how these tools expand the druggable space and open up new ways to treat diseases

T cell engagers (TcEs) based on T cell receptor mimic (TcRm) antibodies allow for the targeting of non-surface tumor antigens, estimated to comprise around 80-85% of the tumor cell's proteome, grounded on specific interaction of antibodies towards MHC-presented peptides. In this talk, I will discuss the methods we have developed to address the challenge of identification of peptide-MHC specific TcEs employing phage and yeast display for high-throughput discovery of TcRm antibodies.

The constantly growing demand for novel biotherapeutics drives technology innovation, enabling efficient antibody discovery. Optimization and digitalization of discovery workflows is essential for successful identification of antibodies against challenging targets and the sampling of diverse repertoires. In this talk, automated platform technologies for biotherapeutics discovery workflows are presented highlighting the integration of sequence information, screening data, and informatics for large panels of antibodies, laying the groundwork for AI/ML model development.

Antibodies against membrane proteins such as GPCRs and other receptors are critical for therapeutic modulation, yet discovery remains slow. Functional epitopes are often conformational and only accessible in native membrane contexts. By combining droplet microfluidics with cell-based assays, antibodies can be screened directly from primary B cells for both binding and functional activity. This high-throughput approach enables discovery of modulatory antibodies targeting native conformations of complex membrane-associated proteins.

G protein-coupled receptors (GPCRs) pose numerous challenges to drug development. Most notably, their poor expression and nonideal biochemical properties present major hurdles for in vitro manipulation such as reconstitution into lipid bilayers or formation of GPCR-transducer complexes. In this presentation, I will highlight approaches taken at Regeneron to produce GPCRs to support antibody-discovery campaigns and the use of G proteins as tools to functionally validate purified receptors.

Orphan G-protein-coupled receptors—receptors with no identified endogenous ligands—represent an untapped reservoir of therapeutic potential, offering promising avenues for developing innovative treatments across a spectrum of diseases. However, drug development for these—100 uncharacterized GPCRs is challenging due to the absence of validated ligands and limited understanding of their signaling, complicating drug screening assay design. I will discuss different constitutive activity, i.e., ligand independent-based applications of our enhanced bystander bioluminescence resonance energy transfer (ebBRET) platform, bioSens-All, to develop high-throughput screening assays for orphan GPCR drug-discovery efforts (e.g., GPR75 and GPR151).

Antibodies targeting membranes have traditionally been evaluated using ensemble-based measurements, which mask molecular heterogeneity and dynamic interactions. In this talk, I will discuss a single-antibody labeling (SAL) technique that enables precise localization of antibody binding with 10–20 nm resolution, reveals binding kinetics that distinguish specific from non-specific targets, and resolves membrane nanostructures to uncover their functional roles in receptor-mediated signaling. Using immune T cells as a model system, I will discuss the use of SAL to visualize tetraspanin-enriched microdomains on membrane microvilli. SAL offers a precision approach to evaluate antibody-based therapeutics in target cell membranes.

Membrane proteins make common drug targets, but their structures are sometimes difficult to resolve at high resolution. This can be challenging when using cryo-EM to study proteins without any distinctive soluble features or domains. Here, I present examples of drug targets being structurally enabled by applying modern protein design tools for further study by cryo-EM. Promising results, as well as failure points, showcase these workflows in greater detail.

Human voltage-gated potassium channel, Kv1.3, is a key therapeutic target for autoimmune and neuroinflammatory diseases. We used deep-learning-based RFdiffusion and AlphaFold2 methods to design de novo proteins targeting the extracellular Kv1.3 pore region. Functional testing of top designs using whole-cell patch clamp electrophysiology revealed three designs with nanomolar range potency for Kv1.3. These results highlight the potential of de novo design for generating high-affinity binders targeting ion channels.

To identify effective immune engagers, including T-cell therapies or T-cell-dependent bispecific antibodies, robust screening of T-cell-mediated tumor killing co-culture is crucial. Traditional imaging relies on fluorescently labeled cells, risking artifacts and phototoxicity. We introduce an AI/ML-based method utilizing only brightfield images to identify phenotypic changes, eliminating fluorescent markers. This innovative approach applied to T-cell killing assays maintains consistency, enhances efficiency, and allows analysis of diverse tumor cells without complex segmentation.