Over the last few years, we have built high-throughput screening and directed evolution platforms to profile, engineer, and modulate the substrate specificity and activity of peptide bond forming/breaking enzymes. In this talk, I will first present HARP (High-Throughout Activity Reprogramming for Proteases), a yeast-based functional screening platform designed to isolate protease-inhibitory macromolecules from large synthetic libraries. HARP links macromolecule-mediated inhibition of an endoplasmic reticulum (ER)-resident protease target to a robust, quantifiable cell-surface phenotype, enabling selection via fluorescence-activated cell sorting. Using HARP, we successfully identified nanomolar-potency and highly selective inhibitory nanobodies against Tobacco Etch Virus Protease (TEVp) and human Kallikrein 6, including a rare TEVp uncompetitive inhibitor with an inhibitory constant of 7.6 nM. The TEVp inhibitors will be crucial for building compressed protein circuits. HARP's design principles suggest that conventional binding-first platforms would likely overlook these inhibitors, particularly uncompetitive inhibitors and those with strong inhibition despite moderate binding affinities. To validate our findings, we developed a rigorous characterization pipeline incorporating biochemical assays, binding affinity measurements, deep sequencing, and structural analysis. Notably, coupling HARP with deep sequencing revealed a linear correlation between yeast-derived inhibition phenotypes and in vitro performance, reinforcing HARP’s reliability as a quantitative inhibitor discovery platform. This study introduces HARP as the first yeast-based inhibitor discovery platform of its kind, boasting high dynamic range, precision, and versatility in enzyme targets. For example, we are concurrently working on expanding the HARP concept to other scaffolds (endogenous inhibitors, ScFvs, DARPins, Fabs, cyclic peptides), other protease targets, and other post-translational modification enzymes (kinases, acetyltransferases), thereby positioning it as a premier platform for discovering modulatory macromolecules.
Second, I will present our recently-developed platform for called PERRC (Protease engineering with reactant residence control) to engineer proteases with bespoke substrate specificities. PERRC exploits the correlation between endoplasmic reticulum (ER) retention sequence strength and ER residence time. PERRC allows precise control over the stringency of protease evolution by adjusting counterselection to selection substrate ratios. Using PERRC, we evolved an orthogonal tobacco etch virus protease variant, TEVESNp, that selectively cleaves a substrate (ENLYFES) that differs by only one amino acid from its parent sequence (ENLYFQS). TEVESNp exhibits a remarkable 65-fold preference for the evolved substrate, marking the first example of an engineered orthogonal protease driven by such a slight difference in substrate recognition. Furthermore, TEVESNp functions as a competent protease for constructing orthogonal protein circuits in bacteria, and molecular dynamic simulations analysis reveals subtle yet functionally significant active site rearrangements. PERRC is a modular dual-substrate display system that facilitates precise engineering of protease specificity.
Lastly, I will present our novel way to comprehensively reprogram the substrate specificity of sortases, combining substrate profiling, directed evolution, and inhibitor discovery, called HEROSS (High-Throughput Exploration and Reprogramming of Sortase Specificity). Using Streptococcus pyogenes sortase A as a model, we show that extending the sortase substrate beyond the P1’ residue enhances sortase-mediated ligation kinetics. Most importantly, this comprehensive profiling reveals several non-canonical sortase substrates, some of which exhibit higher ligation kinetics compared to known sortase substrates.
Taken together, these platforms are positioned to significantly advance our ability to reprogram protein-modifying enzymes for biomedical, biotechnological, and synthetic biology applications.