2022 Annual Meeting
(58d) Pro-Apoptotic Stapled Peptides Discovered Using Bacterial Cell Surface Display Demonstrate Improved Affinity, Specificity, and Efficacy
In this work, we employ a novel technique, developed in the Thurber Lab, known as Stabilized Peptide Engineering by E. coli Display (SPEED) to rapidly characterize and develop >109 unique stapled peptide therapeutics against members of the Bcl-2 protein family, which are important regulators of apoptosis and play key roles in resistance to chemotherapy. In this work, libraries of DNA encoding unique peptides are computationally designed by mining genome and linear peptide library data, transformed into bacteria, and presented as peptides on the cell surface. To enable characterization of stapled peptides, azide containing residues are incorporated in place of methionine through use of methionine auxotrophic bacteria. Then, copper catalyzed click chemistry (CuAAC) is used to form stapled peptides directly on the cell surface through reaction with bisalkyne staples. Finally, cells are sorted for given molecular properties by incubating with fluorescently labeled target protein. This technique was previously applied to discover an inhibitor with eightfold improved affinity against mdm2, an important oncoprotein in the p53 pathway.
Here, we improve on this technique and further demonstrate its utility in discovering potent stapled peptide inhibitors by applying it to the Bcl-2 protein family, which is comprised of five highly homologous protein targets. Because of their homology, methods that can simultaneously optimize specificity and affinity are greatly needed. First, we utilized on-cell staple scanning to identify locations for the linker that maintain target binding. The next improvement in the technique is incorporating Next Generation Sequencing (NGS) into the workflow, which enables quantitative measurement of affinity and specificity based on high-throughput fluorescent-activated cell sorting data. To identify lead molecules, computational models were constructed based on affinity and specificity profiles of >105 peptides from cell sorting. Interestingly, these models generated peptides with improved specificity and affinity compared to those that emerged directly from the sorting campaign. Finally, we translated these molecules off the cell surface and evaluated their mechanisms of action and efficacy, proving they demonstrate improved efficacy in vitro over their linear counterparts. The ability to improve affinity, specificity, stability, and in vitro efficacy demonstrates SPEEDâs multifaceted capability.
In summary, we apply SPEED to design tight binding, highly specific, and protease resistant stapled peptide inhibitors of Bcl-2 proteins. To our knowledge, this work represents the first high-throughput study of stapled peptide Bcl-2 inhibitors. Peptides with these improved drug-like properties promise better selective treatment for cancer with in vitro and in vivo validation of efficacy. This approach provides a framework to discover potent stapled peptide inhibitors towards other important protein targets.