Comprehensive Peptide Cyclization Examination Yields Optimized APP Scaffolds with Improved Affinity toward Mint2.

Peptides targeting disease-relevant protein-protein interactions are an attractive class of therapeutics covering the otherwise undruggable space between small molecules and therapeutic proteins. However, peptides generally suffer from poor metabolic stability and low membrane permeability. Hence, peptide cyclization has become a valuable approach to develop linear peptide motifs into metabolically stable and potentially cell-permeable cyclic leads. Furthermore, cyclization of side chains, also known as "stapling", can stabilize particular secondary peptide structures. Here, we demonstrate that a comprehensive examination of cyclization strategies in terms of position, chemistry, and length is a prerequisite for the selection of optimal cyclic peptide scaffolds. Our systematic approach identifies cyclic APP dodecamer peptides targeting the phosphotyrosine binding domain of Mint2 with substantially improved affinity. We show that especially all-hydrocarbon stapling provides improved metabolic stability, a significantly stabilized secondary structure and membrane permeability.

Targeting the APP-Mint2 Protein-Protein Interaction with a Peptide-Based Inhibitor Reduces Amyloid-ß Formation.

There is an urgent need for novel therapeutic approaches to treat Alzheimer's disease (AD) with the ability to both alleviate the clinical symptoms and halt the progression of the disease. AD is characterized by the accumulation of amyloid-ß (Aß) peptides which are generated through the sequential proteolytic cleavage of the amyloid precursor protein (APP). Previous studies reported that Mint2, a neuronal adaptor protein binding both APP and the γ-secretase complex, affects APP processing and formation of pathogenic Aß. However, there have been contradicting results concerning whether Mint2 has a facilitative or suppressive effect on Aß generation. Herein, we deciphered the APP-Mint2 protein-protein interaction (PPI) via extensive probing of both backbone H-bond and side-chain interactions. We also developed a proteolytically stable, high-affinity peptide targeting the APP-Mint2 interaction. We found that both an APP binding-deficient Mint2 variant and a cell-permeable PPI inhibitor significantly reduced Aß42 levels in a neuronal in vitro model of AD. Together, these findings demonstrate a facilitative role of Mint2 in Aß formation, and the combination of genetic and pharmacological approaches suggests that targeting Mint2 is a promising therapeutic strategy to reduce pathogenic Aß levels.

Investigating the Influence of Tracer Kinetics on Competition-Kinetic Association Binding Assays: Identifying the Optimal Conditions for Assessing the Kinetics of Low-Affinity Compounds.

An increased appreciation of the importance of optimizing drug-binding kinetics has lead to the development of various techniques for measuring the kinetics of unlabeled compounds. One approach is the competition-association kinetic binding method first described in the 1980s. The kinetic characteristics of the tracer employed greatly affects the reliability of estimated kinetic parameters, a barrier to successfully introducing these kinetic assays earlier in the drug discovery process. Using a modeling and Monte Carlo simulation approach, we identify the optimal tracer characteristics for determining the kinetics of the range of unlabeled ligands typically encountered during the different stages of a drug discovery program (i.e., rapidly dissociating, e.g., k off = 10 minute-1 low-affinity "hits" through to slowly dissociating e.g., k off = 0.01 minute-1 high-affinity "candidates"). For more rapidly dissociating ligands (e.g., k off = 10 minute-1), the key to obtaining accurate kinetic parameters was to employ a tracer with a relatively fast off-rate (e.g., k off = 1 minute-1) or, alternatively, to increase the tracer concentration. Reductions in assay start-time ≤1second and read frequency ≤5 seconds significantly improved the reliability of curve fitting. Timing constraints are largely dictated by the method of detection, its inherent sensitivity (e.g., TR-FRET versus radiometric detection), and the ability to inject samples online. Furthermore, we include data from TR-FRET experiments that validate this simulation approach, confirming its practical utility. These insights into the optimal experimental parameters for development of competition-association assays provide a framework for identifying and testing novel tracers necessary for profiling unlabeled competitors, particularly rapidly dissociating low-affinity competitors.