Reversal of synapse loss in Alzheimer mouse models by targeting mGluR5 to prevent synaptic tagging by C1Q.

Microglia-mediated synaptic loss contributes to the development of cognitive impairments in Alzheimer's disease (AD). However, the basis for this immune-mediated attack on synapses remains to be elucidated. Treatment with the metabotropic glutamate receptor 5 (mGluR5) silent allosteric modulator (SAM), BMS-984923, prevents ß-amyloid oligomer-induced aberrant synaptic signaling while preserving physiological glutamate response. Here, we show that oral BMS-984923 effectively occupies brain mGluR5 sites visualized by [18F]FPEB positron emission tomography (PET) at doses shown to be safe in rodents and nonhuman primates. In aged mouse models of AD (APPswe/PS1ΔE9 overexpressing transgenic and AppNL-G-F/hMapt double knock-in), SAM treatment fully restored synaptic density as measured by [18F]SynVesT-1 PET for SV2A and by histology, and the therapeutic benefit persisted after drug washout. Phospho-TAU accumulation in double knock-in mice was also reduced by SAM treatment. Single-nuclei transcriptomics demonstrated that SAM treatment in both models normalized expression patterns to a far greater extent in neurons than glia. Last, treatment prevented synaptic localization of the complement component C1Q and synaptic engulfment in AD mice. Thus, selective modulation of mGluR5 reversed neuronal gene expression changes to protect synapses from damage by microglial mediators in rodents.

Identifying Loop-Mediated Protein-Protein Interactions Using LoopFinder.

Peptides are an increasingly useful class of molecules, finding unique applications as chemical probes and potential drugs. They are particularly adept at inhibiting protein-protein interactions, which are often difficult to target using small molecules. The identification and rational design of protein-binding epitopes remains a bottleneck in the development of bioactive peptides. One fruitful strategy has been using structured scaffolds to present essential hot spot residues involved in protein-protein recognition, and this process has been greatly advanced by computational tools that can identify hot spot residues. Here we discuss LoopFinder, a program that uses structures from the Protein Data Bank to comprehensively search for protein-protein interactions that are mediated by nonhelical, nonsheet loop structures. We developed LoopFinder to identify these "hot loops" and to assist in the design of cyclic peptides that mimic these important structures. In this article, we provide all key files, outline step-by-step methods for users to conduct independent LoopFinder searches, and provide guidance on additional potential applications for the LoopFinder program.

Analysis of Loops that Mediate Protein-Protein Interactions and Translation into Submicromolar Inhibitors.

Effective strategies for mimicking α-helix and ß-strand epitopes have been developed, producing valuable inhibitors for some classes of protein-protein interactions (PPIs). However, there are no general strategies for translating loop epitopes into useful PPI inhibitors. In this work, we use the LoopFinder program to identify diverse sets of "hot loops," which are loop epitopes that mediate PPIs. These include loops that are well-suited to mimicry with macrocyclic compounds, and loops that are most similar to variable loops on antibodies and ankyrin repeat proteins. We present data-driven criteria for scoring loop-mediated PPIs, uncovering a trove of potentially druggable interactions. We also use unbiased clustering to identify common structures among the hot loops. To translate these insights into real-world inhibitors, we describe a robust, diversity-oriented strategy for the rapid production and evaluation of cyclized loops. This method is applied to a computationally identified loop in the PPI between stonin2 and Eps15, producing submicromolar inhibitors. The most potent inhibitor is well-structured in water and successfully mimics the native epitope. Overall, these computational and experimental strategies provide new opportunities to design inhibitors for an otherwise intractable set of PPIs.

Comprehensive analysis of loops at protein-protein interfaces for macrocycle design.

Inhibiting protein-protein interactions (PPIs) with synthetic molecules remains a frontier of chemical biology. Many PPIs have been successfully targeted by mimicking α-helices at interfaces, but most PPIs are mediated by nonhelical, nonstrand peptide loops. We sought to comprehensively identify and analyze these loop-mediated PPIs by writing and implementing LoopFinder, a customizable program that can identify loop-mediated PPIs within all of the protein-protein complexes in the Protein Data Bank. Comprehensive analysis of the entire set of 25,005 interface loops revealed common structural motifs and unique features that distinguish loop-mediated PPIs from other PPIs. 'Hot loops', named in analogy to protein hot spots, were identified as loops with favorable properties for mimicry using synthetic molecules. The hot loops and their binding partners represent new and promising PPIs for the development of macrocycle and constrained peptide inhibitors.