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| Funder | NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE |
|---|---|
| Recipient Organization | University of North Carolina Chapel Hill |
| Country | United States |
| Start Date | Sep 19, 2024 |
| End Date | Aug 31, 2026 |
| Duration | 711 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10974397 |
ABSTRACT Research Component (RC) 3 includes the 1) development of new in vitro and/or ex vivo assays, and 2) screening and/or rational design efforts to identify and characterize novel assets for pain conditions/disorders. Our team has already established binding as well as G protein and arrestin signaling in vitro assays to comprehensively
profile NTSR1 ligands, including ligands with complex allosteric modulator activities such as SBI-553. Here we propose to 1) develop a novel ex vivo assay enabling electrophysiological recording of NTSR1 ligand modulation of NTSR1-expressing amygdalar neuron excitability in brain slices (Aim 1), and 2) perform an ultra-large-scale
computational screen and structure-guided early optimization of NTSR1 assets (Aim 2). For Aim 1, we will cross mice in which expression of the DNA recombinase Cre is driven by the prompter of the Ntsr1 gene (Ntsr1Cre mice) with Ai14 reporter mice to generate Ntsr1Cre::Ai14 mice, in which NTSR1-expressing neurons are labeled
with the red fluorescent protein tdTomato. We will then slice the brains and perform whole-cell patch-clamp recordings, in both voltage- and current-clamp modes, on visually identified fluorescent neurons, to record standard parameters of neuronal excitability (e.g., membrane potential, rheobase, action potential firing
frequency), as in our previous studies, in this case focusing on amygdalar neurons. For Aim 2, we develop an ultra-large-scale computational screen and structure-guided early optimization of NTSR1 assets. We will dock a library of 5 billion make-on-demand molecules against the NTSR1 allosteric site, seeking novel chemotypes with
the best possible physical properties (e.g., cLogP
University of North Carolina Chapel Hill
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