# Decoding Structural Determinants of Efficacy and Specificity in a GPCR Subfamily

> **NIH NIH K99** · UNIVERSITY OF CALIFORNIA BERKELEY · 2024 · $106,161

## Abstract

Project Summary
 G protein–coupled receptors (GPCRs), the largest family of membrane proteins and a major class of drug
targets, convert extracellular stimuli into intracellular responses by undergoing conformational changes that
enable them to bind and activate signaling proteins. Identifying the mechanisms that underly activation––the
atomic-level rearrangements that propagate from the ligand-binding pocket to induce large-scale motions on the
intracellular surface––can powerfully impact drug discovery but requires measurement of conformational change
at multiple temporal and spatial scales. Thus, activation mechanisms for only a small number of GPCRs have
been carefully mapped at the atomic level, hindering the rational design of therapeutics with high selectivity and
few side effects. Uncovering these mechanisms for those therapeutically promising GPCRs that operate as
multimers, with large extracellular domains, requires biophysical approaches that can bridge multiple scales.
 From my Ph.D., I have expertise in using physics-based simulations to capture conformational change in
membrane proteins with high spatial and temporal resolution, but the computational cost of molecular dynamics
(MD) limits accessible timescales and investigation of many members of a protein family. As a postdoctoral fellow
at UC-Berkeley, I have pursued experimental studies to fill in the gaps associated with classical MD simulations.
I have learned to carry out hydrogen-deuterium exchange–mass spectrometry (HDX-MS) under the supervision
of Dr. Susan Marqusee, enabling me to quantify the local stability of structural elements in a protein. More
recently, I have pursued an additional strategy, single-molecule Förster Resonance Energy Transfer (smFRET),
to quantify the relative populations of states in a protein conformational landscape, under the guidance of Dr.
Ehud Isacoff. I will pursue computational and experimental studies of a difficult-to-drug class of GPCRs, the
metabotropic glutamate receptors (mGluRs). The mGluRs have a complex topology: the ligand-binding domains
(LBD) of these GPCRs transmit a ligand's effects laterally, to the neighboring subunit, and intracellularly, to the
transmembrane domain. In Aim 1, I will determine the mechanisms by which ligand binding affects
conformational changes within a single subunit; across the dimer interface; and below, to the transmembrane
domain. In Aim 2, I will investigate how sequence variation in the mGluR family leads to the strikingly broad
range of glutamate affinity and efficacy previously observed for the eight mGluR subtypes. In Aim 3, I will
investigate how endogenous extracellular binding partners modulate mGluRs to affect downstream activation.
This work will provide a general strategy for investigating mechanisms of conformational change for multi-domain
proteins and will enable discovery of allosteric ligands that can selectively target a particular receptor while
eliciting a specific signaling output. T...

## Key facts

- **NIH application ID:** 10757453
- **Project number:** 5K99GM148823-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** Naomi Latorraca
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $106,161
- **Award type:** 5
- **Project period:** 2023-01-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10757453

## Citation

> US National Institutes of Health, RePORTER application 10757453, Decoding Structural Determinants of Efficacy and Specificity in a GPCR Subfamily (5K99GM148823-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10757453. Licensed CC0.

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