Designing Rigid Protein Fiducials to Visualize GPCR Conformational States

G-protein coupled receptors (GPCRs) mediate precise ligand-specific signaling profiles, yet structural visualization of how ligands alter receptor conformational landscapes in the absence of signaling partners or mimetics has proven incredibly challenging. Here we show that by combining generative protein design with deep-learning based conformational ensemble prediction we can reliably design 'fiducial markers' to facilitate cryogenic electron microscopy (cryoEM) of GPCRs at arbitrary fusion points, enabling the visualization of previously intractable states. We validate the approach with high-throughput determination of inactive state structures of four pharmaceutically relevant GPCRs, allowing for key details of receptor pharmacology to be resolved in each case. We then engineered an extracellular fiducial marker for the prototypical β2-adrenergic receptor that enabled direct structural characterization of the rearrangement of key intracellular motifs in the absence of G-protein. Comparison with recent co-folding models highlights gaps in current methods for predicting ligand-induced GPCR conformational changes. These results present a generalizable framework for accessing traditionally inaccessible structural states of small, dynamic proteins.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-01-26
DOI
https://doi.org/10.64898/2026.01.24.701540
Primary Topic
Receptor Mechanisms and Signaling
Type
article
Field-Weighted Citation Impact
0.00

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article

Designing Rigid Protein Fiducials to Visualize GPCR Conformational States

Michael J. Robertson, Justin G. English, Yuan-En Sun, Alina A. Vo
bioRxiv (Cold Spring Harbor Laboratory)
Receptor Mechanisms and Signaling
article

Designing Rigid Protein Fiducials to Visualize GPCR Conformational States

Michael J. Robertson, Justin G. English, Yuan-En Sun, Alina A. Vo
article en

Abstract

G-protein coupled receptors (GPCRs) mediate precise ligand-specific signaling profiles, yet structural visualization of how ligands alter receptor conformational landscapes in the absence of signaling partners or mimetics has proven incredibly challenging. Here we show that by combining generative protein design with deep-learning based conformational ensemble prediction we can reliably design 'fiducial markers' to facilitate cryogenic electron microscopy (cryoEM) of GPCRs at arbitrary fusion points, enabling the visualization of previously intractable states. We validate the approach with high-throughput determination of inactive state structures of four pharmaceutically relevant GPCRs, allowing for key details of receptor pharmacology to be resolved in each case. We then engineered an extracellular fiducial marker for the prototypical β2-adrenergic receptor that enabled direct structural characterization of the rearrangement of key intracellular motifs in the absence of G-protein. Comparison with recent co-folding models highlights gaps in current methods for predicting ligand-induced GPCR conformational changes. These results present a generalizable framework for accessing traditionally inaccessible structural states of small, dynamic proteins.

bioRxiv (Cold Spring Harbor Laboratory)
Baylor College of Medicine (US), University of Utah (US)
Cancer Prevention and Research Institute of Texas, National Institutes of Health
Openalex Percentile: Top 77%
Receptor Mechanisms and Signaling
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