Designing Rigid Protein Fiducials to Visualize GPCR Conformational States

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The paper investigates whether generative protein design combined with deep-learning-based conformational ensemble prediction can create rigid “fiducial markers” that enable cryoEM visualization of GPCR conformational states at arbitrary fusion points, without requiring signaling partners or mimetics. Using high-throughput cryoEM structural determination, the authors validate the approach by resolving inactive state structures of four pharmaceutically relevant GPCRs and detail ligand-related pharmacology-relevant features, while noting comparison to co-folding models to identify gaps in predicting ligand-induced conformational changes. They further engineer an extracellular fiducial for the β2-adrenergic receptor to characterize intracellular motif rearrangements directly in the absence of G-protein. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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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.
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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. Competing Interest Statement The authors have declared no competing interest. Footnotes The results section has been revised to include an additional reference.

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europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
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License: CC-BY-NC-ND-4.0