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De novo design of GPCR exoframe modulators

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Abstract

G-protein-coupled receptors (GPCRs) are important therapeutic targets and have been targeted mainly through their orthosteric site, where the endogenous agonist binds1. However, allosteric modulation has emerged as a promising and innovative strategy in the realm of GPCR drug discovery1. Here, drawing inspiration from the natural regulation of GPCRs by transmembrane proteins, we have developed GPCR exoframe modulators (GEMs), de novo designed proteins that specifically target the transmembrane domain of GPCRs. Utilizing a hallucination-like design approach, we crafted GEMs with three strategic structural prompts to achieve the desired binding modes. We selected the dopamine D1 receptor as a prototypical model and systematically investigated four GEMs. Structural studies and functional assays revealed that these GEMs bind to the transmembrane domains and function as diverse allosteric modulators, including agonist-positive allosteric modulator, negative allosteric modulator and biased allosteric modulator. The ago-PAM GEM restores the activity of various D1 receptor loss-of-function mutants, suggesting a promising therapeutic target for GPCR-related disorders. Our work introduces GEMs that target the transmembrane domain as potent agents for allosteric GPCR modulation and highlights the potential of deep learning-based approaches in the design of function-oriented membrane proteins.

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Fig. 1: De novo Design of GEM.
Fig. 2: In silico assessment of design results.
Fig. 3: High-resolution structures of de novo designed GEMs in complex with D1R.
Fig. 4: Structural assessment and molecular basis of GEM-mediated GPCR regulation.

Data availability

Atomic coordinates and cryo-EM maps have been deposited in the Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB), respectively, under the following accessions: \(\text{GE}{\text{M}}_{\text{anchor}}^{\text{TM}1/2/4}\)–D1R–Gs (9LLE and EMD-63199), \(\text{GE}{\text{M}}_{\text{BAM}}^{\text{TM}3/4/5}\)–D1R–Gs (9LLF and EMD-63200), \(\text{GE}{\text{M}}_{\text{NAM}}^{\text{TM}5/6/7}\)D1R (9LLG and EMD-63201), \(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\)–D1R–Gs (9LLH and EMD-63202), \(\text{GE}{\text{M}}_{\text{anchor}}^{\text{TM}1/2/4}\)–\(\text{GE}{\text{M}}_{\text{BAM}}^{\text{TM}3/4/5}\)–\(\text{GE}{\text{M}}_{\text{NAM}}^{\text{TM}5/6/7}\)–D1R (9LLI and EMD-63203) and \(\text{GE}{\text{M}}_{\text{anchor}}^{\text{TM}1/2/4}\)–\(\text{GE}{\text{M}}_{\text{BAM}}^{\text{TM}3/4/5}\)–\(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\)–D1R–Gs (9LLJ and EMD-63204). All data produced or analysed in this study are included in the main text or the supplementary materials.

Code availability

RFDiffusion code and weights can be downloaded from https://github.com/RosettaCommons/RFdiffusion. ColabDesign implementation of ProteinMPNN is available from https://github.com/sokrypton/ColabDesign/. The local AF2 is available from https://github.com/YoshitakaMo/localcolabfold and AF2 model weights used for optimization and predictions can be downloaded from https://storage.googleapis.com/alphafold/alphafold_params_2021-07-14.tar.

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Acknowledgements

The cryo-EM data were collected at the Cryo-Electron Microscopy Facility, Liangzhu Laboratory, Zhejiang University. We thank C. Ma for technical support. Cryo-EM specimens were examined with help from S. Chang at the Center of Cryo-Electron Microscopy (CCEM), Zhejiang University. This study was funded by the National Science and Technology Major Project (2022ZD0117000 to M.Z.), the National Natural Science Foundation of China (92353303, 32430051 and 32141004 to Y.Z., 62202426 to M.Z.), the Pioneer and Leading Goose R&D Program of Zhejiang (2024C03147 to Y.Z.); the Fundamental Research Funds for the Central Universities (226-2022-00205 to Y.Z.).

Author information

Author notes

  1. These authors contributed equally: Shizhuo Cheng, Jia Guo, Yun-li Zhou, Xumei Luo, Gufang Zhang

Authors and Affiliations

  1. Department of Pathology of Sir Run Run Shaw Hospital, Department of Pharmacology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, and Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, China

    Shizhuo Cheng, Jia Guo, Yun-li Zhou, Xumei Luo, Yixin Yang, Jiannan Xie, Dan-dan Shen, Shaokun Zang & Yan Zhang

  2. College of Computer Science and Technology, Zhejiang University, Hangzhou, China

    Shizhuo Cheng & Min Zhang

  3. Shanghai Institute for Advanced Study of Zhejiang University, Shanghai, China

    Shizhuo Cheng & Min Zhang

  4. Jiangsu Key Laboratory of Neuropsychiatric Diseases and Department of Pharmacology, College of Pharmaceutical Sciences, Soochow University, Suzhou, China

    Gufang Zhang, Huicui Yang & Xuechu Zhen

  5. School of Pharmacy, Hangzhou Medical College, Hangzhou, China

    Ya-zhi Zhang & Ping Xu

Authors
  1. Shizhuo Cheng
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  2. Jia Guo
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  3. Yun-li Zhou
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  14. Min Zhang
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  15. Yan Zhang
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Contributions

Y.Z. conceived, designed and supervised the overall project. M.Z. and Y.Z. supervised the computational part of the project. X.Z. supervised the receptor binding assay. S.C. developed the binder design pipeline and designed the GEMs. Y.-L.Z., J.G., X.L., Y.-Z.Z., Y.Y. and P.X. prepared the constructs for functional assays and performed the cellular functional assays. J.G. and Y.-L.Z. prepared the constructs for protein purification and purified the GEM–D1R complexes. D.-D.S. evaluated the samples by negative-stain electron microscopy. J.G. and Y.-L.Z. prepared the cryo-EM grids. J.G. and S.Z. collected the cryo-EM data. J.G. performed cryo-EM map calculation and model building. G.Z. and H.Y. performed the receptor binding assay. S.C., J.G., Y.-L.Z. and X.L. prepared the figures. S.C., J.G. and Y.Z. wrote the manuscript with the input from the other authors.

Corresponding authors

Correspondence to Min Zhang or Yan Zhang.

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Nature thanks Justin English, David Thal and Jason Yim for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Probing D1R transmembrane domain with single helices.

a-c, Surface overview of probe-targeting sites for RFdiffusion binder protocol. The presented surface of D1R (PDB: 7LJC59) is colored by electrostatic potential. The approximate targeting regions are highlighted in yellow for cavity near TM1/2/4 (a), cavity near TM3/4/5 (b), and cavity near TM5/6 (c). d, Cartoon overview of probe-targeting sites. e, SeqLogo of probing sequences. Probes designed as binders with scaffolds generated with RFDiffusion binder protocol targeting TM1/2/4, TM3/4/5 and TM5/6. ProteinMPNN input the resulting complex structures and design sequences for probes only. f, Binding conformation of probing, predicted with AF2, colored by pLDDT. The probe-receptor complex predicted for probes designed as binder. Probes having clashes with the receptor are hidden (distance cutoff set as 0.8 Å).

Extended Data Fig. 2 The top views of single transmembrane helices binding poses and probe binding pose distribution analysis respect to different targeting sites.

a-h, Models are super-positioned with the D1R chain as reference, overlayed with the probe point cloud. CD69 in CD69-S1PR1 complex (PDB: 8G9420) (a). MRAP1 in MRAP1-MC2R complex (PDB: 8GY721) (b). RAMP1 in CGRPR (PDB: 6E3Y22) (c). RAMP1 in AMY1R (PDB: 7TYF23) (d). RAMP2 in AMY2R (PDB: 7TYY23) (e). RAMP2 in AM1R (PDB: 6UUN24) (f). RAMP3 in AMY3R (PDB: 7TZF23) (g). RAMP3 in AM2R (PDB: 6UVA24) (h). i-k, Probe point clouds with different TMD targeting sites (TM1/2/4, TM3/4/5, TM5/6) as the RFDiffusion binder protocol condition, colored by normalized density. Each point cloud is roughly divided into three distinct sub-clouds: TM1/2/4, TM3/4/5 and TM5/6/7. The number near the sub-cloud is calculated as the number of related predicted models contributing to this sub-cloud. The color of a point represents the normalized density value of the grid it belongs to. Density normalization is calculated individually for each point cloud. Probe point clouds were generated with starting scaffolds targeting TM1/2/4 (i), targeting TM3/4/5 (j) and targeting TM5/6 (k).

Extended Data Fig. 3 AlphaFold3 (AF3) predicted representative GEMs in the final iteration, bound to dopamine D1 receptor.

a, Five structures predicted for each GEM, colored by pLDDT, with ipTM scores reported by AF3. The active state prediction included the Gαs sequence. b, Predicted aligned error plot reported by AF3. Red rectangle highlights the GEM-related sub-matrix.

Extended Data Fig. 4 Influence of gradient transfection of GEM on cAMP accumulation and β-arrestin 2 recruitment mediated by D1R, and the effects of GEM insertions on dopamine-induced D1R signaling.

a-h, Dopamine dose-response curves for cAMP accumulation with increasing amounts of \(\text{GE}{\text{M}}_{\text{anchor}}^{\text{TM}1/2/4}\) (a), \(\text{GE}{\text{M}}_{\text{BAM}}^{\text{TM}3/4/5}\) (b), \(\text{GE}{\text{M}}_{\text{NAM}}^{\text{TM}5/6/7}\) (c) and \(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\) (d) and for β-arrestin 2 recruitment with increasing amounts of \(\text{GE}{\text{M}}_{\text{anchor}}^{\text{TM}1/2/4}\) (e), \(\text{GE}{\text{M}}_{\text{BAM}}^{\text{TM}3/4/5}\) (f), \(\text{GE}{\text{M}}_{\text{NAM}}^{\text{TM}5/6/7}\) (g) and \(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\) (h). i-l, Dose-response curves showing the effects of various D1R constructs in which \(\text{GE}{\text{M}}_{\text{anchor}}^{\text{TM}1/2/4}\) (i), \(\text{GE}{\text{M}}_{\text{BAM}}^{\text{TM}3/4/5}\) (j), \(\text{GE}{\text{M}}_{\text{NAM}}^{\text{TM}5/6/7}\) (k) and \(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\) (l) were fused with the receptor. The signaling was dopamine-induced, measured by cAMP accumulation and β-arrestin 2 recruitment assays. Values are shown as the mean ± SEM from three independent experiments performed in triplicate. A detailed statistical evaluation is provided in Extended Data Tables 1–3.

Extended Data Fig. 5 Cryo-EM data processing and validation.

a-d, Results of \(\text{GE}{\text{M}}_{\text{anchor}}^{\text{TM}1/2/4}\)-D1R-Gs complex. a, Cryo-EM map. b, Cryo-EM map colored according to local resolution. c, Representative 2D averages. d, Fourier shell correlation (FSC) curve, the resolution was assessed by the Gold Standard of FSC = 0.143. e-h, Results of \(\text{GE}{\text{M}}_{\text{BAM}}^{\text{TM}3/4/5}\)-D1R-Gs complex. e, Cryo-EM map. f, Cryo-EM map colored according to local resolution. g, Representative 2D averages. h, FSC curve. i-l, Results of \(\text{GE}{\text{M}}_{\text{NAM}}^{\text{TM}5/6/7}\)-D1R-BRIL complex. i, Cryo-EM map. j, Cryo-EM map colored according to local resolution. k, Representative 2D averages. l, FSC curve. m-p, Results of \(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\)-D1R-Gs complex. m, Cryo-EM map. n, Cryo-EM map colored according to local resolution. o, Representative 2D averages. p, FSC curve. q-t, Results of \(\text{GE}{\text{M}}_{\text{anchor}}^{\text{TM}1/2/4}\)-\(\text{GE}{\text{M}}_{\text{BAM}}^{\text{TM}3/4/5}\)-\(\text{GE}{\text{M}}_{\text{NAM}}^{\text{TM}5/6/7}\)-D1R-BRIL complex. q, Cryo-EM map. r, Cryo-EM map colored according to local resolution. s, Representative 2D averages. t, FSC curve. u-x, Results of\(\,\text{GE}{\text{M}}_{\text{anchor}}^{\text{TM}1/2/4}\)-\(\text{GE}{\text{M}}_{\text{BAM}}^{\text{TM}3/4/5}\)-\(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\)-D1R-Gs complex. u, Cryo-EM map. v, Cryo-EM map colored according to local resolution. w, Representative 2D averages. x, FSC curve.

Extended Data Fig. 6 The interfaces between D1R and GEMs.

a-c, The interactions between D1R and \(\text{GE}{\text{M}}_{\text{anchor}}^{\text{TM}1/2/4}\). a, The interaction surface. b, Analysis of hydrophobic and hydrophilic properties of interface residues. c, Detailed view showing residues and side chains at the \(\text{GE}{\text{M}}_{\text{anchor}}^{\text{TM}1/2/4}\)-D1R interface. d-f, The interactions between D1R and \(\text{GE}{\text{M}}_{\text{BAM}}^{\text{TM}3/4/5}\). d, The interaction surface. e, Analysis of hydrophobic and hydrophilic properties of interface residues. f, Detailed view showing residues and side chains at the \(\text{GE}{\text{M}}_{\text{BAM}}^{\text{TM}3/4/5}\)-D1R interface. g-i, The interactions between D1R and \(\text{GE}{\text{M}}_{\text{NAM}}^{\text{TM}5/6/7}\). g, The interaction surface. h, Analysis of hydrophobic and hydrophilic properties of interface residues. i, Detailed view showing residues and side chains at the \(\text{GE}{\text{M}}_{\text{NAM}}^{\text{TM}5/6/7}\)-D1R interface. j-l, The interactions between D1R and \(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\). j, The interaction surface. k, Analysis of hydrophobic and hydrophilic properties of interface residues. l, Detailed view showing residues and side chains at the \(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\)-D1R interface.

Extended Data Fig. 7 rescues LoF mutations of D1R.

\({{\rm{GEM}}}_{{\rm{ago}}-{\rm{PAM}}}^{{\rm{TM5}}/6/7}\) a, Schematic illustration of the therapeutic mechanism of \(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\) for LoF mutations. b, Location and types of LoF mutations in D1R. c, The effect of \(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\) on cAMP accumulation in the LoF mutant D1R. The relative efficacy is defined as the range between the maximal response (1 μM dopamine or with \(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\)) and the vehicle baseline (no agonist). Values are shown as the mean ± SEM from three independent experiments performed in triplicate. NSP ≥ 0.05, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 by two-way ANOVA followed by Sidak’s multiple comparisons test (P = 0.0683, <0.0001, <0.0001, <0.001, <0.001, <0.001, <0.001 from left to right). A detailed statistical evaluation is provided in Extended Data Table 6. Schematics in a,b were created in BioRender. Qin, J. (2025) https://BioRender.com/9l51ggt.

Extended Data Fig. 8 Rescue of LoF mutant D1R mediated by \({{\bf{GEM}}}_{{\bf{ago}}{\boldsymbol{-}}{\bf{PAM}}}^{{\bf{TM5}}{\boldsymbol{/}}{\bf{6}}{\boldsymbol{/}}{\bf{7}}}\).

a-f, Dose-response curves showing dopamine-induced cAMP accumulation in cells expressing various D1R LoF mutants rescued by \(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\): D103A (a), L66F (b), D70A (c), F281R (d), N327A (e), and T37K (f). The experiments were conducted in the presence of low (light blue), medium (blue), or high (dark blue) concentrations of \(\text{GE}{\text{M}}_{\text{ago}-\text{PAM}}^{\text{TM}5/6/7}\). Wild-type D1R (D1R-WT, dashed grey line) and the mutant D1R alone (D1R-mut, yellow) are shown as controls. Values are shown as the mean ± SEM from three independent experiments performed in triplicate. A detailed statistical evaluation is provided in Extended Data Table 6.

Extended Data Table 1 Influence of gradient transfection of \({{\bf{GEM}}}_{{\bf{anchor}}}^{{\bf{TM1}}{\boldsymbol{/}}{\bf{2}}{\boldsymbol{/}}{\bf{4}}}\), \({{\bf{GEM}}}_{{\bf{BAM}}}^{{\bf{TM3}}{\boldsymbol{/}}{\bf{4}}{\boldsymbol{/}}{\bf{5}}}\), and \({{\bf{GEM}}}_{{\bf{NAM}}}^{{\bf{TM5}}{\boldsymbol{/}}{\bf{6}}{\boldsymbol{/}}{\bf{7}}}\) on cAMP accumulation and β-arrestin 2 recruitment mediated by D1R
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Extended Data Table 2 Influence of gradient transfection of \({{\bf{GEM}}}_{{\bf{ago\mbox{--}PAM}}}^{{\bf{TM5}}{\boldsymbol{/}}{\bf{6}}{\boldsymbol{/}}{\bf{7}}}\) on cAMP accumulation and β-arrestin 2 recruitment mediated by D1R
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Extended Data Table 3 Influence of fused-GEM on cAMP accumulation and β-arrestin 2 recruitment mediated by D1R
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Extended Data Table 4 Cryo-EM data collection, model refinement and validation statistics
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Extended Data Table 5 Relative efficacy of D1R mediated by \({{\bf{D1R\mbox{--}GEM}}}_{{\bf{BAM}}}^{{\bf{TM3}}{\boldsymbol{/}}{\bf{4}}{\boldsymbol{/}}{\bf{5}}}\) and \({{\bf{GEM}}}_{{\bf{ago\mbox{--}PAM}}}^{{\bf{TM5}}{\boldsymbol{/}}{\bf{6}}{\boldsymbol{/}}{\bf{7}}}\)
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Extended Data Table 6 Rescue of LoF mutant D1R mediated by \({{\bf{GEM}}}_{{\bf{ago\mbox{--}PAM}}}^{{\bf{TM5}}{\boldsymbol{/}}{\bf{6}}{\boldsymbol{/}}{\bf{7}}}\)
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Cheng, S., Guo, J., Zhou, Yl. et al. De novo design of GPCR exoframe modulators. Nature (2026). https://doi.org/10.1038/s41586-025-09957-1

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