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Structural basis for partial agonism in 5-HT3A receptors

Nature Structural & Molecular Biology volume 31, pages 598–609 (2024)Cite this article

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An Author Correction to this article was published on 05 April 2024

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Abstract

Hyperactivity of serotonin 3 receptors (5-HT3R) underlies pathologies associated with irritable bowel syndrome and chemotherapy-induced nausea and vomiting. Setrons, a class of high-affinity competitive antagonists, are used in the treatment of these conditions. Although generally effective for chemotherapy-induced nausea and vomiting, the use of setrons for treating irritable bowel syndrome has been impaired by adverse side effects. Partial agonists are now being considered as an alternative strategy, with potentially less severe side effects than full antagonists. However, a structural understanding of how these ligands work is lacking. Here, we present high-resolution cryogenic electron microscopy structures of the mouse 5-HT3AR in complex with partial agonists (SMP-100 and ALB-148471) captured in pre-activated and open-like conformational states. Molecular dynamics simulations were used to assess the stability of drug-binding poses and interactions with the receptor over time. Together, these studies reveal mechanisms for the functional differences between orthosteric partial agonists, full agonists and antagonists of the 5-HT3AR.

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Fig. 1: Functional characterization of 5-HT3AR and orthosteric ligands.
Fig. 2: Cryo-EM analysis of 5-HT3AR in complex with orthosteric ligands.
Fig. 3: Orthosteric binding pocket and drug–receptor interactions.
Fig. 4: Comparison of binding poses between orthosteric ligands.
Fig. 5: Distinct pore conformations and ion permeation pathway.
Fig. 6: Protein–ligand interactions during molecular dynamics simulations.

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Data availability

The coordinates of the 5-HT3AR–ligand structures and the cryo-EM maps have been deposited with the Worldwide Protein Data Bank (wwPDB) and Electron Microscopy Data Bank (EMDB) under 5-HT3AR–SMP (pre-activated) PDB 8FRX, EMD-29410; 5-HT3AR–SMP (open-like) PDB 8FSP, EMD-29421; 5-HT3AR–ALB (pre-activated) PDB 8FRW, EMD-29409; 5-HT3AR–ALB (open-like) PDB 8FSZ, EMD-29422; 5-HT3AR–5-HT (pre-activated) PDB 8FRZ, EMD-29411; and 5-HT3AR–5-HT (open-like) PDB 8FSB, EMD-29418. All relevant data have been deposited in publically available repositories. Source data are provided with this paper.

Code availability

Python scripts for Euler angle calculations and relevant PyMOL session files are deposited in GitHub (https://github.com/kcf26/5HT3A_partial_agonism.git). Simulation files are deposited in Zenodo (https://doi.org/10.5281/zenodo.7967135).

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Acknowledgements

We acknowledge the use of instruments at the Cryo-Electron Microscopy Core at the Case Western Reserve University School of Medicine. We are grateful to K. Li and K. Whiddon for assistance with cryo-EM imaging and data collection. We thank D. Major for assistance with hybridoma and cell culture at the Department of Ophthalmology and Visual Sciences (supported by the National Institutes of Health Core Grant P30EY11373). We thank W. F. Boron for kindly providing us with the Xenopus oocytes. We are grateful to S. Basak for training K.F. in protein biochemistry and cryo-EM sample preparation, and to A. Kumar and E. Gibbs for inputs on data processing. We are very grateful to the members of the Chakrapani lab for assistance with the project and critical reading and comments on the manuscript. K.F. would like to acknowledge the cryo-EM training by the University of Michigan Department of Life Sciences Summer Training School. Computational work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai and supported by the Clinical and Translational Science Awards (CTSA) grant UL1TR004419 from the National Center for Advancing Translational Sciences. Computations were supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD026880. Research reported in this paper was supported by the National Institutes of Health grants R01GM131216 and R35GM134896 to S.C. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Author notes

  1. These authors contributed equally: Madeleine Stauffer, Leslie Salas-Estrada.

Authors and Affiliations

  1. Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, OH, USA

    Kevin Felt, Madeleine Stauffer & Sudha Chakrapani

  2. Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Leslie Salas-Estrada & Marta Filizola

  3. SciMount Therapeutics (Shenzhen) Co. Ltd., Shenzhen, China

    Peter R. Guzzo, Dejian Xie & Jinkun Huang

  4. Department of Pharmacology, School of Medicine, Case Western Reserve University, Cleveland, OH, USA

    Sudha Chakrapani

  5. Cleveland Center for Membrane and Structural Biology, Case Western Reserve University, Cleveland, OH, USA

    Sudha Chakrapani

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Contributions

K.F. and S.C. conceived the project and designed experimental procedures. P.R.G., D.X. and J.H. synthesized the orthosteric ligands and carried out binding studies. K.F. purified the protein and optimized the cryo-EM sample preparation, collected the cryo-EM data and carried out data processing. M.S. performed two-electrode voltage-clamp recordings. L.S-E. performed the molecular dynamics simulations and other computational analyses under the supervision of M.F. S.C. supervised the execution of the experiments, data analysis and interpretation. K.F. and S.C. drafted the manuscript with contributions from all the authors. All authors reviewed the final manuscript.

Corresponding author

Correspondence to Sudha Chakrapani.

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Competing interests

D.X. and J.H. are employees of SciMount Therapeutics and are developing SMP in clinical trials as a potential treatment for IBS. The remaining authors declare no competing interests.

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Peer review information

Nature Structural & Molecular Biology thanks Jeff Abramson and Rebecca Howard for their contribution to the peer review of this work. Primary Handling Editor: Katarzyna Ciazynska, in collaboration with the Nature Structural & Molecular Biology team. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 5-HT3AR–5-HT cryo-EM data processing.

(A) Representative 2D-classes of the 5-HT3AR in the presence of 5-HT, generated by RELION. (B) Final 5-HT3AR-5-HT 3D maps of the pre-activated (left) and open-like (right) states with surface colored to indicate local resolution based on Phenix local resolution. (C) Fourier shell correlation (FSC) plots for 5-HT3AR-5-HT pre-activated (left) and open-like (right) states generated by comparing two independent half maps produced during refinement in RELION. Horizontal dotted line represents the FSC threshold at 0.143. Nominal resolution of FSC0.143 of unmasked (black FSC curve) and masked (red FSC curve) maps are indicated. (D) Map-to-model correlation plot for 5-HT3AR–5-HT half and full maps (E) 5-HT3AR–5-HT map-model correlation for various regions from each domain of the pre-activated (left) and open-like (right) conformation.

Extended Data Fig. 2 5-HT3AR–SMP cryo-EM data processing.

(A) Representative 2D-classes of the 5-HT3AR in the presence of SMP-100, generated by RELION. (B) Final 5-HT3AR–SMP 3D maps of the pre-activated (left) and open-like (right) states with surface colored to indicate local resolution based on Phenix local resolution. (C) Fourier shell correlation (FSC) plots for 5-HT3AR–SMP pre-activated (left) and open-like (right) states generated by comparing two independent half maps produced during refinement in RELION. Horizontal dotted line represents the FSC threshold at 0.143. Nominal resolution of FSC0.143 of unmasked (black FSC curve) and masked (red FSC curve) maps are indicated by arrow. (D) Map-to-model correlation plot for 5-HT3AR–SMP half and full maps (E) 5-HT3AR–SMP map-model correlation for various regions from each domain of the pre-activated (left) and open-like (right) conformation.

Extended Data Fig. 3 5-HT3AR–ALB cryo-EM data processing.

(A) Representative 2D-classes of the 5HT3AR in the presence of ALB-148471, generated by RELION. (B) Final 5-HT3AR–ALB 3D maps of the pre-activated (left) and open-like (right) states with surface colored to indicate local resolution based on Phenix local resolution. (C) Fourier shell correlation (FSC) plots for 5-HT3AR–ALB pre-activated (left) and open-like (right) states generated by comparing two independent half maps produced during refinement in RELION. Horizontal dotted line represents the FSC threshold at 0.143. Nominal resolution of FSC0.143 of unmasked (black FSC curve) and masked (red FSC curve) maps are indicated by arrow. (D) Map-to-model correlation plot for 5HT3AR-ALB half and full maps (E) 5-HT3AR–ALB map-model correlation for various regions from each domain of the pre-activated (left) and open-like (right) conformation.

Extended Data Fig. 4 Conformational differences among liganded pre-activated states and 5-HT3AR–Apo.

Comparison of multiple 5HT3AR models representing a range of activities. (A) Alignment of 5-HT3AR–Apo, 5-HT3AR–PAL, 5-HT3AR–SMP, 5-HT3AR–ALB, and 5-HT3AR–5-HT reveals a consistent directionality to the observed displacement in the extracellular domain. Insets zoom in on regions covering Loop C, Loop B, β1- β2 Loop, and the β6 - β7 Loop (Cys-Loop). The arrows indicate the direction of conformational change and the color codes highlight the movement going from Apo → PAL → SMP → ALB → 5HT. (B) Displacement of ECD β-sheets also tracks with ligand efficacy.

Extended Data Fig. 5 Positional differences of the binding pocket in pre-activated and open-like states.

(Left) Map and model alignments for comparison of the pre-activated and open-like states for A) SMP, B) ALB, and C) 5-HT. Only the ECD (residues 7–220) and the corresponding map densities were used for alignment, with map contour levels set to approximate equivalent visible map volumes (Phenix). (Right) Moments of inertia calculated for each model after alignment, which includes the ligand and surrounding binding pocket residues (Trp63, Tyr64, Arg65, Trp156, Arg169, Asp202). The vectors (\({\overrightarrow{I}}_{1}\), \({\overrightarrow{I}}_{2}\), \({\overrightarrow{I}}_{3}\)) originate from the center of mass of the combined ligand and binding pocket, are scaled to the size of the binding pocket, and point in the direction of the principle axes of inertia. For each ligand, in comparison to the pre-activated state, the open-like state shows a consistent clockwise rotation (top-down perspective) and upward tilt (side-perspective) of the ligand and binding pocket, indicated by arrows in the density map comparisons and the orientation of the principle axes of inertia vectors. Quantification of this rotation is given as Euler angles (Ψ, Θ, Φ) for the rotation of the principle axes of inertia from the pre-activated to open-like conformations.

Extended Data Fig. 6 LigPlot diagrams for orthosteric ligands.

LigPlot+ diagrams displaying the hydrophobic and polar interactions between each orthosteric ligand and the surrounding binding pocket residues in the pre-activated (left) and open-like (right) conformations. Hydrophobic interactions are represented as curves with radiating lines, and polar interactions < 4 Å are represented as green dashed lines.

Extended Data Fig. 7 5-HT3AR–SMP pre-activated state heterogeneity analysis.

(A) A slice-through of pre-activated state maps for 5-HT3AR–SMP, 5-HT3AR–ALB, and 5-HT3AR–5-HT (left to right, respectively). Equivalent contour levels set for each map (Phenix). Position Leu260 (Leu9′) is shown in stick representation. Additional density, likely to represent an alternate subunit conformation in which the Leu260 side chain and backbone are rotated out of the pore, is marked by dotted circles. The pore-facing conformation is referred to as ‘Leu260-in’ and the alternate conformation is referred to as ‘Leu260-out’. (B) 395k particles contributing to the 5-HT3AR–SMP pre-activated conformation at 2.92 Å were subjected to iterative 3D classification with full signal, without image alignment (with τ = 50), and C1 symmetry while applying a monomer solvent mask. This resulted in a 36k particle subset which contained strong ‘Leu260-out’ density upon 3D refinement in C5 (3.20 Å). The strong L260-out particle subset was used for C5 symmetry expansion (36k x 5 = 180k monomer particles), followed by signal subtraction (discarding the signal outside of a loose monomer mask). The C5 symmetry-expanded, signal-subtracted particles were then subjected to iterative 3D classification as before, allowing the separation of ‘Leu260-in’ and ‘L260-out’ particle subsets. (C) 5-HT3AR–SMP pre-activated ‘L260-in’ (left) and ‘L260-out’ (middle) density maps, with a Leu260-in-vs-out alignment on the right showing their distinct orientations in relation to the channel pore (purple circles). The heterogeneity analysis is biased toward particles with ‘Leu260-out’ signal (cyan color) due to manual particle sorting. However, the resulting map when all the particles are included shows stronger signal for the ‘L260-in’ orientation (wheat color).

Extended Data Fig. 8 Binding pocket analyses from molecular dynamics simulations.

(A) SMP and ALB r.m.s.d. (2.19 ± 0.05 Å and 1.77 ± 0.02 Å, respectively). The ECD of each subunit was aligned onto the corresponding cryo-EM structure using the Cα’s of the helices and β-sheets as the alignment selection. The r.m.s.d. of the heavy atoms of the ligand was calculated with respect to the cryo-EM structure. (B) SMP and ALB distance to Trp156 (3.67 ± 0.04 Å and 3.45 ± 0.03 Å, respectively) over 100 ns M.D. simulations. Ligand to Trp156 distance measured from backbone carbonyl oxygen to bicyclic ring nitrogen. (C) Average number of water molecules present in the ligand binding pocket for SMP and ALB (5.54 ± 2.31 and 5.69 ± 2.33, respectively). Number of water molecules in the binding pocket defined as a count of water oxygen atoms within 3 Å of any ligand atom in each protomer per simulation frame. Average obtained over 100 ns of simulation sampled every 500 ps (n = 200). Error bars correspond to the standard deviation.

Extended Data Fig. 9 Electrostatic network of the complementary subunit.

(Left) Model representation of electrostatic interactions between Arg65-Asp42, Arg169-Asp42, Arg169-Asp177 and Arg169-ligand for (A) 5-HT3AR–SMP pre-activated, (B) 5-HT3AR–ALB pre-activated, and (C) 5-HT3AR–5-HT pre-activated. (Right) Distributions of the distance between residues Arg65-Asp42, Arg169-Asp42, Arg169-Asp177 and Arg169 and each ligand over 100 ns simulations. Distances were calculated as the minimum distance between the heavy polar atoms in the side chain of residues Asp42, Arg65, Arg169 or Asp177, as well as the heavy polar atoms in the side chain of residue Arg169 and the N1 atom of the compounds. (Bottom right) Alignment of SMP, ALB, and 5-HT electrostatic networks.

Extended Data Fig. 10 M1 helix movement during activation reveals lipidic binding site.

Alignment of the 5-HT3AR–5-HT pre-activated and open-like Cryo-EM density maps (left) and zoomed inset of the M1 helix region (right). A lipid-like density is observed only in the open-like conformation above Phe233.

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Felt, K., Stauffer, M., Salas-Estrada, L. et al. Structural basis for partial agonism in 5-HT3A receptors. Nat Struct Mol Biol 31, 598–609 (2024). https://doi.org/10.1038/s41594-023-01140-2

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