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Bottom-up design of Ca2+ channels from defined selectivity filter geometry

Nature volume 648, pages 468–476 (2025)Cite this article

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Abstract

Native ion channels play key roles in biological systems, and engineered versions are widely used as chemogenetic tools and in sensing devices1,2. Protein design has been harnessed to generate pore-containing transmembrane proteins, but the design of selectivity filters with precise arrangements of amino acid side chains specific for a target ion, a crucial feature of native ion channels3, has been constrained by the lack of methods for placing the metal-coordinating residues with atomic-level precision. Here we describe a bottom-up RFdiffusion-based approach to construct Ca2+ channels from defined selectivity filter residue geometries, and use this approach to design symmetric oligomeric channels with Ca2+ selectivity filters having different coordination numbers and different geometries at the entrance of a wider pore buttressed by multiple transmembrane helices. The designed channel proteins assemble into homogeneous pore-containing particles and, for both tetrameric and hexameric ion-coordinating configurations, patch-clamp experiments show that the designed channels have higher conductances for Ca2+ than for Na+ and other divalent ions (Sr2+ and Mg2+) that are eliminated after mutation of selectivity filter residues. Cryogenic electron microscopy indicates that the design method has high accuracy: the structure of the hexameric Ca2+ channel is nearly identical to that of the design model. Our bottom-up design approach now enables the testing of hypotheses relating filter geometry to ion selectivity by direct construction, and provides a roadmap for creating selective ion channels for a wide range of applications.

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Fig. 1: A general approach for designing Ca2+ channels from selectivity filter geometry.
Fig. 2: Biophysical characterization of designed Ca2+ channels.
Fig. 3: Ca2+ conduction by the designed channels.
Fig. 4: Ion selectivity of designed Ca2+ channels.
Fig. 5: Determination of selectivity filter geometry and function.

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Data availability

EM maps of CalC6_3 with DHR extensions have been deposited in the Electron Microscopy Data Bank (hexamer: EMD-47340; heptamer: EMD-47356). Cryo-EM structure files of CalC6_3 with DHR extensions have been deposited to the Protein Data Bank (hexamer: 9DZW; heptamer: 9E0H). Source data are provided with this paper.

Code availability

Example design scripts are available at https://github.com/ylliu15/2025_Ca_channel. Documentation for RFdiffusion is available at https://github.com/RosettaCommons/RFdiffusion. Documentation for ProteinMPNN is available at https://github.com/dauparas/ProteinMPNN. Documentation for LigandMPNN is available at https://github.com/dauparas/LigandMPNN. AlphaFold2 and AlphaFold3 used for filtering the designs are available at https://github.com/google-deepmind/alphafold and https://alphafoldserver.com/welcome, respectively.

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Acknowledgements

We thank G. R. Lee, N. Hanikel, D. Juergens, C. Xu, G. Wisedchaisri, M. Lenaeus, L. Wang for helpful discussions; D. Feldman for support in lentivirus preparation and transduction; D. E. Clapham and R. E. Hulse for invaluable advice on channel biophysical characterization and comments on the manuscript; E. Navaluna, M. Ahlrichs, S. Cheng, C. Dobbins, for support in tissue culture; J. Quispe and S. Dickinson for management of the Arnold and Mabel Beckman Cryo-EM Center at the University of Washington and the cryo-EM facility at HHMI Janelia Research Campus for cryo-EM usage; and K. VanWormer, L. Goldschmidt and J. Li for general technical support. This research was supported by the Audacious Project at the Institute for Protein Design (Y.L., T.Y., K.D.C., R.D.K. and D.B.), National Institutes of Health research grant R01 HL112808 (W.A.C.), the Air Force Office of Scientific Research under award number FA9550-22-1-0506 (Y.L., L.M., S.M. and D.B.), US Department of Energy (DOE) under award number DE-SC0018940 (Y.L., S.M., R.D.K. and D.B.), Wu Tsai Protein Innovation Fund (Y.L. and T.Y.), Bill and Melinda Gates Foundation Cores and INV-043758 (K.D.C., C.W. and A.J.B.), grant R01AG063845 from the National Institutes of Health’s National Institute on Aging (A.J.B.), the Open Philanthropy Project Improving Protein Design Fund (K.D.C.), Alexandria Venture Investments Translational Investigator Fund (R.D.K), Nan Fung Life Sciences Translational Investigator Fund (R.D.K), BASF Corporation (L.M.), the HHMI Helen Hay Whitney Fellowship (L.M.), and the Howard Hughes Medical Institute (L.M and D.B.). We would also like to express our sadness on the passing of W. A. Catterall, who provided invaluable guidance and inspiration for this work.

Author information

Author notes

  1. Deceased: William A. Catterall

Authors and Affiliations

  1. Department of Biochemistry, University of Washington, Seattle, WA, USA

    Yulai Liu, Connor Weidle, Ljubica Mihaljević, Joseph L. Watson, Zhe Li, Le Tracy Yu, Sagardip Majumder, Andrew J. Borst, Kenneth D. Carr, Ryan D. Kibler & David Baker

  2. Institute for Protein Design, University of Washington, Seattle, WA, USA

    Yulai Liu, Connor Weidle, Ljubica Mihaljević, Joseph L. Watson, Zhe Li, Le Tracy Yu, Sagardip Majumder, Andrew J. Borst, Kenneth D. Carr, Ryan D. Kibler & David Baker

  3. Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, USA

    Yulai Liu

  4. Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA

    Ljubica Mihaljević & David Baker

  5. Department of Pharmacology, University of Washington, Seattle, WA, USA

    Tamer M. Gamal El-Din & William A. Catterall

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Contributions

This study was conceptualized by Y.L. and D.B. The methodology, including computational design, was developed by Y.L., L.M., J.L.W., S.M. and R.D.K. Experimental investigation and characterization were carried out by Y.L., C.W., L.M., Z.L., L.T.Y., A.J.B. and K.D.C. Data curation and formal analysis were performed by Y.L., C.W., L.M., Z.L., L.T.Y., A.J.B. and K.D.C. This study was supervised by D.B., T.M.G.E.-D. and W.A.C. The original draft of the manuscript was written by Y.L. and D.B. All authors contributed to the review and editing of the manuscript.

Corresponding author

Correspondence to David Baker.

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Extended data figures and tables

Extended Data Fig. 1 Examples of AlphaFold2-predicted structures of designed Ca2+channels with pTM scores higher than 0.8.

a, Designs with C4 symmetry. b, Designs with C6 symmetry.

Extended Data Fig. 2 Flux assay in HEK293T cells using Fura-2 AM.

a-b (cyan), c-d (blue), and e-f (red) were data for CalC4, CalC6, CalC6_H designs, respectively. Ba2+ ions were added at the 900-s time point indicated by the vertical dashed lines. The gray traces represented measurements from mock-transduced cells as the negative control and were overlaid with the colored traces representing the cells transduced with the designs in each plot for comparison. b, d and f were close-up views of the plots highlighted by the red dashed frames in a, c and e, respectively, which were examples that were identified as the putative designs manifesting divalent ion permeability.

Extended Data Fig. 3 Biophysical characterizations of more designed channels.

In addition to the three designs shown in Fig. 2, two more CalC4 designs, CalC4_1 (a) and CalC4_4 (b), one more CalC6 design, CalC6_7 (c), and three more CalC6_H designs, CalC6_H1 (d), CalC6_H13 (e), and CalC6_H21 (f), were observed to elute as desired oligomeric states from SEC and assemble into homogeneous pore-containing particles on the ns-EM grids. The close-up views shown on the upper right corners of the ns-EM micrographs corresponded to the regions highlighted by the dashed yellow frames. Scale bars, 100 nm.

Extended Data Fig. 4 Circular dichroism results of CalC4_24 (a-b), CalC6_3 (c-d), and CalC6_H4 (e-f).

a, c, and e, CD spectra at 25 °C (cyan lines), 95 °C (red lines), and cooled back to 25 °C (black lines). b, d, and f, CD melting curves at 222 nm.

Extended Data Fig. 5 Comparison between three representative designed channels and native channels, as well as the closest structures in the PDB (by Foldseek).

CalC4_24 was compared with TRPV6 (PDB 6BO8), CalC6_3 was compared with Orai (PDB 7KR5), and CalC6_H4 was compared with connexin 26 (PDB 2ZW3) from the top (a, d, and g) and the side view (b, e, and h), respectively. c, f, and i, Overlay of CalC4_24 (c), CalC6_3 (f), and CalC6_H (i) and their closest structures in the PDB (3zci in c, TM Score=0.35; 8d9p in f, TM Score=0.48; 6z0c in i, TM Score=0.41).

Extended Data Fig. 6 Predicted biophysical properties of designed channels.

a-d, AlphaFold3-predicted binding of CalC6_3 and CalC4_24 to Ca2+ (a and b) and to Mg2+ (c and d), respectively. The models were colored based on the confidence level (pLDDT) of the prediction results, with the color gradient shown on the bottom right. e and f, calculated electrostatic potential of the protein surfaces and the ion permeation pathways of CalC6_3 (e) and CalC4_24 (f). For clarity only the opposing chains of the designed channels are shown. The ion permeation pathways are calculated using MoleOnline. The electrostatic potential is calculated using the Adaptive Poisson-Boltzmann Solver (APBS) in PyMOL.

Extended Data Fig. 7 Additional characterizations of designs and negative controls.

a, An example of I-V curve plot demonstrating the data processing method. The black curve represented the raw data obtained from a − 100 mV to +100 mV ramp protocol in 10 mM [Ca2+] solution. The gray curve represented the raw data obtained using the same ramp protocol in 0.02 mM [Ca2+] solution, and was defined as the background. The blue curve was obtained by subtracting the gray curve from the black curve, and was defined as the Ca2+ conductance. The same process was used to determine conductances for other ions as well. b, Expression of designs in Hi5 cells examined by western blot using an anti-His antibody. The four samples loaded on the gel (lanes indicated by the black bars) were whole-cell lysates of cells expressing CalC6_3 and CalC4_24, cells infected with the control virus (made from an empty pFastBac_Dual vector), and uninfected cells alone. c, The time course of currents at −100 mV in 10 mM [Ca2+] and 40 mM [Na+] extracellular solutions recorded on cells infected with the control virus. d, I-V relations obtained from a − 100 mV to +100 mV ramp protocol in 10 mM [Ca2+] (cyan) and 40 mM [Na+] (red) solutions, averaged over three separate cells infected with the control virus. The shaded regions represent bootstrapped 95% confidence intervals. e-h, Comparison of Ca2+ current densities elicited by the voltage step protocol in the 10 mM [Ca2+] extracellular solution between the designs and the negative control (without subtraction of background leak currents). e, The schematic illustration of the voltage step protocol (also shown in Fig. 3). f and g, Current densities obtained from the cells expressing CalC4_24 (f) and CalC6_3 (g). The source data are the same as those shown in Fig. 3e and f. Here, the currents are normalized by cell capacitances to obtain current densities. h, Current densities obtained from the cell treated with the control virus.

Extended Data Fig. 8 Cryo-EM micrographs and 2D averages for CalC6_3 before and after DHR extensions.

a-d, Design model (a), a representative cryo-EM micrograph of protein particles on a lacey carbon grid (b), and 2D class averages (c-d) from three different 2D classification settings, with an extraction box size of 300 pixels used in c and an extraction box size of 680 pixels (pixel size 0.4135 Å) used in d. e-i, Design model (e) and cryo-EM data (f-i) for CalC6 with DHR extensions. f and h, Representative cryo-EM micrographs of protein particles on a thin carbon grid (f) and a holey carbon grid (h), respectively. g and i, 2D class averages from the thin carbon grid (g) and from the holey carbon grid (h), respectively. Scale bars in the micrographs, 100 nm. Scale bars in c, 10 nm. Scale bar in d, 23 nm. Scale bars in i, 12 nm.

Extended Data Fig. 9 Workflow for cryo-EM data processing of the CalC6_3 design with DHR extensions.

The flowchart demonstrated particle picking, classification, reconstruction and refinement processes that enabled determination of both a hexamer and a heptamer structure. All data processing steps were carried out in CryoSPARC v4.4. Detailed processes can be found in Methods (2.11 and 2.12).

Extended Data Fig. 10 NFAT-RE-luciferase expression assay.

a, Schematic diagram of the assay. Ca2+ influx through the designed channel in HEK293T cells would induce expression of the luciferase reporter through the Ca2+-dependent NFAT signaling pathway. b and c, Bar plots showing the average maximum luminescence intensity measured from cells (n = 3) expressing the wild-type CalC6_3 design (cyan), the E101L mutant (yellow), and the negative control (purple), respectively. The channel constructs contain a C-terminal mScarlet3 linked to the channel via the P2A self-cleaving sequence. The psPAX2 plasmid, which expresses proteins unrelated to Ca2+ flux or buffering, was used as the negative control. b, Raw luminescence intensity. c, Luminescence intensity normalized by mScarlet3 fluorescence. Error bars represent bootstrapped 95% confidence intervals around the mean.

Extended Data Table 1 Cryo-EM data collection and processing parameters for CalC6_3 with DHR extension domains
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Liu, Y., Weidle, C., Mihaljević, L. et al. Bottom-up design of Ca2+ channels from defined selectivity filter geometry. Nature 648, 468–476 (2025). https://doi.org/10.1038/s41586-025-09646-z

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