Kaupp, U. B. & Seifert, R. Molecular diversity of pacemaker ion channels. Annu. Rev. Physiol. 63, 235–257 (2001).
DiFrancesco, D. Pacemaker mechanisms in cardiac tissue. Annu. Rev. Physiol. 55, 455–472 (1993).
Biel, M., Wahl-Schott, C., Michalakis, S. & Zong, X. Hyperpolarization-activated cation channels: from genes to function. Physiol. Rev. 89, 847–885 (2009).
Tibbs, G. R. et al. An anchor-tether ‘hindered’ HCN1 inhibitor is antihyperalgesic in a rat spared nerve injury neuropathic pain model. Br. J. Anaesth. 131, 745–763 (2023).
Bleakley, L. E. et al. Cation leak underlies neuronal excitability in an HCN1 developmental and epileptic encephalopathy. Brain 144, 2060–2073 (2021).
Lyashchenko, A. K., Redd, K. J., Yang, J. & Tibbs, G. R. Propofol inhibits HCN1 pacemaker channels by selective association with the closed states of the membrane embedded channel core. J. Physiol. 583, 37–56 (2007).
Poduri, A. HCN1 gain-of-function mutations—a new cause of epileptic encephalopathy. Epilepsy Curr. 14, 348–349 (2014).
Marini, C. et al. HCN1 mutation spectrum: from neonatal epileptic encephalopathy to benign generalized epilepsy and beyond. Brain 141, 3160–3178 (2018).
Lee, C. H. & MacKinnon, R. Structures of the human HCN1 hyperpolarization-activated channel. Cell 168, 111–120 e111 (2017).
Lee, C. H. & MacKinnon, R. Voltage sensor movements during hyperpolarization in the HCN channel. Cell 179, 1582–1589 e1587 (2019).
Mannikko, R., Elinder, F. & Larsson, H. P. Voltage-sensing mechanism is conserved among ion channels gated by opposite voltages. Nature 419, 837–841 (2002).
Vemana, S., Pandey, S. & Larsson, H. P. S4 movement in a mammalian HCN channel. J. Gen. Physiol. 123, 21–32 (2004).
Wu, X., Cunningham, K. P., Ramentol, R., Perez, M. E. & Larsson, H. P. Similar voltage-sensor movement in spHCN channels can cause closing, opening, or inactivation. J. Gen. Physiol. 155, e202213170 (2023).
Mandala, V. S. & MacKinnon, R. Voltage-sensor movements in the Eag Kv channel under an applied electric field. Proc. Natl Acad. Sci. USA 119, e2214151119 (2022).
Whicher, J. R. & MacKinnon, R. Structure of the voltage-gated K+ channel Eag1 reveals an alternative voltage sensing mechanism. Science 353, 664–669 (2016).
Kim, D. M. & Nimigean, C. M. Voltage-gated potassium channels: a structural examination of selectivity and gating. Cold Spring Harb. Perspect. Biol. 8, a029231 (2016).
Dai, G., Aman, T. K., DiMaio, F. & Zagotta, W. N. The HCN channel voltage sensor undergoes a large downward motion during hyperpolarization. Nat. Struct. Mol. Biol. 26, 686–694 (2019).
Wu, X., Ramentol, R., Perez, M. E., Noskov, S. Y. & Larsson, H. P. A second S4 movement opens hyperpolarization-activated HCN channels. Proc. Natl Acad. Sci. USA 118, e2102036118 (2021).
Lu, Z., Klem, A. M. & Ramu, Y. Coupling between voltage sensors and activation gate in voltage-gated K+ channels. J. Gen. Physiol. 120, 663–676 (2002).
Long, S. B., Campbell, E. B. & Mackinnon, R. Voltage sensor of Kv1.2: structural basis of electromechanical coupling. Science 309, 903–908 (2005).
Lorinczi, E. et al. Voltage-dependent gating of KCNH potassium channels lacking a covalent link between voltage-sensing and pore domains. Nat. Commun. 6, 6672 (2015).
Fernandez-Marino, A. I., Harpole, T. J., Oelstrom, K., Delemotte, L. & Chanda, B. Gating interaction maps reveal a noncanonical electromechanical coupling mode in the Shaker K+ channel. Nat. Struct. Mol. Biol. 25, 320–326 (2018).
de la Pena, P., Dominguez, P. & Barros, F. Gating mechanism of Kv11.1 (hERG) K+ channels without covalent connection between voltage sensor and pore domains. Pflugers Arch. 470, 517–536 (2018).
Flynn, G. E. & Zagotta, W. N. Insights into the molecular mechanism for hyperpolarization-dependent activation of HCN channels. Proc. Natl Acad. Sci. USA 115, E8086–E8095 (2018).
Cowgill, J. & Chanda, B. Mapping electromechanical coupling pathways in voltage-gated ion channels: challenges and the way forward. J. Mol. Biol. 433, 167104 (2021).
Rivolta, I., Binda, A., Masi, A. & DiFrancesco, J. C. Cardiac and neuronal HCN channelopathies. Pflugers Arch. 472, 931–951 (2020).
Butler, K. M., da Silva, C., Alexander, J. J., Hegde, M. & Escayg, A. Diagnostic yield from 339 epilepsy patients screened on a clinical gene panel. Pediatr. Neurol. 77, 61–66 (2017).
Bleakley, L. E. & Reid, C. A. HCN1 epilepsy: from genetics and mechanisms to precision therapies. J. Neurochem. https://doi.org/10.1111/jnc.15928 (2023).
Thollon, C. et al. Use-dependent inhibition of hHCN4 by ivabradine and relationship with reduction in pacemaker activity. Br. J. Pharmacol. 150, 37–46 (2007).
Lu, X., Smaill, J. B. & Ding, K. New promise and opportunities for allosteric kinase inhibitors. Angew. Chem. Int. Ed. Engl. 59, 13764–13776 (2020).
Kim, E. D. et al. Allosteric drug discrimination is coupled to mechanochemical changes in the kinesin-5 motor core. J. Biol. Chem. 285, 18650–18661 (2010).
Zhu, S. et al. Structural and dynamic mechanisms of GABAA receptor modulators with opposing activities. Nat. Commun. 13, 4582 (2022).
Ramirez, D., Zuniga, R., Concha, G. & Zuniga, L. HCN channels: new therapeutic targets for pain treatment. Molecules 23, 2094 (2018).
Cacheaux, L. P. et al. Impairment of hyperpolarization-activated, cyclic nucleotide-gated channel function by the intravenous general anesthetic propofol. J. Pharmacol. Exp. Ther. 315, 517–525 (2005).
Saponaro, A. et al. Gating movements and ion permeation in HCN4 pacemaker channels. Mol. Cell 81, 2929–2943 e2926 (2021).
Tanguay, J., Callahan, K. M. & D’Avanzo, N. Characterization of drug binding within the HCN1 channel pore. Sci. Rep. 9, 465 (2019).
Faulkner, C., Santos-Carballal, D., Plant, D. F. & de Leeuw, N. H. Atomistic molecular dynamics simulations of propofol and fentanyl in phosphatidylcholine lipid bilayers. ACS Omega 5, 14340–14353 (2020).
Joyce, R. L. et al. Alkylphenol inverse agonists of HCN1 gating: H-bond propensity, ring saturation and adduct geometry differentially determine efficacy and potency. Biochem. Pharmacol. 163, 493–508 (2019).
Shintre, C. et al. Human hyperpolarization activated cyclic nucleotide gated ion channel 4. Zenodo https://doi.org/10.5281/zenodo.1434068 (2018).
Schmidpeter, P. A. M. et al. Anionic lipids unlock the gates of select ion channels in the pacemaker family. Nat. Struct. Mol. Biol. 29, 1092–1100 (2022).
Hung, A. et al. Biophysical analysis of an HCN1 epilepsy variant suggests a critical role for S5 helix Met-305 in voltage sensor to pore domain coupling. Prog. Biophys. Mol. Biol. 166, 156–172 (2021).
Ludwig, A., Zong, X., Jeglitsch, M., Hofmann, F. & Biel, M. A family of hyperpolarization-activated mammalian cation channels. Nature 393, 587–591 (1998).
Decher, N., Chen, J. & Sanguinetti, M. C. Voltage-dependent gating of hyperpolarization-activated, cyclic nucleotide-gated pacemaker channels: molecular coupling between the S4-S5 and C-linkers. J. Biol. Chem. 279, 13859–13865 (2004).
Flynn, G. E. & Zagotta, W. N. Molecular mechanism underlying phosphatidylinositol 4,5-bisphosphate-induced inhibition of SpIH channels. J. Biol. Chem. 286, 15535–15542 (2011).
Bruening-Wright, A., Elinder, F. & Larsson, H. P. Kinetic relationship between the voltage sensor and the activation gate in spHCN channels. J. Gen. Physiol. 130, 71–81 (2007).
Ramentol, R., Perez, M. E. & Larsson, H. P. Gating mechanism of hyperpolarization-activated HCN pacemaker channels. Nat. Commun. 11, 1419 (2020).
Valley, C. C. et al. The methionine-aromatic motif plays a unique role in stabilizing protein structure. J. Biol. Chem. 287, 34979–34991 (2012).
Ryu, S. & Yellen, G. Charge movement in gating-locked HCN channels reveals weak coupling of voltage sensors and gate. J. Gen. Physiol. 140, 469–479 (2012).
Porro, A. et al. Do the functional properties of HCN1 mutants correlate with the clinical features in epileptic patients? Prog. Biophys. Mol. Biol. 166, 147–155 (2021).
Boonsimma, P. et al. Exome sequencing as first-tier genetic testing in infantile-onset pharmacoresistant epilepsy: diagnostic yield and treatment impact. Eur. J. Hum. Genet. 31, 179–187 (2023).
Kim, J. J. et al. Shared structural mechanisms of general anaesthetics and benzodiazepines. Nature 585, 303–308 (2020).
Zivanov, J., Nakane, T. & Scheres, S. H. W. Estimation of high-order aberrations and anisotropic magnification from cryo-EM data sets in RELION-3.1. IUCrJ 7, 253–267 (2020).
Zivanov, J. et al. New tools for automated high-resolution cryo-EM structure determination in RELION-3. eLife 7, e42166 (2018).
Kimanius, D., Dong, L., Sharov, G., Nakane, T. & Scheres, S. H. W. New tools for automated cryo-EM single-particle analysis in RELION-4.0. Biochem. J. 478, 4169–4185 (2021).
Zheng, S. Q. et al. MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat. Methods 14, 331–332 (2017).
Wagner, T. et al. SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM. Commun. Biol. 2, 218 (2019).
Sanchez-Garcia, R. et al. DeepEMhancer: a deep learning solution for cryo-EM volume post-processing. Commun. Biol. 4, 874 (2021).
Liebschner, D. et al. Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix. Acta Crystallogr. D Struct. Biol. 75, 861–877 (2019).
Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and development of Coot. Acta Crystallogr. D Biol. Crystallogr. 66, 486–501 (2010).
Casanal, A., Lohkamp, B. & Emsley, P. Current developments in Coot for macromolecular model building of electron cryo-microscopy and crystallographic data. Protein Sci. 29, 1069–1078 (2020).
Croll, T. I. ISOLDE: a physically realistic environment for model building into low-resolution electron-density maps. Acta Crystallogr. D Struct. Biol. 74, 519–530 (2018).
Pettersen, E. F. et al. UCSF ChimeraX: structure visualization for researchers, educators, and developers. Protein Sci. 30, 70–82 (2021).
Smart, O. S., Neduvelil, J. G., Wang, X., Wallace, B. A. & Sansom, M. S. HOLE: a program for the analysis of the pore dimensions of ion channel structural models. J. Mol. Graph. 14, 354–360 (1996).
Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).
Liu, Y. et al. CB-Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting. Nucleic Acids Res. 50, W159–W164 (2022).
Wang, S., Xie, J., Pei, J. & Lai, L. CavityPlus 2022 update: an integrated platform for comprehensive protein cavity detection and property analyses with user-friendly tools and cavity databases. J. Mol. Biol. 435, 168141 (2023).
Maglic, J. B. & Lavendomme, R. MoloVol: an easy-to-use program for analyzing cavities, volumes and surface areas of chemical structures. J. Appl. Crystallogr. 55, 1033–1044 (2022).
Laskowski, R. A. & Swindells, M. B. LigPlot+: multiple ligand-protein interaction diagrams for drug discovery. J. Chem. Inf. Model. 51, 2778–2786 (2011).
Jubb, H. C. et al. Arpeggio: a web server for calculating and visualising interatomic interactions in protein structures. J. Mol. Biol. 429, 365–371 (2017).
Procter, J. B. et al. Alignment of biological sequences with Jalview. Methods Mol. Biol. 2231, 203–224 (2021).
Webb, B. & Sali, A. Comparative protein structure modeling using MODELLER. Curr. Protoc. Bioinformatics 54, 5.6.1–5.6.37 (2016).
Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996).
Wu, E. L. et al. CHARMM-GUI Membrane Builder toward realistic biological membrane simulations. J. Comput. Chem. 35, 1997–2004 (2014).
Kasimova, M. A. et al. Helix breaking transition in the S4 of HCN channel is critical for hyperpolarization-dependent gating. eLife 8, e53400 (2019).
Elbahnsi, A. et al. Interplay between VSD, pore, and membrane lipids in electromechanical coupling in HCN channels. eLife 12, e80303 (2023).
Best, R. B. et al. Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone ɸ, ψ and side-chain χ1 and χ2 dihedral angles. J. Chem. Theory Comput. 8, 3257–3273 (2012).
Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W. & Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926–935 (1983).
Arcario, M. J., Mayne, C. G. & Tajkhorshid, E. Atomistic models of general anesthetics for use in in silico biological studies. J. Phys. Chem. B 118, 12075–12086 (2014).
Olsson, M. H., Sondergaard, C. R., Rostkowski, M. & Jensen, J. H. PROPKA3: consistent treatment of internal and surface residues in empirical pKa predictions. J. Chem. Theory Comput. 7, 525–537 (2011).
Abraham, M. J. et al. GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1-2, 19–25 (2015).
Tribello, G. A., Bonomi, M., Branduardi, D., Camilloni, C. & Bussi, G. PLUMED 2: new feathers for an old bird. Comput. Phys. Commun. 185, 604–613 (2014).
Darden, T. A., York, D. M. & Pedersen, L. G. Particle mesh Ewald: an N⋅log(N) method for Ewald sums in large systems. J. Chem. Phys. 98, 10089–10092 (1993).
Hess, B., Bekker, H., Berendsen, H. J. C. & Fraaije, J. G. E. M. LINCS: a linear constraint solver for molecular simulations. J. Comput. Chem. 18, 1463–1472 (1997).
Kim, E. D. et al. Propofol rescues voltage-dependent gating of HCN1 channel epilepsy mutants. Zenodo https://doi.org/10.5281/zenodo.11528212 (2024).
