Lau, C. et al. Never at rest: insights into the conformational dynamics of ion channels from cryo-electron microscopy. J. Physiol. 596, 1107 (2018).
Google Scholar
Clapham, D. E. TRP channels as cellular sensors. Nature 426, 517 (2003).
Google Scholar
Nilius B., Flockerzi V. Handbook of Experimental Pharmacology, 223 (Springer, 2014)
Morales-Lazaro, S. L., Lemus, L. & Rosenbaum, T. Regulation of thermoTRPs by lipids. Temperature 4, 24 (2017).
Google Scholar
Pumroy, R. A., Fluck, E. C., Ahmed, T. & Moiseenkova-Bell, V. Y. Structural insights into the gating mechanisms of TRPV channels. Cell Calcium 87, 102168 (2020).
Google Scholar
Lansky, S. et al. A pentameric TRPV3 channel with a dilated pore. Nature 621, 206 (2023).
Google Scholar
Rao, S. et al. Water and hydrophobic gates in ion channels and nanopores. Faraday Discuss. 209, 231 (2018).
Google Scholar
Huffer, K. E. et al. Global alignment and assessment of TRP channel transmembrane domain structures to explore functional mechanisms. eLife 9, 58660 (2020).
Google Scholar
Klesse, G., Rao, S., Sansom, M. S. P. & Tucker, S. J. CHAP: a versatile tool for the structural and functional annotation of ion channel pores. J. Mol. Biol. 431, 3353 (2019).
Google Scholar
Zubcevic, L. & Lee, S.-Y. The role of Ï-helices in TRP channel gating. Curr. Opin. Struct. Biol. 58, 314 (2019).
Google Scholar
McGoldrick, L. et al. Opening of the human epithelial calcium channel TRPV6. Nature 553, 233 (2018).
Google Scholar
Lubova, K. I. et al. Probing temperature and capsaicin-induced activation of TRPV1 channel via computationally guided point mutations in its pore and TRP domains. Int. J. Biol. Macromol. 158, 1175 (2020).
Google Scholar
Zheng, W. et al. Identification and characterization of hydrophobic gate residues in TRP channels. FASEB J. 32, 639â653 (2018).
Google Scholar
Zhang, K., Julius, D. & Cheng, Y. Structural snapshots of TRPV1 reveal mechanism of polymodal functionality. Cell 184, 1â13 (2021).
Google Scholar
Nadezhdin, K. D. et al. Structural mechanism of heat-induced opening of a temperature-sensitive TRP channel. Nat. Struct. Mol. Biol. 28, 564 (2021).
Google Scholar
Kasimova, M. A. et al. A hypothetical molecular mechanism for TRPV1 activation that invokes rotation of an S6 asparagine. J. Gen. Physiol. 150, 1554 (2018).
Google Scholar
Cao, E. Structural mechanisms of transient receptor potential ion channels. J. Gen. Physiol. 152, e201811998 (2020).
Google Scholar
Singh, A. K. et al. Structural basis of temperature sensation by the TRP channel TRPV3. Nat. Struct. Mol. Biol. 26, 994 (2019).
Google Scholar
Bhardwaj, R. et al. Inactivation-mimicking block of the epithelial calcium channel TRPV6. Sci. Adv. 6, 1508 (2020).
Google Scholar
Neuberger, A., Nadezhdin, K. D. & Sobolevsky, A. I. Structural mechanisms of TRPV6 inhibition by ruthenium red and econazole. Nat. Commun. 12, 6284 (2021).
Google Scholar
Efremov, R. G. Dynamic âmolecular portraitsâ of biomembranes drawn by their lateral nanoscale inhomogeneities. Int. J. Mol. Sci. 22, 6250 (2021).
Google Scholar
Efremov, R. G. et al. Molecular lipophilicity in protein modeling and drug design. Curr. Med. Chem. 14, 393 (2007).
Google Scholar
Koromyslova, A. D., Chugunov, A. O. & Efremov, R. G. Deciphering fine molecular details of proteinsâ structure and function with a Protein Surface Topography (PST) method. J. Chem. Inf. Model. 54, 1189 (2014).
Google Scholar
Chugunov, A. et al. Temperature-sensitive gating of TRPV1 channel as probed by atomistic simulations of its trans- and juxtamembrane domains. Sci. Rep. 6, 33112 (2016).
Google Scholar
Eisenberg, D., Lüthy, R. & Bowie, J. U. VERIFY3D: assessment of protein models with three-dimensional profiles. Methods Enzymol. 277, 396 (1997).
Google Scholar
Bowie, J. U., Lüthy, R. & Eisenberg, D. A method to identify protein sequences that fold into a known three-dimensional structure. Science 253, 164â170 (1991).
Google Scholar
Clapham, D. E. & Miller, C. A thermodynamic framework for understanding temperature sensing by transient receptor potential (TRP) channels. Proc. Natl Acad. Sci. USA 108, 19492 (2011).
Google Scholar
Nadezhdin, K. D. et al. TRPV3 activation by different agonists accompanied by lipid dissociation from the vanilloid site. Sci. Adv.10, eadn2453 (2024).
Google Scholar
Singh, A. K., McGoldrick, L. L. & Sobolevsky, A. I. Structure and gating mechanism of the transient receptor potential channel TRPV3. Nat. Struct. Mol. Biol. 25, 805 (2018).
Google Scholar
Deng, Z. et al. Gating of human TRPV3 in a lipid bilayer. Nat. Struct. Mol. Biol. 27, 635 (2020).
Google Scholar
Yonkunas, M. & Kurnikova, M. The hydrophobic effect contributes to the closed state of a simplified ion channel through a conserved hydrophobic patch at the pore-helix crossing. Front. Pharmacol. 6, 284 (2015).
Google Scholar
Nadezhdin, K. D. et al. Structure of human TRPV4 in complex with GTPase RhoA. Nat. Commun. 14, 3733 (2023).
Google Scholar
Nadezhdin, K. D. et al. Extracellular cap domain is an essential component of the TRPV1 gating mechanism. Nat. Commun. 12, 2154 (2021).
Google Scholar
Pumroy, R. A. et al. Molecular mechanism of TRPV2 channel modulation by cannabidiol. eLife 8, 48792 (2019).
Google Scholar
Pumroy, R. A. et al. Structural insights into TRPV2 activation by small molecules. Nat. Commun. 13, 2334 (2022).
Google Scholar
Dosey, T. L. et al. Structures of TRPV2 in distinct conformations provide insight into role of the pore turret. Nat. Struct. Mol. Biol. 26, 40 (2019).
Google Scholar
Zhen Su, N. et al. Structural mechanisms of TRPV2 modulation by endogenous and exogenous ligands. Nat. Chem. Biol. 19, 72 (2023).
Google Scholar
Kwon, D. H. et al. TRPV4-Rho GTPase complex structures reveal mechanisms of gating and disease. Nat. Commun. 14, 3732 (2023).
Google Scholar
Fluck, E. C., Yazici, A. T., Rohacs, T. & Moiseenkova-Bell, V. Y. Structural basis of TRPV5 regulation by physiological and pathophysiological modulators. Cell Rep. 39, 110737 (2022).
Google Scholar
Hughes, T. E. T. et al. Structural insights on TRPV5 gating by endogenous modulators. Nat. Commun. 9, 4198 (2018).
Google Scholar
Dang, S. et al. Structural insight into TRPV5 channel function and modulation. Proc. Natl Acad. Sci. USA 116, 8869 (2019).
Google Scholar
Neuberger, A. et al. Structural mechanism of human oncochannel TRPV6 inhibition by the natural phytoestrogen genistein. Nat. Commun. 14, 2659 (2023).
Google Scholar
Nordquist, E. B., Schultz, S. A. & Chen, J. Using metadynamics to explore the free energy of dewetting in biologically relevant nanopores. J. Phys. Chem. B 126, 6428 (2022).
Google Scholar
Trofimov, Y. A., Krylov, N. A. & Efremov, R. G. Confined dynamics of water in transmembrane pore of TRPV1 ion channel. Int J. Mol. Sci. 20, 4285 (2019).
Google Scholar
Kasimova, M. et al. Ion Channel sensing: are fluctuations the crux of the matter? J. Phys. Chem. Lett. 9, 1260 (2018).
Google Scholar
Trofimov Y. A., Minakov A. S., Krylov N. A., Efremov R. G. Structural mechanism of ionic conductivity of the TRPV1 channel. Dokl Biochem. Biophys. https://doi.org/10.1134/S1607672922600245 (2023)
Lee, C. H. & MacKinnon, R. Activation mechanism of a human SK-calmodulin channel complex elucidated by cryo-EM structures. Science 360, 508â513 (2018).
Google Scholar
Rohaim, A. et al. Open and closed structures of a barium-blocked potassium channel. J. Mol. Biol. 432, 4783â4798 (2020).
Google Scholar
Twomey, E. et al. Channel opening and gating mechanism in AMPA-subtype glutamate receptors. Nature 549, 60 (2017).
Google Scholar
Rao, S. et al. A heuristic derived from analysis of the ion channel structural proteome permits the rapid identification of hydrophobic gates. Proc. Natl Acad. Sci. USA 116, 13989 (2019).
Google Scholar
Lynch, C. I. et al. Water nanoconfined in a hydrophobic pore: molecular dynamics simulations of transmembrane protein 175 and the influence of water models. ACS Nano 15, 19098 (2021).
Google Scholar
Xenakis, M. N. et al. Cumulative hydropathic topology of a voltage-gated sodium channel at atomic resolution. Proteins 88, 1319 (2020).
Google Scholar
Marks, C. & Deane, C. M. Increasing the accuracy of protein loop structure prediction with evolutionary constraints. Bioinformatics 35, 2585 (2019).
Google Scholar
Jurrus, E. et al. Improvements to the APBS biomolecular solvation software suite. Prot. Sci. 27, 112 (2018).
Google Scholar
Abraham, M. J. et al. GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1, 19 (2015).
Google Scholar
Lindorff-Larsen, K. et al. Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins 8, 1950 (2010).
Google Scholar
Jorgensen, W. L. & Tirado-Rives, J. Potential energy functions for atomic-level simulations of water and organic and biomolecular systems. Proc. Natl Acad. Sci. USA 102, 6665 (2005).
Google Scholar
Hess, B., Bekker, H., Berendsen, H. J. C. & Fraaije, J. G. E. M. LINCS: a linear constraint solver for molecular simulations. J. Comp. Chem. 18, 1463 (1997).
Google Scholar
Darden, T., York, D. & Pedersen, L. Particle mesh Ewald: an Nâ log(N) method for Ewald sums in large systems. J. Chem. Phys. 98, 10089 (1993).
Google Scholar
Joung, I. S. & Cheatham, T. E. Determination of alkali and halide monovalent ion parameters for use in explicitly solvated biomolecular simulations. J. Phys. Chem. B 30, 9020 (2008).
Google Scholar
Li, P., Roberts, B. P., Chakravorty, D. K. & Merz, K. M. Jr. Rational design of particle mesh ewald compatible lennard-jones parameters for +2 metal cations in explicit solvent. J. Chem. Theory Comput. 9, 2733 (2013).
Google Scholar
Ghose, A. K., Viswanadhan, V. N. & Wendoloski, J. J. Prediction of hydrophobic (lipophilic) properties of small organic molecules using fragmental methods: an analysis of ALOGP and CLOGP methods. J. Phys. Chem. A 102, 3762 (1998).
Google Scholar
Wildman, S. A. & Crippen, G. M. Prediction of physicochemical parameters by atomic contributions. J. Chem. Inf. Comput. Sci. 39, 868 (1999).
Google Scholar
Amanatides J., Woo A. A fast voxel traversal algorithm for ray tracing. Eurographics https://doi.org/10.2312/egtp.19871000 (1987).
Goldstein, R. A. & Nagel, R. 3-D Visual simulation. Simulation 16, 25â31 (1971).
Google Scholar
Roth, S. D. Ray casting for modeling solids. Comp. Graph Im. Proc. 18, 109 (1982).
Google Scholar
Connolly, M. L. Analytical molecular surface calculation. J. Appl Cryst. 16, 548â558 (1983).
Google Scholar
Smart, O. S., Goodfellow, J. M. & Wallace, B. A. The pore dimensions of gramicidin A. Biophys. J. 65, 2455 (1993).
Google Scholar