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  • Open Access

Improved Anisotropic Network Models for Membrane Protein Dynamics and Mechanosensitive Ion Channels

Zhongjie Han, Lei Wang, and Chen Song*

  • Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China

  • *Contact author: c.song@pku.edu.cn
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PRX Life 4, 013025 – Published 27 February, 2026

DOI: https://doi.org/10.1103/xc5f-xr7n

Abstract

Mechanosensitive (MS) ion channels are crucial for translating mechanical stimuli into cellular responses; however, their dynamic properties pose significant challenges for experimental investigations. This study introduces two enhanced anisotropic network models (ANMs) that incorporate membrane contact probability (MCP) to more effectively capture the influence of the cell membrane on protein dynamics. MCP-ANM and MCP-multiscale ANM (mANM) outperform traditional ANM models that do not explicitly consider membranes when predicting the flexibility of various types of membrane proteins. Furthermore, by integrating MCP-mANM with perturbation response scanning, we are able to efficiently simulate the conformational changes of MS proteins subjected to different mechanical forces. This methodology allows for the examination of various gating mechanisms, including force-from-lipids and force-from-tether, across multiple MS ion channels such as no mechanoreceptor potential C, mechanosensitive channel of small conductance, and Piezo-type mechanosensitive ion channel. The calculated mechanosensitivity of the MS channels aligns well with the experimental findings. These results demonstrate the effectiveness of MCP-incorporated ANM in linking mechanical stimuli to protein dynamics, providing a reliable and efficient framework for understanding the mechanotransduction and gating mechanisms of MS ion channels.

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References (68)

  1. J. Kefauver, A. Ward, and A. Patapoutian, Discoveries in structure and physiology of mechanically activated ion channels, Nature (London) 587, 567 (2020).
  2. P. Jin, L. Jan, and Y. Jan, Mechanosensitive ion channels: Structural features relevant to mechanotransduction mechanisms, Annu. Rev. Neurosci. 43, 207 (2020).
  3. C. Cheng, V. Deivasikamani, D. J. Beech, and P. Sukumar, Association of Piezo1 variants with hypertension in UK Biobank participants, Circulation 140, A14307 (2019).
  4. Y. Wan, J. Zhou, and H. Li, The role of mechanosensitive Piezo channels in chronic pain, J. Pain Res. 17, 4199 (2024).
  5. L. Qin, T. He, S. Chen, D. Yang, W. Yi, H. Cao, and G. Xiao, Roles of mechanosensitive channel Piezo1/2 proteins in skeleton and other tissues, Bone Res. 9, 44 (2021).
  6. J. Richardson, A. Kotevski, and K. Poole, From stretch to deflection: The importance of context in the activation of mammalian, mechanically activated ion channels, FEBS J. 289, 4447 (2022).
  7. C. Vénien-Bryan, Z. Li, L. Vuillard, and J. Boutin, Cryo-electron microscopy and X-ray crystallography: Complementary approaches to structural biology and drug discovery, Acta Cryst. F 73, 174 (2017).
  8. S. A. Hollingsworth and R. O. Dror, Molecular dynamics simulation for all, Neuron 99, 1129 (2018).
  9. B. Reddy, N. Bavi, A. Lu, Y. Park, and E. Perozo, Molecular basis of force-from-lipids gating in the mechanosensitive channel MscS, eLife 8, e50486 (2019).
  10. M. Britt, E. Moller, J. Maramba, A. Anishkin, and S. Sukharev, MscS inactivation and recovery are slow voltage-dependent processes sensitive to interactions with lipids, Biophys. J. 123, 195 (2024).
  11. O. N. Rogacheva and W. Kopec, Asymmetric nature of MscL opening revealed by molecular dynamics simulations, J. Chem. Inf. Model. 65, 6129 (2025).
  12. M. V. Clausen, Y. Chen, and M. A. Hedegaard, Others atomistic mechanism of coupling between cytosolic sensor domain and selectivity filter in TREK K2P channels, Nat. Commun. 15, 1541 (2024).
  13. M. Zhang, D. Wang, Y. Kang, J.-X. Wu, F. Yao, C. Pan, Z. Yan, C. Song, and L. Chen, Structure of the mechanosensitive OSCA channels, Nat. Struct. Mol. Biol. 25, 850 (2018).
  14. Y. Han, Z. Zhou, and R. Jin, Others mechanical activation opens a lipid-lined pore in OSCA ion channels, Nature (London) 628, 910 (2024).
  15. Y. Wang, Y. Guo, G. Li, C. Liu, L. Wang, A. Zhang, Z. Yan, and C. Song, The push-to-open mechanism of the tethered mechanosensitive ion channel NompC, eLife 10, e58388 (2021).
  16. J. Duan and C. Song, Twist is the key to the gating of mechanosensitive ion channel NOMPC, eLife 13, RP102941 (2024).
  17. A. Buyan, C. D. Cox, J. Barnoud, J. Li, H. S. Chan, B. Martinac, S. J. Marrink, and B. Corry, Piezo1 forms specific, functionally important interactions with phosphoinositides and cholesterol, Biophys. J. 119, 1683 (2020).
  18. W. Jiang, J. S. D. Rosario, and W. Botello-Smith, Others crowding-induced opening of the mechanosensitive Piezo1 channel in silico, Commun. Biol. 4, 84 (2021).
  19. W. Jiang, T. D. Wijerathne, and H. Zhang, Others structural and thermodynamic framework for PIEZO1 modulation by small molecules, Proc. Natl. Acad. Sci. USA 120, e2310933120 (2023).
  20. M. Tirion, Large amplitude elastic motions in proteins from a single-parameter, atomic analysis, Phys. Rev. Lett. 77, 1905 (1996).
  21. L. Yang, G. Song, and R. Jernigan, How well can we understand large-scale protein motions using normal modes of elastic network models?, Biophys. J. 93, 920 (2007).
  22. A. R. Atilgan, S. R. Durell, R. L. Jernigan, M. C. Demirel, O. Keskin, and I. Bahar, Anisotropy of fluctuation dynamics of proteins with an elastic network model, Biophys. J. 80, 505 (2001).
  23. T. Lezon and I. Bahar, Constraints imposed by the membrane selectively guide the alternating access dynamics of the glutamate transporter GltPh, Biophys. J. 102, 1331 (2012).
  24. L. Wang, J. Zhang, D. Wang, and C. Song, Membrane contact probability: An essential and predictive character for the structural and functional studies of membrane proteins, PLoS Comput. Biol. 18, e1009972 (2022).
  25. L. Wang, K. Kang, and C. Song, ProtRAP-LM: Fast and accurate protein relative accessibility prediction and membrane protein screening through protein language model embeddings, bioRxiv 2025–01 (2025).
  26. C. Atilgan and A. Atilgan, Perturbation-response scanning reveals ligand entry-exit mechanisms of ferric binding protein, PLoS Comput. Biol. 5, e1000544 (2009).
  27. K. Xia, K. Opron, and G.-W. Wei, Multiscale Gaussian network model (mGNM) and multiscale anisotropic network model (mANM), J. Chem. Phys. 143, 194106 (2015).
  28. P. Stansfeld, J. Goose, M. Caffrey, E. Carpenter, J. Parker, S. Newstead, and M. Sansom, MemProtMD: Automated insertion of membrane protein structures into explicit lipid membranes, Structure 23, 1350 (2015).
  29. T. D. Newport, M. S. P. Sansom, and P. J. Stansfeld, The MemProtMD database: A resource for membrane-embedded protein structures and their lipid interactions, Nucl. Acids Res. 47, D390 (2019).
  30. P. Debye, Interference of x rays and heat movement, Ann. Phys. 348, 49 (1913).
  31. Z. Sun, Q. Liu, G. Qu, Y. Feng, and M. T. Reetz, Utility of B-factors in protein science: Interpreting rigidity, flexibility, and internal motion and engineering thermostability, Chem. Rev. 119, 1626 (2019).
  32. P. J. Bond, J. Holyoake, A. Ivetac, S. Khalid, and M. S. P. Sansom, Coarse-grained molecular dynamics simulations of membrane proteins and peptides, J. Struct. Biol. 157, 593 (2007).
  33. P. J. Loll, Membrane protein structural biology: The high throughput challenge, J. Struct. Biol. 185, 288 (2014).
  34. X. Robert, J. Kassis-Sahyoun, N. Ceres, J. Martin, M. R. Sawaya, R. J. Read, P. Gouet, P. Falson, and V. Chaptal, X-ray diffraction reveals the intrinsic difference in the physical properties of membrane and soluble proteins, Sci. Rep. 7, 17013 (2017).
  35. V. Zampieri, C. Hilpert, M. Garnier, Y. Gestin, S. Delolme, J. Martin, P. Falson, G. Launay, and V. Chaptal, The Det.Belt Server: A tool to visualize and estimate amphipathic solvent belts around membrane proteins, Membranes 11, 459 (2021).
  36. V. Chaptal, Quantification of detergents complexed with membrane proteins, Sci. Rep. 7, 41751 (2017).
  37. A. Wlodawer, Z. Dauter, B. T. Porebski, W. Minor, R. Stanfield, and M. Jaskolski, High-resolution cryo-EM maps and models: A crystallographer's perspective, Structure 26, 875 (2018).
  38. B. A. Barad, N. Echols, R. Wang, Y. Cheng, F. DiMaio, P. D. Adams, and J. S. Fraser, EMRinger: Side chain-directed model and map validation for 3D cryo-electron microscopy, Nat. Methods 12, 943 (2015).
  39. M. A. Herzik, M. S. Wu, and G. C. Lander, High-resolution structure determination of sub-100 kDa complexes using conventional cryo-EM, Nat. Commun. 10, 1032 (2019).
  40. See Supplemental Material at http://link.aps.org/supplemental/10.1103/xc5f-xr7n for additional statistical analyses, model details, quantitative validation of PRS-induced conformational changes, and Supplemental Figures and Tables.
  41. M. C. Lagerström and H. B. Schiöth, Structural diversity of G protein-coupled receptors and significance for drug discovery, Nat. Rev. Drug Discov. 7, 339 (2008).
  42. A. S. Hauser, M. M. Attwood, M. Rask-Andersen, H. B. Schiöth, and D. E. Gloriam, Trends in GPCR drug discovery: New agents, targets and indications, Nat. Rev. Drug Discov. 16, 829 (2017).
  43. B. Sorum, T. Docter, V. Panico, A. Rietmeijer, and S. Brohawn, Tension activation of mechanosensitive two-pore domain K channels TRAAK, TREK-1, and TREK-2, Nat. Commun. 15, 3142 (2024).
  44. D. A. Doyle, J. M. Cabral, R. A. Pfuetzner, A. Kuo, J. M. Gulbis, S. L. Cohen, B. T. Chait, and R. MacKinnon, The structure of the potassium channel: Molecular basis of K+ conduction and selectivity, Science 280, 69 (1998).
  45. A. C. Pan, L. G. Cuello, E. Perozo, and B. Roux, Thermodynamic coupling between activation and inactivation gating in potassium channels revealed by free energy molecular dynamics simulations, J. Gen. Physiol. 138, 571 (2011).
  46. R. B. Bass, P. Strop, M. Barclay, and D. C. Rees, Crystal structure of the Escherichia coli mechanosensitive channel of small conductance, MscS Sci. 298, 1582 (2002).
  47. Y. R. Guo and R. MacKinnon, Structure-based membrane dome mechanism for Piezo mechanosensitivity, eLife 6, e33660 (2017).
  48. I. Rowe, A. Anishkin, K. Kamaraju, and K. Yoshimura, The cytoplasmic cage domain of the mechanosensitive channel MscS is a sensor of macromolecular crowding, J. Gen. Physiol. 143, 543 (2014).
  49. Y. Zhang, C. Daday, R.-X. Gu, C. D. Cox, B. Martinac, B. L. de Groot, and T. Walz, Visualization of the mechanosensitive ion channel MscS under membrane tension, Nature (London) 590, 509 (2021).
  50. M. Sotomayor and K. Schulten, Molecular dynamics study of gating in the mechanosensitive channel MscL, Biophys. J. 87, 3050 (2004).
  51. B. Coste, A. Mathur, S. Schmidt, A. Mechioukhi, C. Delmas, and A. Patapoutian, Piezo1 and Piezo2 are essential components of distinct mechanically activated ion channels, Science 330, 55 (2010).
  52. J. Ge, W. Li, Q. Zhao, N. Li, M. Chen, P. Zhi, R. Li, N. Gao, B. Xiao, and M. Yang, Architecture of the mammalian mechanosensitive Piezo1 channel, Nature (London) 527, 64 (2015).
  53. K. Saotome, S. E. Murthy, J. M. Kefauver, T. Whitwam, A. Patapoutian, and A. B. Ward, Structure of the mechanically activated ion channel Piezo1, Nature (London) 554, 481 (2018).
  54. X. Yang, C. Lin, X. Chen, S. Li, X. Li, and B. Xiao, Structure deformation and curvature sensing of Piezo1 in lipid membranes, Nature (London) 604 377 (2022).
  55. T. Zhang, S. Chi, F. Jiang, Q. Zhao, and B. Xiao, Structure, kinetic properties and biological function of mechanosensitive Piezo channels, Cell Biosci. 11, 13 (2021).
  56. Y. C. Park, B. Reddy, N. Bavi, E. Perozo, and J. D. Faraldo-Gómez, State-specific morphological deformations of the lipid bilayer explain mechanosensitive gating of MscS ion channels, Structure 30, 1251 (2022).
  57. P. Jin, D. Bulkley, Y. Guo, W. Zhang, Z. Guo, W. Huynh, S. Wu, S. Meltzer, T. Cheng, L. Y. Jan, Y.-N. Jan, and Y. Cheng, Electron cryo-microscopy structure of the mechanotransduction channel NOMPC, Nature (London) 547, 118 (2017).
  58. D. Argudo, S. Capponi, N. P. Bethel, and M. Grabe, A multiscale model of mechanotransduction by the ankyrin chains of the NOMPC channel, J. Gen. Physiol. 151, 316 (2019).
  59. M. Van Kempen, S. S. Kim, C. Tumescheit, M. Mirdita, J. Lee, C. L. Gilchrist, J. Söding, and M. Steinegger, Fast and accurate protein structure search with Foldseek, Nat. Biotechnol. 42, 243 (2024).
  60. W. Kim, M. Mirdita, E. L. Karin, C. L. Gilchrist, H. Schweke, J. Söding, E. D. Levy, and M. Steinegger, Rapid and sensitive protein complex alignment with foldseek-multimer, Nat. Methods 22, 469 (2025).
  61. ProtRAP-LM: MCP predictor source code, https://github.com/ComputBiophys/ProtRAP-LM.
  62. ProtRAP-LM online computation server, http://www.songlab.cn/ProtRAP-LM/home/.
  63. F. Tama, F. J. Gadea, O. Marques, and Y. H. Sanejouand, Building-block approach for determining low-frequency normal modes of macromolecules, Proteins: Struct. Funct. Genet. 41, 1 (2000).
  64. M. Ikeguchi, J. Ueno, and M. Sato, Others protein structural change upon ligand binding: Linear response theory, Phys. Rev. Lett. 94, 078102 (2005).
  65. I. Bahar, A. R. Atilgan, and B. Erman, Direct evaluation of thermal fluctuations in proteins using a single-parameter harmonic potential, Fold. Des. 2, 173 (1997).
  66. T. R. Lezon, I. H. Shrivastava, Z. Yang, and I. Bahar, Elastic network models for biomolecular dynamics Theory andapplication to membrane proteins and viruses, Handbook on Biological Networks 10, 129 (2009).
  67. E. Eyal, L. W. Yang, and I. Bahar, Anisotropic network model: Systematic evaluation and a new web interface, Bioinformatics 22, 2619 (2006).
  68. MCP-ANM source code, https://github.com/ComputBiophys/MCP-ANM.

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PRX Life 4, 013025– Published 27 February, 2026
  • Received 18 June 2025
  • Accepted 23 January 2026
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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