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Monte Carlo modeling of the formation and organization of ion channel clustering.

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Title: Monte Carlo modeling of the formation and organization of ion channel clustering.
Authors: Moise N; Department of Biomedical Engineering, The Ohio State University, Columbus, Ohio, United States of America.; Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America., Weinberg SH; Department of Biomedical Engineering, The Ohio State University, Columbus, Ohio, United States of America.; Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America.
Source: PLoS computational biology [PLoS Comput Biol] 2026 Sep 17; Vol. 22 (9), pp. e1014791. Date of Electronic Publication: 2026 Sep 17 (Print Publication: 2026).
Publication Type: Journal Article
Language: English
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE
Imprint Name(s): Original Publication: San Francisco, CA : Public Library of Science, [2005]-
MeSH Terms: Ion Channels*/chemistry , Ion Channels*/metabolism , Ion Channels*/physiology , Ion Channel Gating*/physiology , Monte Carlo Method* , Models, Biological*, Cell Membrane/metabolism ; Cell Membrane/chemistry ; Computer Simulation ; Computational Biology ; Animals
Abstract: The spatial organization of ion channels on cell membranes critically influences many key physiological processes, such as cardiac and neuronal excitability and cellular signaling, yet the mechanisms governing channel clustering remain poorly understood. In this study, we present a stochastic computational framework that models the dynamic organization of ion channels through Monte Carlo simulations incorporating membrane insertion, removal, channel-channel interactions, and diffusion processes. Our model reveals several fundamental principles of membrane domain formation. In single-channel systems, we demonstrate a biphasic relationship between interaction energy and cluster size, with optimal clustering occurring at intermediate interaction strengths, suggesting that excessively strong interactions can impede cluster growth by restricting channel mobility. In two-channel systems, we find that the interplay between homotypic and heterotypic interactions determines whether channels form mixed or segregated clusters, with asymmetric clustering behaviors emerging when homotypic interaction strengths differ between channel types. Simulations of three-channel systems demonstrate emergent organizational principles leading to hierarchical clustering patterns and specialized domain formation. These findings generate testable predictions about how channel density, trafficking dynamics, and interaction energies collectively alter ion channel spatial organization, in the setting of both physiological function and pathophysiological conditions.
(Copyright: © 2026 Moise, Weinberg. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Competing Interests: The authors have declared that no competing interests exist.
References: J Physiol. 2026 Jun 22;:. (PMID: 42330017)
Pflugers Arch. 2015 Oct;467(10):2093-105. (PMID: 25578859)
Proc Natl Acad Sci U S A. 2009 Dec 29;106(52):22275-80. (PMID: 20018773)
Dev Neurobiol. 2021 Jul;81(5):427-437. (PMID: 31859465)
J Physiol. 2007 Aug 1;582(Pt 3):1205-17. (PMID: 17525113)
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JACC Clin Electrophysiol. 2024 May;10(5):829-842. (PMID: 38430092)
Physiol Rev. 2001 Oct;81(4):1415-59. (PMID: 11581493)
QJM. 2006 Apr;99(4):201-17. (PMID: 16495302)
Endocr Relat Cancer. 2016 Nov;23(11):R517-R525. (PMID: 27619258)
Sci Rep. 2020 Nov 24;10(1):20463. (PMID: 33235263)
Nat Commun. 2017 Sep 29;8(1):740. (PMID: 28963530)
Neuron. 2001 Apr;30(1):105-19. (PMID: 11343648)
Curr Top Membr. 2016;77:143-84. (PMID: 26781832)
Biophys Rev (Melville). 2023 Mar;4(1):011315. (PMID: 37034130)
Physiol Rev. 2014 Apr;94(2):519-608. (PMID: 24692355)
Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics. 1995 Sep;52(3):2522-2534. (PMID: 9963695)
Proc Natl Acad Sci U S A. 2002 Feb 19;99(4):2303-8. (PMID: 11842202)
Proc Natl Acad Sci U S A. 2003 Jul 8;100(14):8053-8. (PMID: 12832616)
Sci Rep. 2019 Jul 15;9(1):10179. (PMID: 31308393)
J Gen Physiol. 2021 Aug 2;153(8):. (PMID: 34264306)
J Cell Sci. 2007 Jul 15;120(Pt 14):2413-23. (PMID: 17606996)
Eur Biophys J. 2004 Oct;33(6):506-12. (PMID: 14997356)
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Neuron. 2018 Feb 7;97(3):555-570.e6. (PMID: 29395909)
J Neurochem. 2006 Sep;98(5):1345-52. (PMID: 16787401)
Proc Natl Acad Sci U S A. 2022 Jul 26;119(30):e2123056119. (PMID: 35867835)
Physiol Rev. 2022 Jul 1;102(3):1159-1210. (PMID: 34927454)
Adv Physiol Educ. 2004 Dec;28(1-4):143-54. (PMID: 15545343)
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Langmuir. 2019 Jan 8;35(1):21-40. (PMID: 30589556)
J Neurosci. 2004 Apr 21;24(16):4030-42. (PMID: 15102918)
Eur J Clin Invest. 2018 Nov;48 Suppl 2:e12964. (PMID: 29873837)
Physiol Rev. 2021 Jul 1;101(3):1083-1176. (PMID: 33118864)
Cell. 2012 Jun 8;149(6):1353-67. (PMID: 22682254)
Microsc Microanal. 2024 Apr 29;30(2):306-317. (PMID: 38498601)
J Cell Biol. 1998 Nov 30;143(5):1295-304. (PMID: 9832557)
Cancer Metastasis Rev. 2006 Sep;25(3):493-500. (PMID: 17111226)
Microsc Microanal. 2020 Feb;26(1):157-165. (PMID: 31931893)
Front Cell Neurosci. 2017 May 09;11:136. (PMID: 28536506)
PLoS Comput Biol. 2018 Jan 16;14(1):e1005906. (PMID: 29338006)
Nat Commun. 2016 Jan 20;7:10342. (PMID: 26787348)
Grant Information: R01 HL165751 United States HL NHLBI NIH HHS
Substance Nomenclature: 0 (Ion Channels)
Entry Date(s): Date Created: 20260917 Date Completed: 20260922 Latest Revision: 20260924
Update Code: 20260924
PubMed Central ID: PMC13596815
DOI: 10.1371/journal.pcbi.1014791
PMID: 42752396
Database: MEDLINE
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  Data: <searchLink fieldCode="AU" term="%22Moise+N%22">Moise N</searchLink>; Department of Biomedical Engineering, The Ohio State University, Columbus, Ohio, United States of America.; Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America.<br /><searchLink fieldCode="AU" term="%22Weinberg+SH%22">Weinberg SH</searchLink>; Department of Biomedical Engineering, The Ohio State University, Columbus, Ohio, United States of America.; Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America.
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  Data: <searchLink fieldCode="JN" term="%22101238922%22">PLoS computational biology</searchLink> [PLoS Comput Biol] 2026 Sep 17; Vol. 22 (9), pp. e1014791. <i>Date of Electronic Publication: </i>2026 Sep 17 (<i>Print Publication: </i>2026).
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  Data: The spatial organization of ion channels on cell membranes critically influences many key physiological processes, such as cardiac and neuronal excitability and cellular signaling, yet the mechanisms governing channel clustering remain poorly understood. In this study, we present a stochastic computational framework that models the dynamic organization of ion channels through Monte Carlo simulations incorporating membrane insertion, removal, channel-channel interactions, and diffusion processes. Our model reveals several fundamental principles of membrane domain formation. In single-channel systems, we demonstrate a biphasic relationship between interaction energy and cluster size, with optimal clustering occurring at intermediate interaction strengths, suggesting that excessively strong interactions can impede cluster growth by restricting channel mobility. In two-channel systems, we find that the interplay between homotypic and heterotypic interactions determines whether channels form mixed or segregated clusters, with asymmetric clustering behaviors emerging when homotypic interaction strengths differ between channel types. Simulations of three-channel systems demonstrate emergent organizational principles leading to hierarchical clustering patterns and specialized domain formation. These findings generate testable predictions about how channel density, trafficking dynamics, and interaction energies collectively alter ion channel spatial organization, in the setting of both physiological function and pathophysiological conditions.<br /> (Copyright: © 2026 Moise, Weinberg. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
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  Data: The authors have declared that no competing interests exist.
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  Data: J Physiol. 2026 Jun 22;:. (PMID: <searchLink fieldCode="PM" term="%2242330017%22">42330017)</searchLink><br />Pflugers Arch. 2015 Oct;467(10):2093-105. (PMID: <searchLink fieldCode="PM" term="%2225578859%22">25578859)</searchLink><br />Proc Natl Acad Sci U S A. 2009 Dec 29;106(52):22275-80. (PMID: <searchLink fieldCode="PM" term="%2220018773%22">20018773)</searchLink><br />Dev Neurobiol. 2021 Jul;81(5):427-437. (PMID: <searchLink fieldCode="PM" term="%2231859465%22">31859465)</searchLink><br />J Physiol. 2007 Aug 1;582(Pt 3):1205-17. (PMID: <searchLink fieldCode="PM" term="%2217525113%22">17525113)</searchLink><br />Cell. 2015 Apr 23;161(3):581-594. (PMID: <searchLink fieldCode="PM" term="%2225910209%22">25910209)</searchLink><br />JACC Clin Electrophysiol. 2024 May;10(5):829-842. (PMID: <searchLink fieldCode="PM" term="%2238430092%22">38430092)</searchLink><br />Physiol Rev. 2001 Oct;81(4):1415-59. (PMID: <searchLink fieldCode="PM" term="%2211581493%22">11581493)</searchLink><br />QJM. 2006 Apr;99(4):201-17. (PMID: <searchLink fieldCode="PM" term="%2216495302%22">16495302)</searchLink><br />Endocr Relat Cancer. 2016 Nov;23(11):R517-R525. (PMID: <searchLink fieldCode="PM" term="%2227619258%22">27619258)</searchLink><br />Sci Rep. 2020 Nov 24;10(1):20463. (PMID: <searchLink fieldCode="PM" term="%2233235263%22">33235263)</searchLink><br />Nat Commun. 2017 Sep 29;8(1):740. (PMID: <searchLink fieldCode="PM" term="%2228963530%22">28963530)</searchLink><br />Neuron. 2001 Apr;30(1):105-19. (PMID: <searchLink fieldCode="PM" term="%2211343648%22">11343648)</searchLink><br />Curr Top Membr. 2016;77:143-84. (PMID: <searchLink fieldCode="PM" term="%2226781832%22">26781832)</searchLink><br />Biophys Rev (Melville). 2023 Mar;4(1):011315. (PMID: <searchLink fieldCode="PM" term="%2237034130%22">37034130)</searchLink><br />Physiol Rev. 2014 Apr;94(2):519-608. (PMID: <searchLink fieldCode="PM" term="%2224692355%22">24692355)</searchLink><br />Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics. 1995 Sep;52(3):2522-2534. (PMID: <searchLink fieldCode="PM" term="%229963695%22">9963695)</searchLink><br />Proc Natl Acad Sci U S A. 2002 Feb 19;99(4):2303-8. (PMID: <searchLink fieldCode="PM" term="%2211842202%22">11842202)</searchLink><br />Proc Natl Acad Sci U S A. 2003 Jul 8;100(14):8053-8. (PMID: <searchLink fieldCode="PM" term="%2212832616%22">12832616)</searchLink><br />Sci Rep. 2019 Jul 15;9(1):10179. (PMID: <searchLink fieldCode="PM" term="%2231308393%22">31308393)</searchLink><br />J Gen Physiol. 2021 Aug 2;153(8):. (PMID: <searchLink fieldCode="PM" term="%2234264306%22">34264306)</searchLink><br />J Cell Sci. 2007 Jul 15;120(Pt 14):2413-23. (PMID: <searchLink fieldCode="PM" term="%2217606996%22">17606996)</searchLink><br />Eur Biophys J. 2004 Oct;33(6):506-12. (PMID: <searchLink fieldCode="PM" term="%2214997356%22">14997356)</searchLink><br />Pflugers Arch. 2016 Oct;468(10):1651-61. (PMID: <searchLink fieldCode="PM" term="%2227510622%22">27510622)</searchLink><br />J Gen Physiol. 2019 Sep 2;151(9):1116-1134. (PMID: <searchLink fieldCode="PM" term="%2231371391%22">31371391)</searchLink><br />Neuron. 2018 Feb 7;97(3):555-570.e6. (PMID: <searchLink fieldCode="PM" term="%2229395909%22">29395909)</searchLink><br />J Neurochem. 2006 Sep;98(5):1345-52. (PMID: <searchLink fieldCode="PM" term="%2216787401%22">16787401)</searchLink><br />Proc Natl Acad Sci U S A. 2022 Jul 26;119(30):e2123056119. (PMID: <searchLink fieldCode="PM" term="%2235867835%22">35867835)</searchLink><br />Physiol Rev. 2022 Jul 1;102(3):1159-1210. (PMID: <searchLink fieldCode="PM" term="%2234927454%22">34927454)</searchLink><br />Adv Physiol Educ. 2004 Dec;28(1-4):143-54. (PMID: <searchLink fieldCode="PM" term="%2215545343%22">15545343)</searchLink><br />Elife. 2018 Aug 14;7:. (PMID: <searchLink fieldCode="PM" term="%2230106376%22">30106376)</searchLink><br />Langmuir. 2019 Jan 8;35(1):21-40. (PMID: <searchLink fieldCode="PM" term="%2230589556%22">30589556)</searchLink><br />J Neurosci. 2004 Apr 21;24(16):4030-42. (PMID: <searchLink fieldCode="PM" term="%2215102918%22">15102918)</searchLink><br />Eur J Clin Invest. 2018 Nov;48 Suppl 2:e12964. (PMID: <searchLink fieldCode="PM" term="%2229873837%22">29873837)</searchLink><br />Physiol Rev. 2021 Jul 1;101(3):1083-1176. (PMID: <searchLink fieldCode="PM" term="%2233118864%22">33118864)</searchLink><br />Cell. 2012 Jun 8;149(6):1353-67. (PMID: <searchLink fieldCode="PM" term="%2222682254%22">22682254)</searchLink><br />Microsc Microanal. 2024 Apr 29;30(2):306-317. (PMID: <searchLink fieldCode="PM" term="%2238498601%22">38498601)</searchLink><br />J Cell Biol. 1998 Nov 30;143(5):1295-304. (PMID: <searchLink fieldCode="PM" term="%229832557%22">9832557)</searchLink><br />Cancer Metastasis Rev. 2006 Sep;25(3):493-500. (PMID: <searchLink fieldCode="PM" term="%2217111226%22">17111226)</searchLink><br />Microsc Microanal. 2020 Feb;26(1):157-165. (PMID: <searchLink fieldCode="PM" term="%2231931893%22">31931893)</searchLink><br />Front Cell Neurosci. 2017 May 09;11:136. (PMID: <searchLink fieldCode="PM" term="%2228536506%22">28536506)</searchLink><br />PLoS Comput Biol. 2018 Jan 16;14(1):e1005906. (PMID: <searchLink fieldCode="PM" term="%2229338006%22">29338006)</searchLink><br />Nat Commun. 2016 Jan 20;7:10342. (PMID: <searchLink fieldCode="PM" term="%2226787348%22">26787348)</searchLink>
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