Computing the lateral diffusion coefficient of lipids on lipid membranes

Computing the lateral diffusion coefficient of lipids on lipid membranes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Computing the lateral diffusion coefficient of lipids on lipid membranes Bayelign Gedefaw Fentie, Gebre kalute Gebino, Tegegn Teferi Agago, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7904555/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 20 You are reading this latest preprint version Abstract In biological membranes, lateral diffusion refers to the movement of constituent molecules, such as lipids and proteins, within each leaflet of the bilayer. Understanding this process is crucial for elucidating membrane dynamics, molecular interactions, and the physical basis of cellular transport. The present study aims to compute the lateral diffusion coefficient (D) of lipid molecules subjected to a harmonic potential within a model lipid membrane. The stochastic dynamics of individual lipid molecules arise from both random thermal collisions with the surrounding medium and deterministic forces characterized by a potential energy function U(r). The system was modeled using the overdamped form of the Langevin equation, appropriate for regimes with large frictional coefficients and small diffusion constants. Numerical simulations were performed using the Euler-Maruyama integration scheme, implemented in Python. The mean square displacement (MSD) of lipid molecules was computed from the simulated trajectories, from which the diffusion coefficient Dwas extracted. The calculated value, D = 1.28 x 10^-12 m^2/s, indicates a diffusion process consistent with thermally driven motion in a viscous membrane environment. The linear relationship observed between MSD and lag time confirms that membrane components exhibit unrestricted lateral mobility in the absence of strong intermolecular constraints or structural barriers. These results contribute to a quantitative understanding of lipid dynamics under harmonic confinement and demonstrate the applicability of stochastic numerical methods for modeling molecular transport processes in complex biological membranes. Keywords: Lateral diffusion; Lipid membranes; Mean square displacement; Langevin dynamics Biological sciences/Biophysics Biological sciences/Computational biology and bioinformatics Physical sciences/Mathematics and computing Physical sciences/Physics Lateral diffusion Lipid membranes Mean square displacement Langevin dynamics Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 13 Feb, 2026 Reviews received at journal 10 Feb, 2026 Reviews received at journal 10 Feb, 2026 Reviews received at journal 05 Feb, 2026 Reviewers agreed at journal 04 Feb, 2026 Reviewers agreed at journal 03 Feb, 2026 Reviewers agreed at journal 03 Feb, 2026 Reviews received at journal 18 Dec, 2025 Reviews received at journal 11 Dec, 2025 Reviews received at journal 08 Dec, 2025 Reviewers agreed at journal 02 Dec, 2025 Reviewers agreed at journal 29 Nov, 2025 Reviewers agreed at journal 28 Nov, 2025 Reviewers agreed at journal 28 Nov, 2025 Reviewers agreed at journal 27 Nov, 2025 Reviewers invited by journal 27 Nov, 2025 Editor invited by journal 29 Oct, 2025 Editor assigned by journal 25 Oct, 2025 Submission checks completed at journal 25 Oct, 2025 First submitted to journal 20 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7904555","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":552767672,"identity":"c4f607d6-7039-45fc-8027-b084284de094","order_by":0,"name":"Bayelign Gedefaw 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Understanding this process is crucial for elucidating membrane dynamics, molecular interactions, and the physical basis of cellular transport. The present study aims to compute the lateral diffusion coefficient (D) of lipid molecules subjected to a harmonic potential within a model lipid membrane. The stochastic dynamics of individual lipid molecules arise from both random thermal collisions with the surrounding medium and deterministic forces characterized by a potential energy function U(r). The system was modeled using the overdamped form of the Langevin equation, appropriate for regimes with large frictional coefficients and small diffusion constants. Numerical simulations were performed using the Euler-Maruyama integration scheme, implemented in Python. The mean square displacement (MSD) of lipid molecules was computed from the simulated trajectories, from which the diffusion coefficient Dwas extracted. 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