A method to construct the dynamic landscape of a bio-membrane with experiment and simulation

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This paper presents a novel method using NMR relaxation and molecular dynamics simulations to construct a dynamic landscape of biomolecules, revealing site-specific motions across various timescales and positions.

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The paper presents a method to construct a “dynamic landscape” of biomolecules by combining NMR relaxation data with molecular dynamics simulations, focusing on lipid membranes as a biological interface. Using a dynamics detector approach, the authors generate site-specific amplitudes that are separated by both motion type and correlation timescale, revealing substantial differences in dynamics across molecular positions. The dynamic landscape is described as broadly adaptable to other systems and timescale-sensitive techniques, but the study’s demonstrations are specifically on lipid membranes and the method’s performance depends on the availability and compatibility of NMR relaxation and simulation inputs. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Abstract Biomolecular function is based on a complex hierarchy of molecular motions. While biophysical methods can reveal details of specific motions, a concept for the comprehensive description of molecular dynamics over a wide range of correlation times has been unattainable. Here, we report a novel approach to construct the dynamic landscape of biomolecules, which describes the aggregate influence of multiple motions acting on various timescales and on multiple positions in the molecule. To this end, we use NMR relaxation and molecular dynamics simulation data for the characterization of lipid membranes, the most important biological interface. We develop a dynamics detector method that yields site-specific amplitudes, separated both by type and timescale of motion. This separation allows the detailed description of the dynamic landscape, which reveals vast differences in motion depending on molecular position. More generally, the method is applicable to a broad range of molecular systems, and can be adapted to other timescale-sensitive techniques.
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A method to construct the dynamic landscape of a bio-membrane with experiment and simulation | 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 A method to construct the dynamic landscape of a bio-membrane with experiment and simulation Albert Smith, Alexander Vogel, Oskar Engberg, Peter Hildebrand, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-645823/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Jan, 2022 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Biomolecular function is based on a complex hierarchy of molecular motions. While biophysical methods can reveal details of specific motions, a concept for the comprehensive description of molecular dynamics over a wide range of correlation times has been unattainable. Here, we report a novel approach to construct the dynamic landscape of biomolecules, which describes the aggregate influence of multiple motions acting on various timescales and on multiple positions in the molecule. To this end, we use NMR relaxation and molecular dynamics simulation data for the characterization of lipid membranes, the most important biological interface. We develop a dynamics detector method that yields site-specific amplitudes, separated both by type and timescale of motion. This separation allows the detailed description of the dynamic landscape, which reveals vast differences in motion depending on molecular position. More generally, the method is applicable to a broad range of molecular systems, and can be adapted to other timescale-sensitive techniques. Biophysics Analytical Chemistry Analytical Biochemistry Physical Chemistry Biomolecular Function NMR Relaxation Molecular Dynamics Simulation Data Dynamics Detector Method Timescale-sensitive Techniques Full Text Additional Declarations There is NO Competing Interest. Supplementary Files tensorperpMOIHGBBintern.mov Tensors for motion perpendicular to the MOI and internal motion of the HG/BB detperpMOIHGBBintern.mov Detectors for motion perpendicular to the MOI and internal motion of the HG/BB detlib.mov Detectors for librational motion tensorparaMOI.mov Tensors for motion parallel to the MOI dettotal.mov Detectors for the total motion detall.mov Detectors for all motions tensorMOIHGBB.mov Tensors for the overall motion of the chains and HG/BB tensortotal.mov Tensors for the total motion DynamicLSSI.pdf Supplementary Information detparaMOI.mov Detectors for motion parallel to the MOI detMOIHGBB.mov Detectors for overall motion of the chains and HG/BB tensorlib.mov Tensors for librational motion flatsmithnrsoftwarepolicy.pdf Software and code checklist smithreportingsummarycomplete.pdf Reporting Summary Cite Share Download PDF Status: Published Journal Publication published 10 Jan, 2022 Read the published version in Nature Communications → Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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