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


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
10 01 2022
Historique:
received: 21 06 2021
accepted: 11 11 2021
entrez: 11 1 2022
pubmed: 12 1 2022
medline: 27 1 2022
Statut: epublish

Résumé

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 an 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

Identifiants

pubmed: 35013165
doi: 10.1038/s41467-021-27417-y
pii: 10.1038/s41467-021-27417-y
pmc: PMC8748619
doi:

Substances chimiques

Buffers 0
Carbon Isotopes 0
Lipid Bilayers 0
Membranes, Artificial 0
Phosphatidylcholines 0
Solutions 0
1-palmitoyl-2-oleoylphosphatidylcholine TE895536Y5

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

108

Informations de copyright

© 2022. The Author(s).

Références

Henzler-Wildman, K. & Kern, D. Dynamic personalities of proteins. Nature 450, 964–972 (2007).
pubmed: 18075575 doi: 10.1038/nature06522
Lewandowski, J. R., Halse, M. E., Blackledge, M. & Emsley, L. Direct observation of hierarchical protein dynamics. Science 348, 578 (2015).
pubmed: 25931561 doi: 10.1126/science.aaa6111
Palmer, A. G. 3rd NMR probes of molecular dynamics: overview and comparison with other techniques. Annu. Rev. Biophys. Biomol. Struct. 30, 129–155 (2001).
pubmed: 11340055 doi: 10.1146/annurev.biophys.30.1.129
Schanda, P. & Ernst, M. Studying dynamics by magic-angle spinning solid-state NMR spectroscopy: principles and applications to biomolecules. Prog. Nucl. Magn. Res. Spectrosc. 96, 1–46 (2016).
doi: 10.1016/j.pnmrs.2016.02.001
Brown, M. F. Deuterium relaxation and molecular dynamics in lipid bilayers. J. Magn. Reson. 35, 203–215 (1979).
Brown, M. F., Seelig, J. & Häberlen, U. Structural dynamics in phospholipid bilayers from deuterium spin–lattice relaxation time measurements. J. Chem. Phys. 70, 5045–5053 (1979).
doi: 10.1063/1.437346
Lipari, G. & Szabo, A. Model-free approach to the interpretation of nuclear magnetic resonance relaxation in macromolecules. 1. Theory and range of validity. J. Am. Chem. Soc. 104, 4546–4559 (1982).
doi: 10.1021/ja00381a009
Henry, E. R. & Szabo, A. Influence of vibrational motion on solid state line shapes and NMR relaxation. J. Chem. Phys. 82, 4753 (1985).
doi: 10.1063/1.448692
Smith, A. A., Ernst, M. & Meier, B. H. Because the light is better here: correlation-time analysis by NMR spectroscopy. Angew. Chem. Int. Ed. 56, 13778–13783 (2017).
doi: 10.1002/ange.201707316
Antila, H. S., M. Ferreira, T., Ollila, O. H. S. & Miettinen, M. S. Using open data to rapidly benchmark biomolecular simulations: phospholipid conformational dynamics. J. Chem. Inf. Model. 61, 938–949 (2021).
pubmed: 33496579 pmcid: 7903423 doi: 10.1021/acs.jcim.0c01299
Singer, S. J. & Nicolson, G. L. The fluid mosaic model of the structure of cell membranes. Science 175, 720–731 (1972).
pubmed: 4333397 doi: 10.1126/science.175.4023.720
Goñi, F. M. The basic structure and dynamics of cell membranes: an update of the Singer–Nicolson model. Biochim. Biophys. Acta 1838, 1467–1476 (2014).
pubmed: 24440423 doi: 10.1016/j.bbamem.2014.01.006
Casares, D., Escribá, P. V. & Rosselló, C. A. Membrane lipid composition: effect on membrane and organelle structure, function and compartmentalization and therapeutic avenues. Int. J. Mol. Sci. 20, 2167 (2019).
pmcid: 6540057 doi: 10.3390/ijms20092167
White, S. H., Ladokhin, A. S., Jayasinghe, S. & Hristova, K. How membranes shape protein structure. J. Biol. Chem. 276, 32395–32398 (2001).
pubmed: 11432876 doi: 10.1074/jbc.R100008200
Venable, R. M., Zhang, Y., Hardy, B. J. & Pastor, R. W. Molecular dynamics simulations of a lipid bilayer and of hexadecane: an investigation of membrane fluidity. Science 262, 223–226 (1993).
pubmed: 8211140 doi: 10.1126/science.8211140
Huster, D., Arnold, K. & Gawrisch, K. Investigation of lipid organization in biological membranes by two-dimensional nuclear Overhauser enhancement spectroscopy. J. Phys. Chem. B 103, 243–251 (1999).
doi: 10.1021/jp983428h
Feller, S. E., Huster, D. & Gawrisch, K. Interpretation of NOESY cross-relaxation rates from molecular dynamics simulation of a lipid bilayer. J. Am. Chem. Soc. 121, 8963–8964 (1999).
doi: 10.1021/ja991456n
Vermeer, L. S., de Groot, B. L., Réat, V., Milon, A. & Czaplicki, J. Acyl chain order parameter profiles in phospholipid bilayers: computation from molecular dynamics simulations and comparison with 2H NMR experiments. Eur. Biophys. J. 36, 919–931 (2007).
pubmed: 17598103 doi: 10.1007/s00249-007-0192-9
Ferreira, T. M. et al. Cholesterol and POPC segmental order parameters in lipid membranes: solid state 1H-13C NMR and MD simulation studies. Phys. Chem. Chem. Phys. 15, 1976–1989 (2013).
pubmed: 23258433 doi: 10.1039/C2CP42738A
Lindahl, E. & Edholm, O. Molecular dynamics simulation of NMR relaxation rates and slow dynamics in lipid bilayers. J. Chem. Phys. 115, 4938–4950 (2001).
doi: 10.1063/1.1389469
Ferreira, T. M., Ollila, O. H. S., Pigliapochi, R., Dabkowska, A. P. & Topgaard, D. Model-free estimation of the effective correlation time for C–H bond reorientation in amphiphilic bilayers:
pubmed: 25638007 doi: 10.1063/1.4906274
Brown, M. F., Ribeiro, A. A. & Williams, G. D. New view of lipid bilayer dynamics from
pubmed: 6576340 pmcid: 384030 doi: 10.1073/pnas.80.14.4325
Smith, A. A., Ernst, M. & Meier, B. H. Optimized ‘detectors’ for dynamics analysis in solid-state NMR. J. Chem. Phys. 148, 045104 (2018).
pubmed: 29390848 doi: 10.1063/1.5013316
Smith, A. A., Ernst, M., Meier, B. H. & Ferrage, F. Reducing bias in the analysis of solution-state NMR data with dynamics detectors. J. Chem. Phys. 151, 034102 (2019).
pubmed: 31325945 doi: 10.1063/1.5111081
Halle, B. & Wennerström, H. Interpretation of magnetic resonance data from water nuclei in heterogeneous systems. J. Chem. Phys. 75, 1928–1943 (1981).
doi: 10.1063/1.442218
Brown, M. F. Theory of spin-lattice relaxation in lipid bilayers and biological membranes.
doi: 10.1063/1.443940
Brown, M. F. In Biological Membranes: A Molecular Perspective from Computation and Experiment (eds Merz, K. M. & Roux, B.) (Birkhäuser, 1996).
Salvi, N., Abyzov, A. & Blackledge, M. Analytical description of NMR relaxation highlights correlated dynamics in intrinsically disordered proteins. Angew. Chem. Int. Ed. 56, 14020–14024 (2017).
doi: 10.1002/anie.201706740
Beckmann, P. A. Spectral densities and nuclear spin relaxation in solids. Phys. Rep. 171, 85–128 (1988).
doi: 10.1016/0370-1573(88)90073-7
Smith, A. A., Ernst, M., Riniker, S. & Meier, B. H. Localized and collective motions in HET-s(218-289) fibrils from combined NMR relaxation and MD simulation. Angew. Chem. Int. Ed. 58, 9483–9488 (2019).
doi: 10.1002/ange.201901929
Halle, B. The physical basis of mode-free analysis of NMR relaxation data from proteins and complex fluids. J. Chem. Phys. 131, 224507 (2009).
pubmed: 20001057 doi: 10.1063/1.3269991
Lipari, G., Szabo, A. & Levy, R. M. Protein dynamics and NMR relaxation: comparison of simulations with experiment. Nature 300, 197–198 (1982).
doi: 10.1038/300197a0
Wennerström, H., Lindman, B., Soederman, O., Drakenberg, T. & Rosenholm, J. B. Carbon-13 magnetic relaxation in micellar solutions. Influence of aggregate motion on T1. J. Am. Chem. Soc. 101, 6860–6864 (1979).
doi: 10.1021/ja00517a012
Gross, J. D., Warschawski, D. E. & Griffin, R. G. Dipolar recoupling in MAS NMR: a probe for segmental order in lipid bilayers. J. Am. Chem. Soc. 119, 796–802 (1997).
doi: 10.1021/ja962951b
Ferreira, T. M. et al. Acyl chain disorder and azelaoyl orientation in lipid membranes containing oxidized lipids. Langmuir 32, 6524–6533 (2016).
doi: 10.1021/acs.langmuir.6b00788
Istratov, A. A. & Vyvenko, O. F. Exponential analysis in physical phenomena. Rev. Sci. Instrum. 70, 1233–1257 (1999).
doi: 10.1063/1.1149581
Nowacka, A., Bongartz, N. A., Ollila, O. H. S., Nylander, T. & Topgaard, D. Signal intensities in 1H–13C CP and INEPT MAS NMR of liquid crystals. J. Magn. Reson. 230, 165–175 (2013).
pubmed: 23542743 doi: 10.1016/j.jmr.2013.02.016
Nevzorov, A. A. & Brown, M. F. Dynamics of lipid bilayers from comparative analysis of
doi: 10.1063/1.474169
Brown, M. F. 7. In Characterization of Biological Membranes, 231–268 (Walter de Gruyter, 2019).
Nevzorov, A. A., Trouard, T. P. & Brown, M. Correlation functions for lipid membrane dynamics obtained from NMR spectroscopy. Phys. Rev. E 55, 3276–3282 (1997).
doi: 10.1103/PhysRevE.55.3276
Weisz, K., Groebner, G., Mayer, C., Stohrer, J. & Kothe, G. Deuteron nuclear magnetic resonance study of the dynamic organization of phospholipid/cholesterol bilayer membranes: molecular properties and viscoelastic behavior. Biochemistry 31, 1100–1112 (1992).
pubmed: 1734959 doi: 10.1021/bi00119a019
Stohrer, J. et al. Collective lipid motions in bilayer membranes studied by transverse deuteron spin relaxation. J. Chem. Phys. 95, 672–678 (1991).
doi: 10.1063/1.461417
Chakraborty, S. et al. How cholesterol stiffens unsaturated lipid membranes. Proc. Natl Acad. Sci. USA 117, 21896–21905 (2020).
pubmed: 32843347 pmcid: 7486787 doi: 10.1073/pnas.2004807117
Fraenza, C. C., Meledandri, C. J., Anoardo, E. & Brougham, D. F. The effect of cholesterol on membrane dynamics on different timescales in lipid bilayers from fast field-cycling NMR relaxometry studies of unilamellar vesicles. ChemPhysChem 15, 425–435 (2014).
pubmed: 24482248 doi: 10.1002/cphc.201301051
Seelig, A. & Seelig, J. Dynamic structure of fatty acyl chains in a phospholipid bilayer measured by deuterium magnetic resonance. Biochemistry 13, 4839–4845 (2002).
doi: 10.1021/bi00720a024
Seelig, J. Deuterium magnetic resonance: theory and application to lipid membranes. Q. Rev. Biophys. 10, 353–418 (1977).
pubmed: 335428 doi: 10.1017/S0033583500002948
Fraenza, C. C. & Anoardo, E. Dynamical regimes of lipids in additivated liposomes with enhanced elasticity: a field-cycling NMR relaxometry approach. Biophys. Chem. 228, 38–46 (2017).
pubmed: 28697447 doi: 10.1016/j.bpc.2017.06.007
Brown, M. F. & Nevzorov, A. A.
doi: 10.1016/S0927-7757(99)00154-5
Otten, D., Brown, M. F. & Beyer, K. Softening of membrane bilayers by detergents elucidated by deuterium NMR spectroscopy. J. Phys. Chem. B 104, 12119–12129 (2000).
doi: 10.1021/jp001505e
Milburn, M. P. & Jeffrey, K. R. Dynamics of the phosphate group in phospholipid bilayers. A 31P nuclear relaxation time study. Biophys. J. 52, 791–799 (1987).
pubmed: 3427188 pmcid: 1330183 doi: 10.1016/S0006-3495(87)83273-3
Seelig, J. & Niederberger, W. Deuterium-labeled lipids as structural probes in liquid crystalline bilayers. Deuterium magnetic resonance study. J. Am. Chem. Soc. 96, 2069–2072 (1974).
doi: 10.1021/ja00814a014
Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W. & Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926–935 (1983).
doi: 10.1063/1.445869
Jo, S., Kim, T., Iyer, V. G. & Im, W. CHARMM-GUI: a web-based graphical user interface for CHARMM. J. Comput. Chem. 29, 1859–1865 (2008).
pubmed: 18351591 doi: 10.1002/jcc.20945
Wu, E. L. et al. CHARMM-GUI Membrane Builder toward realistic biological membrane simulations. J. Comput. Chem. 35, 1997–2004 (2014).
pubmed: 25130509 pmcid: 4165794 doi: 10.1002/jcc.23702
Jo, S., Lim, J. B., Klauda, J. B. & Im, W. CHARMM-GUI membrane builder for mixed bilayers and its application to yeast membranes. Biophys. J. 97, 50–58 (2009).
pubmed: 19580743 pmcid: 2711372 doi: 10.1016/j.bpj.2009.04.013
Brooks, B. R. et al. CHARMM: the biomolecular simulation program. J. Comput. Chem. 30, 1545–1614 (2009).
pubmed: 19444816 pmcid: 2810661 doi: 10.1002/jcc.21287
Lee, J. et al. CHARMM-GUI input generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM simulations using the CHARMM36 additive force field. Biophys. J. 110, 641a (2016).
doi: 10.1016/j.bpj.2015.11.3431
Klauda, J. B. et al. Update of the CHARMM all-atom additive force field for lipids: validation on six lipid types. J. Phys. Chem. B 114, 7830–7843 (2010).
pubmed: 20496934 pmcid: 2922408 doi: 10.1021/jp101759q
Hess, B., Bekker, H., Berendsen, H. J. C. & Fraaije, J. G. E. M. LINCS: a linear constraint solver for molecular simulations. J. Comput. Chem. 18, 1463–1472 (1997).
doi: 10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H
Fung, B. M., Khitrin, A. K. & Ermolaev, K. An improved broadband decoupling sequence for liquid crystals and solids. J. Magn. Reson. 142, 97–101 (2000).
pubmed: 10617439 doi: 10.1006/jmre.1999.1896
Krushelnitsky, A., Gauto, D., Rodriguez Camargo, D. C., Schanda, P. & Saalwachter, K. Microsecond motions probed by near-rotary-resonance R1rho(15)N MAS NMR experiments: the model case of protein overall-rocking in crystals. J. Biomol. NMR 71, 53–67 (2018).
pubmed: 29845494 pmcid: 5986846 doi: 10.1007/s10858-018-0191-4
Bielecki, A., Kolbert, A. C., De groot, H. J. M., Griffin, R. G. & Levitt, M. H. In Advances in Magnetic and Optical Resonance (ed. Warren, W. S.) Vol. 14, 111–124 (Academic Press, 1990).
Smith, A. A. INFOS: spectrum fitting software for NMR analysis. J. Biomol. NMR 67, 77–94 (2017).
pubmed: 28160196 doi: 10.1007/s10858-016-0085-2
Smith, Albert A., Vogel, A., Engberg, O., Hildebrand, P. W., Huster, D. A method to construct the dynamic landscape of a bio-membrane with experiment and simulation. GitHub: alsinmr/POPC_frames_archive. https://doi.org/10.5281/zenodo.5642559 (2021).
Smith, A. A., Vogel, A., Engberg, O., Hildebrand, P. W. & Huster, D. A method to construct the dynamic landscape of a bio-membrane with experiment and simulation. https://doi.org/10.5281/zenodo.5645031 (2021).
Tiemann, J. K. S., Guixà-González, R., Hildebrand, P. W. & Rose, A. S. MDsrv: viewing and sharing molecular dynamics simulations on the web. Nat. Methods 14, 1123–1124 (2017).
pubmed: 29190271 doi: 10.1038/nmeth.4497
Pettersen, E. F. et al. UCSF ChimeraX: structure visualization for researchers, educators, and developers. Protein Sci. 30, 70–82 (2021).
pubmed: 32881101 doi: 10.1002/pro.3943

Auteurs

Albert A Smith (AA)

Institute for Medical Physics and Biophysics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany. albert.smith-penzel@medizin.uni-leipzig.de.

Alexander Vogel (A)

Institute for Medical Physics and Biophysics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany.

Oskar Engberg (O)

Institute for Medical Physics and Biophysics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany.

Peter W Hildebrand (PW)

Institute for Medical Physics and Biophysics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany.

Daniel Huster (D)

Institute for Medical Physics and Biophysics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany.

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Classifications MeSH