117970 20220831095648.0 doi 10.1021/acsnano.6b07352 sideral 129420 ART-2017-129420 eng Willems, Nathalie Biomimetic Phospholipid Membrane Organization on Graphene and Graphene Oxide Surfaces: A Molecular Dynamics Simulation Study 2017 Access copy available to the general public Unrestricted Supported phospholipid membrane patches stabilized on graphene surfaces have shown potential in sensor device functionalization, including biosensors and biocatalysis. Lipid dip-pen nanolithography (L-DPN) is a method useful in generating supported membrane structures that maintain lipid functionality, such as exhibiting specific interactions with protein molecules. Here, we have integrated L-DPN, atomic force microscopy, and coarse-grained molecular dynamics simulation methods to characterize the molecular properties of supported lipid membranes (SLMs) on graphene and graphene oxide supports. We observed substantial differences in the topologies of the stabilized lipid structures depending on the nature of the surface (polar graphene oxide vs nonpolar graphene). Furthermore, the addition of water to SLM systems resulted in large-scale reorganization of the lipid structures, with measurable effects on lipid lateral mobility within the supported membranes. We also observed reduced lipid ordering within the supported structures relative to free-standing lipid bilayers, attributed to the strong hydrophobic interactions between the lipids and support. Together, our results provide insight into the molecular effects of graphene and graphene oxide surfaces on lipid bilayer membranes. This will be important in the design of these surfaces for applications such as biosensor devices. info:eu-repo/grantAgreement/EC/FP7/328163/EU/In depth characterization of bio-mimetic lipid membrane structures generated by dip-pen nanolithography/DPNLipidMembranes info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 13.709 2017 CHEMISTRY, PHYSICAL 7 / 146 = 0.048 2017 Q1 T1 NANOSCIENCE & NANOTECHNOLOGY 5 / 92 = 0.054 2017 Q1 T1 CHEMISTRY, MULTIDISCIPLINARY 10 / 171 = 0.058 2017 Q1 T1 MATERIALS SCIENCE, MULTIDISCIPLINARY 12 / 285 = 0.042 2017 Q1 T1 7.203 2017 Engineering (miscellaneous) 2017 Q1 Physics and Astronomy (miscellaneous) 2017 Q1 Nanoscience and Nanotechnology 2017 Q1 Materials Science (miscellaneous) 2017 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Urtizberea, Ainhoa (orcid)0000-0002-8424-9780 Verre, Andrea F. Iliut, Maria Lelimousin, Mickael Hirtz, Michael Vijayaraghavan, Aravind Sansom, Mark S. P. 11, 2 (2017), 1613-1625 ACS Nano ACS NANO 1936-0851 5003240 http://zaguan.unizar.es/record/117970/files/texto_completo.pdf Versión publicada 3143206 http://zaguan.unizar.es/record/117970/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:117970 articulos driver 2022-08-31-09:48:34 ARTICLE