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" Carbohydrate-derived amphiphilic macromolecules: "
Martin, Adriana AT; Tomasini, Michael; Kholodovych, Vladyslav; Gu, Li; Sommerfeld, Sven Daniel; Uhrich, Kathryn E; Murthy, N Sanjeeva; Welsh, William J; Moghe, Prabhas V
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AL
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| Record Number
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909381
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LA59596870
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| Title & Author
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Carbohydrate-derived amphiphilic macromolecules:. a biophysical structural characterization and analysis of binding behaviors to model membranes. [Article]\ Martin, Adriana AT; Tomasini, Michael; Kholodovych, Vladyslav; Gu, Li; Sommerfeld, Sven Daniel; Uhrich, Kathryn E; Murthy, N Sanjeeva; Welsh, William J; Moghe, Prabhas V
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2015
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UC Riverside
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| Abstract
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The design and synthesis of enhanced membrane-intercalating biomaterials for drug delivery or vascular membrane targeting is currently challenged by the lack of screening and prediction tools. The present work demonstrates the generation of a Quantitative Structural Activity Relationship model (QSAR) to make a priori predictions. Amphiphilic macromolecules (AMs) "stealth lipids" built on aldaric and uronic acids frameworks attached to poly(ethylene glycol) (PEG) polymer tails were developed to form self-assembling micelles. In the present study, a defined set of novel AM structures were investigated in terms of their binding to lipid membrane bilayers using Quartz Crystal Microbalance with Dissipation (QCM-D) experiments coupled with computational coarse-grained molecular dynamics (CG MD) and all-atom MD (AA MD) simulations. The CG MD simulations capture the insertion dynamics of the AM lipophilic backbones into the lipid bilayer with the PEGylated tail directed into bulk water. QCM-D measurements with Voigt viscoelastic model analysis enabled the quantitation of the mass gain and rate of interaction between the AM and the lipid bilayer surface. Thus, this study yielded insights about variations in the functional activity of AM materials with minute compositional or stereochemical differences based on membrane binding, which has translational potential for transplanting these materials in vivo. More broadly, it demonstrates an integrated computational-experimental approach, which can offer a promising strategy for the in silico design and screening of therapeutic candidate materials.
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