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Has files: Yes × Subject: Animals × Subject: Nanostructures ×

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    Detection of Protein Glycosylation Using Tip-Enhanced Raman Scattering
    (Columbus, Ohio : American Chemical Society, 2016) Cowcher, David P.; Deckert-Gaudig, Tanja; Brewster, Victoria L.; Ashton, Lorna; Deckert, Volker; Goodacre, Royston
    The correct glycosylation of biopharmaceutical glycoproteins and their formulations is essential for them to have the desired therapeutic effect on the patient. It has recently been shown that Raman spectroscopy can be used to quantify the proportion of glycosylated protein from mixtures of native and glycosylated forms of bovine pancreatic ribonuclease (RNase). Here we show the first steps toward not only the detection of glycosylation status but the characterization of glycans themselves from just a few protein molecules at a time using tip-enhanced Raman scattering (TERS). While this technique generates complex data that are very dependent on the protein orientation, with the careful development of combined data preprocessing, univariate and multivariate analysis techniques, we have shown that we can distinguish between the native and glycosylated forms of RNase. Many glycoproteins contain populations of subtly different glycoforms; therefore, with stricter orientation control, we believe this has the potential to lead to further glycan characterization using TERS, which would have use in biopharmaceutical synthesis and formulation research.
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    Simulations of Protein Adsorption on Nanostructured Surfaces
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2019) Manzi, Berardo M.; Werner, Marco; Ivanova, Elena P.; Crawford, Russell J.; Baulin, Vladimir A.
    Recent technological advances have allowed the development of a new generation of nanostructured materials, such as those displaying both mechano-bactericidal activity and substrata that favor the growth of mammalian cells. Nanomaterials that come into contact with biological media such as blood first interact with proteins, hence understanding the process of adsorption of proteins onto these surfaces is highly important. The Random Sequential Adsorption (RSA) model for protein adsorption on flat surfaces was modified to account for nanostructured surfaces. Phenomena related to the nanofeature geometry have been revealed during the modelling process; e.g., convex geometries can lead to lower steric hindrance between particles, and hence higher degrees of surface coverage per unit area. These properties become more pronounced when a decrease in the size mismatch between the proteins and the surface nanostructures occurs. This model has been used to analyse the adsorption of human serum albumin (HSA) on a nano-structured black silicon (bSi) surface. This allowed the Blocking Function (the rate of adsorption) to be evaluated. The probability of the protein to adsorb as a function of the occupancy was also calculated.