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Surface Curvature Relation to Protein Adsorption for Carbon-based Nanomaterials
- Source :
- Scientific Reports
- Publication Year :
- 2015
- Publisher :
- Nature Publishing Group, 2015.
-
Abstract
- The adsorption of proteins onto carbon-based nanomaterials (CBNs) is dictated by hydrophobic and π-π interactions between aliphatic and aromatic residues and the conjugated CBN surface. Accordingly, protein adsorption is highly sensitive to topological constraints imposed by CBN surface structure; in particular, adsorption capacity is thought to increase as the incident surface curvature decreases. In this work, we couple Molecular Dynamics (MD) simulations with fluorescence spectroscopy experiments to characterize this curvature dependence in detail for the model protein bovine serum albumin (BSA). By studying BSA adsorption onto carbon nanotubes of increasing radius (featuring descending local curvatures) and a flat graphene sheet, we confirm that adsorption capacity is indeed enhanced on flatter surfaces. Naïve fluorescence experiments featuring multi-walled carbon nanotubes (MWCNTs), however, conform to an opposing trend. To reconcile these observations, we conduct additional MD simulations with MWCNTs that match those prepared in experiments; such simulations indicate that increased mass to surface area ratios in multi-walled systems explain the observed discrepancies. In reduction, our work substantiates the inverse relationship between protein adsorption capacity and surface curvature and further demonstrates the need for subtle consideration in experimental and simulation design.
- Subjects :
- Models, Molecular
Materials science
Protein Conformation
Surface Properties
chemistry.chemical_element
Carbon nanotube
Curvature
Article
law.invention
Nanomaterials
Molecular dynamics
Adsorption
law
Animals
Multidisciplinary
Graphene
Proteins
Reproducibility of Results
Serum Albumin, Bovine
Carbon
Nanostructures
Spectrometry, Fluorescence
chemistry
Chemical physics
Protein adsorption
Subjects
Details
- Language :
- English
- ISSN :
- 20452322
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....2f11ab99c7e14fe1c41540f233b4012a
- Full Text :
- https://doi.org/10.1038/srep10886