271374 Predicting the Nature of the Protein Corona Surrounding Nanoparticles

Monday, October 29, 2012: 1:40 PM
411 (Convention Center )
Lauren Ridge and Carol K. Hall, Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC

Our knowledge of the risks of exposure to nanoparticles is essentially in its infancy since the current in vivo and in vitro studies of “nanotoxicology” span only a minute subset of the many different types of nanoparticles being made today.  A key step in analyzing the risks posed by nanoparticles is to determine the composition of the corona of plasma proteins adsorbed onto the surface of nanoparticles. The nature of the protein corona is expected to have a marked influence on the fate of nanoparticles in the body. 

The goal of this research is to develop an algorithm to predict the affinities of proteins for a given nanoparticle based on their specific properties, and hence predict which proteins are most likely to form a corona around that nanoparticle. Discontinuous molecular dynamics simulations with the coarse-grained force field PRIME20 were used to calculate the adsorption of polyalanine (polyA) and polytryptophan (polyW) onto a hydrophobic nanoparticle.  In single-protein systems, a decrease in temperature led to an increase in adsorption for all concentrations and peptide lengths.  However, the effect of increased protein concentration on adsorption was not as straightforward, as short chains (A16 and W16) had a direct relationship between adsorption and protein concentration, while longer chains had an inverse relationship between adsorption and protein concentration.  On the whole, polyA was more likely to adsorb than polyW under identical conditions.  For polyA, the degree of adsorption appears to affect the deformation of chains adsorbed on the nanoparticle surface.  For short chains, A16, as the density of the protein corona increases, so does the likelihood that an adsorbed protein will deform and lose its α-helical character, but not for the longer A30.  Competitive adsorption between polyA and polyW was also simulated.  When W30 competes with short A16, the adsorption of polyW depends directly on concentration, and when W30 competes with longer A30, the adsorption of polyW depends inversely on concentration, trends that are similar to those found in the single-protein simulations.


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