Protein corona fingerprinting predicts the cellular interaction of gold and silver nanoparticles
Carl D Walkey, Jonathan B Olsen, Fayi Song, Rong Liu, Hongbo Guo, D Wesley H Olsen, Yoram Cohen, Andrew Emili, Warren CW Chan
ACS Nano 2014, 8, 3, 2439–2455 | DOI: 10.1021/nn406018q
Using quantitative models to predict the biological interactions of nanoparticles will accelerate the translation of nanotechnology. Here, we characterized the serum protein corona ‘fingerprint’ formed around a library of 105 surface-modified gold nanoparticles. Applying a bioinformatics-inspired approach, we developed a multivariate model that uses the protein corona fingerprint to predict cell association 50% more accurately than a model that uses parameters describing nanoparticle size, aggregation state, and surface charge. Our model implicates a set of hyaluronan-binding proteins as mediators of nanoparticle–cell interactions. This study establishes a framework for developing a comprehensive database of protein corona fingerprints and biological responses for multiple nanoparticle types. Such a database can be used to develop quantitative relationships that predict the biological responses to nanoparticles and will aid in uncovering the fundamental mechanisms of nano–bio interactions.