Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles
University of California, Los Angeles · University of Toronto
Abstract
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…
Citation impact
- FWCI
- 38.16
- Percentile
- 100%
- References
- 78
Authors
9- CWCarl WalkeyCorresponding
University of California, Los Angeles, University of Toronto
- JBJonathan B. Olsen
University of California, Los Angeles, University of Toronto
- FSFayi Song
University of California, Los Angeles, University of Toronto
- RLRong Liu
University of California, Los Angeles, University of Toronto
- HGHongbo Guo
University of California, Los Angeles, University of Toronto
Topics & keywords
- Nanoparticle
- Corona (planetary geology)
- Nanotechnology
- Colloidal gold
- Silver nanoparticle
- Fingerprint (computing)
- Materials science
- Biological system