Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles

TLDR

A database of protein corona fingerprints can enable quantitative predictions of nanoparticle biological responses and help uncover fundamental nano‑bio interaction mechanisms. The study aims to develop quantitative models that predict nanoparticle–cell interactions, accelerating nanotechnology translation by building a comprehensive database of protein corona fingerprints and biological responses. The authors characterized the serum protein corona fingerprints of 105 surface‑modified gold nanoparticles and established a framework for compiling these fingerprints with corresponding biological responses. A multivariate model based on protein corona fingerprints predicts cell association 50 % more accurately than size, aggregation, and charge parameters, implicating hyaluronan‑binding proteins as key mediators of nanoparticle–cell interactions.

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 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.