The protein corona from nanomedicine to environmental science

Abstract

The protein corona spontaneously develops and evolves on the surface of nanoscale materials when they are exposed to biological environments, altering their physiochemical properties and affecting their subsequent interactions with biosystems. In this Review, we provide an overview of the current state of protein corona research in nanomedicine. We next discuss remaining challenges in the research methodology and characterization of the protein corona that slow the development of nanoparticle therapeutics and diagnostics, and we address how artificial intelligence can advance protein corona research as a complement to experimental research efforts. We then review emerging opportunities provided by the protein corona to address major issues in healthcare and environmental sciences. This Review details how mechanistic insights into nanoparticle protein corona formation can broadly address unmet clinical and environmental needs, as well as enhance the safety and efficacy of nanobiotechnology products.

Keywords: Diagnosis; Nanobiotechnology; Nanomedicine; Therapeutics.

Fig. 1. History of protein corona research.

AI, artificial intelligence; ML, machine learning; NP, nanoparticle; SA, sensor array.

Fig. 2. Schematics showing the major challenges created by the NP protein corona and proposed strategies to address them.

a, The use of protein-repellent compounds to coat nanoparticles (NPs) can minimize corona formation and, therefore, reduce the shielding effect of corona on active/functional sites of targeting moieties. b, The use of specific proteins to pre-coat NPs to enhance recruitment of proteins with intrinsic targeting capacities during corona formation. c, Maintaining the exposure of active site of antibodies, even after corona formation by pre-adsorbing targeting antibodies to the surface of NPs. d, Using strategies to attach targeting moieties to the surface of corona-coated NPs.

Fig. 3. Representative workflow used to predict protein corona formation with machine learning.

Protein corona data, usually from mass spectrometry experiments, are used to train a machine learning classifier that learns which features of proteins are likely to be found in versus out of the nanoparticle protein corona. Classifiers can be tested through experimental validation of single-protein binding affinities, or by predicting and validating protein adsorption from biofluids different from those used in the training set.

Fig. 4. New emerging technologies offered by the protein corona.

Nanoparticles (NPs) specifically decorated with targeting moieties such as immune system activating proteins can serve to modulate the immune system and catalyse the design of new therapeutics. Proteomics analysis of protein coronas of various NPs (for example, sensor array) provide a unique opportunity for identification of novel biomolecular patterns with disease detection capacity. The eco-corona forms when NPs enter ecological environments, resulting in spontaneous protein adsorption from ecological sources.