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Updated: Sep 10, 2025

Capillary Electrophoresis Mass Spectrometry Approaches for Characterization of the Protein and Metabolite Corona Acquired by Nanomaterials
Published on: October 27, 2020
A review on protein corona formation on nanoparticles and prediction of its composition using artificial intelligence
Mahnaz Ahmadi1, Seyed Mohammad Ayyoubzadeh2, Sara Afshar Ardekani3
1Department of Regenerative Medicine, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Abstract:
Nanoparticles (NPs) represent critical roles both for drug delivery systems and diagnostics. Nevertheless, due to interaction in a biological medium and specific consequences-like formation of protein corona (PC), changes may happen that have influenced its behavior. Such a PC depicts the formation of biomolecule dynamic layers over the NPs, normally starting at exposure in any form to biofluid, because this altered cellular targeting, biodistribution, and toxic potential happen very well. This review summarizes PC formation mechanisms and how NP physicochemical properties impact PC composition. It then explores the two-edged sword role of the PC, which may improve biocompatibility and targeted delivery, yet sometimes at the expense of NP functionality and/or off-target effects. This work further discusses how AI has been employed to predict PC composition, an exciting avenue ahead for NP and therapeutic performance optimization. The incorporation of AI tools will considerably improve NP behavior prediction within biological systems, allowing for customized nanomedicine. Even though there is increasing interest, there still lacks an extensive synthesis on AI tools applied to predict PC composition and NP design optimization. Key findings demonstrate how NP properties impact PC formation, and how AI models predict corona composition from such features. These tools allow improved NP designing by foretelling protein adsorption patterns and thus mitigating off-target effects and improving biocompatibility. Clinically, AI incorporation might help to create customized nanomedicines that possess improved therapeutic efficacy and reduced systemic toxicity.
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