4.7 Review

Toward the Specificity of Bare Nanomaterial Surfaces for Protein Corona Formation

Journal

Publisher

MDPI
DOI: 10.3390/ijms22147625

Keywords

nanoparticles; biomolecules; protein corona; uncoated nanomaterials; surface recognition

Funding

  1. Veneto Region project Safe, Smart, Sustainable Food for Health (3S_4H)-POR FESR 2014-2020, 1.1.4. [1139]

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Nanotechnology is aimed at developing intelligent nanomaterials capable of recognizing biological components, with a common belief that coatings are necessary for their application in biological systems. Interdisciplinary research in recent decades has explored the interactions between uncoated inorganic materials and biological systems, emphasizing the role of nanomaterial surface coatings in the biological environment.
Aiming at creating smart nanomaterials for biomedical applications, nanotechnology aspires to develop a new generation of nanomaterials with the ability to recognize different biological components in a complex environment. It is common opinion that nanomaterials must be coated with organic or inorganic layers as a mandatory prerequisite for applications in biological systems. Thus, it is the nanomaterial surface coating that predominantly controls the nanomaterial fate in the biological environment. In the last decades, interdisciplinary studies involving not only life sciences, but all branches of scientific research, provided hints for obtaining uncoated inorganic materials able to interact with biological systems with high complexity and selectivity. Herein, the fragmentary literature on the interactions between bare abiotic materials and biological components is reviewed. Moreover, the most relevant examples of selective binding and the conceptualization of the general principles behind recognition mechanisms were provided. Nanoparticle features, such as crystalline facets, density and distribution of surface chemical groups, and surface roughness and topography were encompassed for deepening the comprehension of the general concept of recognition patterns.

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